Ecommerce

Every time a card payment is processed, 𝘁𝗵𝗿𝗲𝗲 main types of fees are involved. Here’s a simple breakdown of the Three Core Fees: 1️⃣ Interchange Fee This is paid by your acquiring bank (or payment processor) to the cardholder’s bank (the issuer). It’s set by the card networks (like Visa and Mastercard; sometimes regulated), and is designed to cover things like fraud, credit losses, and infrastructure costs. 2️⃣ Scheme Fee Charged by the card networks themselves, this fee covers the operation of the payment system (“rails” that process the transaction). 3️⃣ Acquirer Markup This is the fee your acquirer or payment service provider (PSP) charges you, the merchant. It includes their costs, risk management, and profit margin for processing and settling the payment. The total cost a merchant pays is called the Merchant Service Charge, which is the sum of these three components. The Main Pricing Models: ► Bundled Pricing All fees are grouped into one flat rate. This is very common with small businesses. It’s easy to understand but doesn’t provide insight into what you’re actually paying for. ► Interchange+ The interchange fee and the acquirer’s fee are shown separately, but the scheme fee is typically bundled with the markup. This model offers some transparency. ► Interchange++ Each fee—the interchange, scheme, and acquirer markup—is itemized separately. This is the most transparent model and is favored by larger or multi-country merchants who want to track costs precisely. Who Chooses the Pricing Model? Most acquirers and PSPs decide what pricing model you’re offered. Unless you negotiate or have significant transaction volume, you’re likely to get bundled pricing by default. Larger or more experienced merchants who understand payments often push for Interchange++ for its clarity and fairness. Smaller merchants often aren’t aware that alternatives exist or find it difficult to compare offers. How Interchange Fees Vary Globally: Some regions (like the EU, UK, China, and Brazil) cap interchange fees to lower costs for merchants and stimulate competition. The US regulates only part of the system—such as capping debit card fees for large banks (the Durbin Amendment)—while credit card interchange remains uncapped and usually higher. Other countries, like India and Brazil, regulate interchange as part of broader financial inclusion goals. In markets with stricter regulation, merchants often benefit from lower, more predictable fees, making it easier to accept cards. Where fees are higher and less regulated, issuers can offer consumers more rewards (like cashback), but those costs are passed back to merchants—and sometimes their customers. Every model shifts the balance of costs and benefits between banks, merchants, and consumers in different ways. More info below👇, and I highly recommend reading my complete deep dive article about Interchange Fee and what factors impact the rate: https://bit.ly/44T4VJA

Website traffic was a valuable metric correlated to growth. Now it may be a vanity metric, not correlated to growth. Search has been disrupted. Visits to your website are declining. So, marketers - what now? The search landscape was already shifting (I talked about this at INBOUND last year). Now, the change is accelerating dramatically: - AI Overviews appear in 43% of Google searches – when they do, organic CTR drops by nearly 35%. - Google’s AI Mode and audio AI overviews are coming – they will cause clicks to collapse further. - More buyers are using LLMs to find information, ChatGPT search in Europe grew 3.7x in six months. So, what should marketers do? And how can AI help? 1. Be everywhere and diversify your channels The days of relying solely on Google search are way over. You need to show up on YouTube, LinkedIn, Instagram, podcasts, and in niche communities. The good news? AI makes multi-channel, multi-format content creation scalable – even for small teams. 2. Be specific with context In the past, broad informational content was the way to rank in Google. Today, buyers expect results deeply relevant to them, whether they’re on Google, LLMs, or Reddit. You need specific content that reflects your expertise and resonates with your buyers. 3. Optimize for conversion, not clicks Traffic was once the lever you could pull. Now, conversion is where the opportunity lies. AI enables you to deliver personal messages that drive better conversion. Don’t ask, “How do we get more blog visits?” Ask, “How do we convert more prospects into customers across all channels?” The changes in search are sending shockwaves across marketing teams and media companies everywhere. The era of traffic-based marketing is ending. But a new era full of opportunity is just beginning. Super exciting times for marketers to reinvent the playbook!

