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Intercom

Users only use one feature and never discover the rest

Drip-reveal features over time

Don't show everything at once. Reveal features gradually based on usage. Users who discover more features stay longer.

RetentionIntermediate
3-4 weeks

When to use

Your product has multiple features but users stick to a few, and deeper usage correlates with retention.

Hypothesis template

If we introduce [feature] to users after they've used [prerequisite feature] for [time period], feature adoption will reach [target]% because the timing matches their readiness.

Method

The problem: You built 20 features. Users found 3 of them. They think your product is simpler than it is, and they eventually outgrow (what they think is) your product.

What Intercom does: Instead of showing all features on day one, reveals them based on user behavior. Used the messenger? "Did you know you can add chatbots?" Set up chatbots? "Try our help center." Each feature unlocks naturally.

Why gradual discovery works:

  • Too many features at once = overwhelming = uses none
  • Features revealed when relevant feel like gifts, not noise
  • Users who use more features have higher switching costs
  • Each new feature is a mini "aha moment" that re-engages

How to implement:

  1. Map your features from "core" to "power user"
  2. Define triggers: what usage pattern suggests readiness?
  3. Reveal with in-app tips, emails, or subtle UI changes
  4. Time it right: after they've mastered the current level
  5. Track: do users who discover features X stay longer?

Revelation methods (ranked by effectiveness):

  1. Contextual tooltip when they're doing something related
  2. "New for you" section in dashboard
  3. Email: "You're doing great with X. Try Y"
  4. Guided tour triggered by behavior
  5. Feature highlight in weekly digest

Key insight: Users don't have a feature discovery problem. They have a timing problem. Show the right feature at the right moment.

Success metrics

  • •Feature adoption rate per tier
  • •Time to discover key features
  • •Retention: users who adopt N features vs fewer
  • •Feature discovery-to-usage rate
  • •Churn rate by features used

Prerequisites

  • Usage analytics per feature
  • In-app messaging system or email triggers
  • Clear feature hierarchy
  • Behavioral tracking

Common pitfalls

  • •Revealing advanced features too early
  • •Interrupting users mid-task
  • •Too many discovery prompts at once
  • •Not tracking if revealed features actually get used

Source: Intercom. Behavioral feature reveal increases power-user conversion.

Suggested ICE scores

8Impact
7Confidence
5Ease
retentionfeaturesdiscoveryintercomonboarding

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