Problem context

You see reasonable activation, but many users and accounts go dormant after a few days or weeks.

Retention charts show steep drop-offs after the first few cohorts, and sales teams mostly work with a small subset of high-touch accounts.

Product discussions focus heavily on new features rather than strengthening the loops that keep existing users engaged.

What breaks if this is not solved

Top-of-funnel efforts become expensive because you constantly need new signups to replace churned users.
Self-serve revenue underperforms; most growth comes from a small number of sales-driven deals.
It becomes difficult to justify PLG investments because retention metrics do not reflect the value of acquired users.

You already have a clear activation definition and a non-trivial number of users reach it.
Your product has natural repeatable workflows (for example, reviewing analytics, shipping changes, or managing projects) that could support habits.
You can see at least basic retention or usage metrics over time, even if they are coarse.

Shift the mental model from funnels to loops: focus on the actions that should repeat weekly or monthly and what makes each repetition more valuable.

Identify one or two core loops—such as collaboration, data, or habit loops—and design triggers, rewards, and investments around them.

Align product, success, and marketing so that campaigns, in-product prompts, and lifecycle messaging reinforce the same loops.

Define what “healthy ongoing usage” means for your product in behavioral terms (for example, “runs at least one workflow per week” or “views key dashboard monthly”).
Plot retention cohorts for activated users and identify where curves flatten; note differences by segment or use case.
Map existing product behaviors that could form loops: recurring tasks, notifications, collaboration, or accumulating configuration/data.
Choose one core loop to strengthen first (for example, “weekly review of analytics dashboard”) and write down the trigger → action → reward → investment pattern.
Audit your product to see where that loop currently breaks: weak or missing triggers, unclear rewards, or no lasting investment.
Design concrete product changes to reinforce the loop: better scheduling, saved views, collaborative comments, or progress indicators tied to real work.
Add instrumentation to measure loop participation (for example, “dashboards viewed per active account per week”) and connect it to retention and expansion metrics.
Ship changes to a subset of users or a specific segment; monitor retention curves and loop metrics over multiple periods.
Once the first loop shows improvement, document the pattern and apply it to adjacent loops or segments.

D7, D30, and D90 retention for activated users
Trend up over successive cohorts.
Track by persona and plan; small changes in later-period retention can have large revenue impacts.
Frequency of core loop actions per active account
Increase and stabilize over time.
Examples: dashboards viewed per week, workflows run per month, or collaborative sessions per account.
Expansion revenue or seat growth from self-serve accounts
Trend up as loops deepen.
Measure upgrades, additional seats, or usage-based overages driven primarily by product usage rather than human outreach.
Cohort-based net revenue retention (NRR) for self-serve segments
Move toward or above 100% for target cohorts.
Even small improvements in NRR for self-serve tiers can materially change long-term unit economics.

Treating retention purely as a notification or email problem instead of addressing whether the product actually fits into repeatable workflows.
Trying to design many loops at once, which dilutes focus and makes it hard to see which changes affected retention.
Ignoring the qualitative reasons users stop coming back (for example, lack of trust, unclear value, or competing tools).
Assuming loops that work for high-touch, enterprise accounts will automatically transfer to self-serve segments.

Pillar

Glossary

Adjacent playbooks