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We make shopping smoooth. Our aim is to become the world’s favorite way to shop and bring flexible healthy financial services to consumers. Klarna was founded in Stockholm, Sweden and now has offices in Stockholm, London, New York, Berlin and many more. We offer products and services to consumers and retailers within payments, social shopping, and personal finances. Since 2005 Klarna has been on a mission to revolutionize the retail banking industry. With over 150 million global active users and 2 million transactions per day, Klarna is meeting the changing demands of consumers by saving them time and money while helping them be informed and in control of their finances. Over 450,000 global retail partners, including H&M, Saks, Sephora, Macys, IKEA, Expedia Group, and Nike have integrated Klarna's innovative technology to deliver a seamless shopping experience online and in-store. Klarna has over 6,000 employees and is active in 45 markets. If you're as excited about this as we are: join us! It’s a hell of a ride.

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Sequoia Capital has named a new board member for fintech Klarna Bank AB, seeking to quell a conflict that has ensnared the storied venture capital firm, its high-profile former partner and one of the largest startups in Europe.

Sequoia Klarna Bank Spat Rooted in Tension Between Startup’s Founders - Bloomberg

Sequoia Capital has picked partner Andrew Reed to replace Matthew Miller on the board of ‘buy now, pay later’ company Klarna, according to people familiar with the matter.Miller had joined the board in January and recently led a failedeffort to remove former Sequoia leader Michael Moritz ...

Sequoia to Appoint Andrew Reed to Klarna Board After Failed Moritz Ouster — The Information

Silicon Valley VC firm says it fully supports its former partner ‘upon a fuller assessment’

Sequoia abandons effort to oust Michael Moritz from Klarna board

Sequoia Capital has retracted its request to remove Michael Moritz as chairman of Klarna’s board, according to emails reviewed by The Information. Sequoia partner Matthew Miller, the director who in recent days had asked Klarna shareholders to remove Moritz, is instead leaving the Klarna board.

Sequoia Retracts Request to Oust Moritz From Klarna Board — The Information

Sequoia seeks to oust Klarna chairman Michael Moritz from the board ahead of a possible float by the “buy now, pay later” lender

Sequoia seeks to oust Klarna chairman Michael Moritz

Plus, a UK electronics retailer sparks a cross-border bidding war and meet the auditors that signed off on China Evergrande

Friends now, foes later: Sequoia’s drama at Klarna

Hey everyone! and just like you, I’ve been fascinated with the recent progress of artificial intelligence. Realizing that I needed to stay abreast with all the developments happening, I decided to embark on a personal journey of learning, thus was born! With this series, I will be learning about LLMs and share ideas, experiments, opinions, trends & learnings through my blog posts. You can follow along the journey on HackerNoon or my personal website . In today’s article, we’ll be looking at the case study of how Klarna leveraged Gen AI and what other companies can learn from it. , I’m Nataraj 100 days of AI here here How is Klarna using generative AI? There are lots of ways generative AI is being used by companies, and we have explored some of them . In case of Klarna, they launched an AI customer support assistant that is available 24*7 and supports 30+ languages. They launched the assistant using Open AI as their LLM provider. If we have to guess, they have finetuned it using their own customer support interaction data set that they have collected over the years. in a previous post What features does the Klarna AI assistant support? The assistant is designed to handle wide range of questions related to refunds, returns, payment-related issues, cancellations, disputes, and invoice inaccuracies, ensuring swift and effective solutions. Like any tech feature, its available 24*7 across all geographies. For customers who want to know what they can afford and not afford, it also provides info related to purchase power, spending limits and the reasons why it exists. All the info of a customer account is with the assistant to help any questions related to it. Is the new AI assistant effective? Its cool to say that we have used gen AI and see the stock pop up, but the real question is, does the feature deliver value to the company. And from the numbers, it looks like it is beating expectations. Here are some of the numbers. Two-thirds of all customer service chats are handled by the assistant, which is an impressive 2.3M conversations. Customer satisfaction same as human conversations. 25% drop in repeat inquiries Estimated to drive $40M in profit improvements to the company. What are the takeaways from Klarna’s gen AI assistant? Its clear that generative AI is being adopted and creating value for companies at all stages. Customer support will get more effective and cheaper. If the new assistant is handling two-thirds of all conversations, it means the next set of companies which start their customer support teams will not require the same number of people in their teams. And this also means the existing customer support teams might be larger than needed. We will see a lot of growth stage startups follow Klarna to boost their profitability and reduce expenses. For companies like Klarna whose stocks are down due to the concern of profitability, companies with similar concerns will start to look at leveraging AI to cut costs and boost profitability. Open AI’s board drama didn’t effect its trust among companies to use them for production scale deployments. When Sam Altman was fired and re-hired at Open Ai, one of the concerns was that this would reduce the trust among developers to use Open Ai to create AI applications. When a large public company publishes such a case study its clear that the board drama at Open Ai didn’t effect Open AI’s abilities. Expect more companies to announce improvements because of using gen AI technology in fields outside customer support. More case studies using generative AI will come from more public companies showing how they are leveraging Ai. This is a function of every company wanting to get a piece of the AI narrative and the fact that gen AI features are actually delivering on value. If you are a company with large data set related to customer support, you should explore creating an AI assistant for support interactions. That’s it for Day 19 of 100 Days of AI. I write a newsletter called Above Average where I talk about the second order insights behind everything that is happening in big tech. If you are in tech and don’t want to be average, . subscribe to it Follow me on , or for latest updates on 100 days of AI or . If you are in tech you might be interested in joining my community of tech professionals . Twitter LinkedIn HackerNoon bookmark this page here

100 Days of AI, Day 19: Klarna’s AI Chatbot and The Rise of Generative AI in Startups

এআই-এর 100 দিন, 19তম দিন: ক্লারনার এআই চ্যাটবট এবং স্টার্টআপে জেনারেটিভ এআইয়ের উত্থান

100 Tage KI, Tag 19: Klarnas KI-Chatbot und der Aufstieg der generativen KI in Startups

100 días de IA, día 19: El chatbot de IA de Klarna y el auge de la IA generativa en las empresas emergentes

100 jours d'IA, jour 19 : le chatbot IA de Klarna et l'essor de l'IA générative dans les startups

एआई के 100 दिन, दिन 19: क्लार्ना का एआई चैटबॉट और स्टार्टअप्स में जनरेटिव एआई का उदय

100日間のAI、19日目: KlarnaのAIチャットボットとスタートアップにおける生成AIの台頭

AI 100일, 19일차: Klarna의 AI 챗봇과 스타트업에서 생성 AI의 부상

100 dias de IA, dia 19: AI Chatbot de Klarna e a ascensão da IA generativa em startups

100 дней искусственного интеллекта, день 19: чат-бот Klarna с искусственным интеллектом и рост генеративного искусственного интеллекта в стартапах

100 Gün Yapay Zeka, 19. Gün: Klarna'nın Yapay Zeka Sohbet Robotu ve Yeni İşletmelerde Üretken Yapay Zekanın Yükselişi

100 ngày của AI, Ngày 19: Chatbot AI của Klarna và Sự trỗi dậy của AI sáng tạo trong các công ty khởi nghiệp

人工智能 100 天，第 19 天：Klarna 的人工智能聊天机器人和初创企业中生成式人工智能的兴起

Today's digital shoppers love to shop online instead of visiting a brick-and-mortar store. Daily marketing tactics make brands think of something new and strategic to beat the competition. Buy Now Pay Later is one of the marketing strategies and a convenient payment option that drives customers to buy the products. Let’s understand in detail about Buy Now, Pay Later. What does Buy Now Pay Later, or BNPL, mean? "Buy now, pay later" means you can buy something and get it right away, but you pay for it later, usually in several installments. Recent growth in buy now, pay later (BNPL) doesn't look like it will slow down. Source: eMarketer Even though this kind of payment plan has been around for a long time, it took off during the pandemic when more people started shopping online. You can now use a "buy now, pay later" plan at most significant stores, but whether you should use the BNPL method for purchasing a product as a consumer depends on your financial capacity. On the other hand, whether you should offer this method of purchase as a business owner should be determined by your business model and objective. Your purchase from BNPL is split into equal payments, the first of which is due at checkout. Your debit or credit card is charged for the rest of the costs until your purchase is paid for in full. Source When you shop online, you'll often see BNPL payment plans. There are also BNPL sites for travel and health care. How Do Buying Now and Paying Later Work? For an example of BNPL operation, let's look at Meg, a shopper who wants the best air purifier for her house and pay for it later. She looks for one online and finds the one she wants at one  site for $200. It costs more than other models that fit her budget of $125, but it has all the features she wants. The following steps show how she got to the point where she could buy the item in installments. Meg finds out that she can pay over time. On the product page for the air purifier, she sees a $200 price tag and a message that says she could pay $50 each month for four months and own the item. This 4-way split is attractive to her because she can't afford to pay $200 immediately. But it's easier to handle if you spend $50 every two weeks. The pricing information also links to a BNPL service, so she can apply to see if she is eligible. She applies by clicking the link. Then, she gives four short pieces of information (name, birthdate, phone number, and email address). Affirm, an app used for BNPL uses an underwriting technology that looks at the data and lets her know within seconds if she has been approved or not. Meg buys an air cleaner. At checkout, she chooses to Affirm as her payment method. She can see exactly how her payments will work and agrees to them. This finishes the deal. (In this case, she doesn't have to pay any interest. Other BNPL purchases may have longer terms and fixed monthly payments with interest. For these kinds of deals, you might also need to get more information.) The store gets paid right away. Generic Air doesn't have to collect Meg's payments because of the tie-up with Affirm. Meg gets the air cleaner she's been wanting. Meg gives money to Affirm. In this case, she pays her bills every two weeks, which is what she agreed to do. How does BNPL Help Business Owners? Lots of sales Customers are more likely to buy more products from stores that offer more ways to pay, like BNPL. Customer usually only buys things when they are comfortable with how to pay for them. When customers can choose how to pay, they are more likely to buy more than one product, even if it is a bit more expensive. For example, you are a Magento store owner, and you want to provide better payment options to your customer. You can consider adding the buy now, pay later option to your store. You can purchase the extension from the marketplace, or you can take help from who can develop this custom solution for you. expert Magento developers Fewer people are giving up on their carts A found that using BNPL at checkout can cut the number of carts that are left empty by 35%. Most shoppers go to their carriages to look around, but that's not always the case. These problems can be solved well by BNPL. For example, suppose shoppers abandon their carts because they couldn't find a good way to pay or because the products were too expensive. In that case, BNPL will be able to reject every reason because customers can deliver when it's convenient for them. The price of expensive products can be split up into more affordable payments. Mastercard study Increase the customer's value over time When a customer buys from an online platform that accepts BNPL payments repeatedly, the merchant has met the customer's needs. Also, returning to a platform to buy something shows that the merchant has earned the customers' trust and loyalty by giving them flexible payment terms. Customer Lifetime Value can be easily raised when customers return to the same shopping platform to buy things. Raise the average value of each order When customers order products one at a time, the total amount is higher, which is good for a business. Customers can shop more by choosing BNPL at checkout because they can make the payment later and also in installments despite having low cash at the time of purchase.  Paying overtime and not having to pay anything upfront makes it easier to buy more. Paying overtime and not having to pay anything upfront makes it easier to buy more. When customers know how BNPL can help them and shop more, the average order value increases, and merchants get more from each customer. Why Millennials and Gen Zs are jumping on the buy now pay later trend? In 2018 when apps like Affirm, Klarna, and Afterpay were still establishing themselves as the key players in the BNPL, the primary users of the payment method were Gen X and the millennials. These two groups will continue to be the driving force in the BNPL method, where last year, 40 percent of the users were millennials, and in the next four years, Gen Z will eat into the share. it was reported Millennials and Gen Z are jumping into this trend because they find it a financially flexible payment solution with a limited cash flow. It is often used for larger ticket items like clothing, fashion items, jewelry, digital leisure goods, and appliances. All of these are the most frequently purchased items by the younger cohort. Apart from the financial convenience it offers, certain other benefits that make the younger generation buy into the trend are: Items can be bought even if they don’t have credit cards; it is a perfect alternative to credit cards. Alternative To Credit Cards: The easy integration of the BNPL apps into the stores makes purchasing easy for these two generations. Often the service is integrated into the buyer’s e-wallet, giving the consumer a wider choice for purchases. E-Wallet Integration: The refunds are accessible with the method, where the money is transferred back to the wallet immediately when a payment is made when the customer cancels the purchase. Whereas in case of payment is made through net banking or debit/credit cards, the refund can happen after a couple of days. Easy Refund: The easy EMI feature offered by BNPL makes the method a hit among the millennials and Gen Z. They can repay the amount in small EMIs without interest, allowing them to buy items that would otherwise be out of their reach. Easy EMI: Moreover, Buy Now Pay Later (BNPL) is a significant change in alternative financing and payments for online shopping. The pandemic sped up this trend; it became trendy very quickly. BNPL has become a digital lifestyle solution as more merchants start to use it. The most recent report showed that e-commerce in Western Europe will grow at a CAGR of 10%, bringing the size of the market to EUR 715 billion by 2026. Why shouldn't you buy now and pay later? Buy now, pay later. Financing can give you more money to spend and help your credit score simultaneously. But each loan offer is different. The three main things that should make you not want to join the BNPL are: You might be tempted to spend more than you can afford With BNPL, you only have to pay for a portion of your purchase up front. The rest can be paid off over several months. Buy now, pay later E-commerce you can't pay for immediately makes it much more manageable. But that could lead you to spend more than you can afford. Say you want to buy something that costs $500, but you only have $50. If you can pay for it over time, you might be more likely to buy it. But in reality, if you only have $50 left over in your budget, it may be a sign that you shouldn't buy a $500 item unless you need it in an emergency (like if you're a freelance writer and that $500 item is a laptop you need to do your job). If you don't pay on time, you might have to pay fees and penalties BNPL plans are better than credit cards because they don't start charging interest right away. But if you don't make your payments on time, you might have to pay penalties and fees that make your purchases much more expensive. It could hurt your credit score You don't have a good credit score to get a BNPL plan. These services don't check your credit report as thoroughly as other loans. But if you got into your BNPL payments, your credit score could take a big hit, just like it would if you didn't make the minimum payment on your credit card when it was due. The Impact Of Buy Now Pay Later Buy Now, Pay Later sounds attractive to customers. It can also be risky for the brands to go for this. It’s advisable no matter which marketing strategy you opt to attract customers. So, make sure to plan out smartly to offer buy now and pay later to customers. In the short run, this tactic can show you a good number of product sales. For more interesting information about the latest eCommerce trends, visit our blog and stay up to date.

