Utilizing Data For Ecommerce Decision Making

"Is $20/month too much for our product?" Instead of guessing, we used the Van Westendorp method to find our pricing sweet spot. 4 questions revealed exactly what users would pay (and we haven't touched our pricing since). Here's the framework any founder can steal: 1. Send a survey to actual users, not prospects We surveyed people already using Gamma. They understood the real value of our product, not hypothetical value. Too many founders survey their waitlist or randomly select people who have never used their product. That's like asking someone who's never driven about car prices. 2. Ask these 4 specific questions - At what price would this be too expensive for you to consider it? - At what price is it expensive but still delivering value? - At what price does it feel like a bargain? - At what price is it so cheap you'd question if it's reliable? These create bookends for perceived value. You're mapping the entire spectrum of price psychology, not just asking "what would you pay?" 3. Plot the responses and find where the lines intersect Graph responses from lots of users. Where "too expensive" and "too cheap" lines cross: that's your acceptable range. Where "expensive but fair" meets "bargain": this is your optimal price point. 4. Test within the range, don't just pick the middle The intersection gives you a range, not a number. We ran pricing experiments within that range to see actual conversion rates. A survey shows willingness to pay; testing reveals actual behavior. 5. Lean towards generous (especially for product-led growth) We chose to be more generous with AI usage than our "optimal" price suggested. Word-of-mouth growth matters more than maximizing initial revenue. Not everything shows up in the numbers. 6. Lock it in and stop tinkering Once you find the sweet spot through data, stick with it. We haven't changed pricing in 2 years. Every month debating pricing is a month not improving product. Remember: pricing is a signal, not just a number (Image: First Principles)

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

Ecommerce SEO Tip: Use internal search data to discover ideas for new SEO category pages. You can create a "Search Terms" report in GA4 to do this: If you have a site that gets a sizable amount of traffic, internal search data can be an extremely valuable asset. You'll be able to see all the different terms that users are putting in your search bar. From an SEO standpoint, this is a huge opportunity to discover new category pages to create. If users are typing this through search, it might be an indication that they can't find those products through the standard navigation. You might uncover categories/products people are looking for but you don't have a dedicated SEO page for. Here's how you get the data: 1. Navigate to GA4 (scary, I know) 2. Go to Admin > Data Streams > Your Data Stream.  4. Ensure that “Enhanced Measurement” is turned on 5. Click on the"Site Search" section. Ensure the "Search Term Query Parameters" box has the query parameter associated with your search.  6. Now navigate to Reports > Engagement > Events and click the "Pencil" icon 7. For "Dimensions" choose "Search Term". For "Metrics", keep these the same and click "Apply" 8. Select Save > Save As New Report and name your report. You'll now be able to see all the queries that users are searching in your search bar. Review these and compare them with your site. If you see queries that people are searching but there is no landing page set up, you might want to create one. If they're typing these queries in your search bar, they're likely typing them in Google too. 

As an analyst, I was intrigued to read an article about Instacart's innovative "Ask Instacart" feature integrating chatbots and chatgpt, allowing customers to create and refine shopping lists by asking questions like, 'What is a healthy lunch option for my kids?' Ask Instacart then provides potential options based on user's past buying habits and provides recipes and a shopping list once users have selected the option they want to try! This tool not only provides a personalized shopping experience but also offers a gold mine of customer insights that can inform various aspects of a business strategy. Here's what I inferred as an analyst : 1️⃣ Customer Preferences Uncovered: By analyzing the questions and options selected, we can understand what products, recipes, and meal ideas resonate with different customer segments, enabling better product assortment and personalized marketing. 2️⃣ Personalization Opportunities: The tool leverages past buying habits to make recommendations, presenting opportunities to tailor the shopping experience based on individual preferences. 3️⃣ Trend Identification: Tracking the types of questions and preferences expressed through the tool can help identify emerging trends in areas like healthy eating, dietary restrictions, or cuisine preferences, allowing businesses to stay ahead of the curve. 4️⃣ Shopping List Insights: Analyzing the generated shopping lists can reveal common item combinations, complementary products, and opportunities for bundle deals or cross-selling recommendations. 5️⃣ Recipe and Meal Planning: The tool's integration with recipes and meal planning provides valuable insights into customers' cooking habits, preferred ingredients, and meal types, informing content creation and potential partnerships. The "Ask Instacart" tool is a prime example of how innovative technologies can not only enhance the customer experience but also generate valuable data-driven insights that can drive strategic business decisions. A great way to extract meaningful insights from such data sources and translate them into actionable strategies that create value for customers and businesses alike. Article to refer : https://lnkd.in/gAW4A2db #DataAnalytics #CustomerInsights #Innovation #ECommerce #GroceryRetail

