Here is how I increase product adoption after onboarding.
In short: Product adoption is how many of a customer's users rely on your product, how often and how deeply. To increase product adoption after onboarding, find the few features that matter for renewal, measure how many eligible users actually use them, and run targeted plays on those gaps. The core formula is feature adoption rate = users active in a feature ÷ eligible users × 100.
Adoption is one of the strongest inputs to a customer health score, so the numbers below can go straight into your scoring.
This is Part 4 of The Customer Onboarding Playbook. Part 3 covered the customer kickoff call. This part starts after onboarding, when the customer is live but usage is not yet a habit.
How do you measure product adoption?
Three numbers describe adoption for one account:
Seat utilization = weekly active users ÷ licensed seats × 100
Feature adoption rate = users active in a feature ÷ eligible users × 100
Stickiness = average daily active users ÷ monthly active users × 100
active user = a user who performed a real action (built a report, ran a workflow), not a login
eligible users = users whose plan and role give them access to the feature
Feature adoption formulas vary between tools. Some divide by all monthly active users instead of eligible users. Pick one definition and keep it.
What does a worked adoption example look like?
Take a customer with 120 licensed seats, 96 monthly active users, 54 weekly active users and 21 daily active users on average.
| Measure | Calculation | Result |
|---|---|---|
| Seat utilization | 54 ÷ 120 × 100 | 45% |
| Stickiness | 21 ÷ 96 × 100 | about 22% |
| Users needed for 65% target | 0.65 × 120 | 78 weekly users |
| Gap to close | 78 − 54 | 24 more weekly users |
A 120-seat account at 45% utilization
Seat utilization = weekly active users ÷ licensed seats × 100, so 54 ÷ 120 = 45%. Stickiness = DAU ÷ MAU × 100, so 21 ÷ 96 ≈ 22%. Reaching 65% means 0.65 × 120 = 78 weekly active users, 24 more than today.
Adoption is the next checkpoint after time to value. Once you know the gap, test how much it moves the account's risk in the health score calculator.
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Which feature gap should you fix first?
Your portfolio tells you where to invest. Say 200 accounts have access to the same five features, and you count accounts with at least three users active in each one over 30 days.
| Feature | Accounts active | Adoption rate |
|---|---|---|
| Dashboards | 156 | 78% |
| Integrations | 108 | 54% |
| Reporting exports | 92 | 46% |
| Automated workflows | 62 | 31% |
| Roles and permissions | 48 | 24% |
The lowest number is not automatically the priority. The priority is the feature closest to the outcome customers bought. Compare renewals: if accounts using automated workflows renewed at 94% and the others at 81%, workflows is your priority feature, even though dashboards look healthier.
Adoption by core feature across 200 accounts
Workflows is the priority feature here because it separates renewing accounts, not because it is lowest.
Treat that as a signal, not proof. Accounts that adopt workflows may simply be the healthier accounts to begin with.

Which plays increase product adoption?
- Tie usage to the customer's goals. Go back to the goals agreed at kickoff and show which features deliver them. A customer success plan keeps goal, feature and owner on one page.
- Train by role. Short sessions built on one role's daily work beat a general tour.
- Run working sessions. A 45-minute session where the customer builds one real workflow with you does more than any webinar.
- Remove blockers. Unfinished SSO, missing integrations and unclear permissions stop adoption more often than lack of interest. Check the items in the onboarding checklist that were pushed back at go-live.
- Show usage to the sponsor. A short monthly note on active users and progress against goals gives the sponsor a reason to push adoption internally.
How do you match the effort to each account?
Not every account gets a workshop. Give each play a trigger, a target and an owner.
Signals, targets and owners for each play
High-touch accounts get workshops and sponsor reviews. Mid-touch accounts get group sessions by role. Tech-touch accounts get triggered emails and in-app prompts, and go to a human only when a signal persists, such as utilization below 40% for two months.

How do you know the adoption plays worked?
Measure plays by cohort. Record the baseline first: 62 of 200 accounts use automated workflows, or 31%. After one quarter, count again. If 84 accounts use it, adoption is 84 ÷ 200 × 100 = 42%, an 11-point gain. Then check whether those accounts held or improved their health score and, at renewal, their retention rate.
Ignore usage that means little, such as mandated logins or API calls counted as users.
What I've seen in practice
I once ran working sessions with hotel partners who had stopped using a reporting feature. Most of them were still using it a month later, because they had built their own report, not watched me build mine.
What I learned the hard way: on one partner account, nearly all the usage came from one operations manager. When she left, activity dropped to almost nothing within weeks, and we spent the next quarter rebuilding. Now I aim for at least two or three trained power users in every account that matters, and I track that number as closely as utilization.
An adoption dashboard for one account
For a high-touch account, I keep a monthly table like this one and share a short version with the sponsor. These are the numbers for the 120-seat example.
| Metric | Target | This month | Last month | Change |
|---|---|---|---|---|
| Weekly active users | 78 | 54 | 49 | +5 |
| Seat utilization | 65% | 45% | 41% | +4 pts |
| Monthly active users | 100 | 96 | 92 | +4 |
| Stickiness (DAU/MAU) | 30% | 22% | 20% | +2 pts |
| Active automated workflows | 10 | 4 | 2 | +2 |
| Trained power users | 3 | 1 | 1 | 0 |
The gap to close is 24 weekly users, but the row I would fix first is power users. One trained person carries the account, and that number can drop to zero overnight.
What to do this week
Pick one feature you believe drives renewal. Compare renewal rates for accounts that use it and accounts that do not, then list the ten largest accounts that are not using it and plan one play for each.
Frequently asked questions
What is a good seat utilization rate?
It depends on how the product is used. A daily tool should show most seats active each week. A monthly reporting tool will not. Set the target from your healthiest renewing accounts.
What is the difference between product adoption and feature adoption?
Product adoption looks at the whole account: how many users are active and how often. Feature adoption looks at one feature and the users who could use it.
Is DAU/MAU useful for B2B products?
Yes, for products people use every working day. For tools used weekly or monthly, a weekly active users ÷ monthly active users ratio is a fairer view.
How long after onboarding should adoption be measured?
Start at go-live and review monthly. The first 90 days show whether habits form. After that, a quarterly view is enough for most accounts.
Sources
- What is product adoption?, Pendo: definitions and ways to measure product adoption.
- What is feature adoption?, Pendo: feature adoption at user and account level, and how to raise it.
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