Buy Now, Pay Later: What is it, and Should You Offer it to the Customers?

The average return rate in eCommerce is estimated at 17.6% for 2024. Nearly 1 in 5 products sold was returned. There are many factors affecting this high number, including the two opposing trends that I will elaborate on in this article. The first is the increase in the number of products and alternatives offered by online retailers. The second is the lowering of payment and return thresholds. Both factors impact the psychological decision making of us as consumers, and in doing so are partly responsible for the global ‘return pile’. But can we use the same psychological and marketing principles to reverse this trend? With this article, in addition to exploring these two trends, I try to take a positive look at how online providers can become part of the solution. The ever-expanding product catalog There are now more online stores and products globally than ever before. The barriers to entry for starting online businesses have dropped tremendously over the past 10 years. Take Shopify for example, it charges €1 for the first 3 months of running your online store. One. Euro. Along with other global trends such as dropshipping, the number of online stores has skyrocketed. And that's a great trend for consumers, right? All those extra products and stores to choose from, that will help us choose the perfect product for our specific situation. Unfortunately, that is not the reality. All those extra products and brands do not help us make decisions that make us more satisfied. On the contrary, the opposite is itself the case. “Decision fatigue” is a long-studied phenomenon, including in eCommerce: Research shows that consumers are up to 10 times more likely to make a confident decision when presented with fewer options. This highlights the undeniable impact of the overload of choices when making decisions. In our family, we have renamed this phenomenon “the vacuum cleaner's dilemma.” Referring to my father's extensive search for the right vacuum cleaner. With a cord? Without cord? With bag? Without bag? Integrated dust buster? Or is that a waste of the dust buster still in the closet? How important is weight? Battery life? Collection capacity? ... Adding more products or alternatives to choose from not only impairs our ability to decide. It even reduces how satisfied we are with the purchase we made. This is due to the increase in the number of trade-offs (trade-offs) we have to make when choosing a product or product category. The more trade-offs we have to make, the more we become aware of the shortcomings of our chosen product and the advantages of the alternatives we could have chosen. This reduces our satisfaction with the product we chose. Combined with lower thresholds for returns and payment, returning the purchase is a very small step. Lowering the barriers to payment and returns Now that we know that the increase in product and brand alternatives comes at the expense of our satisfaction with the product eventually delivered to our doorstep, why do we buy it anyway? One reason can be found in the lowering of barriers to making online payments and return options for online purchases. Payment providers like Klarna play well on psychological mechanisms like “the pain of paying.” These strategies are very successful (if success is measured by the number of products sold) because they exploit our psychological and biological mechanisms. B.J. Fogg, professor of psychology and researcher at Stanford University, discovered this back in 2009. Behavior occurs when someone is motivated to do something (e.g., make a purchase) and when the barriers to performing that behavior are low. Online marketers have been applying this for years. They know how to “trigger” behavior online, increasing the likelihood that buyers will make a purchase. Just when we begin to doubt our decision, we come across a flashy text that reassures us: “Buy now, pay later” or “Return free within 30 days. Ah, what a relief… If we do not make the right decision, if we are not satisfied with our new AirFryer, iPhone case or even a new car, we can return it without worry. All the barriers that once stood between us and the purchase are gone. This trend, combined with our tendency to be less satisfied with what we buy, has a big part in why we return our newly purchased items just as easily. Becoming part of the solution: helping consumers make better decisions. Online stores can help people feel happier with their own purchase, or in more commercial terms: increase the perceived value of a purchase. This can reduce the likelihood that people will effortlessly return a purchase. How can we increase this perceived value? First, by helping consumers decide which product to choose and not overloading them with all the hundreds of products and alternatives the Web shop offers. Web stores need to work on their ability to give consumers product advice so they know they are making the right decision. There are already tools available to help you do this. This principle is known as “guided selling”, which involves asking questions about the buyer's individual situation, preferences and intended use of the product. Based on their answers, a product that meets their needs is recommended. This approach eliminates the need for endless product comparisons. Another way to increase the perceived value of a purchase is to make it feel “theirs.” This is due to a phenomenon called the “endowment effect.” This is a psychological bias that causes us to place a higher value on things we own, as opposed to things we don't own. This is one reason why physical technology stores often have showrooms where you can just grab a phone and try it out. This increases the feeling that the product is “yours,” and thus the psychological price tag you attach to it. There is a good chance that using psychological principles to increase the perceived value of products can help reduce returns. Currently, 1 in 5 products sold that are returned is excessive. This problem also requires a change in mindset among online retailers. They really need to ask themselves if the product they are selling is a perfect fit for their customers. By doing this, we can improve buyers' online decision-making and collectively contribute to improving global e-commerce. The average return rate in eCommerce is estimated at 17.6% for 2024. Nearly 1 in 5 products sold was returned. There are many factors affecting this high number, including the two opposing trends that I will elaborate on in this article. The first is the increase in the number of products and alternatives offered by online retailers. The second is the lowering of payment and return thresholds. Both factors impact the psychological decision making of us as consumers, and in doing so are partly responsible for the global ‘return pile’. But can we use the same psychological and marketing principles to reverse this trend? With this article, in addition to exploring these two trends, I try to take a positive look at how online providers can become part of the solution. 17.6% The ever-expanding product catalog There are now more online stores and products globally than ever before. The barriers to entry for starting online businesses have dropped tremendously over the past 10 years. Take Shopify for example, it charges €1 for the first 3 months of running your online store. One. Euro. Along with other global trends such as dropshipping, the number of online stores has skyrocketed. And that's a great trend for consumers, right? All those extra products and stores to choose from, that will help us choose the perfect product for our specific situation. Unfortunately, that is not the reality. All those extra products and brands do not help us make decisions that make us more satisfied. On the contrary, the opposite is itself the case. “Decision fatigue” is a long-studied phenomenon, including in eCommerce: Research shows that consumers are up to 10 times more likely to make a confident decision when presented with fewer options. This highlights the undeniable impact of the overload of choices when making decisions. 10 times more likely In our family, we have renamed this phenomenon “the vacuum cleaner's dilemma.” Referring to my father's extensive search for the right vacuum cleaner. With a cord? Without cord? With bag? Without bag? Integrated dust buster? Or is that a waste of the dust buster still in the closet? How important is weight? Battery life? Collection capacity? ... Adding more products or alternatives to choose from not only impairs our ability to decide. It even reduces how satisfied we are with the purchase we made. This is due to the increase in the number of trade-offs (trade-offs) we have to make when choosing a product or product category. The more trade-offs we have to make, the more we become aware of the shortcomings of our chosen product and the advantages of the alternatives we could have chosen. This reduces our satisfaction with the product we chose. Combined with lower thresholds for returns and payment, returning the purchase is a very small step. Lowering the barriers to payment and returns Now that we know that the increase in product and brand alternatives comes at the expense of our satisfaction with the product eventually delivered to our doorstep, why do we buy it anyway? One reason can be found in the lowering of barriers to making online payments and return options for online purchases. Payment providers like Klarna play well on psychological mechanisms like “the pain of paying.” These strategies are very successful (if success is measured by the number of products sold) because they exploit our psychological and biological mechanisms. B.J. Fogg, professor of psychology and researcher at Stanford University, discovered this back in 2009. Behavior occurs when someone is motivated to do something (e.g., make a purchase) and when the barriers to performing that behavior are low. Online marketers have been applying this for years. They know how to “trigger” behavior online, increasing the likelihood that buyers will make a purchase. Just when we begin to doubt our decision, we come across a flashy text that reassures us: “Buy now, pay later” or “Return free within 30 days. Ah, what a relief… If we do not make the right decision, if we are not satisfied with our new AirFryer, iPhone case or even a new car, we can return it without worry. All the barriers that once stood between us and the purchase are gone. This trend, combined with our tendency to be less satisfied with what we buy, has a big part in why we return our newly purchased items just as easily. Becoming part of the solution: helping consumers make better decisions. Online stores can help people feel happier with their own purchase, or in more commercial terms: increase the perceived value of a purchase. This can reduce the likelihood that people will effortlessly return a purchase. How can we increase this perceived value? First, by helping consumers decide which product to choose and not overloading them with all the hundreds of products and alternatives the Web shop offers. Web stores need to work on their ability to give consumers product advice so they know they are making the right decision. There are already tools available to help you do this. This principle is known as “ guided selling ”, which involves asking questions about the buyer's individual situation, preferences and intended use of the product. Based on their answers, a product that meets their needs is recommended. This approach eliminates the need for endless product comparisons. product advice guided selling Another way to increase the perceived value of a purchase is to make it feel “theirs.” This is due to a phenomenon called the “endowment effect.” This is a psychological bias that causes us to place a higher value on things we own, as opposed to things we don't own. This is one reason why physical technology stores often have showrooms where you can just grab a phone and try it out. This increases the feeling that the product is “yours,” and thus the psychological price tag you attach to it. There is a good chance that using psychological principles to increase the perceived value of products can help reduce returns. Currently, 1 in 5 products sold that are returned is excessive. This problem also requires a change in mindset among online retailers. They really need to ask themselves if the product they are selling is a perfect fit for their customers. By doing this, we can improve buyers' online decision-making and collectively contribute to improving global e-commerce.

Returns are Rising Fast — and Not Enough Tools are Focused on Stopping Them at the Source

መመለሻዎች በፍጥነት እያደጉ ናቸው - እና በቂ ያልሆኑ መሳሪያዎች ከምንጩ ላይ በማቆም ላይ ያተኮሩ ናቸው።

Las devoluciones están aumentando rápidamente y no hay suficientes herramientas enfocadas en detenerlas en la fuente

रिटर्न तेजी से बढ़ रहे हैं - और उन्हें स्रोत पर रोकने के लिए पर्याप्त उपकरण नहीं हैं

A visszatérések gyorsan növekednek - és nem elég eszközök összpontosítanak arra, hogy megállítsák őket a Forrásnál

返金は急速に増加しており、十分なツールが源頭でそれらを止めることに集中していない。

ការត្រឡប់មកវិញកំពុងកើនឡើងយ៉ាងឆាប់រហ័ស — ហើយឧបករណ៍មិនគ្រប់គ្រាន់ត្រូវបានផ្តោតលើការបញ្ឈប់ពួកគេនៅប្រភព

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Zwroty rosną szybko - a nie wystarczająco wiele narzędzi koncentruje się na zatrzymaniu ich u Źródła

بیرته راستنیدنه په چټکۍ سره مخ په زیاتیدو ده - او کافي وسایل نشته چې په سرچینه کې یې ودروي

ප්රතිලාභ වේගයෙන් වර්ධනය වන අතර, ප්රභේදයේ ඒවා නතර කිරීම සඳහා ප්රමාණවත් මෙවලම් නොලැබේ

واپسی تیزی سے بڑھ رہی ہے - اور کافی نہیں ٹولز ان کو ماخذ پر روکنے پر مرکوز ہیں

Bu o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z o‘z.

