Optimizing User Journeys For Subscription Platforms

A user journey is the sequence of steps a user takes within your product. Imagine a photo editing app where users explore the “Image Upscaler” before the “Shape Cropper,” leading to a 20% increase in conversion. The trick is identifying that particular user journey out of all the many permutations a user could follow in using your product. It’s hard to go over all of them, measuring the impact of each. Causal analysis is key to understanding what drives the KPI change and what to do next. Even though you might have identified some impactful user journeys, many companies struggle to translate these journeys into real actions. Let’s take a look at a few examples of what you can do next, drawn from a sample photo editing app: 1️⃣ The “Journey Reduce-Noise-Filter” → “Background Eraser” could increase Conversion by 20%. ✅ Amplify the impact of the journey: >> Highlight Reduce Noise Factor in your UI and marketing. >> Use in-app nudges to encourage and Background Eraser exploration. >>Incorporate this flow into a product Walkthrough, educational video or your onboarding process. 2️⃣ Users that complete “Clean Object” after “Cartoon Effect” are 22% more likely to convert if they complete “Clean Object” after “Glitch Video Effect.” ✅ When to promote a feature: >> Surface Glitch Video Effect earlier and provide guidance. >> Showcase success stories reinforcing this journey. 3️⃣ The Journey “Magic Eraser” followed by “Search“ increases Churn Within 2 Weeks by 15%. ✅ Reduce user churn following a journey: >> Is there a bug in the product or a gap in user expectations >> Was there something they searched for and could not find? 4️⃣ The Journey “Use Template” → “Cartoon” → “Glitch Video Effect” → “Clean Object” increases 30-Day Retention by 38%. ✅ Build winning Activation journeys: >> Guide users gradually through a user journey over the first 7 or 30 days. >> Sequentially promote these features in your onboarding process, in-app prompts, timed marketing campaigns etc. 5️⃣ The journey “Campaign= Fast Track” → “Viewed landing page = /FastTrack-US” increases conversion by 23%. ✅ Leverage the right combination of marketing campaigns and landing pages to maximize KPIs: >> Understand and promote the touchpoints that work >> Direct users through the journey with targeted campaigning, incentives, interactive guidance, and contextual nudges. 👉 Key Takeaway User journeys are gold mines of action-ready insights. 🥇 The real power lies in turning them into strategies and actions that optimize the user experience and drive growth. If you’re using Loops, you have likely uncovered high-impact sequences, both positive and negative, along with hidden user segments. I’d love to hear your story. What’s the most actionable insight you’ve gained through a user journey? 🚀 #CausalML #userjourney #productanalytics

"Genchi Genbutsu" is the most powerful optimization principle you've never heard of. Here's how we've used it at The Good... and how you can too. Most users approach a new SaaS tool with a single problem in mind. They sign up, solve that issue, and move on. But what if we could show them the full potential during their trial? Our thinking was to educate users on lesser-known features, then encourage them to explore functionality they might have overlooked. After all, users who discover more value are more likely to subscribe and stick around long-term. Instead of jumping straight into A/B testing, we took a step back. We started with qualitative research. User testing. Consumer interviews. We wanted to understand the why behind the what. This process is reminiscent of Toyota's "genchi genbutsu" principle: ↳ "Go and see for yourself where the work happens." In the digital world, it's harder to "go and see." But it's not impossible. We observed how people actually used the tool. We identified pain points and opportunities. This comprehensive approach led to a revamped onboarding process. One that educates users on all the features they are missing out on. The result? Users now see the full value of our product during the trial period. They're more likely to subscribe because they understand how it solves multiple problems. It's not just about collecting data. It's about understanding the user journeys behind that data. "Go and see for yourself where the work happens." Are you truly seeing the full picture of your user's experience? Or are you making decisions based on incomplete information?

The most immediate and highest-impact application of AI is not a new feature but contextualizing the features you already have. Hear me out... Every user journey has several key moments in which the value of the product needs to be explained or expanded upon. As an example, for a self-serve subscription product, this might be (1) join flow, (2) onboarding and aha moment, (3) driving engagement and repeat usage, (4) extension/expansion, (5) cancellation flow. At each of these critical junctures, there’s a measurable action you want the user to take and you have ever-increasing context to help nudge the user toward that action. Use that context to create interactions or interventions to better demonstrate the value your product provides and measure the direct impact of those interventions with A/B tests. Going backwards (since there is more context and the stakes are higher later in the journey): (5) Cancellation flow - instead of showing a generic “are you sure” message, generate a bespoke sales pitch that showcases unused features, contextualizes them based on their specific use case, and showcases ROI using language likely to resonate. (4) Extension and expansion - before emailing saying their CC is about to be charged, send a customized email for each customer that highlights the value they got from using the product and other success indicators similar to a personalized “year in review”. (3) Driving engagement and usage - contextualize features and explain their value given the context of what the user is doing. For example, by analyzing the image that a user is manipulating in Photoshop, Adobe could describe not just what the smudge tool does, but why it would be useful (ie. “hide blemishes from your HD photo” or “add a finger-paint effect to your painting”). (2) Onboarding and aha moment - tailor help content and timing of progressive disclosure based on observed technical sophistication, feature adoption to-date, and user intent, contextualize the most important engagement moment given their context (1) Join flow - customize the messaging for each potential subscriber based on the acquisition channel, what pages they clicked to (and didn’t), and where they spent their time on the website before starting the flow to maximize conversion rates. Each of these is generally easier and lower risk than building brand new features, with high potential ROI that is relatively easy to measure. Product leaders who achieve early successes with these improvements can leverage them to build stronger cases for more aggressive AI-enabled product investments down the line. Please comment if you agree/disagree or are considering making investments along these lines. I'd love to chat 1:1 to anyone shifting - or interested in shifting - their roadmap in this direction. #productleadership #productmanagement #ai #productstrategy

