How To Use Behavioral Data To Drive Retail Decisions

🛒 You can’t track purchase intent by tracking ATCs. 𝟭. “𝗔𝗧𝗖” 𝗷𝘂𝘀𝘁 𝗺𝗲𝗮𝗻𝘀 “𝘀𝗮𝘃𝗲 𝗳𝗼𝗿 𝗹𝗮𝘁𝗲𝗿”. It’s a placeholder, not a promise. 𝟮. 𝗣𝗲𝗼𝗽𝗹𝗲 𝘂𝘀𝗲 𝘁𝗵𝗲 𝗰𝗮𝗿𝘁 𝗹𝗶𝗸𝗲 𝗣𝗶𝗻𝘁𝗲𝗿𝗲𝘀𝘁. It’s a tool for collecting, not committing. 𝟯. 𝗧𝗵𝗲 𝗰𝗮𝗿𝘁 𝗵𝗲𝗹𝗽𝘀 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗲, 𝗻𝗼𝘁 𝗽𝗿𝗶𝗼𝗿𝗶𝘁𝗶𝘇𝗲. It helps them compare…not decide. 𝟰. 𝗡𝗼 𝗳𝗿𝗶𝗰𝘁𝗶𝗼𝗻 = 𝗻𝗼 𝗰𝗼𝗺𝗺𝗶𝘁𝗺𝗲𝗻𝘁. Clicking isn’t buying. It costs nothing to put something in an online cart. 𝟱. 𝗔𝗧𝗖𝘀 𝗺𝗲𝗮𝘀𝘂𝗿𝗲 𝗰𝘂𝗿𝗶𝗼𝘀𝗶𝘁𝘆 𝗼𝗻𝗹𝘆. Interest? Yes. Intent? Not even close. If you really want to track intent, do this instead: ✅ 1. Track high-friction actions Not all clicks are equal. Look for: • Initiate Checkout • Payment Info Entered • Return Visitor → PDP → Checkout • Product added after reading reviews These behaviors show someone is moving past curiosity into commitment. ✅ 2. Analyze sequence, not single actions One ATC means nothing. But: 𝘈𝘛𝘊 → 𝘝𝘪𝘦𝘸 𝘴𝘩𝘪𝘱𝘱𝘪𝘯𝘨 𝘱𝘰𝘭𝘪𝘤𝘺 → 𝘈𝘥𝘥 𝘢𝘥𝘥𝘳𝘦𝘴𝘴? Now we’re talkin’ intent. Watch the flow, not the isolated click. ✅ 3. Measure time spent on key friction points If someone lingers on: • Product comparisons • Return policy pages • Size charts or FAQs They’re mentally preparing to convert. They’re not just browsing at that point, they’re weighing the trade-offs. ✅ 4. Look for repeat product interactions If someone revisits the same PDP 2–3 times in a week, that’s real consideration. Bonus points if they come back from an email or ad reminder. ✅ 5. Use survey overlays or post-exit polls Ask simple, direct questions like: “Are you planning to buy today?” “What’s stopping you from checking out?” Self-reported “logic” + behavioral data = gold. 𝘛𝘓𝘋𝘙: 𝘈𝘛𝘊 𝘪𝘴 𝘪𝘯𝘵𝘦𝘳𝘦𝘴𝘵-𝘭𝘦𝘷𝘦𝘭 𝘣𝘦𝘩𝘢𝘷𝘪𝘰𝘳 𝘰𝘯𝘭𝘺. 𝘐𝘵 𝘸𝘰𝘯’𝘵 𝘵𝘦𝘭𝘭 𝘺𝘰𝘶 𝘪𝘧 𝘺𝘰𝘶𝘳 𝘤𝘶𝘴𝘵𝘰𝘮𝘦𝘳𝘴 𝘢𝘳𝘦 𝘵𝘳𝘶𝘭𝘺 𝘳𝘦𝘢𝘥𝘺 𝘵𝘰 𝘣𝘶𝘺. 𝘛𝘰 𝘵𝘳𝘶𝘭𝘺 𝘵𝘳𝘢𝘤𝘬 𝘪𝘯𝘵𝘦𝘯𝘵, 𝘮𝘰𝘯𝘪𝘵𝘰𝘳 𝘤𝘩𝘦𝘤𝘬𝘰𝘶𝘵 𝘮𝘰𝘮𝘦𝘯𝘵𝘶𝘮.

