Technique · Hooked
Codify: count habitual users and map the path they share
Set a realistic cadence for a devoted user, count the share of each signup cohort who meet it, and compare what those users did in their first days with users who left. The book's rule of thumb: below about 5% habitual, you have the wrong audience or a product to rethink.
Plain label: habitual-user rate and Habit PathAlso known as: habitual user rate, devoted user, Habit Path, aha moment, cohort analysis, 5 percent rule, habit strength
How it works
A habit shows up as repeated use at the behavior's natural cadence. Measuring who already meets that cadence, and what they did in their first days, turns habit design from opinion into a testable guess about which early actions matter. Reporting this rate next to user counts keeps teams from mistaking sign-ups for habits.
Evidence warning
The 5% figure is the author's rule of thumb, not a tested threshold; a sustainable business usually needs far more.
Early-action differences between stayers and leavers are hypotheses until an experiment confirms them.
What the research says
One social network reported that following about 30 accounts marked users likely to stay; it is a dated outside figure the book cites (correlational).
Hooked Ch.8 (Twitter, historical), 2014
Before you start
- The value event is tracked.
- Some users already at the devoted cadence; a path shared by only one or two people is a personal habit, not a pattern
How to build it
- B2B
- Define the devoted cadence per account (for example, a team that publishes weekly) and compute it from the database before any analytics tool exists.
- Web
- Weekly signup cohorts with the share meeting the cadence at weeks 4, 8 and 12, and release dates marked on the chart.
- E-commerce
- For repeat purchase, set the devoted cadence from the product's natural reorder interval, not from the best customers.
- Mobile
- Compare the first 7-14 days of users still active at week 8 with those gone, across follows, connections, content and integrations.
What can go wrong
- Calibrating the cadence on power users or best-case rivals.
- Declaring a habit after one or two weeks of data.
- Treating a correlation as the cause.
Pairs well with
- Steer onboarding down the mined path, then test it.
- Report the habitual rate next to sign-ups.
In practice
Where it shows up
Facebook (Meta) · 2016
RoundFacebook: 7 friends in 10 days
“7 friends in 10 days” as Facebook's activation milestone, per growth leader Chamath Palihapitiya's public talk and repeated by Index Ventures (Nov 28, 2016). Correlational; the exact derivation was never published. Reforge frames it as a setup threshold whose aha moment is an interesting feed.
M2-M3 ×StartCase grade for the number: C. Evidence grade for the mechanism link: B.CorrelationalPress-reportedSlack · 2015
RoundSlack: the 2,000-message threshold
About 93% of teams past 2,000 messages were still using Slack, per co-founder Stewart Butterfield (First Round Review interview, Feb 27, 2015). No underlying data was published; correlational. It is not a paid-conversion figure.
M2 ×StartCase grade for the number: B. Evidence grade for the mechanism link: B.CorrelationalCompany-reportedTwitter (now X) · 2017
RoundTwitter: follow about 30 accounts
Users who followed about 30 accounts became long-term active users, per Twitter's Josh Elman (Hacking Growth excerpt, Apr 25, 2017; also in Hooked, Ch8). Correlational; a variant of 5-10 follows on day one circulates secondhand. Twitter was renamed X in 2023.
M2 ×StartCase grade for the number: B. Evidence grade for the mechanism link: B.CorrelationalCompany-reported
Limits
What we don’t claim
- The Hook Model is a practical design tool, not a validated or complete theory of behavior.Hooked, Introduction
- This is a practitioner heuristic (grade D): test it in your own product before relying on it.
- The threshold is a heuristic, not a measured cut-off.
- The evidence is correlational until it is tested in your product.
- Habit metrics need the longer habit horizon (weeks to months) before they can be read.
Sources
Hooked · Nir Eyal
Ch.8 · Ch.1
Source IDs: HK-MEA03HK-MEA01HK-MEA02HK-MEA04HK-STR04HK-STR05
Book content is paraphrased, never quoted at length. Last verified October 24, 2026.
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