As an analysis & insight professional, I've witnessed the slow and steady evolution of our industry over the last 2 decades into more behavioural metrics with the aim to improve accuracy. Then came GPT, and it changed everything. This journey has led me to profound insights about the future of work and the role of artificial intelligence in shaping our professional landscape. The revolution will not be televised As I talk to fellow professionals in the industry, it’s clear that everyone is fascinated, and has at least tried to gain insights from data with the help of AI. Few ambitious pilots and programs have been tested and organizations are learning their way into professionalizing the use of generative AI to support employees and business processes. But the numbers suggest a much deeper change; besides programming and marketing assets production, research and data analysis pops up in the Top10 use cases of AI. It’s not just the repetitive and basic tasks like open-text coding that can be automated, it’s everything from research design, questionnaire writing, data production to insights extraction. In fact, all aspects of my own job could be obsolete in 2025! Machines are beating humans at their own game When I started my career, the idea of AI replacing human analysts seemed like a distant possibility. Recent research from the University of Chicago Booth School of Business has found that large language models like ChatGPT and Claude can be better predictors of financial analysis than their human counterparts. These AI models can achieve a 60% rate of accuracy in predictive financial performance, compared to the 53-57% accuracy of human experts. This isn't just a marginal improvement; it's a quantum leap that signals a fundamental shift in how analysis will be conducted in the future. The writing on the wall: Human analysts face extinction It became clear to me for some time that the days of traditional human analysts were numbered. The speed, accuracy, and scalability of AI in processing and analysing vast amounts of data far surpassed what any team of human analysts could achieve. I never questioned why I started the journey to build [ANDRE](https://(https://andre.ai) back in 2018. It started quietly, slowly, but it burst in 2024  with 5 product releases and hundreds of improvements. That’s not even enough to sustain our competitive advantage for long considering the pace of development in RAG and AI-enabled technologies. An old study by Accenture found that AI has the potential to boost labour productivity by up to 40 percent by 2035. This isn't just about doing more with less; it's about unlocking human potential. In 2021 already, Gartner predicted that over 70% of organizations would be augmenting their analytics workforce with synthetic help by 2025. According to a recent McKinsey study, by 2030, up to 30 percent of current hours worked could be automated, accelerated by generative AI. All three position papers are likely dramatically underestimating the shift, however. The transition to AI-augmented workforces isn't a future prospect anymore – it's our present reality. The speed of the transition to “AI-first” is likely to become evident only in hindsight, after a series of cascading announcements bring it to light. As I developed my SaaS platform, I saw first-hand how AI could enhance human capabilities rather than simply replace them. The platform I created didn't just mimic my analytical processes; it expanded upon them, uncovering insights and patterns that would have taken me weeks to discover manually. How could others not notice the incredible opportunity that this represents? Welcome to the age of agentic organizations As I delved deeper into the potential of AI, I began to envision a future where organizations would be largely self-directed, with AI agents handling a significant portion of analytical and decision-making processes. In fact I had purchased the website “synthetic.company” for a couple of cents in 2018 as I thought it was pretty cool to imagine a company solely run by AI. A great thought experiment back then. I discovered recently, however, after having stopped to renew the domain for 3 years, that the site is for sale in the high 4-digits range. I console myself with the thought that it’s better to be too early than too late. This is market-proof evidence that "agentic organizations" isn't science fiction now – it's our reality. In this new paradigm, work looks dramatically different. Human roles will shift towards ignition, and perhaps control and orchestration, if anything. A venture capital fund active in Web3 was launched in October 2024. Its main particularity? It’s run exclusively by AI agents. This project is worth over 2 $Bn in its first 2 months of existence… Besides its wild speculative nature, this project suggests that human involvement may not be an absolute necessity for managing organizations. Many frameworks have emerged that let users design entirely synthetic workers with their own set of objectives, skills and tools, and get them to interact together to get things done, like organizing events automatically or generating marketing campaigns. Technology bright and dark side Every new technology can be used for good and for bad. The benefits of this AI revolution are immense. For companies, the increased efficiency and depth of insights lead to better decision-making and competitive advantages. For business owners and start-up teams, it levels up the competition. It provides anyone with a wealth of extra resources for business growth and innovation. The opportunities presented by AI are equally significant. AI is not just about automation—it's about augmentation and innovation. It's creating new roles and industries that we couldn't have imagined a decade ago. For example, the World Economic Forum has identified AI-driven productivity enhancement as a key driver for potential economic growth. PwC predicts that AI could add up to $15.7 trillion to the global economy by 2030. But it also means that the same output can be achieved by fewer people, and this will inevitably have an impact on the workforce. The more innovative companies like Klarna have already slashed in their highly skilled workforce (about 22%). A study by Oxford Economics suggests that robots could replace up to 20 million jobs globally by 2030. It would be short-sighted to miss the parallel with industrial automation in the late 20th century. News from the trenches Being in the trenches at the frontier isn’t comfortable nor comforting. Uncertainty is everywhere, too much is happening and most of it is stealth. The stakes are high. But being where things happen helps move history in the way we want. As I reflect on my journey on creating my synthetic replacement, I feel like I'm not just building a tool that will eventually outperform me, I'm helping to shape the future of work. The MIT Technology Review highlights the importance of responsible AI development, emphasizing the need for transparency, fairness, and accountability. As creators and early adopters of these technologies, we have a responsibility to ensure they benefit humanity as a whole. Embracing the AI-powered future The transformative power of AI is huge, and recent developments give us a glimpse into work in 2025 and beyond. My experience of building ANDRE with the aim to replace myself has been both humbling and exhilarating. I'm convinced that by embracing change and actively participating in shaping the future, we can create a world where AI unlocks unprecedented levels of innovation and progress. It’s just not fully clear yet where we humans will fit in cognition intensive workflows. And whether we manage to build AI that benefits all or not, I’ll sleep much better knowing that I have my synthetic clone ready for business ! As an analysis & insight professional, I've witnessed the slow and steady evolution of our industry over the last 2 decades into more behavioural metrics with the aim to improve accuracy. Then came GPT, and it changed everything. This journey has led me to profound insights about the future of work and the role of artificial intelligence in shaping our professional landscape. The revolution will not be televised The revolution will not be televised As I talk to fellow professionals in the industry, it’s clear that everyone is fascinated, and has at least tried to gain insights from data with the help of AI. Few ambitious pilots and programs have been tested and organizations are learning their way into professionalizing the use of generative AI to support employees and business processes. But the numbers suggest a much deeper change; besides programming and marketing assets production, research and data analysis pops up in the T op10 use cases of AI . op10 use cases of AI It’s not just the repetitive and basic tasks like open-text coding that can be automated, it’s everything from research design, questionnaire writing, data production to insights extraction. In fact, all aspects of my own job could be obsolete in 2025! Machines are beating humans at their own game Machines are beating humans at their own game When I started my career, the idea of AI replacing human analysts seemed like a distant possibility. Recent research from the University of Chicago Booth School of Business has found that large language models like ChatGPT and Claude can be better predictors of financial analysis than their human counterparts. Recent research These AI models can achieve a 60% rate of accuracy in predictive financial performance, compared to the 53-57% accuracy of human experts. This isn't just a marginal improvement; it's a quantum leap that signals a fundamental shift in how analysis will be conducted in the future. The writing on the wall: Human analysts face extinction The writing on the wall: Human analysts face extinction It became clear to me for some time that the days of traditional human analysts were numbered. The speed, accuracy, and scalability of AI in processing and analysing vast amounts of data far surpassed what any team of human analysts could achieve. I never questioned why I started the journey to build [ANDRE](https://(https://andre.ai) back in 2018. It started quietly, slowly, but it burst in 2024  with 5 product releases and hundreds of improvements. That’s not even enough to sustain our competitive advantage for long considering the pace of development in RAG and AI-enabled technologies. An old study by Accenture found that AI has the potential to boost labour productivity by up to 40 percent by 2035. This isn't just about doing more with less; it's about unlocking human potential. In 2021 already, Gartner predicted that over 70% of organizations would be augmenting their analytics workforce with synthetic help by 2025. According to a recent McKinsey study , by 2030, up to 30 percent of current hours worked could be automated, accelerated by generative AI. An old study by Accenture Gartner predicted McKinsey study All three position papers are likely dramatically underestimating the shift, however. The transition to AI-augmented workforces isn't a future prospect anymore – it's our present reality. The speed of the transition to “AI-first” is likely to become evident only in hindsight, after a series of cascading announcements bring it to light. As I developed my SaaS platform, I saw first-hand how AI could enhance human capabilities rather than simply replace them. The platform I created didn't just mimic my analytical processes; it expanded upon them, uncovering insights and patterns that would have taken me weeks to discover manually. How could others not notice the incredible opportunity that this represents? Welcome to the age of agentic organizations Welcome to the age of agentic organizations As I delved deeper into the potential of AI, I began to envision a future where organizations would be largely self-directed, with AI agents handling a significant portion of analytical and decision-making processes. In fact I had purchased the website “synthetic.company” for a couple of cents in 2018 as I thought it was pretty cool to imagine a company solely run by AI. A great thought experiment back then. I discovered recently, however, after having stopped to renew the domain for 3 years, that the site is for sale in the high 4-digits range. I console myself with the thought that it’s better to be too early than too late. This is market-proof evidence that "agentic organizations" isn't science fiction now – it's our reality. In this new paradigm, work looks dramatically different. Human roles will shift towards ignition, and perhaps control and orchestration, if anything. A venture capital fund active in Web3 was launched in October 2024. Its main particularity? It’s run exclusively by AI agents. This project is worth over 2 $Bn in its first 2 months of existence… Besides its wild speculative nature, this project suggests that human involvement may not be an absolute necessity for managing organizations. Many frameworks have emerged that let users design entirely synthetic workers with their own set of objectives, skills and tools, and get them to interact together to get things done, like organizing events automatically or generating marketing campaigns. Technology bright and dark side Technology bright and dark side Every new technology can be used for good and for bad. The benefits of this AI revolution are immense. For companies, the increased efficiency and depth of insights lead to better decision-making and competitive advantages. For business owners and start-up teams, it levels up the competition. It provides anyone with a wealth of extra resources for business growth and innovation. The opportunities presented by AI are equally significant. AI is not just about automation—it's about augmentation and innovation. It's creating new roles and industries that we couldn't have imagined a decade ago. For example, the World Economic Forum has identified AI-driven productivity enhancement as a key driver for potential economic growth. PwC predicts that AI could add up to $15.7 trillion to the global economy by 2030. PwC predicts But it also means that the same output can be achieved by fewer people, and this will inevitably have an impact on the workforce. The more innovative companies like Klarna have already slashed in their highly skilled workforce (about 22%). A study by Oxford Economics suggests that robots could replace up to 20 million jobs globally by 2030. A study by Oxford Economics It would be short-sighted to miss the parallel with industrial automation in the late 20th century. News from the trenches News from the trenches Being in the trenches at the frontier isn’t comfortable nor comforting. Uncertainty is everywhere, too much is happening and most of it is stealth. The stakes are high. But being where things happen helps move history in the way we want. As I reflect on my journey on creating my synthetic replacement, I feel like I'm not just building a tool that will eventually outperform me, I'm helping to shape the future of work. The MIT Technology Review highlights the importance of responsible AI development, emphasizing the need for transparency, fairness, and accountability. As creators and early adopters of these technologies, we have a responsibility to ensure they benefit humanity as a whole. MIT Technology Review Embracing the AI-powered future Embracing the AI-powered future The transformative power of AI is huge, and recent developments give us a glimpse into work in 2025 and beyond. My experience of building ANDRE with the aim to replace myself has been both humbling and exhilarating. I'm convinced that by embracing change and actively participating in shaping the future, we can create a world where AI unlocks unprecedented levels of innovation and progress. ANDRE It’s just not fully clear yet where we humans will fit in cognition intensive workflows. And whether we manage to build AI that benefits all or not, I’ll sleep much better knowing that I have my synthetic clone ready for business !

Why I Built a SaaS to Replace Myself

Γιατί έφτιαξα ένα SaaS για να αντικαταστήσω τον εαυτό μου

Por qué creé un SaaS para reemplazarme a mí mismo

Zergatik eraiki nuen SaaS bat nire burua ordezkatzeko

自分自身に代わるSaaSを構築した理由

Pourquoi Natongaki SaaS Pona Mi Remplacer

किन मैले आफैलाई प्रतिस्थापन गर्न सास बनाएँ

De ce am construit un SaaS pentru a mă înlocui

මා ප්‍රතිස්ථාපනය කිරීමට මම SaaS එකක් ගොඩනඟා ගත්තේ ඇයි?

Varför jag byggde en SaaS för att ersätta mig själv

เหตุใดฉันจึงสร้าง SaaS เพื่อมาแทนที่ตัวเอง

ስለምንታይ ንነብሰይ ንምትካእ SaaS ሰሪሐ

Neden Kendimi Değiştirmek İçin Bir SaaS Kurdum

SaaS is for Suckers: AI Already Builds Better Custom Software

Turbocharging Profitability: Growth Hacking Your Customer Retention to Drive Growth For 2025

Profitabilnost turbo punjenja: Hakiranje rasta za zadržavanje vaših kupaca kako biste potaknuli rast do 2025.

Impulsando la rentabilidad: cómo retener a sus clientes para impulsar el crecimiento en 2025

Boostez votre rentabilité : Growth Hacking pour fidéliser vos clients afin de stimuler la croissance d'ici 2025

収益性を加速させる: 顧客維持率をグロースハックして 2025 年の成長を促進

Turbocharging Profitability: Bokoli Hacking Retention ya Client na yo mpo na ko diriger croissance Pona 2025

Профитабилност со турбо полнење: Хакирање на растот на задржувањето на вашите клиенти за да се поттикне растот за 2025 година

Turbocharged Profitability: Growth Hacking van uw klantenbehoud om groei te stimuleren voor 2025

Turbocarga Rentabilidad: Wiñay Hacking Cliente Retenciónniyki Wiñay 2025 kaqpaq purichinapaq

Përfitueshmëria e turbocharging: Growth Hacking Mbajtja e klientit tuaj për të nxitur rritjen për 2025

Профитабилност турбо пуњења: раст Хаковање задржавања ваших купаца како би подстакао раст до 2025.

Faida ya Turbocharging: Ukuaji Kuingilia Uhifadhi wa Wateja Wako ili Kuendeleza Ukuaji wa 2025

Turbocharging Profitability: Ku Kula Ku Hacking Ku Hlayisa Ka Khasimende Ya Wena Ku Fambisa Ku Kula Ka 2025