Personalizing user journeys at scale is sh*t hard and you can't do it if you don't have the right data. Notion brilliantly nails this with targeted segmentation and data-driven campaigns. I got these emails when I signed up. Their approach isn’t flashy. It's simple, human and it works! A few things that caught my attention: 1️⃣ They actually know their users. They've learnt about their users by leveraging data—when someone signed up, what they’ve done in the app, and even company details. Just clear smart segmentation helps, if you have all your data about your users across sources like CRMs, Product DBs and more. 2️⃣ Messaging feels real. Look at their "First Week in Notion" email. It feels like a thoughtful check-in. Also, celebrates small wins (“You created a workspace!”) and gently nudges you to try more. 3️⃣ The Upsell CTA is high intent. If they see you adding teammates, they don’t send a generic “Upgrade Now” email. They frame it as, “Here’s why having your team makes collaboration better.” It’s timely, helpful, and makes sense. 4️⃣ They keep it simple. They’ve probably automated the messy stuff—segmenting users, activating campaigns, measuring results. No over-engineering, no reinventing the wheel. Personalization doesn’t need to be perfect—it needs to be useful. It’s about showing up with the right message, at the right time, for the right person. We launched a new offering in beta where you can send out growth campaigns straight from your dashboards. Since then, we've been using Airbook to do this for ourselves. Here’s how: 1️⃣ Pull data from everywhere. HubSpot for user details. Salesforce for account context. PostHog for product usage/events. 2️⃣ Create segments. We join this data and create specific customer segments. Example: “Tech startup users in Ops roles who know SQL and connected HubSpot, Salesforce & Stripe in the last 30 days.” 3️⃣ Activate campaigns instantly. Send targeted nudges through Customer.io Example: “Explore the SaaS full-funnel overview template to get more out of Airbook" 4️⃣ Measure and Iterate Did users click on the email, try the template, usage increased? You can go back to tracking it and shifting your efforts based on the results. Anyone who'd like to set this up? Send me a note and I'll be happy to help!

I've been providing digital businesses with analytics to help them make better decisions for over a decade now. And one stat consistently shocks me more than any other: Most consumer subscription services lose over a quarter of all New Subscribers in month 1 and over half of them by month 6. Sure, you expect some immediate churn. After all, Marketing's job is to bring in new users. Not all of them will fall in love with the product. But... over a quarter canceling immediately... how have we normalized this?! And this isn't a one-off phenomenon. It exists across: – Cohorts: loyal vs. disloyal users – SKUs / plans: ad-free vs. ad-supported – Promotions: promotional vs non-promotional sign-ups – Industries / categories  [not pictured but trust me] Netflix spent ~$3B on marketing last year. Given that type of spend, you'd think this would be everyone's number one "hair on fire" problem to solve. The solution: the user's day 1 and month 1 experience should be SPECIAL. This is universal. All of us have had experience with various digital & physical goods / services: they spend endless effort bringing you in and, once you're there, immediately forget about you. No one feels special when treated like this. In product lingo, this is the job of the new user experience ("NUX") team. That team should be much more powerful than they are. Potential even direct report to the CEO/CPO/CMO. A couple obvious ways to make the first moments special: – Personalization: Any product does different "jobs" for different user personas. The entire new user experience should be crafted around the job we think our product does for you. – Registration walls: Sometimes it's hard to know who you are. A little friction can be a good thing. Collect the information you need to do the above. And not with a gimmicky "select your interests" menu. This isn't 2015. – Leverage market data: It can still be hard to know your users on day 1. Luckily, their entire digital history is accessible (in a privacy-centric way). Find the data, bring it in at the right time, and voilà! – Leverage social graphs: Recommendations hit a lot harder coming from friends, not faceless email listservs. I'd love to see more non-social products leverage social graphs for this purpose. – Native product integration: There are times to hit users, and times to let them do what they want. Bland lifecycle marketing emails accomplish neither. Find native product integrations to make the experience special. This all sounds obvious but, again, think about your most recent experiences. Was the experience highly personalized? Did you feel special? The data would indicate that users do not and, therefore, quickly churn. Consumer subscriptions have a lot more work to do. We shouldn't normalize losing a quarter of new users in the first 30 days.