Six months in, onboarding is failing: early-product mistakes to avoid

[JeffreyL]

My co-founder and I are about six months into building our SaaS product for small retail businesses, and we've just hit our first major roadblock with user onboarding. We built a ton of features based on our initial assumptions, but new users are getting confused and dropping off before seeing the core value. I'm worried we fell into the classic trap of building for ourselves, not the customer. I'd like to hear from other founders about the most common startup mistakes you made in the early product development phase, especially regarding feature prioritization and user testing, and what you wish you had done differently to validate demand sooner.

[HannahQS]

Onboarding needs that 'aha' moment within minutes. Identify the single action a new user must take to realize value and make it frictionless—everything else can wait.

[Jacob_H]

We narrowed to 3 core flows and used a ruthless priority rubric: impact times feasibility, and risk. Map each flow to a specific job-to-be-done. Then run quick usability tests with 5–6 users and ship a minimal onboarding pass first.

[Eleanor.R]

Try the 'first user walk-through' exercise: invite 3 ideal customers to go through onboarding while you observe, jot every friction point, then rebuild a minimal onboarding that only covers the essentials. Measure activation and 7‑day retention after the change.

[Camila69]

Sometimes the issue isn't onboarding complexity but whether you’ve clearly stated the core value proposition. If people drop off early, they might not see the payoff or the price; run a quick value framing test (landing page + signup) before heavy features.

[Natalie55]

What's your single onboarding metric? Activation, time-to-first-value, or 7‑day retention? Do you run small A/B experiments or a weekly feedback loop with early users to validate changes before a bigger push?

[Penelope.J]

Low-risk experiments: publish a simple onboarding narrative or explainer video, or offer a 2‑week early-access cohort. Use that to gauge interest and refine the messaging before committing to larger features.