Replenishment isn’t a side feature, it’s a force multiplier. This is a big mistake. We’ve seen replenishment flows outperform promos and win-back emails combined. They convert better every time with the right timing and zero customer effort. Brands overspend on ads to win new customers, then forget to win them again. They need to predict exactly when a customer needs to repurchase and trigger the message at the perfect moment. Not too soon, not too late. Just right. ++ 𝗪𝗵𝘆 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿𝘀 𝗗𝗼𝗻’𝘁 𝗥𝗲𝗼𝗿𝗱𝗲𝗿 – 𝗔𝗻𝗱 𝗛𝗼𝘄 𝘁𝗼 𝗙𝗶𝘅 𝗜𝘁 ++  𝗧𝗵𝗲𝘆 𝗙𝗼𝗿𝗴𝗲𝘁 ✅ Fix: Replenit’s AI triggers proactive reminders across channels exactly when customers are likely to run out, via the brand's own marketing automation vendors, without any migration. 𝗣𝗼𝗼𝗿 𝗧𝗶𝗺𝗶𝗻𝗴 𝗼𝗿 𝗖𝗵𝗮𝗻𝗻𝗲𝗹 ✅ Fix: Multichannel orchestration (SMS, push, email) with personalized timing based on consumption behavior. 𝗡𝗼 𝗖𝗹𝗲𝗮𝗿 𝗜𝗻𝗰𝗲𝗻𝘁𝗶𝘃𝗲 ✅ Fix: Smart upsell bundles, urgency messages (“running low?”), and loyalty integration improve reorder ROI.   • Food & Beverage, pet food and treats, wellness & beauty products hold the highest repeat purchase potential, being very high due to frequent, perishable-driven consumption patterns. • Online groceries and FMCG rank high in habitual/impulsive behavior, presenting a strong fit for mobile push and SMS-driven replenishment campaigns. Brands like Glosel turned a leaky bucket into a revenue engine with Replenit’s AI-powered multichannel replenishment flows. 🚀 53.75% more automation revenue 🛒 +28% higher AOV 📲 100% of the Multichannel approach, email, SMS & Push channel revenue -12X Higher Engagement Rate Why does it work? Because Replenit activates timely, no-effort reorders across email, SMS, push, and more. Most brands forget to remind customers. ++ 𝟯 𝗧𝗮𝗰𝘁𝗶𝗰𝗮𝗹 𝗥𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝗥𝗲𝘁𝗮𝗶𝗹𝗲𝗿𝘀 ++ 1️⃣ Make Replenishment an Always-On Growth Engine Don’t treat it as a postscript. Integrate replenishment flows as a core revenue pillar in your retention strategy. 2️⃣ Automate Across Channels With Smart Triggers Use AI-powered solutions to trigger SMS, email, and push notifications based on usage cycles, not guesswork. 3️⃣ Track and Optimize With First-Party Data Loops Leverage Replenit’s dashboards to identify top retention products, run experiments on timing, and iterate continuously. 𝗧𝗼 𝗮𝗰𝗰𝗲𝘀𝘀 𝗮𝗹𝗹 𝗼𝘂𝗿 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗳𝗼𝗹𝗹𝗼𝘄 ecommert® 𝗮𝗻𝗱 𝗷𝗼𝗶𝗻 𝟭𝟰,𝟮𝟬𝟬+ 𝗖𝗣𝗚, 𝗿𝗲𝘁𝗮𝗶𝗹, 𝗮𝗻𝗱 𝗠𝗮𝗿𝗧𝗲𝗰𝗵 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝘃𝗲𝘀 𝘄𝗵𝗼 𝘀𝘂𝗯𝘀𝗰𝗿𝗶𝗯𝗲𝗱 𝘁𝗼 𝗲𝗰𝗼𝗺𝗺𝗲𝗿𝘁® : 𝗖𝗣𝗚 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗚𝗿𝗼𝘄𝘁𝗵 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿. About ecommert We partner with CPG businesses and leading technology companies of all sizes to accelerate growth through AI-driven digital commerce solutions. #CPG #ecommerce #Replenishment #AI #FMCG

COULD TRUMP'S TARIFFS SPELL THE END OF CHEAP FASHION? Analysis by Apparel Insider suggests President Trump's tariff hikes on key garment hubs could translate to retail price increases of between 10 to 25 per cent. The effect is expected to be particularly pronounced for fast fashion retailers who operate on tight margins. We spoke to manufacturers as well as a couple of well known brands. Our analysis suggests: - A pair of Nike running shoes currently retailing at U.S.$100 and manufactured in Vietnam may soon be priced between U.S.$115 and U.S.$125, as import costs climb from U.S.$40 to over U.S.$58 - A U.S.$30 H&M summer dress made in Cambodia could soon cost upwards of U.S.$35, reflecting an almost 50 per cent rise in import duty - Jeans from Bangladesh, sold at U.S.$40 by brands like Old Navy, may increase to around U.S.$50 - A U.S.$60 sports bra produced in Sri Lanka by brands like Under Armour could retail for closer to U.S.$75 Brands also have a choice of absorbing some costs or passing price increases on to suppliers by asking for discounts. History tells us the former us unlikely, while the latter may prove tricky with many suppliers already working on very low margins. Brands have always been extremely loathe to increase prices for clothing where deflation (in real terms) has been a trend in recent decades. The scale of the current tariff hikes might leave them with no choice. Comments and thoughts welcome.

