Analyzing Customer Journey Analytics

Most assume data stories will consist entirely of charts, but that’s not always the best approach. Sometimes, non-data visuals do a better job at structuring ideas, clarifying relationships, and guiding decisions. Yes, bar charts, line charts, and scatterplots help communicate key findings and insights, but data storytelling isn’t just about presenting numbers—it’s about explaining, persuading, and driving action. That’s where non-data visuals can help. They can establish the problem, clarify key concepts, and frame possible solutions in a way that is easier to grasp. Here are a few examples of how you might use non-data visuals: 𝐕𝐞𝐧𝐧 𝐝𝐢𝐚𝐠𝐫𝐚𝐦 → 𝐒𝐡𝐨𝐰𝐬 𝐫𝐞𝐥𝐚𝐭𝐢𝐨𝐧𝐬𝐡𝐢𝐩𝐬 𝐚𝐧𝐝 𝐨𝐯𝐞𝐫𝐥𝐚𝐩𝐬 📌 Use case: Analyzing customer behavior across two product categories. "60% of Product A users also use Product B, but 40% don’t. This suggests an opportunity for cross-selling." 𝐇𝐢𝐞𝐫𝐚𝐫𝐜𝐡𝐲 𝐩𝐲𝐫𝐚𝐦𝐢𝐝 → 𝐈𝐥𝐥𝐮𝐬𝐭𝐫𝐚𝐭𝐞𝐬 𝐡𝐢𝐞𝐫𝐚𝐫𝐜𝐡𝐲 𝐚𝐧𝐝 𝐩𝐫𝐨𝐠𝐫𝐞𝐬𝐬𝐢𝐨𝐧 📌 Use case: Explaining the drivers of customer satisfaction. "At the base level, customers expect reliability. Moving up, customer support influences satisfaction, but at the top, personalization creates long-term loyalty." 2𝐱2 𝐦𝐚𝐭𝐫𝐢𝐱 → 𝐂𝐚𝐭𝐞𝐠𝐨𝐫𝐢𝐳𝐞𝐬 𝐚𝐧𝐝 𝐩𝐫𝐢𝐨𝐫𝐢𝐭𝐢𝐳𝐞𝐬 📌 Use case: Evaluating marketing strategies based on impact vs. effort. "High-impact, low-effort strategies (top-right quadrant) should be our priority—like social media campaigns. Meanwhile, high-effort, low-impact tactics like print ads should be reconsidered." Great data storytelling blends science (data) with art (visual communication). The best stories aren’t just about numbers—they help your audience understand what’s at stake and what to do next. What’s a non-data visual you’ve used (or seen) that made an impact? 🔽 🔽 🔽 🔽 🔽 📬 Craving more of my data storytelling, analytics, and data culture content? Sign up for my newsletter today: https://lnkd.in/gRNMYJQ7 📚Check out my new data storytelling masterclass: https://lnkd.in/gy5Mr5ky 🛠️ Need a virtual or onsite data storytelling workshop or speaker? Let's talk. https://lnkd.in/gNpR9g_K

Many amazing presenters fall into the trap of believing their data will speak for itself. But it never does… Our brains aren't spreadsheets, they're story processors. You may understand the importance of your data, but don't assume others do too. The truth is, data alone doesn't persuade…but the impact it has on your audience's lives does. Your job is to tell that story in your presentation. Here are a few steps to help transform your data into a story: 1. Formulate your Data Point of View. Your "DataPOV" is the big idea that all your data supports. It's not a finding; it's a clear recommendation based on what the data is telling you. Instead of "Our turnover rate increased 15% this quarter," your DataPOV might be "We need to invest $200K in management training because exit interviews show poor leadership is causing $1.2M in turnover costs." This becomes the north star for every slide, chart, and talking point. 2. Turn your DataPOV into a narrative arc. Build a complete story structure that moves from "what is" to "what could be." Open with current reality (supported by your data), build tension by showing what's at stake if nothing changes, then resolve with your recommended action. Every data point should advance this narrative, not just exist as isolated information. 3. Know your audience's decision-making role. Tailor your story based on whether your audience is a decision-maker, influencer, or implementer. Executives want clear implications and next steps. Match your storytelling pattern to their role and what you need from them. 4. Humanize your data. Behind every data point is a person with hopes, challenges, and aspirations. Instead of saying "60% of users requested this feature," share how specific individuals are struggling without it. The difference between being heard and being remembered comes down to this simple shift from stats to stories. Next time you're preparing to present data, ask yourself: "Is this just a data dump, or am I guiding my audience toward a new way of thinking?" #DataStorytelling #LeadershipCommunication #CommunicationSkills

