Best Practices for Digital Marketing Analytics

Back when I worked on user growth @ Pinterest, I conducted 3 retention analyses that helped Pinterest grow to 450M+ MAU’s. Excited to share those analyses on Reforge Artifacts. Check it out 👇 🔗 Link to each artifact/analysis in comments. 🕹 1. Feature Retention Analysis: How can you tell when a new feature is good enough? When should you promote it? It's a question you often run into in a rapidly evolving startup. At Pinterest, we were developing an AR/VR feature called Lens. It allowed users to take pictures of objects around them and find similar pins. Before we poured time and effort on the growth team into driving users to it, we wanted to know if the feature had “product-feature fit” — i.e. were people getting value out of this feature regularly, or was it just a novelty? We benchmarked the new AR features against Pinterest features like repinning and search. We built retention curves for each feature to see if the new AR features were falling in the ballpark of other core features. In the data we saw that retention was low, people were checking it out because it was cool, but not coming back since they weren’t finding recurring use cases for it, so we made the call to not have the growth team heavily promote the feature. 📊 2. Churn Probability Analysis: In the early days of Pinterest we were developing one of our first retention emails. One of the primary questions we needed to answer was when should we intervene to try and win someone back? Our intuition was that for a really active user, you might get worried after a few days, but for a less engaged user it might be ok if they are inactive for a week or more. So we created a heatmap to show the relationship between how active a user was and how many days they had been inactive on churn probability. 🔥 To actually use the heat map, we set a cut line of 20%. We decided that when a user's churn probability hit 20%, that's when we'd send a notification or email to try to re-engage them. 📵 3. Cost of Unsubscribe Analysis: Notifications are a core lever to driving retention for many products. A couple years into scaling Pinterest’s email program, the team was sending a dozen types of emails. We wanted to understand how unsubscribing impacted user retention. We needed to get some sort of feel for the cost associated with an unsubscribe to help us understand how many emails were too much. So we did a analysis to look at correlations between someone unsubscribing and their longer-term retention after that action. 🤯 We were really surprised to see that unsubscribes had a pronounced increase in churn propensity for our core and casual users, but virtually no impact on churn for dormant, new, and resurrected users.  Our key takeaway was that we should be more sensitive about email volume with our core and casual users. Check out the full analysis at the link in the comments. ⬇

If your web analytics strategy still focuses only on pageviews and bounce rates, you may be measuring the past—not the customer journey of today. The digital world has changed. Customer behavior has changed. And the way businesses understand their audience must evolve too. 𝐌𝐨𝐝𝐞𝐫𝐧 𝐰𝐞𝐛 𝐚𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 is no longer just about tracking clicks and sessions. It is about understanding intent, context, and customer needs. The future of analytics is moving towards: 🔹𝐈𝐧𝐭𝐞𝐧𝐭 𝐒𝐢𝐠𝐧𝐚𝐥𝐬 𝐎𝐯𝐞𝐫 𝐁𝐚𝐬𝐢𝐜 𝐁𝐞𝐡𝐚𝐯𝐢𝐨𝐫 Understanding why customers engage, not just what they click. 🔹𝐂𝐨𝐦𝐩𝐨𝐬𝐚𝐛𝐥𝐞 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐎𝐯𝐞𝐫 𝐎𝐧𝐞-𝐒𝐢𝐳𝐞-𝐅𝐢𝐭𝐬-𝐀𝐥𝐥 𝐓𝐨𝐨𝐥𝐬 Building flexible ecosystems that bring together the right data sources. 🔹𝐅𝐢𝐫𝐬𝐭-𝐏𝐚𝐫𝐭𝐲 𝐃𝐚𝐭𝐚 𝐎𝐯𝐞𝐫 𝐓𝐡𝐢𝐫𝐝-𝐏𝐚𝐫𝐭𝐲 𝐃𝐞𝐩𝐞𝐧𝐝𝐞𝐧𝐜𝐞 Creating direct relationships with customers through trusted data strategies. 🔹𝐂𝐨𝐡𝐨𝐫𝐭 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬 𝐎𝐯𝐞𝐫 𝐈𝐧𝐝𝐢𝐯𝐢𝐝𝐮𝐚𝐥 𝐒𝐞𝐬𝐬𝐢𝐨𝐧𝐬 Finding patterns that help businesses make smarter marketing and product decisions. The companies that succeed will not be the ones collecting the most data. They will be the ones who understand their data better and turn insights into action faster. 👉 Analytics is no longer just a reporting function. It is a strategic advantage. How is your organization evolving its analytics approach? #WebAnalytics #DigitalAnalytics #DataStrategy #MarketingAnalytics #DigitalTransformation #Analytics #BusinessIntelligence #FirstPartyData