Having a dominating share on e-commerce marketplaces has been one of the pillars of our growth. 10 pointers for founders to keep in mind while scaling e-com: 1. The fundamental equation of e-com is “Sales= Traffic*Conversion”. Not meeting sales numbers is either a traffic problem or a conversion problem. For every SKU, figure out whether it is a traffic problem or a conversion problem. Do not try to solve traffic problems with conversion levers. And vice versa. 2. Like all performance marketing, e-com media also has diminishing returns. Beyond a point, increasing spends will not increase sales at the same speed. Stop at that point 3. If you want to increase profitability, you need to increase your organic discoverability in the platform. Amazon is a search led platform with search contributing to 60-70% views in most categories. For Flipkart, along with search, merch and reco are equally important. But the fundamentals of organic discoverability is same. Both platforms have an algorithm where SKUs with the best reviews, highest listing quality score, lowest time to delivery and highest conversion rates get pushed. Optimize for these parameters and see organic discoverability skyrocket 4. The other way to reduce dependency on platform ads( and hence increase profitability) is to ensure your branded searches increase. This is directly a function of your off platform marketing activities, word of mouth and repeat customers. So, work on those parameters 5. Category Relationships matter a lot. Understand what the number 1 objective of your category manager is for the year. And help them achieve it. Eg: If they are looking to improve ASP, help them with your premium assortment. If you help them achieve their number 1 KPI, they will ensure you do well on the platform 6. Whatever the ads team tell you, take it with a pinch of salt. Most times they are very helpful. But their number 1 KPI is to sell ads. Not your success. So, sometimes what is good for them might not be good for you 7. All SKUs will not do well. All sub-categories won’t do well. If there is no PPCMF, no amount of good execution will cut it. So, important to cut your losses and stop investing more money on losers. Instead, allocate to your winners in the portfolio 8. Have a E-Commerce dashboard which goes beyond the L0 metrics. Look at your L1 and L2 metrics daily and hold teams accountable for these metrics. Ads driven sales, share of search, organic visits, conversion rates etc are all examples of L1 metrics 9. Sometimes there will be irrational competition and they will bid crazily for keywords. Do not compete with them. They are burning cash and because blind venture money is running out quickly in consumer brands, they will fizzle out. 10. Do not overdo discounts. Discounts are like antibiotics. You use it 2-3 times a year, you see huge spikes. Use it every alternate day, and that becomes your market operating price.