Surveys can serve an important purpose. We should use them to fill holes in our understanding of the customer experience or build better models with the customer data we have. As surveys tell you what customers explicitly choose to share, you should not be using them to measure the experience. Surveys are also inherently reactive, surface level, and increasingly ignored by customers who are overwhelmed by feedback requests. This is fact. There’s a different way. Some CX leaders understand that the most critical insights come from sources customers don’t even realize they’re providing from the “exhaust” of every day life with your brand. Real-time digital behavior, social listening, conversational analytics, and predictive modeling deliver insights that surveys alone never will. Voice and sentiment analytics, for example, go beyond simply reading customer comments. They reveal how customers genuinely feel by analyzing tone, frustration, or intent embedded within interactions. Behavioral analytics, meanwhile, uncover friction points by tracking real customer actions across websites or apps, highlighting issues users might never explicitly complain about. Predictive analytics are also becoming essential for modern CX strategies. They anticipate customer needs, allowing businesses to proactively address potential churn, rather than merely reacting after the fact. The capability can also help you maximize revenue in the experiences you are delivering (a use case not discussed often enough). The most forward-looking CX teams today are blending traditional feedback with these deeper, proactive techniques, creating a comprehensive view of their customers. If you’re just beginning to move beyond a survey-only approach, prioritizing these more advanced methods will help ensure your insights are not only deeper but actionable in real time. Surveys aren’t dead (much to my chagrin), but relying solely on them means leaving crucial insights behind. While many enterprises have moved beyond surveys, the majority are still overly reliant on them. And when you get to mid-market or small businesses? The survey slapping gets exponentially worse. Now is the time to start looking beyond the questionnaire and your Likert scales. The email survey is slowly becoming digital dust. And the capabilities to get you there are readily available. How are you evolving your customer listening strategy beyond traditional surveys? #customerexperience #cxstrategy #customerinsights #surveys

Stop treating your prospects like calculators. I learned this lesson painfully while leading the launch of a new solution for a healthcare transformation organization. The CEO and SVP of Product Innovation were well-intentioned, but they had biases that fueled their convictions. “Show them the science and ROI. Once they see the data, they’ll switch,” said the CEO. “They’ll switch?” I asked curiously. They rarely switched for the logic. They often resisted because we didn’t understand the emotion that tied them to maintaining the status quo. Most B2B marketers still build journeys on the idea that buyers only care about features, scientific studies, and ROI models. But real people buy with their hearts as much as their heads. LinkedIn's B2B Institute found that emotional factors significantly influence B2B buying decisions, accounting for 66%, while rational factors account for the remaining 34%. When you act like every decision is a math problem, you miss the emotional needs and biases that drive action. Fear of missing out. Desire for security. The endorsement of a trusted referral. Those feelings tip the scales long before spreadsheets ever come out. Three quick shifts to make your GTM more human: 💡 Map emotions, not just touchpoints. Ask: What’s the buyer afraid of at each stage? What small win can calm that fear? Use stories to build trust. 💡 Data is important. But a 2-minute customer story about real struggle and success sticks far longer. 💡 Frame decisions around loss-aversion. “Don’t lose your edge” often lands harder than “gain more efficiency.” When you blend hard facts with a genuine understanding of how people feel, you’ll see faster decisions and deeper loyalty. Takeaway: Your next user journey should start with these questions: ✔️ “How do we show up in our customers' struggles? ✔️ "Do they see us as relevant?” ✔️ Can they see their lives as being better because of our help? Build from there. #businessgrowth #GTM #buyerjourney #CMO

Gain a data-driven understanding of your customer through Importance-Performance Maps. In today's competitive business world, differentiating your brand by understanding and delivering what truly matters to your customers is crucial. That’s where Importance-Performance Maps (I-P Maps) come in, providing a powerful visual tool to drive strategic decisions. What exactly is an I-P Map? It's a two-by-two grid that allows you to evaluate how well your brand performs in the areas that are important (as well as *not* important) to consumers. The vertical axis represents the importance of various attributes in consumers' eyes, while the horizontal axis shows your brand's performance in those areas. You can include other brands in your market, too, in order to see how your brand stacks up against the competition along those. When done correctly, every critical attribute of your offering -- whether it's product quality, customer service, or pricing -- is plotted on the I-P Map based on these two dimensions. Why does it matter? I-P Maps reveal your brand's strengths and areas where improvement is needed. Here's a breakdown of the quadrants: - Keep It Up (High Importance, High Performance): These are your strengths—attributes that are both highly important to customers and where your brand performs well. Maintain focus here to keep your competitive edge. - Concentrate Here (High Importance, Low Performance): These are critical areas where your brand is underperforming, despite their high importance to customers. Improving performance here can significantly boost customer satisfaction. - Low Priority (Low Importance, Low Performance): Attributes that are less important and where performance is lower. These areas may not require immediate attention but should be monitored for any shifts in customer priorities. - Possible Overkill (Low Importance, High Performance): Here, your brand may be over-delivering in areas that are not as important to customers. Resources invested here might be better allocated to areas of higher impact. How do I use I-P Maps? Use I-P Maps to make informed decisions backed by data that align with customer expectations. Fix those areas of underperformance that are important to consumers. Stop investing in attributes of your product or service that consumers just don't care about. Prioritize investment in product offerings, elevate aspects of customer service, or reallocate resources to close competitive gaps or strengthen your advantages. Use I-P Maps to make informed choices that improve your business performance in impactful and efficient ways. 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