Update Your Google Analytics Goals in 5 Minutes for Accurate Tracking Google Analytics goals are essential for tracking actions that align with your business objectives, whether that's generating leads, increasing sales, or boosting engagement. Well-defined goals allow you to measure how effectively your website meets these objectives by tracking actions like form submissions, downloads, and page visits. This data helps refine your marketing strategies and supports data-driven decisions. -Destination Goal: Tracks when a user reaches a specific page (e.g., a thank-you page after a form submission). -Duration Goal: Monitors how long users spend on your site. -Pages/Screens per Session Goal: Measures the number of pages viewed in a session. -Event Goal: Tracks specific actions like video plays, button clicks, or downloads. Setting up goals can be challenging due to the need to align them with business objectives. Additionally, the technical setup requires familiarity with analytics tools, as incorrect configurations can lead to inaccurate tracking. Goals must also be updated as business objectives change to maintain relevance, especially for multi-step conversions, which add complexity. Quick 5-Minute Guide to Setting Up or Updating Google Analytics Goals -Access Goals: Log in and navigate to Admin > Goals in the View column. -Create/Update Goal: Click +New Goal or select an existing one; choose a setup option or Custom. -Select Goal Type: Choose the appropriate type (Destination, Duration, Pages per Session, Event). For form submissions, select Destination and enter the confirmation URL. -Define Details: Set specifics like URL or session duration and assign a Goal Value if needed. -Test and Save: Click Verify This Goal to check accuracy, then save it. Setting up goals enhances decision-making by providing insights into website performance. Tracking goal completions can improve conversion rates by optimizing effective site elements. Goals ensure alignment with business objectives, monitor key performance indicators, and help improve user experience. Updating Google Analytics goals is a quick yet impactful way to enhance performance tracking. By aligning goals with key actions—such as form submissions and purchases—you can track conversions and make informed decisions. In just five minutes, you can ensure your website accurately captures data that matters most to your business. #GoogleAnalytics #DigitalMarketing #AnalyticsGoals #DataTracking #MarketingTips #OnlineMarketing #WebsiteMetrics

Your biggest revenue leak isn't failed sales calls. It's what happens after customers buy.   I'm grateful when leaders invite me to challenge their thinking about growth strategy. A recent engagement perfectly illustrates why this matters.   Two partnering companies brought me in to map their customer experience. Everything looked brilliant...until we hit the purchase point.   The journey just... stopped.   When I pushed on Time to Customer Value strategies, the leadership team was candid: "We're product-led. The product speaks for itself."   Their openness to challenge this assumption changed everything.   Here's the math that should concern every executive:   ➡️ A 5% improvement in customer retention drives 25-95% increase in profits. Not 5%. Not 25%. Up to 95%.   ➡️ McKinsey found that existing customers account for 33-50% of total revenue growth, even at startups. The cost? A fraction of new customer acquisition.   But here's where the math gets exponential.   Most companies focus CS efforts on annual renewals. They're thinking additively when they should be thinking exponentially.   Winning by Design's research shows companies focusing on monthly expansion opportunities see 41.6% higher revenue growth over three years.   The compound effect is brutal: 1% improvement daily = 3,778% gain annually. Customer Success isn't support. It's your most scalable revenue engine.   The best CS teams operate like sales teams — with conversion metrics across the post-sale journey: • Onboard • Retain • Expand   When companies cut CS headcount to "save costs," they trigger a death spiral.   More accounts per CSM = less attention per customer = higher churn = shorter contract lengths = massive CLV destruction.   Time to Value isn't just about customer satisfaction; it's the key determinant of ROI and customer confidence in you as a partner.   The question isn't whether you can afford to invest in Customer Success. It's whether you can afford not to.   What assumptions about post-sale strategy deserve to be challenged in your organization? Share your Time to Value insights below.   #CustomerSuccess #GTM #SustainableGrowth #TimeToValue #RevenueGrowth

