Superhuman half-love half-blocker roadmap
Split the product roadmap between what current lovers already value and what blocks adjacent users who value the same core benefit.
Why this can grow a startup
Most roadmaps overcorrect. If the team only chases missing features, the product becomes a flat checklist. If it only polishes what fans already love, the fit score may not move. Superhuman used survey answers to identify speed, focus, and keyboard shortcuts as the love layer, then looked at somewhat-disappointed speed lovers to find blockers such as mobile, calendaring, and integrations. The tactic keeps the product sharp while widening the circle of people who can honestly use it.
Source-backed example
Superhuman devoted roughly half the roadmap to more speed, shortcuts, automation, and design details, while the other half addressed blockers like mobile, integrations, attachments, calendaring, unified inbox, search, and read receipts.
Source-reported evidence
Source: First Round Review: How Superhuman Built an Engine to Find Product Market Fit · Browse First Round Review: How Superhuman Built an Engine to Find Product Market Fit tactics
The same PMF process took Superhuman’s very-disappointed score from 22% to 58% in three quarters.
Attributed to the cited source; GrowthDex has not independently verified it. Use this as context, not as a forecast, benchmark, or recommended target.
Evidence scope: claims and metrics are attributed to the linked source; GrowthDex has not independently replicated the reported result. Check the original context and validate fit before applying it. Read the evidence methodology.
When to use it
Use this when Product, Retention, Activation is relevant to roadmap, retention, activation and you can run a bounded test with a medium budget.
When not to use it
Do not use it as a substitute for customer evidence, a clear owner, or a measurable stop condition. Local platform rules and market behavior still need checking.
How to do it
- Choose one target segment and define the exact next action this tactic should prompt.
- Adapt the tactic to Product and Retention, using evidence from First Round Review: How Superhuman Built an Engine to Find Product Market Fit as context—not as a promised result.
- Record a baseline for: Share of target users completing the product's first-value action. Set a guardrail that would make you pause the test.
- Run a narrow pilot and choose a test window that fits the normal decision or use cycle; do not scale before you have observed the full cycle.
- Compare the signal with its baseline. Scale only if the intended action improves without crossing the guardrail; otherwise revise one variable or stop and record what you learned.
Compare a stack for your situation
Compare source-backed tactics against your product, stage, budget and channel strengths, then choose one experiment to test.
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