Building a User-Centric SaaS Product Roadmap

Most SaaS teams are building features users will never adopt. The reason isn't bad engineering. It's bad prioritization. Traditional feature prioritization follows this broken pattern: Executives want it → Competitors have it → Engineering can build it → Ship it But what users actually need gets lost in the noise. User-centered prioritization flips this completely. Instead of guessing what matters, you let user behavior and research drive every decision. Here's how it works: ↳ Start with user research to identify real pain points ↳ Test concepts with actual users before building anything ↳ Prioritize features that solve frequent, important user tasks ↳ Focus on what drives user satisfaction and business outcomes The difference is dramatic. Companies using internal opinions to prioritize features see adoption rates around 12%. Those using user-centered prioritization consistently hit 40% or higher. User-centered prioritization isn't just a method. It's a mindset shift. ↳ Instead of asking "What should we build next?" you ask "What problems are users struggling with today?" ↳ Instead of following competitor features, you follow user workflows. ↳ Instead of building what sounds impressive, you build what creates value. This approach identifies the features that matter most before you waste engineering resources. It reduces development time by focusing on proven needs. It increases adoption because users actually want what you're building. Your roadmap should serve users first. Everything else follows from there.

How do you figure out what truly matters to users when you’ve got a long list of features, benefits, or design options - but only a limited sample size and even less time? A lot of UX researchers use Best-Worst Scaling (or MaxDiff) to tackle this. It’s a great method: simple for participants, easy to analyze, and far better than traditional rating scales. But when the research question goes beyond basic prioritization - like understanding user segments, handling optional features, factoring in pricing, or capturing uncertainty - MaxDiff starts to show its limits. That’s when more advanced methods come in, and they’re often more accessible than people think. For example, Anchored MaxDiff adds a must-have vs. nice-to-have dimension that turns relative rankings into more actionable insights. Adaptive Choice-Based Conjoint goes further by learning what matters most to each respondent and adapting the questions accordingly - ideal when you're juggling 10+ attributes. Menu-Based Conjoint works especially well for products with flexible options or bundles, like SaaS platforms or modular hardware, helping you see what users are likely to select together. If you suspect different mental models among your users, Latent Class Models can uncover hidden segments by clustering users based on their underlying choice patterns. TURF analysis is a lifesaver when you need to pick a few features that will have the widest reach across your audience, often used in roadmap planning. And if you're trying to account for how confident or honest people are in their responses, Bayesian Truth Serum adds a layer of statistical correction that can help de-bias sensitive data. Want to tie preferences to price? Gabor-Granger techniques and price-anchored conjoint models give you insight into willingness-to-pay without running a full pricing study. These methods all work well with small-to-medium sample sizes, especially when paired with Hierarchical Bayes or latent class estimation, making them a perfect fit for fast-paced UX environments where stakes are high and clarity matters.

Customer Success Leaders—If you're not actively shaping the Product Roadmap, you're missing a critical opportunity. The most effective organizations don’t treat CS as a participant—they rely on it as a strategic partner. Product teams should be co-designing the future with their customers. That means: ✅ Understanding emerging use cases and evolving needs ✅ Enhancing the product based on real customer insights ✅ Prioritizing with business impact and revenue in mind In today’s market—where consolidation, cost-cutting, and efficiency are top priorities—building a product that truly solves business challenges is the difference between success and irrelevance. So, how do you drive better alignment between CS and Product? Here’s what I've seen work: 1️⃣ Lead with Data & Insights -Identify the most adopted and least adopted product features -Pinpoint where customers are dropping off and why -Find personas and use cases that drive the most value -Look for patterns and trends across your customer base 2️⃣ Support Data with Customer Stories -Conduct interviews and surveys to capture direct feedback -Dive into workflows and edge cases to understand nuances -Align product evolution with customer goals and business objectives 3️⃣ Prioritize Product Feedback Strategically -Leverage customer data to rank impact and urgency -Tie feedback to revenue—renewals, expansions, and upsells -Ensure recommendations align with the broader product vision 4️⃣ Maintain an Open Dialogue -Establish a structured collaboration rhythm (bi-weekly syncs, Slack channels, shared roadmaps) -Keep all teams informed on designs, timelines, and priorities -Be clear, concise, and adaptable—Product is balancing competing priorities across the org 5️⃣ Close the Loop—Every Time -Set clear expectations with customers early and often -Enable Product teams to engage directly with customers for firsthand learning -Continue gathering feedback even after launch (beta programs, customer advisory boards) At the end of the day, great products are built by teams who stay close to the customer. CS should not be a passive observer in product development—it should be a driving force. When you get this right, you influence retention, expansion, and advocacy. And that’s a business win. __________________ 📣 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.

I got to see behind the curtain of 100s of SaaS companies. here’s what the best ones had going for them: 1️⃣ Customer Success truly is Product's responsibility first. After analyzing hundreds of retention patterns, the truth became clear: companies that treated CS as a product function (not just a post-sale service) consistently outperformed their peers. The most successful products had customer success principles built into their DNA, not bolted on afterward. 2️⃣ Build advocacy triggers into the product journey. The SaaS companies with the highest NRR didn't just deliver value - they made it unmistakably obvious when that value was delivered. Every "aha moment" was clearly marked, celebrated, and designed to be shareable. Products that made users look good in front of their teams created natural advocates. 3️⃣ Onboarding friction predicts churn with shocking accuracy. We could predict retention rates just by analyzing the first 30 days of engagement. Every additional step, confusion point, or moment of hesitation in early adoption correlated directly with eventual churn. The most successful products weren't necessarily the most feature-rich - they were the ones that delivered value with the least resistance. 4️⃣ Cross-team expansion happens through champions, not features. After analyzing hundreds of expansion patterns, we found that additional seats and modules rarely sold through traditional sales motions. Instead, they spread through internal champions who became unofficial product evangelists. The best products deliberately created and empowered these champions with resources, recognition, and tools to drive internal adoption. 5️⃣ Transparency builds confidence that drives renewals. The SaaS companies with the highest renewal rates weren't hiding behind quarterly business reviews and sanitized metrics. They provided radical transparency into product usage, upcoming roadmap, and even their own internal metrics. This transparency built trust that became the foundation for long-term retention. Working with hundreds of SaaS businesses showed me that successful products aren't just built differently - they're operated differently. Product decisions cascade into customer success outcomes, creating either virtuous or vicious cycles that ultimately determine company trajectory. What patterns have you noticed that separate successful SaaS products from the rest?