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

👀 Lessons from the Most Surprising A/B Test Wins of 2024 📈 Reflecting on 2024, here are three surprising A/B test case studies that show how experimentation can challenge conventional wisdom and drive conversions: 1️⃣ Social proof gone wrong: an eCommerce story 🔬 The test: An eCommerce retailer added a prominent "1,200+ Customers Love This Product!" banner to their product pages, thinking that highlighting the popularity of items would drive more purchases. ✅ The result: The variant with social proof banner underperformed by 7.5%! 💡 Why It Didn't Work: While social proof is often a conversion booster, the wording may have created skepticism or users may have seen the banner as hype rather than valuable information. 🧠 Takeaway: By removing the banner, the page felt more authentic and less salesy. ⚡ Test idea: Test removing social proof; overuse can backfire making users question the credibility of your claims. 2️⃣ "Ugly" design outperforms sleek 🔬 The test: An enterprise IT firm tested a sleek, modern landing page against a more "boring," text-heavy alternative. ✅ The Result: The boring design won by 9.8% because it was more user friendly. 💡 Why It Worked: The plain design aligned better with users needs and expectations. 🧠 Takeaway: Think function over flair. This test serves as a reminder that a "beautiful" design doesn’t always win—it’s about matching the design to your audience's needs. ⚡ Test idea: Test functional designs of your pages to see if clarity and focus drive better results. 3️⃣ Microcopy magic: a SaaS example 🔬 The test: A SaaS platform tested two versions of their primary call-to-action (CTA) button on their main product page. "Get Started" vs. "Watch a Demo". ✅ The result: "Watch a Demo" achieved a 74.73% lift in CTR. 💡 Why It Worked: The more concrete, instructive CTA clarified the action and benefit of taking action. 🧠 Takeaway: Align wording with user needs to clarify the process and make taking action feel less intimidating. ⚡ Test idea: Test your copy. Small changes can make a big difference by reducing friction or perceived risk. 🔑 Key takeaways ✅ Challenge assumptions: Just because a design is flashy doesn’t mean it will work for your audience. Always test alternatives, even if they seem boring. ✅ Understand your audience: Dig deeper into your users' needs, fears, and motivations. Insights about their behavior can guide more targeted tests. ✅ Optimize incrementally: Sometimes, small changes, like tweaking a CTA, can yield significant gains. Focus on areas with the least friction for quick wins. ✅ Choose data over ego: These tests show, the "prettiest" design or "best practice" isn't always the winner. Trust the data to guide your decision-making. 🤗 By embracing these lessons, 2025 could be your most successful #experimentation year yet. ❓ What surprising test wins have you experienced? Share your story and inspire others in the comments below ⬇️ #optimization #abtesting