Attribution has never been perfect, but for DTC brands, it has become significantly harder in the past few years. Apple’s iOS14 updates, third-party cookie deprecation, and increased privacy regulations have disrupted traditional attribution models. Brands that once relied on last-click attribution, ad platform reporting, or rule-based LTV calculations now face major blind spots in understanding which marketing efforts drive long-term value. Even those investing in first-party data strategies, post-purchase surveys, and media mix modeling (MMM) struggle to fully connect the dots. The reality is that data is still fragmented across multiple platforms such as Shopify, Klaviyo, Google Analytics, ad networks, and third-party analytics tools. Most solutions focus on aggregating data, but aggregation alone doesn’t tell the full story of how customers move through the funnel and what actually drives retention. Rob Markey - In his article, "Are You Undervaluing Your Customers?" published in the Harvard Business Review, Markey emphasizes the significance of measuring and managing the value of a company's customer base. He advocates for creating systems that prioritize customer relationships to drive sustainable growth. Chip Bell - Recognized as a pioneer in customer journey mapping, Bell has contributed significantly to the field of customer experience. In an interview titled "The father of customer journey mapping, Chip Bell, talks driving innovation through customer partnership," he discusses how organizations can co-create with customers to drive innovation and enhance the customer journey. So how do brands solve this? 1. Shift from static LTV models to predictive insights - Traditional LTV calculations are backward-looking, often based on averages that don’t account for future behavior. Predictive analytics, using real-time behavioral and transactional data, can provide a more accurate forecast of customer lifetime value at an individual level. 2. Invest in first-party data strategies that go beyond acquisition - Many brands have adapted to privacy changes by collecting more first-party data, but few are fully leveraging it. Loyalty programs, surveys, and on-site behavioral tracking can provide valuable insights into retention and repeat purchase drivers, helping brands reallocate spend more effectively. 3. Adopt AI-driven segmentation and customer equity scoring - RFM segmentation and standard cohort analysis have limitations. AI-powered models can help identify high-value customers earlier in their lifecycle, predict churn risk, and optimize acquisition based on true long-term value, not just early spend. Markey and Bell have long emphasized that customer loyalty isn’t built on transactions alone, it’s about the entire journey. Brands that can better understand and predict customer value will be the ones that thrive in a world where third-party tracking is no longer a reliable option. #CustomerJourney #Attribution #CustomerEquity

I spoke with a D2C brand that had skyrocketed its organic traffic yet their daily orders were still flat. They came to me expecting a quick SEO fix. But as I dug deeper, I realized what they needed was a strategic framework —an integrated set of choices that would drive not just visitors, but profitable orders. Initial Situation: ➜ 10x increase in daily clicks (from almost nothing to 2,000/day) ➜ Average Order Value (AOV) surprisingly low ➜ Order volume: virtually unchanged despite the traffic surge Problem Identification: Why wasn’t all that new traffic turning into sales? The brand had invested in SEO, yes—but without aligning content strategy with top-selling SKUs, profit margins, demographics, and their unique value proposition. ❌ They chased visibility, not viability. Process (Our Discovery Call): I asked questions like: ➜ Top-selling SKUs? ➜ High-margin categories? ➜ Core audience and demographics? ➜ Product Differentiators vs. competition? ➜ Customer repeat purchase cycles? By understanding these, I identified where intent-rich opportunities matched their strongest business levers. What We Did Next (The Proposal): I presented a tailored SEO program that went beyond “just more traffic.” It focused on: a) Where we choose to play: Pinpointing search opportunities that have a short time to value of results. b) How we choose to win: Mapping keywords to product categories with favourable Search Volume, Keyword Difficulty (KD), and Average Order Value. I presented them a scatter chart of commercial-intent keywords plotted by: ➜ Search Volume ➜ Keyword Difficulty ➜ Potential AOV Impact This instantly clarified the path forward. Instead of random traffic, we were going after the right traffic. The prospect’s reaction? He said no previous proposal had offered this level of strategic clarity. It’s easy to chase vanity metrics (traffic, rankings, clicks), but without aligning your SEO strategy to business goals, you’ll never see the revenue catch up. Stop treating SEO as a game of traffic. ➡️ Treat it as a strategic tool that positions you in front of high-intent audiences. ➡️ It’s not about playing everywhere—it’s about winning in the right places. If you’re looking to make strategic choices—on Google, Bing, or next-gen platforms like ChatGPT, Perplexity, Claude —and you want to translate visibility into growth, let’s talk. I’d be excited to help you map your SEO opportunities to real business outcomes.