In my previous article, I explored the evolution of Point of Sale (POS) and Buy Now, Pay Later (BNPL) services, focusing on how these options influence customer choice. That discussion was from the customer's perspective. Now, let’s look at it from the viewpoint of businesses, specifically merchants.This article will explore what’s most important for merchants when they integrate financial solutions like POS and BNPL. We’ll look at how these solutions enhance the customer experience and boost sales.Both POS and BNPL services operate in a B2B2C (Business-to-Business-to-Consumer) model, where merchants play a key role in connecting the service provider with the end customer. In this model, merchants are not just the middlemen — they are vital to attracting customers and increasing sales. By offering flexible payment options, merchants create a smoother purchasing experience, which in turn increases customer satisfaction and conversion rates.From a technical perspective, the better the integration between financial services and merchants, the more appealing the product becomes to customers. This includes not just competitive terms, but also the speed of processing, ease of use, and how quickly issues are resolved.The success of POS and BNPL services depends not only on how appealing they are to customers, but also on the willingness of merchants to adopt and integrate them. Without strong partnerships with merchants, these services wouldn’t reach their full potential. So, what exactly matters most to merchants when considering these financial solutions?Flexibility and Customization Square is a great example of a company that offers flexibility and customization to merchants. Square provides a range of payment solutions that can be tailored to fit the needs of businesses of all sizes. For instance, Square’s point-of-sale system is modular, allowing merchants to choose and pay for only the features they need. This flexibility extends to their financing options, where merchants can offer different payment plans to customers based on their preferences. Square’s ability to adapt to the specific needs of a business—whether it's a small café or a large retail chain—has made it a popular choice for merchants looking for customizable solutions.On the other hand, Oracle’s legacy POS systems have been criticized for their lack of customization options. Many merchants found that the system couldn’t be easily adapted to their specific business processes, leading to frustration and even abandonment of the platform. When systems are too rigid, they can prevent merchants from optimizing their operations, which ultimately affects both their business and customer satisfaction.Merchant and Customer Support A good example of strong merchant and customer support comes from Shopify. Shopify has built its reputation not only on its eCommerce platform but also on the extensive support it provides to its merchants. Shopify offers 24/7 customer support through various channels such as chat, email, and phone. They also provide comprehensive online resources, including tutorials and webinars, to help merchants fully utilize their platform. This type of support reassures merchants that they can resolve issues quickly, reducing downtime and ensuring that their businesses run smoothly.On the flip side, eBay faced criticism for its slow and ineffective customer support in the past. Sellers on the platform complained about long wait times and unhelpful responses, which led some merchants to switch to other platforms like Etsy or Amazon. This example illustrates how poor support can lead to a loss of merchant confidence and ultimately, business. Competitive Rates and Terms Klarna, a leading BNPL provider, is an excellent example of a company offering competitive terms to merchants. Klarna charges merchants a fee per transaction, but these fees are often offset by the increase in sales that Klarna helps generate. Klarna's flexibility in structuring merchant fees based on volume or other business-specific factors has helped them win over large retail clients like H&M and ASOS. These competitive terms are appealing to merchants because they see a clear return on investment through increased sales and customer retention.In contrast, PayPal has been criticized by some merchants for its high fees, especially for international transactions. This has led some businesses to limit their use of PayPal or seek alternatives like Stripe or Square, which offer more favorable terms depending on transaction types and volumes.Speed and Ease of Integration Stripe is often cited as one of the best examples of a payment processor that offers fast and easy integration. Stripe’s APIs are developer-friendly, and their documentation is comprehensive, making it easy for businesses to integrate payment processing quickly. The simplicity and speed of integration have attracted major clients like Lyft and Slack, allowing these companies to focus on their core business operations without getting bogged down by complex payment integrations. This fast setup enables businesses to offer Stripe’s services to their customers without delays, preventing any potential sales loss.On the other hand, SAP’s complex ERP solutions have been known for their lengthy and resource-intensive integration processes. Many businesses, especially smaller ones, have struggled with the time and cost of integrating SAP systems, which can take months or even years to fully implement. This example highlights how a slow or complex integration can deter merchants from adopting a solution, even if it offers other benefits.Ongoing Merchant Support A great example of ongoing merchant support comes from Amazon Web Services (AWS). AWS provides extensive resources to its clients even after initial setup, offering regular updates, analytics tools, and personalized account management to ensure merchants are maximizing the platform’s potential. AWS also hosts events, webinars, and workshops to educate users on new features and best practices. This constant engagement helps merchants grow and adapt, fostering long-term loyalty and improving the merchant's overall experience.In contrast, Facebook has struggled with ongoing support for small and medium-sized businesses (SMBs) using its ad platform. Many SMBs have complained about a lack of communication and support after their ads were flagged or accounts were suspended, often without clear explanations or resolutions. This lack of ongoing support has driven some businesses to other platforms like Google Ads, which provides more proactive assistance and account management services.These real-world examples illustrate the importance of flexibility, support, competitive terms, fast integration, and ongoing assistance in maintaining successful merchant partnerships. Companies that excel in these areas, such as Square, Shopify, Klarna, Stripe, and AWS, foster long-term merchant relationships, driving mutual growth. In contrast, companies like Oracle, eBay, PayPal, SAP, and Facebook have lost merchants due to a lack of customization, poor support, high fees, slow integration, or inadequate follow-up assistance.In a future article, I’ll dive deeper into the technical aspects of integration, exploring how a seamless connection between merchants and financial services can drive further growth. if you ever want to get in touch with me Tg: https://t.me/LinaI LinkedIn: https://www.linkedin.com/in/lina-ivanova23/ In my previous article , I explored the evolution of Point of Sale (POS) and Buy Now, Pay Later (BNPL) services, focusing on how these options influence customer choice. That discussion was from the customer's perspective. Now, let’s look at it from the viewpoint of businesses, specifically merchants. This article will explore what’s most important for merchants when they integrate financial solutions like POS and BNPL. We’ll look at how these solutions enhance the customer experience and boost sales. Both POS and BNPL services operate in a B2B2C (Business-to-Business-to-Consumer) model, where merchants play a key role in connecting the service provider with the end customer. In this model, merchants are not just the middlemen — they are vital to attracting customers and increasing sales. By offering flexible payment options, merchants create a smoother purchasing experience, which in turn increases customer satisfaction and conversion rates. From a technical perspective, the better the integration between financial services and merchants, the more appealing the product becomes to customers. This includes not just competitive terms, but also the speed of processing, ease of use, and how quickly issues are resolved. The success of POS and BNPL services depends not only on how appealing they are to customers, but also on the willingness of merchants to adopt and integrate them. Without strong partnerships with merchants, these services wouldn’t reach their full potential. So, what exactly matters most to merchants when considering these financial solutions? Flexibility and Customization previous article Flexibility and Customization Square is a great example of a company that offers flexibility and customization to merchants. Square provides a range of payment solutions that can be tailored to fit the needs of businesses of all sizes. For instance, Square’s point-of-sale system is modular, allowing merchants to choose and pay for only the features they need. This flexibility extends to their financing options, where merchants can offer different payment plans to customers based on their preferences. Square’s ability to adapt to the specific needs of a business—whether it's a small café or a large retail chain—has made it a popular choice for merchants looking for customizable solutions. On the other hand, Oracle’s legacy POS systems have been criticized for their lack of customization options. Many merchants found that the system couldn’t be easily adapted to their specific business processes, leading to frustration and even abandonment of the platform. When systems are too rigid, they can prevent merchants from optimizing their operations, which ultimately affects both their business and customer satisfaction. Merchant and Customer Support Merchant and Customer Support A good example of strong merchant and customer support comes from Shopify. Shopify has built its reputation not only on its eCommerce platform but also on the extensive support it provides to its merchants. Shopify offers 24/7 customer support through various channels such as chat, email, and phone. They also provide comprehensive online resources, including tutorials and webinars, to help merchants fully utilize their platform. This type of support reassures merchants that they can resolve issues quickly, reducing downtime and ensuring that their businesses run smoothly. On the flip side, eBay faced criticism for its slow and ineffective customer support in the past. Sellers on the platform complained about long wait times and unhelpful responses, which led some merchants to switch to other platforms like Etsy or Amazon. This example illustrates how poor support can lead to a loss of merchant confidence and ultimately, business. Competitive Rates and Terms Competitive Rates and Terms Klarna, a leading BNPL provider, is an excellent example of a company offering competitive terms to merchants. Klarna charges merchants a fee per transaction, but these fees are often offset by the increase in sales that Klarna helps generate. Klarna's flexibility in structuring merchant fees based on volume or other business-specific factors has helped them win over large retail clients like H&M and ASOS. These competitive terms are appealing to merchants because they see a clear return on investment through increased sales and customer retention. In contrast, PayPal has been criticized by some merchants for its high fees, especially for international transactions. This has led some businesses to limit their use of PayPal or seek alternatives like Stripe or Square, which offer more favorable terms depending on transaction types and volumes. Speed and Ease of Integration Speed and Ease of Integration Stripe is often cited as one of the best examples of a payment processor that offers fast and easy integration. Stripe’s APIs are developer-friendly, and their documentation is comprehensive, making it easy for businesses to integrate payment processing quickly. The simplicity and speed of integration have attracted major clients like Lyft and Slack, allowing these companies to focus on their core business operations without getting bogged down by complex payment integrations. This fast setup enables businesses to offer Stripe’s services to their customers without delays, preventing any potential sales loss. On the other hand, SAP’s complex ERP solutions have been known for their lengthy and resource-intensive integration processes. Many businesses, especially smaller ones, have struggled with the time and cost of integrating SAP systems, which can take months or even years to fully implement. This example highlights how a slow or complex integration can deter merchants from adopting a solution, even if it offers other benefits. Ongoing Merchant Support Ongoing Merchant Support A great example of ongoing merchant support comes from Amazon Web Services (AWS). AWS provides extensive resources to its clients even after initial setup, offering regular updates, analytics tools, and personalized account management to ensure merchants are maximizing the platform’s potential. AWS also hosts events, webinars, and workshops to educate users on new features and best practices. This constant engagement helps merchants grow and adapt, fostering long-term loyalty and improving the merchant's overall experience. In contrast, Facebook has struggled with ongoing support for small and medium-sized businesses (SMBs) using its ad platform. Many SMBs have complained about a lack of communication and support after their ads were flagged or accounts were suspended, often without clear explanations or resolutions. This lack of ongoing support has driven some businesses to other platforms like Google Ads, which provides more proactive assistance and account management services. These real-world examples illustrate the importance of flexibility, support, competitive terms, fast integration, and ongoing assistance in maintaining successful merchant partnerships. Companies that excel in these areas, such as Square, Shopify, Klarna, Stripe, and AWS, foster long-term merchant relationships, driving mutual growth. In contrast, companies like Oracle, eBay, PayPal, SAP, and Facebook have lost merchants due to a lack of customization, poor support, high fees, slow integration, or inadequate follow-up assistance. In a future article, I’ll dive deeper into the technical aspects of integration, exploring how a seamless connection between merchants and financial services can drive further growth. if you ever want to get in touch with me Tg: https://t.me/LinaI Tg: https://t.me/LinaI Tg: https://t.me/LinaI https://t.me/LinaI LinkedIn: https://www.linkedin.com/in/lina-ivanova23/ LinkedIn: https://www.linkedin.com/in/lina-ivanova23/ LinkedIn: https://www.linkedin.com/in/lina-ivanova23/ https://www.linkedin.com/in/lina-ivanova23/

What Merchants Care About: How POS and BNPL Improve Customer Experience and Boost Sales

I don't want to alarm anyone, but the entire SaaS industry is about to implode. Or explode. Or both, simultaneously. That’s because AI is making software creation so cheap and fast that current SaaS pricing models are starting to look like a particularly unfunny joke. Remember when people paid actual money for calculators? It's going to be like that, but for entire software suites. Let me take you to this new reality for a moment. The rise of the solo product visionary Large Language Models have quickly become superhuman at generating correct code for entire applications. It's like giving everyone a team of world-class developers in their pocket. For instance, GitHub's Copilot has already shown that developers using AI are 2.2x faster at completing tasks. What could possibly go wrong? Imagine the following: a random person with good product sense and an AI sidekick decides, "You know what? I could make a better version of Salesforce." And then they just... do it. Over the weekend. This may sound crazy, but it’s almost already possible. The YouTube-ification of software distribution Thanks to YouTube, your neighbour's cat can become a viral sensation overnight. Well, soon, your neighbour's hastily cobbled together AI-assisted app could be the next unicorn. There will be product discovery platforms very similar to the App Store that will make or break businesses, just like Youtube’s algorithm makes or breaks content creators. Instead of star ratings and likes, we'll have publicly available user numbers and retention statistics. But many of the most popular apps will be fully open source and remixable, so you will be able to not only tell if an app is good before you download it, but also tweak it yourself to match your preferences. That also means that the era of everyone accepting that most software is bad is over soon, too. We're entering a different kind of era, where most software, from recipe apps to sophisticated crypto indexes, might have a user experience that’s actually good. I firmly believe that those with the best ideas will win this competition - those with the right vision to use technology effectively. Product taste and domain expertise will become more crucial than ever. The other impact of this is that developers will need to pick up new skills, or stay in niches where a human touch will stay important. What about SaaS companies? You might be thinking, "This all sounds great for consumers, but what about the poor SaaS companies?". Let me be blunt: in 2025, SaaS companies without a clear moat will start noticing churn to fresh competition and to internal tools built with AI to serve the same need. It’s already starting: Klarna recently announced it is replacing Salesforce with internally built AI. It’ll be like watching a slow-motion train wreck, except the train is made of bits and bytes, and the wreck is your business model. This shift won't hit everyone equally. Regulated industries will naturally be less impacted. Segments like designers and developers, who are always ready to jump on the best value proposition, will be the canaries in the coal mine, signalling the changes to come. My advice to current SaaS companies is therefore to adopt AI in development to speed up their iteration process, keep zooming into verticals where domain expertise is key, and not to be afraid to disrupt and cannibalise themselves before someone else does. Regardless of how well they prepare though, the shift I’m talking about will go faster and faster, to the point where the willingness to pay for software will approach that of paying for watching a tiktok or youtube video. For those of us in tech, this shift demands relentless adaptation. Ideation and execution are collapsing into a single, AI-accelerated process. We all have to adapt, quickly. The bottom line is that the future belongs to those who can dream up the next big thing and then sweet-talk an AI into building it for them. I don't want to alarm anyone, but the entire SaaS industry is about to implode. Or explode. Or both, simultaneously. That’s because AI is making software creation so cheap and fast that current SaaS pricing models are starting to look like a particularly unfunny joke. Remember when people paid actual money for calculators? It's going to be like that, but for entire software suites. Let me take you to this new reality for a moment. The rise of the solo product visionary The rise of the solo product visionary Large Language Models have quickly become superhuman at generating correct code for entire applications. It's like giving everyone a team of world-class developers in their pocket. For instance, GitHub's Copilot has already shown that developers using AI are 2.2x faster at completing tasks. What could possibly go wrong? Imagine the following: a random person with good product sense and an AI sidekick decides, "You know what? I could make a better version of Salesforce." And then they just... do it. Over the weekend. This may sound crazy, but it’s almost already possible. The YouTube-ification of software distribution The YouTube-ification of software distribution Thanks to YouTube, your neighbour's cat can become a viral sensation overnight. Well, soon, your neighbour's hastily cobbled together AI-assisted app could be the next unicorn. There will be product discovery platforms very similar to the App Store that will make or break businesses, just like Youtube’s algorithm makes or breaks content creators. Instead of star ratings and likes, we'll have publicly available user numbers and retention statistics. But many of the most popular apps will be fully open source and remixable, so you will be able to not only tell if an app is good before you download it, but also tweak it yourself to match your preferences. That also means that the era of everyone accepting that most software is bad is over soon, too. We're entering a different kind of era, where most software, from recipe apps to sophisticated crypto indexes, might have a user experience that’s actually good. I firmly believe that those with the best ideas will win this competition - those with the right vision to use technology effectively. Product taste and domain expertise will become more crucial than ever. The other impact of this is that developers will need to pick up new skills, or stay in niches where a human touch will stay important. What about SaaS companies? What about SaaS companies? You might be thinking, "This all sounds great for consumers, but what about the poor SaaS companies?". Let me be blunt: in 2025, SaaS companies without a clear moat will start noticing churn to fresh competition and to internal tools built with AI to serve the same need. It’s already starting: Klarna recently announced it is replacing Salesforce with internally built AI . It’ll be like watching a slow-motion train wreck, except the train is made of bits and bytes, and the wreck is your business model. Klarna recently announced it is replacing Salesforce with internally built AI Klarna recently announced it is replacing Salesforce with internally built AI This shift won't hit everyone equally. Regulated industries will naturally be less impacted. Segments like designers and developers, who are always ready to jump on the best value proposition, will be the canaries in the coal mine, signalling the changes to come. My advice to current SaaS companies is therefore to adopt AI in development to speed up their iteration process, keep zooming into verticals where domain expertise is key, and not to be afraid to disrupt and cannibalise themselves before someone else does. Regardless of how well they prepare though, the shift I’m talking about will go faster and faster, to the point where the willingness to pay for software will approach that of paying for watching a tiktok or youtube video. For those of us in tech, this shift demands relentless adaptation. Ideation and execution are collapsing into a single, AI-accelerated process. We all have to adapt, quickly. The bottom line is that the future belongs to those who can dream up the next big thing and then sweet-talk an AI into building it for them.

