User Activation Needs a Retention Metric, Not an Aha Moment

Trello found that new users who created four pieces of content within their first 28 days were more likely to become long-term customers, so its onboarding team made “4 in 28” the activation target.

The benchmark does not cover every paying customer. It identifies a behavior with much higher retention value, meaning users who keep creating content are more likely to stay. Most Trello boards have a primary user and collaborators who often only consume content, so the metric tracks output from the primary user.

Teams often reduce user activation to a vague “Aha! moment.” Wave defines it more precisely as the funnel point where users, often on a free trial, realize the product’s value, decide to buy it, and actively use it. The practical goal is to move free-trial users into paying customers, not merely trigger delight.

What makes an FAE different from an Aha moment?

A first activation event, or FAE, may come after several smaller moments. It must be time-bound, rooted in engagement, signal that a business process is forming, and work as a retention lever. A one-time click without those properties does not qualify.

At Wave, the Growth team owns onboarding and the FAE. Its job is to identify valuable customers, move them toward value quickly, and set them up for success.

An activation metric earns its place only when it predicts continued use.

How do you find the first activation event?

A user activation framework is a dedicated plan for reaching that state. The BJ Fogg Behavior Model offers one way to reduce onboarding drop-off, but no universal scoring formula fits every company.

Finding an FAE starts with three questions:

• Which users do you serve?
• What is your ideal customer profile, meaning the customer type the product best fits?
• Which customers have succeeded and stayed longest?

The answers matter because the FAE should come from retained customers, defined by whether they keep using the product over time. Next, choose a customer segment and a retention target, then work backward to the actions that precede retention.

This search will take time. Combine qualitative work—customer interviews, needs discovery and onboarding-map review—with statistical analysis, correlation and onboarding metrics. Here, correlation means checking whether an early action and later retention move together.

There is no single correct method. The evidence should determine the event.

When should different products share one FAE?

Wave sometimes combines products under one FAE when they belong to one business process. It treats sending an invoice and collecting its payment as one transaction, so a unified FAE makes sense even though invoicing and payment remain separate products. The company presents this as its choice, not the only workable model.

Its approach changes with product need. Wave markets invoicing, payroll and accounting according to each product’s traits, while most customers arrive with one immediate problem rather than a cluster of long-term needs. They usually trust one product first, then discover other money-management features; using more products creates more value for the customer and for Wave.

Onboarding must align with that acquisition context. Wave had early trouble identifying the needs behind sign-ups, then found more success in letting users take their first few actions before inferring intent. The company also customized the second screen with questions based on the purchased product, because invoice, accounting and payroll users need different guidance.

The broader requirement is to connect demand generation and Growth before onboarding begins. If teams fail to distinguish who is arriving and why, they can damage retention before users understand the product. A visitor arrives to solve a pain point; the team cannot tailor the solution until it learns which one.

Onboarding should follow the job that brought the customer in, not a generic checklist.

How should onboarding change by segment?

Wave tested guided onboarding with clear steps for every participant, which made drop-off points easy to see. Some users preferred to explore independently, so Wave reduced guidance for specific segments. Blanket guidance was not the answer.

An FAE does not transfer neatly across every company or product. Its form depends on the onboarding process and user base, which is why another product’s metric cannot simply be copied.

A borrowed metric is a hypothesis, not a strategy.

How do Product, Growth and Marketing make it stick?

To secure organizational support, teams need explicit backing across Product, Growth and Marketing, plus executive buy-in. Unilateral decisions create doubt. Growth still depends on experimentation, but experiments must produce predictable results; predictability comes through metric accountability, which means clear ownership and agreed measures, and disciplined project management across functions.

Data, product and project handoffs create friction, but a shared operating method turns those problems into manageable work.

Wave’s Head of Payroll and Invoicing said: “The difference between a good leader and a good manager is that a manager optimizes for the metrics given to them while a leader creates their own metrics.”

That advice does not remove evidence. The sequence remains: study retained customers, infer the actions associated with retention, then build the metric and framework that fit the product. The “why” behind a process or metric matters as much as the steps used to improve it.

Good metrics still start with retained behavior, even when teams create them.

What should Growth optimize now?

For Growth teams, two priorities anchor the work:

• Move users to the FAE as quickly and efficiently as onboarding allows, rather than optimizing activity without a retention link.
• Profile the most retained customers and work backward to the behaviors that precede retention.

Wave offers a free Product-Led Fundamentals course for teams seeking implementation support.

For product practice, the forward path is an owned, segment-specific activation metric tied to retained behavior, then tested and revised as onboarding evidence changes.