The startup math nobody teaches you VCs know this math. Most founders don't. 2% growth + 80% retention curve = UNICORN 🦄 10% growth + 5% retention curve = BANKRUPT 💸 Let me show you the brutal math behind this: Start with 10,000 users. SCENARIO A:  -  10,000 initial users -  5% monthly retention -  10% monthly new user acquisition After 4 months:  • Month 1: 10,000 users • Month 2: (10,000 × 5%) + 1,000 new = 1,500 users  • Month 3: (1,500 × 5%) + 150 new = 225 users  • Month 4: (225 × 5%) + 22 new = 33 users SCENARIO B:  -  10,000 initial users -  80% monthly retention -  2% monthly new user acquisition • Month 1: 10,000 users  • Month 2: (10,000 × 80%) + 200 new = 8,200 users  • Month 3: (8,200 × 80%) + 164 new = 6,724 users  • Month 4: (6,724 × 80%) + 134 new = 5,513 users This still decreases, but the retention math becomes magical when you hit the stability threshold: Simple math: To maintain stable user numbers, your monthly acquisition must equal your monthly churn. Now let's see what happens if both companies can acquire just enough to offset churn: SCENARIO A needs 9,500 new users monthly (95% of 10,000) to stay stable.  SCENARIO B needs 2,000 new users monthly (20% of 10,000) to stay stable. The burn rate math is even more devastating: If your retention curve hits 5%: -  For every 100 users you acquire, 95 disappear -  At $50 CAC, you're spending $1,000 per retained user If your retention curve flattens at 80%: -  For every 100 users you acquire, 80 stay -  At $50 CAC, you're spending $62.50 per retained user People celebrated 10M downloads with 2% retention instead of fixing what made 98% of users leave. If you retain 5% of users, you need 20 new customers to replace every 19 who leave. At 80% retention? You need 1 new customer to replace every 4 who leave. Your marketing budget goes 5X further with good retention. VCs know this math. Most founders don't. Every investor I know secretly plots your retention curve before deciding to fund you.

Customer Success protects $67M with three people. Sales burns $4.2M chasing $8.3M with twenty-eight reps. CEO hired 15 more salespeople while customers canceled $12M. The Head of Customer Success could only watch. At this $80M ARR SaaS company,  her team of three managed $67M in existing revenue. Meanwhile, 28 sales reps chased new deals. The math was backwards. Customer Success cost $340K annually, generated $67M in renewals. Sales cost $4.2M, brought in $8.3M new ARR. Revenue per dollar invested: Customer Success: $197 for every $1 spent Sales: $2 for every $1 spent Board meetings always centered on pipeline. Customer Success was never mentioned until renewal season. The Head of Customer Success ran retention analysis: Current rate: 78% Churn reasons were documented and totally fixable: - Poor onboarding (32%) - Unmet sales expectations (28%) - Inadequate support (23%) - No value realization (17%) Her proposal: Instead of hiring 10 salespeople ($1.4M),  invest that amount in Customer Success. Projected impact: Retention increases from 78% to 88%. On $67M base, that's $6.7M additional recurring revenue. ROI: 479% vs maybe $3M from new salespeople. The CEO's response: "We need growth, not just maintaining what we have." Six months later, they missed annual targets  despite exceeding new customer acquisition. The Head of Customer Success left for a competitor. Her new company: 12 CS managers for $45M ARR. Retention rate: 94%. Growth rate: sustainable. Companies that prioritize retention foundation dominate markets. Companies that don't churn themselves out of business. You can't out-sell a retention problem.