The SaaS Apocalypse and How aI Will Give Birth to One-person Tech Giants

Authors:
(1) Mark Potanin, a Corresponding (authorpotanin.m.st@gmail.com);
(2) Andrey Chertok, (a.v.chertok@gmail.com);
(3) Konstantin Zorin, (berzqwer@gmail.com);
(4) Cyril Shtabtsovsky, (cyril@aloniq.com). Table of Links Abstract and 1. Introduction 2 Related works 3 Dataset Overview, Preprocessing, and Features 3.1 Successful Companies Dataset and 3.2 Unsuccessful Companies Dataset 3.3 Features 4 Model Training, Evaluation, and Portfolio Simulation and 4.1 Backtest 4.2 Backtest settings 4.3 Results 4.4 Capital Growth 5 Other approaches 5.1 Investors ranking model 5.2 Founders ranking model and 5.3 Unicorn recommendation model 6 Conclusion 7 Further Research, References and Appendix ABSTRACT Predicting startup success presents a formidable challenge due to the inherently volatile landscape of the entrepreneurial ecosystem. The advent of extensive databases like Crunchbase jointly with available open data enables the application of machine learning and artificial intelligence for more accurate predictive analytics. This paper focuses on startups at their Series B and Series C investment stages, aiming to predict key success milestones such as achieving an Initial Public Offering (IPO), attaining unicorn status, or executing a successful Merger and Acquisition (M&A). We introduce novel deep learning model for predicting startup success, integrating a variety of factors such as funding metrics, founder features, industry category. A distinctive feature of our research is the use of a comprehensive backtesting algorithm designed to simulate the venture capital investment process. This simulation allows for a robust evaluation of our model’s performance against historical data, providing actionable insights into its practical utility in real-world investment contexts. Evaluating our model on Crunchbase’s, we achieved a 14 times capital growth and successfully identified on B round high-potential startups including Revolut, DigitalOcean, Klarna, Github and others. Our empirical findings illuminate the importance of incorporating diverse feature sets in enhancing the model’s predictive accuracy. In summary, our work demonstrates the considerable promise of deep learning models and alternative unstructured data in predicting startup success and sets the stage for future advancements in this research area. 1 Introduction The prediction of startup success is a crucial task for various stakeholders, including investors, entrepreneurs, and policymakers, as it has significant implications for resource allocation and decision-making. It is estimated that approximately 90% of startups fail within their first five years, a failure rate that has remained relatively constant over the past few decades, despite considerable advancements in technology and business practices. Consequently, the accurate prediction of startup success can assist investors in more effectively allocating their resources and enable entrepreneurs to make better-informed decisions. Recently, the proliferation of data from sources such as Crunchbase has intensified interest in the application of machine learning techniques for the prediction of startup success. Machine learning models can harness various types of data, encompassing funding history, market trends, team composition, and social media activity, to identify patterns and generate predictions. This study presents two distinct methodologies for predicting startup success: a supervised deep learning approach leveraging multiple data sources, and a ranking-based approach focusing on the identification of characteristics common to successful startups and investors. The supervised approach entails collecting and labeling data, constructing a prediction model, and evaluating its performance. In contrast, the ranking-based approach centers on identifying startups and investors that exhibit shared characteristics with successful ones. Our train dataset consists of 34,470 companies The primary novelty of this research lies in the application of deep learning techniques and the integration of heterogeneous input data types. A crucial feature of our research is the simulation of fund operations based on historical data, resulting in a projected 14x capital growth of the fund’s portfolio. As per machine learning metrics, our model exhibits a robust 86% ROC_AUC. The remainder of this paper is organized as follows: Section 2 reviews the related works in the area of startup success prediction and machine learning. Section 3 describes dataset collection, preprocessing, and feature selection. Section 4 presents the experimental results of the supervised approach. Section 5 describes some other ideas about company and investor scoring. Finally, Sections 6 and 7 provide the conclusion of the study and discuss prospective research avenues in this domain. This paper is available on arxiv under CC 4.0 license. Authors: (1) Mark Potanin, a Corresponding (authorpotanin.m.st@gmail.com); (2) Andrey Chertok, (a.v.chertok@gmail.com); (3) Konstantin Zorin, (berzqwer@gmail.com); (4) Cyril Shtabtsovsky, (cyril@aloniq.com). Authors: Authors: (1) Mark Potanin, a Corresponding (authorpotanin.m.st@gmail.com); (2) Andrey Chertok, (a.v.chertok@gmail.com); (3) Konstantin Zorin, (berzqwer@gmail.com); (4) Cyril Shtabtsovsky, (cyril@aloniq.com). Table of Links Abstract and 1. Introduction Abstract and 1. Introduction 2 Related works 2 Related works 3 Dataset Overview, Preprocessing, and Features 3 Dataset Overview, Preprocessing, and Features 3.1 Successful Companies Dataset and 3.2 Unsuccessful Companies Dataset 3.1 Successful Companies Dataset and 3.2 Unsuccessful Companies Dataset 3.3 Features 3.3 Features 4 Model Training, Evaluation, and Portfolio Simulation and 4.1 Backtest 4 Model Training, Evaluation, and Portfolio Simulation and 4.1 Backtest 4.2 Backtest settings 4.2 Backtest settings 4.3 Results 4.3 Results 4.4 Capital Growth 4.4 Capital Growth 5 Other approaches 5.1 Investors ranking model 5.1 Investors ranking model 5.2 Founders ranking model and 5.3 Unicorn recommendation model 5.2 Founders ranking model and 5.3 Unicorn recommendation model 6 Conclusion 6 Conclusion 7 Further Research, References and Appendix 7 Further Research, References and Appendix ABSTRACT Predicting startup success presents a formidable challenge due to the inherently volatile landscape of the entrepreneurial ecosystem. The advent of extensive databases like Crunchbase jointly with available open data enables the application of machine learning and artificial intelligence for more accurate predictive analytics. This paper focuses on startups at their Series B and Series C investment stages, aiming to predict key success milestones such as achieving an Initial Public Offering (IPO), attaining unicorn status, or executing a successful Merger and Acquisition (M&A). We introduce novel deep learning model for predicting startup success, integrating a variety of factors such as funding metrics, founder features, industry category. A distinctive feature of our research is the use of a comprehensive backtesting algorithm designed to simulate the venture capital investment process. This simulation allows for a robust evaluation of our model’s performance against historical data, providing actionable insights into its practical utility in real-world investment contexts. Evaluating our model on Crunchbase’s, we achieved a 14 times capital growth and successfully identified on B round high-potential startups including Revolut, DigitalOcean, Klarna, Github and others. Our empirical findings illuminate the importance of incorporating diverse feature sets in enhancing the model’s predictive accuracy. In summary, our work demonstrates the considerable promise of deep learning models and alternative unstructured data in predicting startup success and sets the stage for future advancements in this research area. 1 Introduction The prediction of startup success is a crucial task for various stakeholders, including investors, entrepreneurs, and policymakers, as it has significant implications for resource allocation and decision-making. It is estimated that approximately 90% of startups fail within their first five years, a failure rate that has remained relatively constant over the past few decades, despite considerable advancements in technology and business practices. Consequently, the accurate prediction of startup success can assist investors in more effectively allocating their resources and enable entrepreneurs to make better-informed decisions. Recently, the proliferation of data from sources such as Crunchbase has intensified interest in the application of machine learning techniques for the prediction of startup success. Machine learning models can harness various types of data, encompassing funding history, market trends, team composition, and social media activity, to identify patterns and generate predictions. This study presents two distinct methodologies for predicting startup success: a supervised deep learning approach leveraging multiple data sources, and a ranking-based approach focusing on the identification of characteristics common to successful startups and investors. The supervised approach entails collecting and labeling data, constructing a prediction model, and evaluating its performance. In contrast, the ranking-based approach centers on identifying startups and investors that exhibit shared characteristics with successful ones. Our train dataset consists of 34,470 companies The primary novelty of this research lies in the application of deep learning techniques and the integration of heterogeneous input data types. A crucial feature of our research is the simulation of fund operations based on historical data, resulting in a projected 14x capital growth of the fund’s portfolio. As per machine learning metrics, our model exhibits a robust 86% ROC_AUC. The remainder of this paper is organized as follows: Section 2 reviews the related works in the area of startup success prediction and machine learning. Section 3 describes dataset collection, preprocessing, and feature selection. Section 4 presents the experimental results of the supervised approach. Section 5 describes some other ideas about company and investor scoring. Finally, Sections 6 and 7 provide the conclusion of the study and discuss prospective research avenues in this domain. This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv

Startup Success Prediction and VC Portfolio Simulation Using CrunchBase Data

POS Financing vs. BNPL: Understanding the Differences and Evolution of Solutions

$10M for Founders, AI Agents, and More. Plus, Can AI Outperform Human Therapists?

'Multimodal is the most unappreciated AI breakthrough' says DoNotPay CEO Joshua Browder

DoNotPayCEO জোশুয়া ব্রাউডার বলেছেন 'মাল্টিমোডাল হল সবচেয়ে অপ্রশংসিত এআই ব্রেকথ্রু'

„Multimodal ist der am wenigsten gewürdigte KI-Durchbruch“, sagt DoNotPayCEO Joshua Browder

"El multimodal es el avance de la IA menos apreciado", dice el director ejecutivo de DoNotPay, Joshua Browder

« Le multimodal est la percée la plus méconnue de l'IA », déclare Joshua Browder, PDG de DoNotPay

DoNotPay के सीईओ जोशुआ ब्राउडर कहते हैं, 'मल्टीमॉडल सबसे कम सराहना प्राप्त AI सफलता है'

「マルチモーダルは最も評価されていないAIのブレークスルーだ」とDoNotPayのCEOジョシュア・ブラウダー氏は語る

DoNotPayCEO Joshua Browder는 '멀티모달은 가장 인정받지 못한 AI 혁신'이라고 말했습니다.

‘Multimodal é o avanço de IA menos apreciado’, diz Joshua Browder, CEO da DoNotPay

«Мультимодальные перевозки — это самый недооцененный прорыв в области искусственного интеллекта», — говорит генеральный директор DoNotPay Джошуа Браудер.

DoNotPayCEO'su Joshua Browder "Multimodal, en takdir edilmemiş yapay zeka atılımıdır" diyor

'Đa phương thức là bước đột phá về AI không được đánh giá cao nhất', Joshua Browder, CEO của DoNotPay, nói

DoNotPay 首席执行官 Joshua Browder 表示，“多模式是最未被重视的人工智能突破”