Can a #socialmedia app originally launched as a 15-second amateur video platform, be the next big thing in #payments? Let’s take a look.   TikTok is the first Chinese app to have taken off in the west. Launched in 2016 as Douyin by ByteDance, it now has more than 1.5 billion monthly active users in 160 countries.   A few days ago, it became the first non-game app to reach $10bn in consumer spending and among just 5 apps to achieve this. The number could even be much higher as China is not included (Google is banned in China, but around 2/3 of smartphones use Android via hundreds of third-party app stores).   But where does this spending come from?   —     TikTok has created TikTok coins, a virtual currency within TikTok that users can buy and spend on gifts for creators on TikTok   —     The feature is called Tips and allows users to reward creators for their content   —     TikTok coins can be eventually converted to normal money (via PayPal or bank account), but with TikTok keeping a 50% commission!   —     Behind TikTok’s tipping feature is Stripe Connect, integrated in 2021   —     Stripe Connect is an API that enables embedded payments with Stripe dealing with all the back-office work needed (handling transactions, AML, KYC, etc)   Why is this important?   In-app purchases are a thing of video game apps. Non-video-game apps rely on subscriptions to make money. TikTok is the only app to have reverse-engineered this model via this reward set-up and makes billions of dollars without the need for subscriptions.   But this is not the only payments’ aspect in TikTok’s game.   On #ecommerce:   —     TikTok has launched in various geographies live shops on user profiles so that users can make direct purchases. In China, TikTok now generates most of its revenue from direct in-app sales and is rapidly taking away market share from e-com giants like JD and Alibaba   —     In Aug 2021 TikTok rolled out (US, UK) TikTok shop, which are digital e-shops directly integrated in the platform enabling merchants and creators to sell products directly to the TikTok community. The tool was powered by Shopify and let sellers make available product catalogs to TikTok so that they can be purchased then on Shopify   However, TikTok has as of late changed #strategy:   —     In Sep 23 it sunset the Shopify partnership and started pushing merchants to switch to its own e-commerce tool   —     TikTok’s parent company, ByteDance, has been working with JP Morgan to build a real-time payments infrastructure   TikTok is sitting on a massive opportunity: billions of dollars are moved every year on the platform. Phasing out all third-party providers and moving to an in-house payments set-up is already under way, with payment processing as a likely next step. TikTok will not be becoming a payments’ company, but it will be sourcing an ever-larger portion of its revenue via payments.   Opinions: my own, Graphic sources: data ai, Business Model Toolbox, FXC Intelligence

Let's be honest... most of us are living in digital chaos right now; Data, technology, and new product overload. How do you make sense of it all? Establishing your own set of Golden Rules Golden rules are the non-negotiable principles that offer a blueprint for success. In digital transformation, they are the critical load-bearing walls that support the entire structure of transformational change. Here are my 10 Golden Rules for Successful Digital Transformation: 𝟏. 𝐏𝐫𝐢𝐨𝐫𝐢𝐭𝐢𝐳𝐞 𝐄𝐧𝐝-𝐔𝐬𝐞𝐫 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞: Always craft your digital interfaces and processes with the end-user in mind, ensuring that every interaction is intuitive, engaging, and satisfying. 𝟐. 𝐂𝐨𝐦𝐦𝐢𝐭 𝐭𝐨 𝐂𝐨𝐧𝐭𝐢𝐧𝐮𝐨𝐮𝐬 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: Foster a culture where ongoing education is valued, enabling your team to stay ahead of the curve by mastering new technologies and methodologies as they emerge. 𝟑. 𝐔𝐩𝐡𝐨𝐥𝐝 𝐃𝐚𝐭𝐚 𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲 & 𝐏𝐫𝐢𝐯𝐚𝐜𝐲: Vigilantly guard your customer’s data as if it were your own, implementing robust security protocols and privacy measures to maintain trust and compliance. 𝟒. 𝐄𝐦𝐛𝐫𝐚𝐜𝐞 𝐀𝐠𝐢𝐥𝐞 𝐌𝐞𝐭𝐡𝐨𝐝𝐨𝐥𝐨𝐠𝐢𝐞𝐬: Adopt a flexible and responsive approach to project management, allowing for rapid iteration and adaptation in the face of changing digital landscapes. 𝟓. 𝐁𝐫𝐞𝐚𝐤 𝐃𝐨𝐰𝐧 𝐃𝐚𝐭𝐚 𝐒𝐢𝐥𝐨𝐬: Encourage a collaborative environment where data flows freely between departments, enhancing decision-making and fostering a unified view of the business. 𝟔. 𝐂𝐨𝐧𝐝𝐮𝐜𝐭 𝐑𝐞𝐠𝐮𝐥𝐚𝐫 𝐓𝐞𝐬𝐭𝐢𝐧𝐠: Implement a rigorous testing regime to identify and address issues early on, ensuring that your digital offerings are resilient and reliable. 