Adoption Atlas
Product Ops · PMM · Feature Adoption
Example · demo data, not live --:--:-- ← All Product views
Core Feature Adoption
41%▲ vs 24.5% SaaS avg
Breadth of Adoption
4.2of 10 features · 42%
Power Users
44%▲ 3 pts MoM
30-Day Retention
68%▲ 5 pts

Top Features

sortable
Feature ↕ % clk ▼ adopt ↕ WoW ↕ trend

Depth Split

users
44% power
Power 44%
Regular 31%
Occasional 25%

Adoption Funnel

Core Editor
Exposed100%
Tried47%
Adopted33%
Retained22%
Exposed→Tried→Adopted→Retained · 30-day window

Feature × Cohort Heatmap

lowhigh · clicks/user/wk
Core Editor runs hot across every cohort. API stays cool — power-tier only. AI Compose warming sharply over the last 4 weeks. ● flagged · click any cell to drill in

Time-to-Adopt · AI Compose

median 3.4d · 30d retention 68%
0d1d2d3d ◆med5d7d10d14d+
AI Coach

Adoption Coach

Reporting adoption is 19%, but accounts that adopt it retain +23% higher. Target the 1,140 high-fit accounts who haven't tried it.

NewDetected 3 new UI elements worth tracking — auto-tagged.
At riskBulk Export adoption −4 pts WoW — declining.

Power-User Leaderboard

top accounts
Account feats sess/wk ▼ depth

Cohort Builder

natural language
accounts using Reporting weekly tried AI Compose, didn't retain 9+ features, <3 seats
Field Guide How a Product Ops / PMM lead reads this atlas — and what a live integration would surface.

How to use this

  • 1Read the heatmap row-first. A row that's blue across every cohort is a feature nobody's finding — that's a positioning or discoverability problem, not a usage one. Hot rows (Core Editor) confirm your value-prop, not your roadmap.
  • 2Watch the warming column. Scan left→right: a cell warming week-over-week (AI Compose, far right) is your adoption flywheel kicking in. Click it to see which accounts are driving the lift before you commit GTM spend.
  • 3Pair adoption % with the retention lift. Low adoption + high retention-among-adopters (Reporting: 19% / +23%) is the single best expansion signal you'll find — it's a targeting problem, not a product gap.
  • 4The AI Coach does the correlation for you. It joins feature-use → retention → fit-score and hands back an account list, so you skip the SQL and go straight to a PMM campaign.
  • 5For your own org: which feature has your highest retention-lift but lowest adoption? That's the one to put in onboarding next quarter — not the one with the most clicks.

Watch the walkthrough

Four AI agents walk this dashboard.

In context

Sample feed

Illustrative — wire to your product-analytics & CRM enrichment feed.

◷ AI Composecohort: Q2 signups · clicks/user/wk 6.1 ▲ 38%
▤ Reportinghigh-fit untapped accounts 1,140 ▲ 112
◆ Power users≥7 features · 50+ sess/wk 2,308 ▲ 4.1%
▾ Bulk Exportfeature-at-risk · adoption 12% ▼ 4 pts
⌖ Net expansion ARRadoption-driven, qtr-to-date $418K ▲ 9.2%