213 Stories To Learn About Writing Prompts

Introduction Mobile banking is not what it used to be just a few years ago. Customers around the world are discovering new kinds of experiences that minimize visits to physical branches (or eliminate them altogether) in favor of hyper-convenient, feature-rich apps that let you track expenses, build a budget, or even trade stocks and crypto. quicker to welcome these new experiences, like the EU, Russia and Latin America. On the other hand, we can see some of the markets, like the US, resisting change owing to legacy banking systems and stricter legislation. But the common truth is that mobile banking is not only here to stay - it will never be the same again. In this article we will look at some of the current mobile banking trends that are redefining your day-to-day financial operations, as well as new approaches to building mobile banking apps and their potential future. Trends Security Let’s first talk about the issue that prevents someone from trying mobile banking in the first place: the safety of their data and funds. As mobile devices introduced new security features like on-device encryption and biometric authentication (first with fingerprints, later with the face and even with your iris), mobile banking has seen an explosion in adoption since it first became a concept with the breakthrough of the smartphone in 2008. Biometrics But progress in that area hasn’t stopped. On the contrary, cybersecurity engineers are constantly introducing new security measures aiming at preventing attacks from happening in the first place and boosting devices’ underlying security. The pandemic has exacerbated the need for security methods that rely on non-fungible traits of the bank account owner rather than passwords or secret codes that can be copied. For example, voice recognition technology has made great strides in becoming available for use in the mobile banking context, and some companies have successfully launched pilots. At Sinara Bank, we aim to build trust in our biometric solutions as we adopt the “One-time contact” approach to offering our retail banking services. This means the client needs to complete a one-time biometric authentication procedure in our branch, and subsequent banking services will be provided on a remote-first basis. We are also experimenting with offering initial biometric authentication without any branch visits at all, and are seeing a positive dynamic with adoption. Voice biometrics is increasingly getting adopted by US bank call centers to securely authenticate account holders who can finally ditch learning a secret phrase or punching in their credit card number on the line. HSBC UK claims it was able to prevent almost £1 billion in customer funds from being stolen by malicious actors thanks to its adoption of voice authentication technology. These “voiceprint” models can be effectively scaled to mobile apps and even combined with existing biometric authentication methods like fingerprint and face recognition to create a unique biometric identity for every customer that is simply impossible to spoof. Real-Time Monitoring Banks also turn to Big Data models to learn how to identify and stop attacks in real time by monitoring millions of active processes across branches and security systems and identifying patterns that would indicate an attack vector. Data analytics derived from banking mobile apps can be a principal contributor to ensuring the security of the banking system. Features Banking apps are more feature-rich than ever. Here are some of the innovations that keep banning customers coming back: Superapps Banking apps have evolved from simply allowing users to check their balance and conduct basic transfer operations to offering the full scope of banking services and even third-party integrations that simplify everyday tasks and empower a healthier financial lifestyle. These bank apps offer instant chat-style customer support, built-in loan instruments and financial expenses dashboards that help customers track their spending habits and plan ahead, automatic bill payment, and sometimes even public transportation payment options, airline tickets and cinema and theater tickets, typically offered as part of the bank’s loyalty program. Of course, customers increasingly find banking apps with better UX to be more appealing. According to internal research by Sinara Bank, only 7% of our clients took advantage of remote APR deposits in 2019. In 2022, that number was 60%. We are seeing a similar dynamic with pre-approved loans as well. This year alone, our app’s MAU and DAU have jumped 11% and 20% respectively. In addition to that, almost all of our clients transitioned to mobile-only banking, abandoning desktop versions and bank branch visits altogether, with just under 10% of our client base sticking to the legacy desktop web application to manage their finances. Overall penetration of our mobile banking app skyrocketed from 40% to 75% over the past few years, with even the most skeptical groups like elderly depositors finally moving on. We can confidently say that clients overwhelmingly prefer a remote-first banking approach, and we responded accordingly with all new features being remote and mobile-only. More Ways To Pay NFC payments are arguably the most convenient way to pay for goods and services - just tap with your phone and you’re done. It’s seamless, secure and blazing fast, but also not the only way to pay with a smartphone. The banking apps of 2023 need to support more ways of payment to offer customers choice and flexibility, plus, retail chains may create special cashback programs that incentivize customers to use one payment method over the other. QR code payments are a fantastic alternative to NFC payments for customers who, for example, don’t have an NFC-enabled device. This way, they can quickly pay by pointing their camera at the QR code at the checkout counter and deduct funds directly from their bank account. Another popular way to pay is digital wallets and bank-enabled BNPL services which have skyrocketed in recent years as players like Klarna, ShopPay and Afterpay introduced simple loan-based payments on websites, typically with zero interest. Banks are creating hybrid services that combine easy-to-use digital wallets that do not require card credentials with BNPL options that incentivize quick purchases and create an additional revenue stream. Instant Transfers Gone are the days when you needed someone's sixteen-digit bank account number and other lengthy details to conduct a basic wire transfer, which would be executed within several banking business days. At Sinara Bank, we introduced instant operations like C2C, C2B and me-2-me pulls several years ago. Now, we’ve added phone number and QR code transfers between individuals and organizations. We already hit a turnover of $4 million on these operations, up from zero, and we are currently testing instant phone number-based cross-border transfers as well. This trend is global: for example, the US’ Federal Reserve is currently testing its instant transfer system called FedNow that would finally allow the aging US banking system to catch up with the modern world. Of course, other phone number-based transfer applications like Zelle aren’t quick to give up their market shares. Virtual Assistants In the advent of virtual assistants, users rely on Siri, Google Assistant, and even on brand new products like Bing Chat to simplify their interactions with devices and boost productivity, and banks are implementing the same functionality in banking apps to speed up routine tasks like sending quick transfers to relatives or paying bills. Artificial intelligence AI is all the rage, and banks can take advantage of it to perform deeper financial analysis of its customers and offer more personalized financial products. Some companies like Affirm already use AI to accurately score potential borrowers with limited credit history. Crypto and Assets Digital currency is not only for enthusiasts anymore. Governments around the world are flocking to legalize and take advantage of all that digital assets have to offer. Even the United States is piloting a so-called “digital dollar” that should unlock next-generation banking capabilities for millions of retail clients. Sinara Bank is proud to be one of the Russian banks partaking in the digital ruble pilot program. But industry-wide adoption does not stop with analogs of regular currency - many banking apps are starting to integrate with popular cryptocurrencies like Bitcoin, Ethereum and USDT. Some of the leading global banks that are opening their doors to crypto include Revolut, Ally Bank, USAA and even Bank of America., Banking-as-a-Service Neobanks have recently sprung up across the financial landscape to provide competition to traditional banks by undercutting them and introducing features previously unheard of. These novel institutions often lack branches and boast convenient apps with features that younger customers have come to expect from digitally native financial services like PayPal. In response, banks are turning to Banking-as-a-Service (BaaS) platforms to create customized neobank-like experiences that rely on their own infrastructure, diversify their offerings and attract more customers. An everyday example of BaaS solutions are airline credit cards that one might use regularly to accumulate miles and fly cheaper. These cards are issued by banks, not airlines, and in this scenario, both of them reap the benefits. Another example of BaaS are neobank-esque financial companies like Chime that rely on the infrastructure of a legacy bank (in this case, Bancorp Bank, N.A. and Stride Bank, N.A.) to provide services that the underlying banks do not, thus netting those banks more clients. Open Banking Similarly to BaaS, open banking involves the bank opening up some of its tightly kept infrastructure to a third party, but unlike BaaS, it is designed to integrate information from your account with a third party app, like a financial management and planning app that keeps track of your expenses for you. An example of this is Wallet by BudgetBakers, which can synchronize with your bank account to unlock insights into your spending, projected income and overall financial outlook. Conclusion Any banking app can check your balance. So if you want your app to stand out in this increasingly crowded feel, think of ways to pack as many features as possible in the simplest app possible. The future of mobile banking is that of peace-of-mind security that customers don’t have to think twice about, and of infinite flexibility that allows them to manage their entire financial life from a single app. And with more artificial intelligence tools becoming available every day, it’s up to the banks and app developers to take advantage of it to create apps customers will rely on throughout their entire financial journey.

Mobile Banking: Predictions For Mobile Applications Development

Assuming you already have a product that has a great product-market fit, meaning customers have an inherent demand for your product without any marketing effort, there are still a variety of approaches to take to achieve growth. Is a massive big marketing campaign always the best way to grow? How about shaping or creating a product that drives growth? To do this, you need to develop a deep understanding of your customer base and what drives their behaviour. One way to do this is to analyze product metrics, such as usage frequency or customer retention rates. This article will guide you through some unique approaches used by product-led companies as examples. By understanding what drives customer behaviour, you can then shape your product to better meet their needs and ultimately drive growth. 1. PRODUCT METRICS AND GROWTH METRICS Product Metrics A product serves as a solution to customers' problems, acting like a black box. When new customers interact with the product, it processes them into active users, profit, support requests, and more. Product metrics show how the product converts new users into other metrics, such as: Product awareness and product adoption (click for more information) here , which how the product converts new users into active users Retention displays Lifetime value (LTV), which measures the profit generated by new users for the entire duration of their service use Purchase conversion, which indicates how the product converts new users into "higher value" customers (i.e., customers willing to pay for the product or generate revenue) Growth Metrics On the other hand, If product metrics describe the product itself, then growth metrics describe the business built around it. Growth metrics are derived from product metrics and the number of new users, which are the primary levers influencing overall business growth. Here are some examples of growth metrics: or daily active audience (new users * retention) DAU : There are multiple ways to create a profit Profit Increase the number of new users to generate more revenue. This can be achieved through multiple marketing techniques such as growth hacking, word of mouth, or creating an exclusive community (such as Clubhouse). However, this strategy could lead to massive failure if the company fails to retain new users. While this may increase revenue in the short term, it could also result in more forced churn. Raise the price of the product to increase revenue. For example, Lyft increased its prices significantly in 2017 in an attempt to increase profits and become more competitive with Uber. However, the price increases were met with backlash from Lyft riders, and many riders began to switch to Uber. As a result, Lyft's ridership declined, and the company's profits began to fall. In 2019, Lyft went public, but its IPO was a disappointment, and its stock price fell sharply. Lyft has continued to struggle financially, and it is now facing increasing competition from other ride-sharing companies, such as Uber and Didi. My preferred approach, in this case, is to focus on acquiring users through product development while also considering their LTV lifetime value Profit can be calculated = (number of new users * LTV) Number of new subscribers (new users * subscription conversion rate) In short, I believe creating a product that fuels growth and paying attention to the connection between product metrics and growth metrics are both effective techniques that many successful product-led companies use. 2. LEVERAGE PRODUCT METRICS FOR GROWTH Let's look at two examples of product-led companies that drive sustainable growth and eventually become profitable by leveraging product metrics such as retention and LTV (lifetime value). CASE STUDY 1: Zilch - Europe's Fastest Unicorn (Became a Unicorn Within 9 Months of Full Launch) : The big names in the industry, such as Klarna and Clearpay, entered the market within the last five years to offer customers an alternative to credit cards. For example, with Klarna's payment method, you can purchase anything on Amazon and split the transaction into four instalments over time. Story (Buy Now Pay Later) industry by optimizing payment points and Ad monetization. Zilch has disrupted the BNPL Zilch offers a similar alternative to borrowing money through the following: A virtual card that allows customers to make debit or credit purchases (pay in four instalments over time). It is flexible and can be used anywhere and anytime, reducing the lengthy process of integrating each merchant as it is with Klarna. This creates a great market fit. Defined well product-market-fit: Shaping the product to higher retention and higher conversion rate. Zilch offers in-app ads to unlock offers. Customers can go to the app and unlock any merchant they want to purchase from and get a 0% interest rate when using a credit product. by providing the benefit to the customer: Zilch turns the ad money paid by the merchant into savings on the interest/fee that the customer has to pay. Higher retention in the phase of educating customers: It is also a smart move to save on 3DS costs when customers choose to unlock the offer in the app and verify their authorization to the transaction (2-3% of payment cost). Knowing the cost and leverage by product feature CASE STUDY 2: turns to profit in July 2023 Uber : Uber is an on-demand transportation technology app that allows customers to easily book the most convenient and fastest mode of transportation. Since its launch in 2009, Uber has disrupted the traditional taxi industry. Its strategy is to hack growth by acquiring as many drivers and customers as possible to adopt the product in the market, and then slowly tightening the rules to optimize the customer journey and experience. Story The downside of this strategy is that for a long time, Uber burned through a huge amount of funds from big names to fuel their growth. As a result, they captured a large market share but struggled to become profitable. However, Uber turned a profit in July 2023.
There are several good approaches to consider: Cut costs by 20% during COVID. Run as lean as possible: Uber sold off non-strategic businesses, such as its self-driving unit, which held a $400M stake in Careem and a $392M stake in Zomato. Focus on what's most important: Leave markets where you're not the #1 or #2 player (e.g., abandon food delivery in Italy) Only play games you can win: Uber leaned into UberOne, a Prime-like membership that includes: But most importantly, create a new product that significantly increases LTV: : In-app popup notifications and direct discounts on trips to encourage action. Awareness : A free trial for the first 1-3 months (depending on the market). Adoption Retention: Over 60% of customers continue to engage (and pay) the following month after their first purchase, resulting in a 12M member increase (2x YoY). This results in lower margins but significantly higher retention and, therefore, a much longer LTV. In the long run, this approach is more profitable and even turns a profit 2-3 years earlier than predicted. In summary, while a big marketing campaign may seem like the obvious solution to drive growth, it is not always the most effective method. Instead, it is important to focus on to achieve higher retention rates and a longer lifetime value for your customers. creating or shaping your product However, it is also worth considering other value metrics that can come into play, such as customer satisfaction, brand loyalty, and market share. By taking a more holistic approach to your business strategy, you can ensure long-term success and sustainability in a constantly evolving market.