During my years in retail I noticed two distinct decision-making camps - the gut-feelers vs. the analytical. It was always a matter of pride as to which camp you belonged to. Gut-feelers thought they were superior because their insights were driven directly from being in touch with the average consumer. The analytical camp thought that they were more reliable because they were uncovering stated and unstated patterns through their analysis of shopper data. For me though, we've got to marry up the two. And this is how I delivered a category turnaround of 40% top-line growth on the declining ready-to-heat pizza category. 1️⃣ Start with data. Because, data never lies. Data showed me that even though everyone wanted to sell $5 pizzas, we simply could not afford to do it. And no, selling more pizzas at a unit loss would not grow the category sufficiently to rub away the losses. 2️⃣ Apply intuition. Visit stores, check out what your competition is doing. Put yourself in the customers' shoes, or better yet, chat with them. This is how I figured out that the $5 price point was a must-have. We just had to find a more profitable way to deliver it. 3️⃣ Challenge assumptions. When folks claimed that the strong sales was linked to $5 promotions, my data showed that it was not the promo price that was doing the trick, but it was the ad and display support that was driving consumption. 4️⃣ Build scenarios. Use the data on hand to test out different scenarios. Using historical data, I built different 4P scenarios to see which would give us the best results with minimal change. How many SKUs would we carry, where would we carry them, would they be EDLP or promoted? 5️⃣ Set up feedback loops. Afraid to see how your initiatives pan out? Forget about being right.. Care more about finding and fixing gaps. I established Units/Store/Week/SKU goals and monitored them obsessively. Some may say I went a tad crazy for a while there. But, it delivered results. Because, I could use this to course correct immediately. The result was market share growth, top-line growth, and gross margin growth - the trifecta. So, next time someone tells you you've got to pick sides of gut-feel vs. analytics, stick to the middle.

When I interviewed Stephan Waldeis, VP of eCommerce Europe at Husqvarna Group, he said this about tracking real-time data and retailer partnerships. “We track customer behavior, we track inventory levels at our partners, we track sales performance — and of course, we possibly... we track all of that in real time. Imagine, our robots — at least the ones from the last 10+ years — are all connected. So, we have a lot of insights in which gardens they are driving, when they are operating, etc. And that is data that we are leveraging, but also data that we are sharing with our channel partners. That’s great even for the channel partners who are not really interested in operating an eCom site. We provide them with a lot of insights… what kind of products are interesting in your area, because we know exactly from visits on our site, which products in a particular region are more relevant — in Amsterdam versus in Berlin versus in Munich.” 𝗛𝗼𝘄 𝘀𝗵𝗼𝘂𝗹𝗱 𝘄𝗲 𝘁𝗿𝗮𝗻𝘀𝗹𝗮𝘁𝗲 𝘁𝗵𝗶𝘀 𝗳𝗼𝗿 𝗖𝗣𝗚 𝗯𝗿𝗮𝗻𝗱𝘀 𝗮𝗿𝗼𝘂𝗻𝗱 𝘁𝗵𝗲 𝘄𝗼𝗿𝗹𝗱 𝘁𝗼 𝗳𝘂𝗲𝗹 𝗴𝗿𝗼𝘄𝘁𝗵? 1️⃣ Activate Real-Time Retailer Collaboration Track and share real-time consumer behavior, inventory, and sales data with retail partners — even those with limited digital capabilities — to strengthen joint decision-making, optimize local assortments, and drive smarter sell-through at the shelf. 2️⃣ Localize Product Strategies with Regional Demand Signals Use geo-specific browsing and purchase data to tailor product recommendations, promotions, and stock levels at the city or neighborhood level — what sells in Amsterdam might flop in Berlin if you don’t read the digital shelf signals correctly. 3️⃣ Turn Connected Product Data into a Competitive Advantage Leverage connected device insights (where available) not only for product innovation but as a marketing and retail sales weapon, identifying usage patterns, seasonal trends, and regional preferences that can feed back into supply chain, DTC, and retail media strategies. 𝗧𝗼 𝗮𝗰𝗰𝗲𝘀𝘀 𝗮𝗹𝗹 𝗼𝘂𝗿 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗳𝗼𝗹𝗹𝗼𝘄 ecommert® 𝗮𝗻𝗱 𝗷𝗼𝗶𝗻 𝟭𝟰,𝟬𝟬𝟬+ 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. Our expertise spans e-channel strategy, retail media optimization, and digital shelf analytics, ensuring more intelligent and efficient operations across B2C, eB2B, and DTC channels. #ecommerce #dataanalytics #CPG #FMCG #data Milwaukee Tool Bosch Makita U.S.A., Inc. STIHL Mondelēz International Nestlé Mars Ferrero General Mills L'Oréal Henkel Beiersdorf Colgate-Palmolive The Coca-Cola Company Unilever L'Oréal Coty Kao Corporation adidas Nike New Balance PUMA Group the LEGO Group Sony Panasonic North America Bose Corporation

