Push Notification Fatigue vs Retention

Notification Strategy

Notifications / week 4

Re-engagement boost 0.22

Fatigue gain / notif 0.10

Base churn sensitivity 0.06

Cohort — Day 0 / 60

Active

100.0%

Opted-out

0.0%

Churned

0.0%

Day-30 retention

—

Legend

Active & engaged At-risk (low engagement) Opted out of notifications Churned / uninstalled

How it works

Each of the 200 users in the cohort carries two hidden numbers: an engagement score E (0–1, chance they stay active) and a fatigue score F (0–∞, annoyance from notifications). Every simulated day:

if notification day:
  E += boost · (1 − E)     // diminishing-returns re-engagement
  F += fatigueGain
else:
  E *= 0.92                // organic decay with no reminder

F *= 0.9                   // fatigue cools down daily
if F > 1 and not opted-out:
  opt-out chance = (F − 1) · 0.08
  → opted-out users get NO more notifications (E decays forever after)

churn chance = baseChurn · (1 − E)
  → churned users leave the cohort permanently

This creates a real trade-off: too few notifications and E decays until users churn from disengagement; too many and F crosses the opt-out threshold, after which those users are cut off from re-engagement and drift to churn anyway. Somewhere between is the frequency that maximizes day-30 retention — sweep the slider and watch the retention curve to find it for a given boost/fatigue/churn profile.

Notification days are spread evenly across each 7-day week (e.g. 4/week ≈ every other day) so the cadence stays realistic rather than bursty.

Day 0 Retention 100.0%

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