Understanding Ecommerce Customer Segmentation

My Favorite Analyses: the Recency-Frequency matrix. This simple yet powerful framework goes beyond traditional segmentation to provide actionable insights into customer behavior. By focusing on how recently and how often customers engage with your brand, you can tailor your strategies to maximize lifetime value. Why it works: - Recency: Customers who have purchased recently are more likely to purchase again. It's a strong indicator of engagement and future behavior. - Frequency: Customers who purchase more often demonstrate loyalty and satisfaction, leading to a higher customer value. Recency and Frequency are the most important indicators of customer value, exhibiting more correlation to CLV than Monetary Value which is the third component in traditional RFM analyses. The Recency-Frequency matrix helps you categorize your customers into segments based on behaviors instead of factors like demographics or psychographics that imply actions. The analysis reveals distinct customer segments that require unique marketing strategies, including your Champions, the customers who Need Attention, and those who have Already Churned. Implementing the Matrix: Depending on the size of your customer dataset, the Recency-Frequency matrix can be built in a spreadsheet or a more hefty tool like SQL or R. - Excel/Google Sheets: Use `MAXIFS`, `COUNT`, `PERCENTRANK`, and a pivot table to build the Recency-Frequency matrix, but watch out for row limits. - SQL: Leverage functions like `DATEDIFF` and `COUNT` to calculate metrics, and segment with `NTILE`. - R: The `RFM` package handles large datasets with ease, offering advanced segmentation and visualization. This approach isn’t just theory — it’s a data-backed method for ensuring your marketing dollars are spent where they’ll make the most impact. DM me if you'd like to learn more, including the marketing strategies that I most commonly recommend for each Recency-Frequency matrix customer segment. Art+Science Analytics Institute | University of Notre Dame | University of Notre Dame - Mendoza College of Business | University of Illinois Urbana-Champaign | University of Chicago | D'Amore-McKim School of Business at Northeastern University | ELVTR | Grow with Google - Data Analytics #Analytics #DataStorytelling #MyFavoriteAnalyses #ROI #MROI

Don't underestimate the power of old-school data analysis techniques. For example, my clients love RFM analysis: (R)ecency (F)requency (M)onetary Here's how RFM analysis works. (R)ecency is the time since a customer's last purchase. Customers in the top 10% of recent purchases receive a score of 9. Customers in the bottom 10% receive a score of 0. Each customer gets a recency score from 0 to 9. (F)requency is the number of customer orders over some time (e.g., the last year). Customers in the top 10% of frequency receive a score of 9. Customers in the bottom 10% receive a score of 0. Each customer gets a frequency score from 0 to 9. (M)onetary is the total lifetime purchases of your customers. Customers in the top 10% of lifetime purchases receive a score of 9. Customers in the bottom 10% receive a score of 0. Each customer gets a monetary score from 0 to 9. Your absolute best customers will have a score of 999. The next tier will have scores of 998, 989, and 899. And so on. Here's the thing, though. You can customize the ideas behind RFM to fit your situation. Here's a real-life example. I performed a marketing analysis of US geographies. The goal was to find the optimal geographies for digital ads. I joined internal data with free data from the US Census Bureau. I then performed an RFM-style analysis of the data. I scored each geography with four characteristics. For example, the count of high-income households. The best geographies scored 9999. Using this analysis, I identified US geographies with opportunities for digital ads.

Remarketing is often the misunderstood middle child of performance marketing. Let’s break a couple of myths🔨 🎯 One size fits all fits probably no one:  I’ve seen many companies burn money on campaigns that don’t recognize that every section of their audience has their own motivations. Why, if I had a penny for every time I visited a site with no intent to purchase their product at all, only to spot a “Schedule a Demo Today” ad by them on whichever site I visit, I’d probably be the richest guy in SaaS! I read somewhere that 84% of users either ignore or are put off by retargeting ads! Shows how important it is to get it right. Start doing these things: - Segment visitors by page depth (1 page vs 3+ pages) - Track time-on-site thresholds (>2 min = higher intent) - Create separate campaigns for pricing page visitors vs. blog readers Tailor your content based on your audience’s behavior and stage in the buyer journey (URL path visitors, action completers, cart abandoners) 🎯 Retargeting works like a mosquito coil:  Retargeting is not plug and play, and it typically doesn’t stop with one level. Retarget for all customer stages. Not only demo and trial signups. This insulates your prospects from leaving the funnel midway. We’ve had cases where we spent thousands of dollars on a retargeting campaign only to make zero sales. But here’s what happened afterward ⭐ : When we triggered another retargeting campaign for the warmer folks from the previous campaign, giving them BOFU content, we made sales. A lot of it! What’s to learn here? You’re unlikely to be bet on with just the first touch point. You have to build that awareness consistently. Create a 3-tier remarketing structure: > Tier 1 (Cold): Educational content, industry reports > Tier 2 (Warm): Case studies, comparison guides > Tier 3 (Hot): Free trials, demos, limited-time offers Build custom audiences for each segment, assign specific content types to each, and implement frequency caps based on ‘bucket temperature’. Also, the focus should also be on increasing the credibility of your company rather than only pushing them towards the CTA. Here's one customized Google + LinkedIn campaign strategy we used for a client recently. What are some retargeting tactics that’s worked for you?