Empowering Growth through Product Metrics

পণ্য মেট্রিক্স মাধ্যমে বৃদ্ধি ক্ষমতায়ন

Förderung des Wachstums durch Produktkennzahlen

Impulsando el crecimiento a través de métricas de productos

Stimuler la croissance grâce aux métriques de produit

उत्पाद मेट्रिक्स के माध्यम से विकास को सशक्त बनाना

製品指標を通じて成長を促進する

제품 지표를 통한 성장 강화

Capacitando o crescimento por meio de métricas de produto

Ürün Metrikleri Yoluyla Büyümeyi Güçlendirmek

Thúc đẩy tăng trưởng thông qua các chỉ số sản phẩm

通过产品指标促进增长

Let's learn about via these 64 free stories. They are ordered by most time reading created on HackerNoon. Visit the to find the most read stories about any technology. Retail Technology /Learn Repo 1. How E-Commerce is Getting Smarter with Artificial Intelligence Artificial Intelligence (A.I.) is the future. 2. Startup Interview with Edris Bemanian, Engage3 CEO Engage3 will transform the way that products are bought and sold by bringing human values into pricing decisions. 3. Why Retail Stores Are More Vulnerable Than Ever to Cybercrime As more security features rely on the internet, the potential for cyber exploits increases, though this isn't the only reason retail stores are susceptible. 4. AI-Powered Predictive Merchandising is Shaping the Future of Shopping As long as consumers choose a hybrid shopping model, merchandising will keep driving sales. 5. How Retail Tech Startups are Providing E-commerce Brands With a Competitive Advantage The rapid rise of retail tech has touched almost every part of shopping; from discovery apps like Yelp to Buy now pay later brands like Klarna and Afterpay. 6. Discover How IoT is Transforming the Retail Industry IoT enables data sharing among all the devices in the network, irrespective of their medium of connectivity. 7. Automate Pricing With a Good Price Optimizer Software Setting product prices is a complex process, involving so many factors. Using good price optimization solutions helps make this task easier and more effective. 8. A Success Story for Asian Retailers Acme Inc. (Operating Department Store in Singapore) 9. How India Revolutionised its Digital Payment System UPI has revolutionised the way Indians used to look at digital payment systems. In four years, it has surpassed Visa and MasterCard. 10. Automation & Fashion on Demand: Producing as Ordered Some brands are choosing to go back in time by using a made-to-order business model. Why aren't other brands making the leap? 11. Shelf Edge Technology: Digital Price Tags Using Renewable Energy Sustainable, cost-effective, and consumer-friendly: digital price tags are entering the fashion industry through shelf-edge technology. 12. How to Build Your Own Automated Self Checkout Service Brick-n-mortar retailers, learn how to implement an AI-powered autonomous checkout from smart vending machines and kiosks to full store automation. 13. BIG ALICE is Revolutionizing Retail via 3D Full-Body Scanners BIG ALICE is a scanning studio that can provide 3D renderings and accurate measurements of any human or object. 14. A Complete Guide To SKU Management For Retailers SKU management is the process of creating, organizing, and perfecting an alphanumeric SKU system for the items in your inventory. SKUs give inventory details. 15. The Digital Shopper: 4 Retail Tech Trends That Will Stay Post-Pandemic Retailers are perfectly poised to adapt with ease as we move into a post-pandemic world, having experienced such a necessary yet dizzying acceleration in digital transformations over the past year. 16. Smart Alternatives to Sampling Campaigns in Supermarkets During COVID-19 Find out how you can replace sampling campaigns during the COVID-19 pandemic to be safe and still engage with customers. 17. How Can Enterprises Utilize Edge Computer Vision? Business applications of computer vision technology for Enterprises, retail analytics, edge computing, intrusion detection and monitoring 18. Welcome to California, Where Your Face Is Your Credit Card Whether you are craving a burger or Chinese food tonight, there is no need to reach for your wallet or phone to buy it. Food vendors in California are embracing facial recognition — technology that lets you pay with a smile. 19. Top 7 Online Certificate Courses for Retail Pros We all know how essential it is for any professional to keep upgrading their skills to stay on top of their game. I've decided to compile a list of useful online courses (both free and paid) to help you further your career if you are a pricing, brand or category manager in need of mastering the power of technology. 20. Zoey The AI: A Friend to “Corona Brides” We experienced digital transformation on an unprecedented scale in 2020. Here’s how artificial intelligence is transforming online shopping. 21. Everything You Must Know About the Business Model of Walmart: World's Largest Retail Giant Let’s learn about the business model of Walmart. How did the world's largest retailer provide Everyday Low Prices yet earn $ 572B as revenue for 2022? Read on. 22. 40% Americans Do Not Know What Affects Their Credit Score Your customers’ credit score is one of the most important numbers of their financial lives. This three-digit number is the most used credit scoring model by lenders for evaluating a borrower's creditworthiness or the likelihood that they’ll repay the money. 23. Innovative Retail Technology For Brick and Mortar Shops Find out the Top 5 Retail Technologies brick and mortar shops should adopt in 2021 and how VR, robots, and other retail tech can help them. 24. How Artificial Intelligence Can Be Beneficial in the Retail Sector A look at how artificial intelligence can be beneficial in the retail sector 25. Bricks-and-Clicks, or Why Omnichannel Is the Future of Retail In-store and online retail have always stood in passive opposition to each other, but in the first quarter of 2019 this confrontation took an especially dramatic turn. Multiple mass media outlets published articles with agitated headlines like “It's Official: "Clicks" Have Topped "Bricks" (CBS News) or “Online Shopping Overtakes a Major Part of Retail for the First Time Ever” (CNBC), which proclaimed the final surrender of bricks to clicks. 26. How AI is Changing the Retail Industry Data is the crucial information businesses need to remain profitable. AI can bridge the gap between unused data and those profits in the retail sector. 27. The Retail Evolution: Customers Demand Enhancements to the Shopping Experience Andreas Hassellof, Founder and CEO of Ombori, explores how changing customer behaviors impact retail, and drive retail technology innovation. 28. 5 Trends Changing Retail Enterprise Resource Planning in 2021 What are the main ERP trends in retail? Feel free to explore this guide to keep up with the best updates to potentially implement them into your business. 29. 8 Ways ERP Systems Can Maximize the Profits of Retail Businesses Large retailers use ERP software to make sure their operations are running smoothly. Such tools are designed to address the problems faced by retailers today. 30. The Future of Retail: The Convergence of Physical and Online Stores Explore the future of retail and the merging of physical and online shopping experiences. Discover the latest trends and technologies shaping the way we shop. 31. 4 Reasons Why Your Business Should Accept Mobile Payments In an age where our daily lives are interconnected to technological advancement, it may be time to consider using a mobile device to make payments while on the go. We live in a world operating on ease and immediate response, so it may be time to convert towards this new, innovative option. 32. Augmented Geomarketing: The Start of a New Era or Just an Evolution? Why the Augmented Geomarketing shall change the real sector and its business? 33. What Makes "Good" Fashion Image Tagging Fashion image tagging is infamously tedious for eCommerce. But, how can AI help create accurate tags--and go a step beyond in understanding fashion information? 34. Technology Should Enable Craftsmen To Go Back To Doing What They Do Best The pandemic (you know the one) has disrupted stores and restaurants in a way no one could have expected at the start of 2020. Health scare, mass unemployment, e-commerce, Amazon competition, ballooning debt… we didn’t start the fire, it was always burning… but now there are ambers everywhere and we’ve got to get to work to save the good china. 35. How Technology Is Enabling Traditional Retailers To Adapt To A New Normal Technology has advanced rapidly when you look at how far we've come in the last decade or two, even when comparing the mobile phones of 2000 versus today. It's changed the world. Something else changing the world is the COVID-19 pandemic. As we get used to our new normal, technology will play a major role. For retailers, technology will be the most important tool in their journey to survive. 36. A World without Digital Technologies But what if digital technologies never existed? What would the world be like? 37. Why the Gap Needs Kanye West Can Kanye West help the Gap dig itself out of deep hole? 38. AI in the Retail Industry: 10 Computer Vision Startups to Follow in 2021 AI-enhanced retail holds the promise to eliminate operational inefficiencies and provide shoppers with frictionless in-store experiences. 39. What Chinese Retail Trends Tell Us About the Future of E-Commerce Amazon, mobile, A.I… there are dozens of new threats, technologies and processes a strategy executive must keep in mind to stay ahead of the curve when faced with skydiving sales. 40. Geofencing Marketing: Beginners Guide Have you considered the idea of using geofencing marketing in your business strategy?  It is one of the best marketing tactics for those retailer stores businesses. Geofencing helps you reach out to potential customers in your confined area. 41. The Retail CIO’s Guide to Mobile Device Management Strategy Are you in retail and planning to make mobile part of your strategy? Do you follow a bring-your-own-device (BYOD) policy and need to separate business and personal data on the same devices? If so, mobile device management (MDM) will become an important strategic consideration for your executive team. 42. NRF 2022: Technology That's Shaping Retail These technologies are expected to become commonplace within the retail industry within a matter of time. 43. New Research Paper May Indicate That Visa is Developing a Retail Blockchain Product Cryptology ePrint Archive has published a paper, entitled ‘LucidiTEE: Policy-compliant Fair Computing at Scale’, credited to a trio of staff members working for Visa and Visa Research by the names of Rohit Sinha, Sivanarayana Gaddam, and Ranjit Kumaresan. 44. Busting Financial Myths: "The Ignorant Retail Investor" If you Google "ignorant retail traders," you'll find mentions on the Financial Times, Seeking Alpha, Wired, Berkshire Money Management, The Street, and even The South China Morning Post. 45. Amidst COVID-19 Restrictions, How Can AI Help Retailers? COVID-19 has changed the world of retail almost overnight. Its impact on e-Commerce is creating challenges to online retailing, selling & services that no one has imagined in the first quarter of 2020-21. 46. How to Get Started with Amazon IVS and Amazon Personalize in Retail This blog will walk through a detailed example of how to configure and deploy live streaming and personalization into an ecommerce site. 47. How Artificial Intelligence Is Shaping The Retail Industry With 96% of Americans shopping online and the rise of AI lead cashier-less retail stores such as one of Amazon’s 15 Go stores, Artificial Intelligence (AI) has become a key element in the digitalization of in-store retail by personalizing the customer experience and creating a more engaged business-to-consumer interaction. For retail companies, AI creates an opportunity to bridge the gap between virtual and physical sales channels. 48. Ultimate Guide to Price Matching for Retailers Price matching might sound like the ultimate pricing strategy that your business should include after you hear about price match Walmart policy. It is true that many consumers put the price as their primary factor to consider when they purchase an item whether it is online or in-store. 49. Predicting Popularity of Retail Products Using AWS SageMaker, AWS Marketplace & AWS Data Exchange This blog is aimed at guiding users to understand how they can leverage AWS SageMaker, AWS Marketplace and AWS Data Exchange to deduce smarter decisions. 50. How To Use Technology To Enhance Your In-Store Marketing Strategy Robots, AI, and other tech are transforming retail experiences. Find out what technologies best suit your in-store marketing efforts and how you can use them. 51. Innovative Solutions That Will Change The Shopping Experience How can fashion brands enter the digital world using AI? Read my new interview with a maker of a highly-innovative technology that makes it a reality. 52. 5 Ways AI is Improving Supermarkets Follow the supermarket industry trends and take your existing retail software solutions to the next level with AI 53. The New Frontier of Price Optimization What would be the price of our product or service? This question has bothered businesses forever. Several pricing models have been spawned as a result. But the concept of price optimization is a fairly new one. At least to businesses that are not in the hospitality or airline sector. 54. Use Cases and Roll-Out Tips for Image Recognition in Retail Heavily shattered by the pandemic, the retail sector is on the lookout for innovation. 55. Blockchain will Disrupt the Shopping Industry: A 2020 market overview Times have changed, and businesses either need to change with them or die. Long gone are the days of niche brick-and-mortar stores, and as Millenials and GenZ consumers start to earn more money, the e-commerce market world needs to shift as well. In order to survive, stores became brands, enticing their customers to remain loyal and shop with them even when they could find better deals elsewhere. 56. An Introduction to Livestream Shopping The concept of live shopping goes back to the 80s and builds on the idea of video shopping. 57. The Problem(s) With Amazon GO 58. How to Offer Customers an Amazing Experience In-Store Find out how to offer an amazing customer experience from four top retail experts. Read their tips and try them out yourself. 59. Improve Monetization By Optimizing In-Store Analytics and Trendspotting Over the years analytics has created an important space for itself in the retail industry where it helps to bridge the gap between what retailers have to offer and what the customers want. 60. 7 Tech Trends Reshaping the Retail Industry What is the future of retail in the post-COVID-19 world? The 2021-reality trends show how technology and innovations help retailers face challenges. 61. 13 Retail Technologies That Could Help Brick-and-Mortar Businesses Learn about key retail technology trends that can help brick-and-mortar retailers sustain their businesses. Dive into the applications of innovative retail tech 62. Virtual Fitting Room Technologies To Boost Retail Sales in a Post COVID-19 World I hate shopping in brick and mortar stores. However, my interest in virtual shopping is not limited to the buyer experience only. With the MobiDev Data Science department, I’ve gained experience in working on AI technologies for virtual fitting room development. The goal of this article is to describe how these systems work from the inside. 63. Is Shopping In-Store An Experience Of The Past? Top retail experts share their knowledge and predictions on the state of in-store marketing in 2021. Check out their views on how COVID-19 affected brick and mo 64. How the Retail Industry is Implementing Machine Learning and Deep Learning Stores are changing. We see it happening before our eyes, even if we don’t always realize it. Little by little, they are becoming just one extra step in an increasingly complex customer journey. Thanks to digitalisation and retail automation, the store is no longer an end in itself, but a mean of serving the needs of the brand at large. The quality of the experience, a feeling of belonging and recognition, the comfort of the purchase… all these parameters now matter as much as sales per square meter, and must therefore submit themselves to the optimizations prescribed by Data Science and its “intelligent algorithms” (aka artificial Intelligence in the form of machine learning and deep learning). Thank you for checking out the 64 most read stories about Retail Technology on HackerNoon. to find the most read stories about any technology. Visit the /Learn Repo