𝟕. 𝐃𝐞𝐬𝐢𝐠𝐧 𝐟𝐨𝐫 𝐅𝐮𝐭𝐮𝐫𝐞 𝐆𝐫𝐨𝐰𝐭𝐡: Anticipate the scalability of your digital solutions, ensuring that they can evolve and expand as your business grows and market demands shift. 𝟖. 𝐑𝐞𝐠𝐮𝐥𝐚𝐫𝐥𝐲 𝐑𝐞𝐯𝐢𝐬𝐞 𝐃𝐢𝐠𝐢𝐭𝐚𝐥 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐞𝐬: Continually reassess and refine your digital strategies to stay relevant and effective in an ever-evolving technological ecosystem. 𝟗. 𝐄𝐧𝐠𝐚𝐠𝐞 𝐚𝐧𝐝 𝐈𝐧𝐯𝐨𝐥𝐯𝐞 𝐋𝐞𝐚𝐝𝐞𝐫𝐬𝐡𝐢𝐩: Ensure that your leadership is actively involved in driving digital initiatives, setting a visionary tone and aligning digital goals with business objectives. 𝟏𝟎. 𝐌𝐚𝐢𝐧𝐭𝐚𝐢𝐧 𝐓𝐫𝐚𝐧𝐬𝐩𝐚𝐫𝐞𝐧𝐭 𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐜𝐚𝐭𝐢𝐨𝐧: Cultivate an environment where communication is clear and open, establishing a foundation of transparency that builds trust and facilitates smoother digital transitions. Use this as a framework to write your own set of Golden Rules, and communicate them to EVERYONE who is a part of the transformation. 𝐅𝐮𝐥𝐥 𝐚𝐫𝐭𝐢𝐜𝐥𝐞: https://lnkd.in/e_TGu_4D What else would you add to the list?

If you want to know where the money is in Machine Learning, look no further than Recommender Systems! Recommender systems are usually a set of Machine Learning models that rank items and recommend them to users. We tend to care primarily about the top-ranked items, the rest being less critical. If we want to assess the quality of a specific recommendation, typical ML metrics may be less relevant. Let’s take the search results of a Google search query, for example. All the results are somewhat relevant, but we need to make sure that the most relevant items are at the top of the list. To capture the level of relevance, it is common to hire human labelers to rate the search results. It is a very expensive process and can be quite subjective since it involves humans. For example, we know that Google performed 757,583 search quality tests in 2021 using human raters: https://lnkd.in/gYqmmT2S. Normalized Discounted Cumulative Gain (NDCG) is a common metric to exploit relevance measured on a continuous spectrum. Let’s break that metric down. Using the relevance labels we can compute diverse metrics to measure the quality of the recommendation. The cumulative gain (CG) metric answers the question: How much relevance is contained in the recommended list? To get a quantitative answer to that question, we simply add the relevance scores provided by the labeler: CG = relevance 1 + relevance 2 + ... The problem with cumulative gain is that it doesn’t take into account the position of the search results. Any order would give the same value however we want the most relevant items at the top. Discounted cumulative gain (DCG) discounts relevance scores based on their position in the list. The discount is usually done with a log function, but other monotonic functions could be used: DCG = relevance 1 / log(position 1) + relevance 2 / log(position 2) + ... DCG is quite dependent on the specific values used to describe relevance. Even with strict guidelines, some labelers may use high numbers and others low numbers. To put those different DCG values on the same level, we normalize them by the highest value DCG can take. The highest value corresponds to the ideal ordering of the recommended items. We call the DCG for ideal ordering the Ideal Discounted Cumulative Gain (IDCG). The Normalized Discounted Cumulative Gain (NDCG) is the normalized DCG NDCG = DCG / IDCG If the relevance scores are all positive, then NDCG is contained in the range [0, 1], where 1 is the ideal ordering of the recommendation. #MachineLearning #DataScience #ArtificialIntelligence

Revenue recognition isn't about when you get paid Most founders mess this up. They see $12,000 hit their bank account and think they just made $12,000 in revenue. Wrong. You made $1,000 in revenue...if it's an annual contract. What is Revenue Recognition? Revenue is earned income from delivering goods or services. Recognition is when it's reported on your income statement. These happen at different times. You collect $12,000 upfront for an annual subscription. But you only earned $1,000 of that in month one. The other $11,000? That's deferred revenue sitting on your balance sheet. The Journal Entries: When the sale happens: Debit Cash $12,000 Credit Deferred Revenue $12,000 Each month as you deliver service: Debit Deferred Revenue $1,000 Credit Revenue $1,000 This moves money from your balance sheet to your P&L as you actually earn it. Daily vs Monthly Methods You can recognize revenue daily or monthly. Daily method: $12,000 ÷ 365 days = $33 per day