Retail Data Analysis for Better Customer Insights

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

What sets you apart from ALL the other products in your category?? It’s more than just your product. It’s about understanding your customer better than anyone else. With Enavi’s Customer Canvas, we don’t rely on assumptions.  We help you build detailed, human-first insights into: → What truly motivates your customers: Are they driven by convenience, prestige, or solving a problem? → What’s causing friction in their decision-making process: Is it confusion around pricing, uncertainty about product benefits, or trust issues with your brand? → How to create a seamless customer journey across every touchpoint: Are there gaps in their journey? Do they struggle with navigation, or lose momentum before checkout? We’re driving improvements across your entire business — from marketing to product development. How? We’re not just tracking clicks. We’re uncovering their motivations. Understanding their pain points. Delivering insights that transform every aspect of your marketing strategy. Not just your on-site experience. Be honest… do you REALLY know: — Motivations: What brings customers to your store?  Is it emotional, practical, or social factors that drive them? — Anxieties: Where are they getting frustrated or confused?  Why do they hesitate before making a purchase? — Behavioural Triggers: What’s the final nudge that pushes them to buy?  Is it a discount, a sense of urgency, or something else entirely? My guess is no. To gather this depth of insight, we use qualitative research tools like: 1. Post-Purchase surveys: Asking questions like: “What made you choose this product?” “What almost made you leave without purchasing?” 2. Customer interviews: Delving into their decision-making process with open-ended questions like: “When did you realise you needed this product?” “What would make you feel 100% confident in your purchase?” 3. Review mining: We analyse what customers are already saying, the praises and complaints. We use these to identify recurring themes in their desires and frustrations. 4. Support ticket analysis: We look at common complaints and issues that arise in customer support.  These often reveal hidden blockers in the customer journey that might not be obvious from the data alone. 5. Competitor benchmarking: What are your competitors doing right or wrong? And how can we leverage that insight to give you a competitive edge? And here’s what makes this approach so powerful: the Customer Canvas is not a static report. It’s a living, breathing document that evolves as your business — and your customers — change. Every update, every new product launch, every marketing campaign feeds into this evolving understanding of who your customers are and how best to serve them. Now, ask yourself: Are your current CRO tactics producing the real results you deserve? If not, it’s time to try something different. The Enavi Human Obsessed CRO is your answer.

Here’s how a customer we work withincreased ROAS 99% with a data-led approach And how you can do the same for your brand by cutting fluff & focusing on the metrics that move the needle. These are the exact 5 steps they used: ↳ Track the right metrics They used PenPath’s Purchase Intent Rate (PIR) dashboard as a guiding metric. Instead of relying solely on ROAS or CVR, they analyzed customer buying signals: - Adding to cart - Begin Checkout - Site searches - Email signups ↳ Clean up campaign data Set up clean campaign naming conventions to make data analysis easy & actionable. Specifically making things segmented by prospecting, retargeting, and by product category. ↳ Optimize by funnel stage Measured PIR by source, medium, and campaign to understand baselines for each stage of the funnel to measure interest for each traffic source and by product categories. ↳ Focus on what’s working For TOF effort with high PIR, they scaled or kept them even when ROAS was not performing and cut the rest. For BOF, they cut any campaign with low ROAS or PIR. This is an over simplification but that was the general approach. ↳ Scale high-intent audiences Lastly, they used purchase intent data to created improved retargeting audiences on Google and Meta. The Results? ✅️ ROAS skyrocketed from 1.35x to 2.69x (+99.555) in three months ✅️ Ad spend increased by 243% --- with no wasted dollars Pro Tip: Map your customer journey with intent-driven metrics. Focus on actions that align with each stage of your funnel (TOF, MOF, BOF) to uncover where customers drop off—and where to double down on winning strategies. If you’re an ecommerce decision maker, what data have you used to scale ROAS as quickly as possible? #Dataanalysis #Ecommercetips #Adspend #Ecommercesolutions