I audited 70 dtc e-commerce klaviyo accounts last year and they all had the same issues with their customer journey. Make sure you avoid these common mistakes and ensure your messages align with the customer's journey: ▸ Welcome Email 🔹Fix: Remove recipients who have started checkout or placed their order after starting the flow. ▸ Browse Abandonment 🔹Fix: Remove recipients who have started checkout or placed their order after starting the flow. ▸ Abandoned Checkout 🔹Fix: Remove recipients who placed their orders after starting the flow. ▸ First and Repeat Customer Thank You 🔹Fix: Remove recipients who placed their orders, started a checkout, or canceled the order after starting the flow. ▸ Replenishment 🔹Fix: Remove recipients who placed their orders or started a checkout after starting the flow. ▸ Post Purchase 🔹Fix: Remove recipients who placed their orders, started a checkout, or canceled the order after starting the flow. ▸ Winback 🔹Fix: Remove recipients who placed their orders or started a checkout after starting the flow. There are other exit conditions you can add to email and sms flows for better messaging and experience, but these are the most common issues I see. You need to consider the number of times a user can receive a particular flow and whether a subscription customer should or shouldn't enter specific flows (assuming you have a subscription program). Sending relevant messages to your audience helps improve the customer experience and nudges them to take the right action at the right time. What are the other flow filters you would like to add? #emailmarketing #ecommerce

Grateful to be featured in the "Shoptalk Hot Takes" interview by Blenheim Chalcot and ClickZ.com alongside George Looker to unpack omnichannel commerce. 5 key takeaways and tactics from my conversation: 1. Design for Customer Continuity, Not Just Channel Expansion 💡 71% of customers expect brands to personalize interactions across every touchpoint. Tactical: Map out customer journey across channels, then design experiences that recognize and reward continuity—cart persistence, loyalty rewards, browsing history sync, etc. 2. Build the Infrastructure: Unify Data Streams Across All Touchpoints 🧠 Data fragmentation = missed opportunity Tactical: Integrate POS, e-commerce, mobile, social, and marketplace data into a centralized data lake or unified commerce platform. 3. Establish a Single Source of Truth for Customer Profiles 🔍 Brands with unified profiles see up to 2x better campaign performance. Tactical: Implement Customer Data Platforms (CDPs) to consolidate behavioral, transactional, and engagement data into unified customer profiles. 4. Partner Strategically for Scale, Not Just Stack ⚙️ A bloated tech stack doesn’t equal agility As I noted, Retailers are getting sharper about which partners can scale with them. Ecosystem efficiency matters more than ever. Tactical Step: Audit your tech stack and partnerships consistently. Prioritize partners that offer extensibility, future-proofing, and proven omnichannel success. 5. Measure What Matters: Unified KPIs Across Commerce 📈 You can’t optimize what you don’t measure holistically Tactical: Align your analytics stack to report holistically across channels—tie marketing to merchandising, CX to LTV, and inventory to revenue. 🧠 Bottom line: think holistically, move strategically, and build ecosystems that scale experience with agility, not just transactions. Complete list in comment 👇 #ecommerce #omnichannel #unifiedcommerce

Let's talk about the emotional algorithm of B2B decision-making. At the core of every buying decision—whether it's enterprise software or sneakers—lies the same human truth: Logic justifies. Emotion decides. Heartstrings loosen purse strings. We've spent decades pretending B2B decisions are purely rational. The data tells a different story: - Kantar research reveals emotionally-driven digital ads are *4X more likely* to build brand equity than their rational counterparts. - LinkedIn x Magna research shows *39% of B2B buyers* prioritize emotional connection when selecting vendors. (Yes, even for those six-figure contracts!) Yet I see most marketers make one of two fundamental mistakes: 1. They ignore emotion entirely, clinging to sterile "professional" content that feels safe but fails to connect. 2. They treat emotion as a blunt instrument, defaulting to generic inspiration that could apply to any brand in any category. There's a smarter, more nuanced approach. Our Creative Labs team at LinkedIn for Marketing decoded an emotional blueprint that maps precisely to the buyer's journey. I'm breaking it down in today's #PurnasProTip because it's too good not to share. After analyzing top-performing tech brands on our platform, we discovered distinct emotional patterns: - Awareness Stage: Winning content sparks celebration and love, mirroring the optimism of discovery. This is where possibility lives. - Consideration Stage: Reactions shift dramatically to insightful, reflecting the brain's need for evaluation and validation. Depth matters here. - Decision Stage: Top performers blend insightful + love, proving final choices require both confidence and emotional resonance. The head and heart must align. What this means for you: LinkedIn isn't a "suit and tie" network where emotions get checked at the door. It's where professionals come to solve problems, feel understood, and align with brands they genuinely like. The most successful B2B marketers are those who understand the emotional journey behind every seemingly "rational" decision. Infuse the right emotion at the right stage, and watch your impact multiply. Because heartstrings loosen purse strings. #HICM #CreativeLabs #B2BEmotion #HeartstringsLoosenPurseStrings