Are You Spending Too Much to Acquire a Customer, Or Not Enough? E-commerce brands often focus on lowering their customer acquisition costs (CAC). But what if cutting CAC is actually hurting growth? The real question isn’t just how much does it cost to acquire a customer? It’s how much should you be spending? If you knew with certainty that a customer would generate $500 in long-term profit, would you hesitate to spend $100 to acquire them? Probably not. But many brands take a one-size-fits-all approach, capping CAC at an arbitrary percentage of their first purchase revenue. This can lead to underinvestment in acquiring high-value customers and overinvestment in customers who won’t stick around. A better approach is to align CAC with long-term customer equity, not just at a blended level, but dynamically across customer segments. Some customers have significantly greater revenue potential than others. The challenge is identifying which customers will create sustainable profitability over time. The chart illustrates that customer acquisition cost (CAC) and lifetime value (LTV) are not linear, spending more on acquisition can lead to higher-value customers, but only up to a certain point. Key Insights: There is an optimal CAC range. - Spending too little on CAC (left side of the chart) may result in acquiring lower-value customers, limiting long-term profitability. - Spending too much (right side of the chart) can lead to diminishing returns, where LTV does not justify the extra spend.   The breakeven threshold matters. - The red dashed line represents where CAC = LTV, meaning any spend above this line is unprofitable unless justified by strategic goals (e.g., market share growth). Smarter spending, not just lower spending, drives profitability. - Many brands mistakenly focus only on reducing CAC, but the real goal is to align CAC with future LTV dynamically across customer segments. What This Means for Retailers Instead of asking, “How much does it cost to acquire a customer?”, the real question is: - How much should we spend to acquire the right customers? - How long will it take to break even on acquisition costs? - Which acquisition channels and products lead to the highest-value customers? Retailers who leverage AI-driven insights to align CAC with future Customer Equity, not just at a blended level but dynamically across customer segments, can spend smarter, scale faster, and drive long-term profitability. If you want to go deeper on this topic, Professor Peter Fader has done extensive research on customer-centric growth strategies. Check out this fascinating podcast with Nick Hague on how businesses can take a more data-driven approach to optimizing CAC. https://lnkd.in/eGu5EM5g #CustomerAcquisition #EcommerceGrowth #MarketingStrategy #CustomerEquity #GrowthMarketing #CACvsLTV #RetailStrategy #Profitability #WGBTpodcast

Most eCommerce brands obsess over revenue and ROAS. But the real game is in the metrics no one talks about. Here are 10 overlooked KPIs that actually drive growth (and how to optimize them): ~~ 1. LTV:CAC Ratio (The Ultimate Health Check) LTV:CAC = Customer Lifetime Value ÷ Customer Acquisition Cost 1:1 = You’re bleeding money 3:1 = Healthy 5:1+ = Printing cash If you’re below 3:1, either: ✅ Lower CAC (better targeting, UGC ads, referrals) ✅ Increase LTV (subscriptions, upsells, memberships) == 2. 90-Day Repurchase Rate If a customer doesn’t buy again within 90 days, they probably won’t. Fix it by: • Winback campaigns with targeted incentives • Selling bundles that create habits • Building a loyalty program that rewards repeat buyers == 3. Contribution Margin (What’s Actually Left?) CM = Revenue – (COGS + Shipping + Discounts + Ad Spend) If your CM is under 30%, you’re scaling a business that won’t survive. Get margins up by: • Cutting discount dependency • Negotiating lower fulfillment costs • Adding Onward shipping protection == 4. Subscription Churn Rate (The Silent Killer) High churn = your brand is a leaky bucket Fix it by: • Adding pause & skip options via SMS (Skio for example) • Add more delivery options and product variety • Sending an email 7 days before renewal reminding them potential lost perks == 5. Time to Second Purchase (T2P) Track how long it takes for a customer to place their second order—then cut that time in half. Tactics to speed it up: • AI-based Email/SMS flows with hyper-targeted recommendations • Exclusive discounts for second-time buyers • Reorder reminders based on average usage time == 6. Gross Margin per Order (The Scaling Checkpoint) At scale, 40%+ gross margins keep you profitable. If you're below that: • Increase prices (test 10% bumps) • Reduce discounting, do Cashback instead (@ Onward) • Negotiate better supplier terms (carrier rates, 3pl, etc) == 7. Refund & Return Rate A high return rate = a CAC multiplier. Fix it by: • Charging for returns (but offering free exchanges) • Clearer product descriptions & sizing charts • Post-purchase emails on how to use the product == 8. Organic vs. Paid Revenue Ratio If 60%+ of your sales come from paid ads, you’re in trouble. Brands with real staying power win on organic channels. The fix? • SEO & content marketing • Affiliate & referral programs • Retention tactics (VIP, loyalty, subscriptions) == 8. SKU Concentration Risk If 80%+ of your revenue comes from one product, you’re vulnerable. Great brands expand without overextending. Turn one-time buyers into multi-SKU customers with: • Bundles • Exclusive add-ons • Subscription perks == 9. % of Revenue from Returning Customers A healthy DTC brand makes 40%+ of revenue from repeat buyers. If you’re below that, focus on LTV levers: • VIP memberships • Personalized email/SMS offers • Post-purchase nurture flows Follow Josh Payne for deep dives on DTC, SaaS, and investing.