64 Stories To Learn About Retail Technology

Let's learn about via these 50 free stories. They are ordered by most time reading created on HackerNoon. Visit the to find the most read stories about any technology. Retail /Learn Repo 1. How Computer Vision is Taking Over Manufacturing and Retail AI continues to take over almost every industry ripe with data. Computer vision expands AI’s capabilities, allowing machines to not only process data, but also gather information on their own, which unlocks completely new opportunities for businesses. According to research by ABI, total shipments of computer vision sensors and cameras will reach 16.9 million by 2025. 2. Discover How IoT is Transforming the Retail Industry IoT enables data sharing among all the devices in the network, irrespective of their medium of connectivity. 3. How Retail Tech Startups are Providing E-commerce Brands With a Competitive Advantage The rapid rise of retail tech has touched almost every part of shopping; from discovery apps like Yelp to Buy now pay later brands like Klarna and Afterpay. 4. The New Frontier of Price Optimization What would be the price of our product or service? This question has bothered businesses forever. Several pricing models have been spawned as a result. But the concept of price optimization is a fairly new one. At least to businesses that are not in the hospitality or airline sector. 5. 5 Steps To Build Your Dynamic Pricing Engine With the emergence of online platforms, B2B businesses have had to reconsider their pricing strategies. But, these same technologies help the organizations create dynamic B2B pricing models that bring substantial profits if implemented correctly. For example, an integrated sales and B2B pricing software can help sales reps negotiate with customers and reduce the processing period. 6. How Can AR Furniture Apps Simplify & Boost Sales: GFG Use Case AR furniture apps have proved its tremendous impact on business. Have you heard about Houzz AR app used by more than a million users? It made customers 11 times more inclined to buy an item and spend 2.7 more time on navigating it. So how can you create a robust app like this? What problems could you solve with another AR app? 7. An Artist’s Homing Beacon to Creativity: Connecting with the Universe is The Ultimate Transcendence Join me on a roller coaster ride of lessons learned, winning Noonies 2022nfor Kubernetes, DevOps, Cheeky Genius of the Year, Retail,  & spiritual transcendence. 8. Customer Support: Is Your Team Ready for the Holidays? This year’s holiday shopping season will be different due to altered consumer behavior from COVID-19. Some things though will stay the same, like the increased pressure on your customer support team. 9. Drop Shipping Alternatives to AliExpress in the US This article will explain why AliExpress isn’t always the best option, and what other options there are if you think AliExpress isn’t for you. 10. Busting Financial Myths: "The Ignorant Retail Investor" If you Google "ignorant retail traders," you'll find mentions on the Financial Times, Seeking Alpha, Wired, Berkshire Money Management, The Street, and even The South China Morning Post. 11. A Complete Guide To SKU Management For Retailers SKU management is the process of creating, organizing, and perfecting an alphanumeric SKU system for the items in your inventory. SKUs give inventory details. 12. Million Dollar Question: Should Retail Investors Get into DeFi for Money Legos? The crypto industry offers users a spectrum of investment tools: synthetic assets, liquidity pools, index tokens, lending solutions, yield farming, hodling, etc. From among the big list, yield farming stands out the most because it promises the highest returns promised by any project. Coming from the traditional financial environment with low interest rates, beginners and small investors are drawn to the idea of quick gains, requiring just a few clicks to start making profits. 13. Bricks-and-Clicks, or Why Omnichannel Is the Future of Retail In-store and online retail have always stood in passive opposition to each other, but in the first quarter of 2019 this confrontation took an especially dramatic turn. Multiple mass media outlets published articles with agitated headlines like “It's Official: "Clicks" Have Topped "Bricks" (CBS News) or “Online Shopping Overtakes a Major Part of Retail for the First Time Ever” (CNBC), which proclaimed the final surrender of bricks to clicks. 14. AI-Powered Predictive Merchandising is Shaping the Future of Shopping As long as consumers choose a hybrid shopping model, merchandising will keep driving sales. 15. Innovative Retail Technology For Brick and Mortar Shops Find out the Top 5 Retail Technologies brick and mortar shops should adopt in 2021 and how VR, robots, and other retail tech can help them. 16. Retailers Guide To Win Holiday Sales in 2020 The holiday season is all about spreading happiness. It is also the season of big sales for retail stores. Retailers have high hopes of ending the year with big profits. But just like many other things, holiday shopping will be different in 2020. And that’s why retailers have to adjust their holiday sales strategy to achieve their year-end goals. 17. D2C 101: Why the Future of Retail is Vertical Commerce and D2C Brands For as long as humanity has existed, so has commerce in the form of sharing, bartering and selling resources. Even before currency in its most rudimentary form has come into existence in Mesopotamia in 3000BC, economies were created through bartering where people would exchange goods/services based on perceived value (Person A would want to sell Item A to Person B who finds Item A valuable in return for Item B which holds more value to Person A than it does to Person B). 18. Walmart Is Now Preparing To Take Part In the Metaverse Walmart, one of the largest retailers in the world, is getting ready to create their own NFT (Non-Fungible-Token) collection. 19. How Artificial Intelligence Can Be Beneficial in the Retail Sector A look at how artificial intelligence can be beneficial in the retail sector 20. Smart Alternatives to Sampling Campaigns in Supermarkets During COVID-19 Find out how you can replace sampling campaigns during the COVID-19 pandemic to be safe and still engage with customers. 21. 40% Americans Do Not Know What Affects Their Credit Score Your customers’ credit score is one of the most important numbers of their financial lives. This three-digit number is the most used credit scoring model by lenders for evaluating a borrower's creditworthiness or the likelihood that they’ll repay the money. 22. The Retail Evolution: Customers Demand Enhancements to the Shopping Experience Andreas Hassellof, Founder and CEO of Ombori, explores how changing customer behaviors impact retail, and drive retail technology innovation. 23. 8 Ways ERP Systems Can Maximize the Profits of Retail Businesses Large retailers use ERP software to make sure their operations are running smoothly. Such tools are designed to address the problems faced by retailers today. 24. 5 Trends Changing Retail Enterprise Resource Planning in 2021 What are the main ERP trends in retail? Feel free to explore this guide to keep up with the best updates to potentially implement them into your business. 25. How To Use Technology To Enhance Your In-Store Marketing Strategy Robots, AI, and other tech are transforming retail experiences. Find out what technologies best suit your in-store marketing efforts and how you can use them. 26. Make Money With Retail-Arbitrage-As-A-Service Using Amazon and AliExpress [A How To Guide] As I detailed in this recent article surrounding Twitter automation to buy cryptocurrency during pumps and in this way-old Hackernoon and Medium discussing how I once toyed with the morality of ethical hacking for profit – it’s obvious that I often have ideas for tech businesses that don’t really get off the ground. 27. How to Improve Sales With Real-Time Price Monitoring Flexibility in pricing is the key to beating the competition 28. A Detailed Guide on Conversion Rate Optimization in E-Commerce Improve your online sales with my comprehensive guide on Conversion Rate Optimization in E-commerce. Learn about website design, UX, A/B testing, sales funnels. 29. Cybersecurity Measures to Secure Dropshipping Automation While automation is a very important innovation in dropshipping, a lot of data is involved for an effective transaction and Hackers tamper with that data. 30. 4 Reasons Why Your Business Should Accept Mobile Payments In an age where our daily lives are interconnected to technological advancement, it may be time to consider using a mobile device to make payments while on the go. We live in a world operating on ease and immediate response, so it may be time to convert towards this new, innovative option. 31. Commerce Advertising in Ukraine: How the Ads Industry Has Changed in 30 Years The Ukrainian advertising market has been affected by different events for over 30 years. I show cool and stupid Ukrainian ads examples throughout its history 32. Why the Gap Needs Kanye West Can Kanye West help the Gap dig itself out of deep hole? 33. How Technology Is Enabling Traditional Retailers To Adapt To A New Normal Technology has advanced rapidly when you look at how far we've come in the last decade or two, even when comparing the mobile phones of 2000 versus today. It's changed the world. Something else changing the world is the COVID-19 pandemic. As we get used to our new normal, technology will play a major role. For retailers, technology will be the most important tool in their journey to survive. 34. Shelf Edge Technology: Digital Price Tags Using Renewable Energy Sustainable, cost-effective, and consumer-friendly: digital price tags are entering the fashion industry through shelf-edge technology. 35. 7 Tech Trends Reshaping the Retail Industry What is the future of retail in the post-COVID-19 world? The 2021-reality trends show how technology and innovations help retailers face challenges. 36. Innovative Solutions That Will Change The Shopping Experience How can fashion brands enter the digital world using AI? Read my new interview with a maker of a highly-innovative technology that makes it a reality. 37. How to Get Started with Amazon IVS and Amazon Personalize in Retail This blog will walk through a detailed example of how to configure and deploy live streaming and personalization into an ecommerce site. 38. How AI is Changing the Retail Industry Data is the crucial information businesses need to remain profitable. AI can bridge the gap between unused data and those profits in the retail sector. 39. What Retailers Can Do with Excessive Inventory Pile Up from the Pandemic Are retailers focusing on sustainable options to move excessive inventory? 40. The Whole Shebang of McDonald’s Business Model and Branding Strategies Let’s unravel McDonald’s Business Model and Branding Strategies. Read what makes the world's largest restaurant chain by revenue profitable & recession proof. 41. Automation & Fashion on Demand: Producing as Ordered Some brands are choosing to go back in time by using a made-to-order business model. Why aren't other brands making the leap? 42. How the Use of Machine Learning is Challenging the Retail Apocalypse Whether retailers like it or not, the future of retail is here, in the form of smart algorithms. Machine learning will change much of the industry's norms, often for the better. Retail trends point to the store of the future being automated using the latest technology. Brick & Mortar, physical retail... however you like to call it, your favourite real-world store is about to get a whole lot more digital. Whether that's the best idea remains to be seen. 43. How do Loyalty Programs [un]work? Thoughts about retail marketing transformation for the fragmented post-covid market with millions of smaller retailers and re-emerging regional manufacturers. 44. A beginner’s guide to Computer Vision in Retail Anyone with a wet finger in the air will by now have heard of the “retail apocalypse” sweeping through the developed world’s malls. “People aren’t spending in stores anymore”, your quarter-informed uncle complains, before moaning that youths are too busy Instagramming their avocado brunches to burn crosses on people’s lawns. Indeed, the old retailing models aren’t working as well as they used to. The fact that they were terrible models to start with probably had something to do with it. 45. Everything You Must Know About the Business Model of Walmart: World's Largest Retail Giant Let’s learn about the business model of Walmart. How did the world's largest retailer provide Everyday Low Prices yet earn $ 572B as revenue for 2022? Read on. 46. What Chinese Retail Trends Tell Us About the Future of E-Commerce Amazon, mobile, A.I… there are dozens of new threats, technologies and processes a strategy executive must keep in mind to stay ahead of the curve when faced with skydiving sales. 47. The Digital Shopper: 4 Retail Tech Trends That Will Stay Post-Pandemic Retailers are perfectly poised to adapt with ease as we move into a post-pandemic world, having experienced such a necessary yet dizzying acceleration in digital transformations over the past year. 48. What are the Sectors Most Prone to Cyber Threats? This article presents a rundown of the industries that have been kicked in the teeth by cybercriminals amid the pandemic. 49. Technology Should Enable Craftsmen To Go Back To Doing What They Do Best The pandemic (you know the one) has disrupted stores and restaurants in a way no one could have expected at the start of 2020. Health scare, mass unemployment, e-commerce, Amazon competition, ballooning debt… we didn’t start the fire, it was always burning… but now there are ambers everywhere and we’ve got to get to work to save the good china. 50. Is Shopping In-Store An Experience Of The Past? Top retail experts share their knowledge and predictions on the state of in-store marketing in 2021. Check out their views on how COVID-19 affected brick and mo Thank you for checking out the 50 most read stories about Retail on HackerNoon. to find the most read stories about any technology. Visit the /Learn Repo

50 Stories To Learn About Retail

is a form of online lending that allows users to buy goods or services with deferred payment. BNPL provides you with the opportunity to access the goods or services you need without having the full amount on hand and pay it off later, usually in several weeks or even months. In this article, I will elaborate on the prospects of such type of financing and the impact it can have on the entire FinTech sector. BNPL (Buy Now, Pay Later) Globalisation of BNPL solutions and their expansion into new markets Nowadays, the BNPL concept is becoming all over the world, especially in Europe, North America and India. One of the reasons BNPL is gradually conquering the FinTech sector is that both customers and merchants are able to reap the benefits of it. On the one hand, it is for people not having to pay the full amount of money at once, and, on the other hand, the majority of modern merchants see BNPL as the . increasingly popular extremely convenient perfect tool to increase their sales The COVID-19 pandemic has also had a positive impact on the online market. As the crisis has limited household incomes across the globe, the search for liquidity has increased and is expected to continue throughout 2023. The pandemic has definitely led to a new normal in online shopping, where consumers are confident in purchasing products using different online payment gateways. that the global BNPL transactions will reach almost . Last year, more than of client assets passed through BNPL services, and this figure is set to triple. It is predicted $600 billion by 2026 $214 billion The main international BNPL providers that benefit significantly from this revolutionary concept are: Paypal (US); Klarna Bank (Sweden); Laybuy Group (New Zealand); Payl8r (UK); Billie (Germany); Affirm Holdings (US); Yandex (Russia) Interaction of BNPL with other FinTech divisions Nevertheless, the BNPL concept isn’t the only thing that has blown up the FinTech market in recent years. The same can be said of cryptocurrencies - digital currencies designed to serve as a medium of exchange through a computer network. These currencies are backed by cryptography and can therefore offer the most secure transactions possible. Along with BNPL, cryptocurrencies are the most talked about trends in the modern global economy. But can these two concepts co-exist? Absolutely. When BNPL providers carry out integrations with crypto wallets, it’s a for both sides. For example, the aforementioned in 2021 and concluded a partnership with , Sweden’s leading online crypto brokerage. As a result of this fruitful cooperation, Klarna customers received much more digital options of paying for their BNPL bills, and Safello users were granted the opportunity to buy cryptocurrencies directly from the bank and with no interest. win-win situation Klarna Bank decided to enter the cryptocurrency market Safello Speaking of BNPL and further FinTech divisions, I cannot but mention e-wallets. , one of the world’s most popular digital wallets, has the whole on its website. At the moment, PayPal offers two primary types of Pay Later products - Pay in 4 and Pay Monthly, each having its own pros and cons. PayPal BNPL section I have no doubt that these integrations are only the beginning of the new wave of innovative partnerships aimed to . The implementation of crypto payment methods into BNPL technologies can be the groundwork for radical changes in the whole FinTech sector, as it will make the market more diversified than ever. blur the boundaries between BNPL and digital assets Adapting BNPL models to local specifics and legislation However, each BNPL model must be adapted to the local market in which it operates and comply with the legislation of a certain country. Let’s have a brief look at BNPL’s situation in some of the world’s leading countries: Despite the fact that BNPL models are currently thriving in the US, they have been facing inconsistent regulatory and enforcement strategies from federal and state regulators. On November 16, 2022, the U.S. Department of the Treasury, in consultation with the White House Competition Council, announced support and encouragement for the CFPB’s inquiries into BNPL providers, in a finding that the FinTech industry requires additional oversight to close gaps, prevent abuses, and protect consumers. United States. report In June 2022, the UK government issued a concerning BNPL. With this document, the government aimed to protect millions of people from being scammed by unfair BNPL providers. As such, if a BNPL provider is willing to enter the UK market, they are immediately captured by the government whether they offer their services offline or at a distance, directly or by third-party lenders. United Kingdom. response document It is widely-believed that the BNPL market has existed in Germany since the early 1970s and it still enjoys popularity. According to the German jurisdiction, the maximum credit period that a BNPL provider can offer to its customers is strictly regulated and cannot exceed 12 months. Quite recently, the German Federal Financial Supervisory Authority has issued the consumer guidance reminding that the country’s consumer protection provisions don’t apply for amounts lower than EUR 200. Simply put, the German law cannot protect people from getting scammed by unfair BNPL providers if they purchase a product that costs lower than EUR 200. Germany. Mergers and partnerships between BNPL providers In order to enter foreign markets faster and easier, or to strengthen the position in the local markets, BNPL providers sometimes merge their businesses or, if the provider is big enough, it can acquire the smaller one. In this way, , a Japanese BNPL firm, for , willing to expand its foothold in the Japanese market. At that time, Japan had the world’s third-largest e-commerce market, and the deal was obviously mutually beneficial. Paidy’s payment services allow Japanese shoppers to make purchases online, and then pay for them each month in a consolidated bill at a convenience store or via bank transfer. The company uses proprietary technology to score creditworthiness, underwrite transactions and guarantee payment to merchants. PayPal acquired Paidy $2.7 billion in cash Another deal worth mentioning is . To put you into context, Square is a digital payment platform founded by Twitter’s Jack Dorsey, and Afterpay is a major Australian BNPL provider. It cost Square to complete the deal, which turned out to be The deal was closed in 2022, and in the world have come together to create an online payment powerhouse. Square’s purchase of Afterpay $29 billion the largest buyout in Australian history. two of the fastest-growing FinTech firms Competition between BNPL and traditional banking products The competition between BNPLs and traditional banking products is becoming immensely fierce. BNPL platforms offer consumers , whereas traditional banking products, such as loans and credit cards, . more flexible payment terms and lower lending costs imply fixed interest rates and usage fees However, banking products still have - you can use a credit card to pay for literally anything, including mortgages or car loans, where BNPLs can’t provide access to such products. On top of that, during the last 6 months, a lot of banks started offering their own BNPL services to customers with a good credit history. Such financial institutions (mostly Indian) as , , , , and , have already introduced this functionality for their clients. This list is going to grow exponentially and soon be replenished with European and American banks. one big advantage HDFC Bank LazyPay OlaMoney ePayLater Kotak Mahindra Bank Overall, the competition between BNPL platforms and traditional banking products will continue and once BNPL providers will be able to offer their landing form for a wider range of products, which will inevitably happen. take a whole new turn Conclusion I firmly believe that the BNPL concept will be . There are already dozens of examples of multi-billion dollar acquisition/merger deals, where BNPL providers serve as one or even two parties involved. Many technology start-ups are developing new products based on BNPL, such as instalment payment applications. Although the BNPL concept still has something to work on, it continues to gradually evolve, and we are about to witness a plethora of innovations and breakthroughs in the nearest future. the main driving force behind the bright future of FinTech

The Future of BNPL and Its Impact on the FinTech Industry

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