What signals convinced you your early SaaS had PMF and you prioritized features?

[AmeliaYJ]

I'm a product manager for an early-stage SaaS tool aimed at freelance designers, and while we have a small group of passionate early adopters, we're struggling to achieve true product-market fit as our user growth has plateaued and our conversion rates from free trials to paid plans are lower than expected. We've conducted numerous user interviews, and the feedback is frustratingly mixed—some love specific features we consider secondary, while others find our core value proposition unclear or not urgent enough to justify switching from their current patchwork of tools. For founders or product leaders who have navigated this ambiguous phase, how did you systematically test and pivot your value proposition to find a stronger fit? What metrics or qualitative signals finally convinced you that you were on the right track, and how did you prioritize which feature requests to build versus which to ignore when trying to satisfy a broader market?

[Stephen16]

TL;DR: pick one core job your product does for designers, craft a crisp message around that, and prove it with a small, repeatable experiment. Don’t try to ‘fix’ everything at once—start with the thing that unlocks value fastest and then build from there.

[Kyle19]

Treat your value proposition as a testable hypothesis. Run short onboarding experiments and messaging tests to see which framing resonates; track activation (first meaningful task), 14‑day retention, and the share of trials that convert to paid. If the data says a different angle lands better, pivot quickly rather than expanding features for everyone.

[Sofia.B]

A practical 6‑week loop I used: 1) lock to a single persona and one job-to-be-done; 2) create three landing variants with distinct value hooks; 3) run two quick experiments (e.g., onboarding flow and pricing page) for 10–14 days; 4) measure cohort behavior (activation, retention, ARPU); 5) pick a path (persevere or pivot) and define a minimal supporting feature set. Build a 2–3 page decision memo after each cycle to force clarity.

[Aurora_R]

I’d push back a bit on chasing every request from every segment. It’s usually better to own a beachhead and prove it with solid unit economics and real customer stories before broadening. If you’re trying to serve too many niches at once, you dilute your core value and confuse your messaging.

[AmeliaJL]

What are your current north-star metrics (e.g., time saved per project, revision count, or design outputs per month)? Do you have a simple onboarding funnel you can run 2–3 experiments on this quarter? If you share a rough target user and your funnel steps, I can sketch a focused test plan with 2–3 experiments you could deploy in 2–4 weeks.

[KennethXP]

If you want, tell me a bit about your pricing model and the features you’re considering. I can draft a minimal, testable value proposition and a lightweight experiment calendar tailored to your product stage.