I often say: Focus on psychographics (values, interests) Over demographics (age, gender, income) The tough part? Gathering psychographics (without being creepy or invasive.) It's easier to rely on demographics. They're: - painless to gather - straightforward - easy to analyze - quantifiable But it's a mistake to depend on them. A costly one. They're a weak data point. The role they play in purchase decisions? Smaller than many marketers think. Psychographics are much more useful. And easier to collect than you think. Here's how I do it: 👉 Customer surveys Ask direct questions about values, interests, and the purchase process. 👉 Social listening Analyze what your audience is saying in comments, reviews, and posts. Look for patterns in their language, pain points, and values. 👉 Website behavior Track which pages customers visit, what content they engage with, and how they navigate your site. 👉 Customer interviews Understand the customer buying process — from the first moment a customer noticed a problem in their life through purchasing your product (and ideally your product solving their problem). 👉 Community engagement Host webinars, engage in online groups, read and respond to customer comments. Learn your target market's pain points and how they phrase those pain points. 👉 Analyze reviews and testimonials Look for recurring themes in what people say about your product — or your competitors'. Psychographics give you: - customer behavior insights - voice-of-customer data - value props - pain points It's priceless info. Use it to hone your messaging, offers, marketing, design, and product. #marketing #customerinsights #strategy

If your CX Program simply consists of surveys, it's like trying to understand the whole movie by watching a single frame. You have to integrate data, insights, and actions if you want to understand how the movie ends, and ultimately be able to write the sequel. But integrating multiple customer signals isn't easy. In fact, it can be overwhelming. I know because I successfully did this in the past, and counsel clients on it today. So, here's a 5-step plan on how to ensure that the integration of diverse customer signals remains insightful and not overwhelming: 1. Set Clear Objectives: Define specific goals for what you want to achieve. Having clear objectives helps in filtering relevant data from the noise. While your goals may be as simple as understanding behavior, think about these objectives in an outcome-based way. For example, 'Reduce Call Volume' or some other business metric is important to consider here. 2. Segment Data Thoughtfully: Break down data into manageable categories based on customer demographics, behavior, or interaction type. This helps in analyzing specific aspects of the customer journey without getting lost in the vastness of data. 3. Prioritize Data Based on Relevance: Not all data is equally important. Based on Step 1, prioritize based on what’s most relevant to your business goals. For example, this might involve focusing more on behavioral data vs demographic data, depending on objectives. 4. Use Smart Data Aggregation Tools: Invest in advanced data aggregation platforms that can collect, sort, and analyze data from various sources. These tools use AI and machine learning to identify patterns and key insights, reducing the noise and complexity. 5. Regular Reviews and Adjustments: Continuously monitor and review the data integration process. Be ready to adjust strategies, tools, or objectives as needed to keep the data manageable and insightful. This isn't a "set-it-and-forget-it" strategy! How are you thinking about integrating data and insights in order to drive meaningful change in your business? Hit me up if you want to chat about it. #customerexperience #data #insights #surveys #ceo #coo #ai