Monthly method: $12,000 ÷ 12 months = $1,000 per month Both get you to $12,000 over the year. Daily gives more precision but monthly is simpler. The Base Formula Every deferred revenue balance follows this pattern: Beginning Balance + Additions - Subtractions = Ending Balance Additions = new cash collections Subtractions = revenue recognized Track this for every contract and you'll know exactly where you stand. The Manual Nightmare Most founders start tracking this in spreadsheets. Works fine for 10 contracts Gets messy at 50. Completely breaks at 100+. Picture this...you've got 50 active contracts. Each one has different start dates, different terms, different recognition schedules. You're tracking everything in Excel. Every month you need to: Update deferred revenue balances for each contract. Calculate how much revenue to recognize. Create journal entries for each one. Make sure everything ties to your GL. I've seen many people spending 3 full days every month just on revenue recognition. And you know what happened? They'd still find errors weeks later. Daily Method Makes it Worse. Think monthly is bad? Try daily recognition with multiple contracts. $12,000 annual contract = $32.88 per day $24,000 contract = $65.75 per day $6,000 contract = $16.44 per day Now multiply that by 50+ contracts...each starting on different dates. You're calculating different daily amounts for hundreds of line items. Automation Saves Your Sanity Maxio completely eliminates this pain. Set up your revenue recognition rules once. The system automatically applies them across every contract. Daily, monthly, whatever method you choose...it just works. 30 minutes to run reports and review everything. That's it. No more manual calculations, no more formula errors, no more audit trail headaches. Everything's automatically GAAP compliant and audit-ready. === How do you currently track your revenue recognition? #MaxioPartner

🔮 Four Levels Of Customer Understanding (https://lnkd.in/eQz36wFw), how to think of underlying reasons for user behavior, hidden motivations, root causes and the different layers of reality that are often overlooked in product design — from what people say to what they think or feel to what they actually do to reasons why they do it. By Hannah Shamji and Helio. 🤔 What people do, say, think and feel are often different. 🚫 Assumptions and hunches rely on most obvious reasons. ✅ But most obvious reasons rarely paint the full picture. ✅ People don’t always cancel because they actually want to. ✅ Pricing is never the only reason why people don’t buy. 🤔 Customers often don’t realize why they made a decision. ✅ We built understanding by studying 4 levels of reality. ✅ Level 1: “What we tell others”, unreliable, opinions, hearsay. ✅ Level 2: “What we tell ourselves”, interviews, debrief, surveys. ✅ Level 3: “What we actually do”, task analysis, observation. ✅ Level 4: “Why we do it”, task walkthroughs, context, interviews. Level 1 is most unreliable, and barely brings good insights. Often people imagine and say things that don’t necessarily represent real reasons for their behavior. They rather explain behavior through the lens of how a customer perceives it, or wants it to be perceived. The real magic happens on higher levels. But they require right questions, interviews and observations and, most importantly, user’s trust. So ask people to walk you through their daily routine. Explain to you where your product fits in their life. Observe how they complete their tasks in their environment. Study where they lose time, repeat actions, hover but don’t click, or click and then go back. Don’t ask them to speak loudly. Pay attention to when they scratch their neck, or raise their eyebrows. Smile, or laugh, or look worried. Many companies speak about “validation”. Yet validation often means accepting and confirming existing assumptions. As Hannah Shamji writes, instead, we should diagnose existing behavior without any preconceived notions or affiliations. So don’t validate — research instead. The hardest part is understanding customer’s real motivations — and the only way to get there is by building a sincere, honest and trustworthy relationship that feels right and that customers can wholeheartedly engage in. Once your customers really care and want to help, getting to real understanding will be much easier. Useful resources: 60 Ways To Understand User Needs, by David Travis https://lnkd.in/eUXJqX6B How To Avoid Bias In UX Research, via Sundar Subramanian https://lnkd.in/ewJt2kF2 People Don’t Always Cancel Because They Want To, by Emily Anderson https://lnkd.in/eMXZWiyT [continues below]