Using Data to Drive Strategy: To lead with confidence and achieve sustainable growth, businesses must lean into data-driven decision-making. When harnessed correctly, data illuminates what’s working, uncovers untapped opportunities, and de-risks strategic choices. But using data to drive strategy isn’t about collecting every data point — it’s about asking the right questions and translating insights into action. Here’s how to make informed decisions using data as your strategic compass. 1. Start with Strategic Questions, Not Just Data: Too many teams gather data without a clear purpose. Flip the script. Begin with your business goals: What are we trying to achieve? What’s blocking growth? What do we need to understand to move forward? Align your data efforts around key decisions, not the other way around. 2. Define the Right KPIs: Key Performance Indicators (KPIs) should reflect both your objectives and your customer's journey. Well-defined KPIs serve as the dashboard for strategic navigation, ensuring you're not just busy but moving in the right direction. 3. Bring Together the Right Data Sources Strategic insights often live at the intersection of multiple data sets: Website analytics reveal user behavior. CRM data shows pipeline health and customer trends. Social listening exposes brand sentiment. Financial data validates profitability and ROI. Connecting these sources creates a full-funnel view that supports smarter, cross-functional decision-making. 4. Use Data to Pressure-Test Assumptions Even seasoned leaders can fall into the trap of confirmation bias. Let data challenge your assumptions. Think a campaign is performing? Dive into attribution metrics. Believe one channel drives more qualified leads? A/B test it. Feel your product positioning is clear? Review bounce rates and session times. Letting data “speak truth to power” leads to more objective, resilient strategies. 5. Visualize and Socialize Insights Data only becomes powerful when it drives alignment. Use dashboards, heatmaps, and story-driven visuals to communicate insights clearly and inspire action. Make data accessible across departments so strategy becomes a shared mission, not a siloed exercise. 6. Balance Data with Human Judgment Data informs. Leaders decide. While metrics provide clarity, real-world experience, context, and intuition still matter. Use data to sharpen instincts, not replace them. The best strategic decisions blend insight with empathy, analytics with agility. 7. Build a Culture of Curiosity Making data-driven decisions isn’t a one-time event — it’s a mindset. Encourage teams to ask questions, test hypotheses, and treat failure as learning. When curiosity is rewarded and insight is valued, strategy becomes dynamic and future-forward. Informed decisions aren't just more accurate — they’re more powerful. By embedding data into the fabric of your strategy, you empower your organization to move faster, think smarter, and grow with greater confidence.

Your highest-intent prospects aren't all the same person. I was reviewing several of our recent BOF campaigns and I was reminded of the fact that: The closer someone gets to conversion, the more your messaging matters. But most marketers treat high-intent audiences like they're all the same person. They're not. Someone who abandoned cart yesterday needs different messaging than someone who's been browsing for three weeks. Someone on mobile at 2pm needs different creative than someone on desktop at 9pm. Here’s what you should do: 1️⃣ Understand intent decay patterns. We've tracked this across client accounts - purchase intent has a half-life. After someone shows buying signals, you have roughly 72 hours of peak conversion opportunity. Day 4-7, intent drops 60%. By week two, you're basically starting over. Many advertisers waste this window with generic "complete your purchase" messaging. 2️⃣ Segment your BOF audiences by recency, not just behavior. Recent cart abandoners get urgency-focused creative. Week-old browsers get social proof and reviews. Month-old prospects need fresh product education. Same goal, different psychology. We've seen 40%+ ROAS improvements just from this basic segmentation. 3️⃣ Rotate creative elements based on engagement, not calendar. Most teams mess up by refreshing on schedule instead of performance. Monitor micro-signals: when CTR drops 15% from peak, when frequency hits 2.5x without converting, when engagement falls while impressions climb. Don't wait for Meta to flag fatigue. 4️⃣ Test messaging depth, not just messaging type. Generic "20% off" performs worse than "still thinking about those running shoes?" for cart abandoners. Specific beats generic at every intent level. We use AI to personalize hooks based on browsing behavior, and it consistently outperforms broad creative by 25-35%. Most BOF campaigns fail because they treat high-intent traffic like low-intent traffic. You've already done the hard work of getting someone interested. Don't waste it with lazy messaging.