We had churn hiding in our high NRR. No one suspected we had a problem. We were crushing our Net Revenue Retention (NRR) targets. Expansion was strong. Customers were increasing usage. Leadership was happy. On paper, everything looked great. But there was something lurking in the data—logo churn. At one of my past companies, we operated on a consumption-based model, and our large customers were growing exponentially. That growth masked a serious issue—we were bleeding smaller customers at an alarming rate. Our Gross Revenue Retention (GRR) was telling a different story, but no one was looking at it because we were too focused on celebrating our NRR success. By the time we realized what was happening, an entire segment of customers had churned before they ever had a chance to grow. We were replacing lost customers with bigger expansions, but let’s be clear: that is not a sustainable business strategy. Lesson learned: You can’t let a strong NRR distract you from the full picture. So, what should you be paying attention to? ✅ GRR (Gross Revenue Retention) – Are you actually keeping customers? A strong GRR means you have a solid foundation. If it’s low, you have a churn issue—or a downsell issue. ✅ NRR (Net Revenue Retention) – Expansion is great, but if it’s masking logo churn, dig deeper. ✅ Logo Retention – Are you retaining the right customers? If a segment is consistently churning, there’s a deeper problem to address. ✅ CAC Payback Period – Are you making money on your customers, or are they churning before you even see a profit? ✅ Understand how you’re achieving your NRR. Is it GRR? Expansion? Upsell? Cross-sell? Churn? Downsell? Revenue increases? NRR is an outcome, not a strategy—know what’s driving it. Key Takeaway: Retention is a house of cards if it’s built only on expansion. NRR growth is meaningless if your GRR is crumbling. _____________________________ 📣 If you liked my post, you’ll love my newsletter. Every week I share learnings, advice and strategies from my experience going from CSM to CCO. Join 12k+ subscribers of The Journey and turn insights into action. Sign up on my profile.

📈 New Adobe data just dropped: generative AI traffic to retail sites surged 4,700% year-over-year in July 2025. But it's not the growth, while impressive, that has me thinking...it's what happens next. Here's what caught my attention and what I think marketing leaders need to pay attention to: AI-referred shoppers spend 32% more time on sites, view 10% more pages, and bounce 27% less. These aren't casual browsers. They're research-driven consumers who arrive knowing exactly what they're looking for. Three things brands need to start thinking about, because the shift in consumer behavior in the Agentic Web is happening fast: - We're optimizing for the wrong thing. 73% of AI users cite LLMs as their primary research source. Keywords won't cut it anymore. Brands need to be the authoritative source that AI systems reference when customers ask questions. - The attribution models are broken. AI traffic converts 23% less but generates 84% more revenue per visit than six months ago. These customers research through AI, then convert elsewhere. How are we tracking that journey? - The infrastructure shift is real. Consumer Electronics and Tech lead in AI visit share because complex purchases benefit most from AI research. But every category will follow. The question isn't if—it's when. For brands who have built great visibility in the current digital economy and are wondering what is happening to their metrics, It feels like the early days of digital all over again, equal parts terrifying and exhilarating. We're not just adding another channel. We're witnessing the emergence of the Agentic Era where AI agents become the new front door to discovery. The brands that recognize this shift and adapt their content, measurement, and customer journey strategies now will own the next decade. Read the full insights from our team at Adobe Digital Insights: https://lnkd.in/g2mGVGud What are you seeing in your data? How are you preparing for this shift? #MarketingStrategy #GenerativeAI #CustomerJourney #DigitalTransformation #AEO #GEO #AISearch #AdobeLLMOptimizer