8 out of 10 analysts struggle with delivering impactful data visualizations. Here are five tips that I learned through my experience that can improve your visuals immensely: 1. Know Your Stakeholder's Requirements: Before diving into charts and graphs, understand who you're speaking to. Tailor your visuals to match their expertise and interest levels. A clear understanding of your audience ensures your message hits the right notes. For executives, I try sticking to a high-level overview by providing summary charts like a KPI dashboard. On the other hand, for front-line employees, I prefer detailed charts depicting day-to-day operational metrics. 2. Avoid Chart Junk: Embrace the beauty of simplicity. Avoid clutter and unnecessary embellishments. A clean, uncluttered visualization ensures that your message shines through without distractions. I focus on removing excessive gridlines, and unnecessary decorations while conveying the information with clarity. Instead of overwhelming your audience with unnecessary embellishments, opt for a clean, straightforward line chart displaying monthly trends. 3. Choose The Right Color Palette: Colors evoke emotions and convey messages. I prefer using a consistent color scheme across all my dashboards that align with my brand or the narrative. Using a consistent color scheme not only aligns with your brand but also aids in quick comprehension. For instance, use distinct colors for important data points, like revenue spikes or project milestones. 4. Highlight Key Elements: Guide your audience's attention by emphasizing critical data points. Whether it's through color, annotations, or positioning, make sure your audience doesn't miss the most important insights. Imagine presenting a market analysis with a scatter plot showing customer satisfaction and market share. By using bold colors to highlight a specific product or region, coupled with annotations explaining notable data points, you can guide your audience's focus. 5. Tell A Story With Your Data: Transform your numbers into narratives. Weave a compelling story that guides your audience through insights. A good data visualization isn't just a display; it's a journey that simplifies complexity. Recently I faced a scenario where I was presenting productivity metrics. Instead of just displaying a bar chart with numbers, I crafted a visual story. I started with the challenge faced, used line charts to show performance fluctuations, and concluded with a bar chart illustrating the positive impact of a recent strategy. This narrative approach helped my audience connect emotionally with the data, making it more memorable and actionable. Finally, remember that the goal of data visualization is to communicate complex information in a way that is easily understandable and memorable. It's both an art and a science, so keep experimenting and evolving. What are your go-to tips for crafting effective data visualizations? Share your insights in the comments below!

Great journey maps start from the intersection of user touchpoints. A customer journey map shows a customer's experiences with your organization, from when they identify a need to whether that need is met. Journey maps are often shown as straight lines with touchpoints explaining a user's challenges. start •—------------>• finish At the heart of this approach is the user, assuming that your product or service is the one they choose to use in their journey. While journey maps help explain the conceptual journey, they often give the wrong impression of how users are trying to solve their problems. In reality, users start from different places, have unique ways of understanding their problems, and often have expectations that your service can't fully meet. Our testing and user research over the years has shown how varied these problem-solving approaches can be. Building a great journey map involves identifying a constellation of touchpoints rather than a single, linear path. Users start from different points and follow various paths, making their journeys complex and varied. These paths intersect to form signals, indicating valuable touchpoints. Users interact with your product or service in many different ways. User journeys are not straightforward and involve multiple touchpoints and interactions…many of which have nothing to do with your company. Here’s how you can create valuable journeys: → Using open-ended questions and a product like Helio, identify key touchpoints, pain points, and decision-making moments within each journey. → Determine the most valuable touchpoints based on the intersection frequency and user feedback. → Create structured lists with closed answer sets and retest with multiple-choice questions to get stronger signals. → Represent these intersections as key touchpoints that indicate where users commonly interact with your product or service. → Focus on these touchpoints for further testing and optimization. Generalizing the linear flow can be practical once you have gone through this process. It helps tell the story of where users need the most support or attention, making it a helpful tool for stakeholders. Using these techniques, we’ve seen engagement nearly double on websites we support. #productdesign #productdiscovery #userresearch #uxresearch