This is the most important table in e-commerce—but no one ever talks about it and it's costing you MILLIONS. It's not a cap table. It's not an AOV table. It's the returning customer cohort table. It shows by month acquired, how much customers are worth on first order and each month thereafter. Why it's the most important thing in ecom: 1. True Customer Value Revealed A $50 first order may become $120 over 6 months. This changes everything - suddenly, that "expensive" acquisition cost is a bargain. Many brands have ROAS targets that are too high, they aren't accounting for 60-90D value. 2. Market Domination Justify higher CAC by looking at long-term value. If 90-day value is $200, you can afford $100 CAC while competitors cap at $50. Dominate your market. 3. Cohort Analysis Insights Discover which channels bring high-value customers. FB ads might cost more but deliver 3x lifetime value vs. Google. Optimize spend accordingly. 4. Cash Flow Management Predict payback periods accurately. If cohorts show 60-day breakeven, confidently reinvest every two months. Scale aggressively but safely. 5. Product Strategy Identify which products create loyal customers. If Product A has 70% retention vs 30% for B, prioritize A in marketing and development. 6. Forecasting Precision If cohorts consistently grow 20% monthly, project revenue 6-12 months out with confidence. Plan inventory, hiring, and expansion strategically. Master the cohort table to build a customer value engine that compounds over time. This is how category-defining brands are built. Not by having the highest ROAS.

Should you retarget by intent? We ran the test... Most B2B retargeting looks something like this: Someone visits your site, any page at all…and immediately: they’re getting hit with “Book a demo” or “Start your free trial” ads. No nuance. No context. Just one-size-fits-all messaging chasing every visitor around the internet. It’s simple. It’s easy. But also pretty broken. Here’s why: > Not everyone on your site is in the same headspace. > Blog readers aren’t ready to talk to sales. > Product page visitors are curious but not convinced. And people on the demo page? They’re this close but something’s holding them back. Treating all three the same? That’s how you burn ad dollars without actually building pipeline. So we ran a test. One of our clients had a basic retargeting setup. One campaign. One CTA. One generic message. We broke it apart and rebuilt it based on intent. ___________________________ Here’s how we segmented it: Blog readers Top-of-funnel folks in research mode. → We showed them value-first content: guides, checklists, downloads. Product & feature page visitors Mid-funnel visitors sniffing around the solution. → We served ROI calculators, interactive tools, and “how do you stack up” style CTAs. Pricing/demo page visitors Bottom-of-funnel leads with real buying signals. → They saw direct “Book a demo” and “Start your trial” ads with tons of social proof. ___________________________ Here’s what happened over 60 days: Old campaign (one-size-fits-all): > Low click-through rates (~0.4%) > Modest form fill volume > Demo-to-close rates hovering around 17% New segmented retargeting: > 3.1x higher CTR > 2.4x more total form fills > 29% increase in demo-to-close conversion from high-intent segments ___________________________ Better message-match. Cleaner funnel transitions. Better results.

One mistake that several marketers make is to treat every user in the same way. All users are not equal. They are at different stages of their buying journey. Knowing how they differ won’t let you control WHEN they’ll buy. But it’ll help you market better so that when they buy, they choose you. Here’s how needs/objections vary with stages of a buyer journey. 🧵 *** [1] Awareness They know you exist.  Maybe they’ve seen an ad, or heard of you from a friend. But they don’t need you. Ex - If you’re selling toys for kids of < 5 yrs, I may be aware of you, but I don't need you as I don't have any kids. You filter an aware audience into an audience with intent/need (more on this in the next post). *** [2] Intent These are people who need your product, looking for options. But they may not buy from you because they don’t trust you…yet. Ex- Parents of kids aged < 5 years in the above example and are concerned about their child's engagement. This is the stage where you identify them and start building trust about your brand. *** [3] Trust + Purchase They’re ready to buy, and you’re their top choice. Good! It’s because you’ve managed to address their objections and won their trust.  Your goal now is to create urgency and remove any friction so they buy from you soon. But that’s not all… *** [5] Loyalty Two ways happy customers can help you grow:  → repeat purchases → referrals Ex - The parents whose kids loved the toys - ask them to refer a friend. That's more customers in the funnel. Also, keep in touch, so next time they want to buy, you’re on top of their minds. *** Consider this, you can’t sell even to your ideal customer without awareness or trust. Your message needs to match the stage of your buyer.

