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Activation metrics: one to steer onboarding, one to check retention

Members of the Growth work group pair a fast early action that onboarding can move with a slower check that users returned, then test both with experiments.

Updated October 13, 2026

Steer onboarding with an early action the team can move and that gives users a first experience of value, and use a later repeat action to check that those users came back when the need recurred.

  • Write it as an action, a count and a window. Hila Qu starts from the moment a new user gets value: X action, Y times, within Z days. She would compare a few candidate actions against retention in later cohorts, with the retention window starting after the activation window, and check the result by channel and user type, since one channel sending better-fit users can make an action look predictive.
  • Separate first value from the habit. Casey Winters would separate the first experience of value from the repeat behavior that shows a habit. Pinterest had to show relevant content in the first session because a second one wasn't guaranteed, while a weekly save later was a higher bar. He would choose the early action onboarding can improve, then check whether more people reach the habit.
  • Use one measure to steer and one to validate. Brian Balfour would make the early action the team's operating metric if onboarding can change it and it gives users a first experience of value, and the later repeat action the validation metric. A stronger link to retention doesn't make a later event a useful target if it arrives too late to guide the team. At HubSpot, importing contacts and creating lists were steps on a journey that could take months before regular use.
  • Randomize before trusting the correlation. Albert Cheng notes that at Chess.com, motivated players may finish a first game and review a move without any help from onboarding. He would randomize a change that makes the action easier to reach and measure both completion and later play; if completion rises and play stays flat, he'd keep looking.
  • Break a team metric into its steps. Lauryn Motamedi says Airtable's week-four multi-user activity hid several paths, so the team split it into signing up as a team, inviting teammates, teammates being active and more than one person active in week four. Individual week-two and week-four retention and a measure of workflow depth sat beside it, because a change could help someone build and return while teammate activity stayed flat.
  • Look at the retained users the metric misses. If they later take the same meaningful action and the timing fits the use case, Lauryn would lengthen the window. If they keep getting value through a different behavior, she would track that path separately. She'd also watch a few of them get started, because in Airtable onboarding how someone learned and built said more about the help they needed than their job function did.

Group chat with Hila, Lauryn, Albert, Brian, Casey — the Growth work group

Question:

How do you pick an activation metric that predicts retention?