Why Buyer Personas Are Often Useless (Unless You Do Them Right) Buyer personas. Every marketer talks about them, but how many of us actually use them to drive real results? Too often, buyer personas are treated as an exercise in check-box marketing: Create a template, fill in some basic demographics, and call it a day. But this is a recipe for wasting time and burning calories. The real power of buyer personas lies in the depth of insight they provide about the emotional, psychological, and behavioral triggers of your target audience. When done right, personas become your roadmap for everything—product decisions, messaging, marketing strategies, and sales enablement. But when done wrong, they’re useless. So, how should you approach Buyer Personas? 1. Go Beyond Demographics It’s easy to create personas based on age, job title, and income. But that’s not what actually drives a purchase decision. You need to understand why your customers buy your product—what pain points are they solving, what motivates them, and what stands in their way. 2. Focus on Behavior and Needs Instead of just a “one-size-fits-all” persona, segment by behavior and customer journey stage. Are they early-stage prospects or ready to buy? How do they interact with your product? Behavior speaks volumes. 3. Constantly Evolve Your personas shouldn’t be static! The market, technology, and customer needs evolve—so should your personas. Continuously gather feedback from your users, sales teams, and customer support. Buyer personas done right can drive growth, shape product development, and create hyper-targeted marketing strategies. But done poorly? They’re just another file on the shelf. #growthmarketing #buyerpersonas #marketing

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.

Way too many e-commerce brands run bare-minimum loyalty programs that don't move the needle. Points. Discounts. It gets old quick. Your top 10% of customers likely drive 40-65% of your profit. But are you treating them like the VIPs they are? Or just sending them the same generic emails as everyone else? Brands that are crushing it right now are building tiered VIP ecosystems that transform transactional shoppers into high-LTV brand advocates. Speaking from 4+ years of experience, I’ve learned a few things that actually work: --> Early access drops that make top customers feel like insiders --> Exclusive product variants unavailable to regular customers --> Private Slack/Discord communities connecting your best customers --> Physical gifts that arrive unexpectedly (not just on birthdays) --> VIP-only virtual events with your founder/designers Data doesn't lie. Well-designed VIP programs consistently deliver 3-5x ROI compared to acquisition campaigns. These programs also cost dramatically less than constantly chasing new customers. Stop treating loyalty like a cost center using discounts, and start treating it like the profit driver it should be, like leveraging experiences, exclusivity, or building relationships. Your competitors are leaving millions on the table with lackluster VIP strategies. The opportunity is massive for brands willing to invest in their best customers the right way. Who's doing VIP programming exceptionally well in your category? Curious to hear some examples.

Ever wonder why most shoppers never finish checking out? Nearly 70% of carts get left behind. Feels personal, right?   The truth: shoppers bail because what they see doesn’t 𝑓𝑒𝑒𝑙 made for them. Static pages and generic product blocks just aren’t cutting it.   𝗗𝘆𝗻𝗮𝗺𝗶𝗰 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 fixes this.💡   When your store adapts in real time, → Shoppers spot products that fit their vibe → Banners shout out sales and bundles that matter to them → Every touchpoint feels personal, not random   We've seen it firsthand. Conversion rates double. Bounce rates drop. Customers actually come back.   𝗤𝘂𝗶𝗰𝗸 𝗪𝗶𝗻𝘀: ✅ Show recently viewed products upfront ✅ Personalize offers based on browsing history ✅ Use urgency—like “selling fast”—only for 𝑟𝑒𝑙𝑒𝑣𝑎𝑛𝑡 items   People want to feel seen, not sold to. It's not about tricking them into buying. Make every visit feel like it was designed 𝑗𝑢𝑠𝑡 𝑓𝑜𝑟 𝑡ℎ𝑒𝑚, and your abandoned cart problem shrinks.   Are you personalizing content for your visitors yet, or still rolling with the same template for everyone?   https://lnkd.in/g-GPkvCW   #eCommerce #ConversionRate #Personalization #CRO