Hila Qu 曲卉
Hila Qu 曲卉PLG advisor. Former Director of Growth at GitLab and VP of Growth at Acorns
I start with the moment a new user actually gets value, then make it measurable: X action, Y times, within Z days. The metric is a proxy for that experience, so I would compare a few candidate actions against retention in later cohorts, using a retention window that starts after the activation window. Check the relationship by acquisition channel and user type too; an action that predicts retention only because one channel sends better-fit users is a weak goal for onboarding.
The failure mode I watch for is a team driving the count without delivering value. I shared the Jira example where the team pre-created three tickets to satisfy its proposed aha metric. It did not lead to retention or conversion. Guide users toward the action and remove friction, then see whether more users take it themselves and whether later retention moves. For B2B, test the user, team, and buyer journeys separately because each may have a different value moment.LinkedIn
Casey Winters
Casey WintersCo-founder at SuperMe. Ran growth at Pinterest, Grubhub and Eventbrite
The expected frequency of the use case should set the clock. At Grubhub, people typically ordered delivery once or twice a month, so we tracked whether a new customer placed a second order within 30 days. At Pinterest, a monthly visit was easy to generate without clear evidence of value. We shifted toward weekly use and saving a pin, which showed someone found something worth keeping.Spotify
I would separate the first experience of value from the repeat behavior that indicates a habit. Pinterest needed to show relevant content in the first session because there was no guarantee of a second one; the later weekly save was a higher bar. Choose an early action you can actually improve through onboarding, then check whether more people also reach that later habit.Spotify
Lauryn Motamedi
Lauryn MotamediFormer VP Growth and Product at Notion and Head of Growth at Airtable
At Airtable, we learned that one team-level activation number hid several different paths. We broke week-four multi-user activity into the share who signed up as a team, invited teammates, had teammates actually active, and had more than one person active in week four. That showed us which part of the journey onboarding could change. We also tracked individual week-two and week-four retention and a separate measure of whether someone had built a more substantial workflow. A change could help someone build and return while leaving teammate activity flat, and the single team number would miss that progress.YouTube
For a collaborative product, I would validate the early action against later team use, then keep individual retention and depth of use visible beside it. Choose the level of measurement that matches how value is delivered, and break the metric into steps before deciding which onboarding step to change.
Albert Cheng
Albert ChengChief Growth Officer at Chess.com. Previously led growth at Grammarly and Duolingo
The experiment is where I’d challenge the candidate metric. At Chess.com, finishing a first game and reviewing a move could be a useful candidate, but more motivated players may do both without any help from onboarding. Randomize a change that makes the experience easier to reach, and measure both completion and subsequent play across all assigned new players. If completion rises while later play stays flat, I would keep looking. My teams have run experiments at high volume across Duolingo, Grammarly, and Chess.com, and this is exactly why I want the retention readout alongside the faster activation readout.LinkedIn
Casey Winters
Casey WintersCo-founder at SuperMe. Ran growth at Pinterest, Grubhub and Eventbrite
Before adopting a first-week activation threshold, inspect the people it calls failures who later become regular users. In one retention analysis, extending the window to 35 days showed why a first-week cut could miss habit formation. Users who skipped the expected core action early and still returned needed a closer look: they might have found another path to value, or needed more time for the use case to recur.
I would plot time to first value and time to repeat value by signup cohort before choosing the cutoff. Then interview a few retained users on each side of it. A metric that marks many eventual retainers as unactivated will send the onboarding team after the wrong bottleneck.
Question:
Brian, Casey would track an early action onboarding can improve, then check whether it leads to repeat use. If a later repeat action predicts retention more strongly, how would you choose the activation metric?
Brian Balfour
Brian BalfourFounder/CEO at Reforge. Previously VP Growth at HubSpot
I would use two measures. The early action is the team’s operating metric if we can change it through onboarding and it gives users a first experience of value. The later repeat action is the validation metric: did those users come back for that value when the need recurred? A stronger statistical link to retention does not make a later event a useful day-to-day activation target if it arrives too late to guide the team.
I’ve argued that activation should carry a user through establishing a habit, rather than end at setup. At HubSpot, importing contacts and creating lists were steps on a journey that could take months before regular use.churn So I’d map both events, run an onboarding experiment aimed at the early one, and judge it by whether more assigned users also reach the later one and retain. If only the early action moves, choose another early signal or change the intervention.
Question:
Lauryn, Casey found retained users who missed the early action, and Brian described setup that can take months. How would you decide whether to lengthen the activation window or track a separate path to value?
Lauryn Motamedi
Lauryn MotamediFormer VP Growth and Product at Notion and Head of Growth at Airtable
I’d inspect the retained users the early metric misses. If they eventually do the same meaningful action and the timing fits the use case, lengthen the window and measure time to that action. If they repeatedly get value through a different behavior, track that path separately. At Airtable, we kept individual retention and depth of building alongside week-four multi-user activity because a user could build a useful workflow and return without yet bringing a team in.YouTube
I’d compare those missed users by how they learn and build, then watch a few of them get started. In Airtable onboarding, learning and building style told us more about the help someone needed than their job function did. That work helps distinguish a slower version of the same path from a genuinely different path to value.YouTube

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In This Conversation

  • Hila Qu 曲卉
    Hila Qu 曲卉

    PLG advisor. Former Director of Growth at GitLab and VP of Growth at Acorns

  • Lauryn Motamedi
    Lauryn Motamedi

    Former VP Growth and Product at Notion and Head of Growth at Airtable

  • Albert Cheng
    Albert Cheng

    Chief Growth Officer at Chess.com. Previously led growth at Grammarly and Duolingo

  • Brian Balfour
    Brian Balfour

    Founder/CEO at Reforge. Previously VP Growth at HubSpot

  • Casey Winters
    Casey Winters

    Co-founder at SuperMe. Ran growth at Pinterest, Grubhub and Eventbrite

See all

Frequently Asked Questions

  • How do you choose a startup's first growth channel?

    Pick a channel the product can feed, test it with one narrow segment on a set budget and date, and judge it by how many users reach value and come back.

  • What should a founder check first when growth stalls?

    That the data is right, then cohort retention split by segment and channel. If curves trend toward zero in every slice, fix the product before spending more on acquisition.

  • How do you tell a growth problem from a product problem?

    Bring in a small batch of users from one clean channel and read their cohorts. If they activate and return but there aren't many, it's distribution. If they leave within the first week, product owns the fix.

  • What moves activation in a new user's first few days?

    Find where users drop, then match the lever: pre-answer setup for users who stall, make the first action an earned win for users who feel nothing, and bring back users who got value.

  • Who should own acquisition and retention, growth or marketing?

    Most members would split near signup, with marketing on channels and the promise and growth on the path to first value. The line still has to follow the growth model, and both teams judge channels by the cohorts that stay.

  • Should a growth team report to product or marketing?

    Wherever the biggest lever is. For most product-led companies that is product, next to core rather than inside it, and once paid spend matters too, one growth leader owns acquisition and activation.

  • Which lifecycle emails should a team build first?

    The ones aimed at the steepest drop on the retention curve, usually the activation email. Depth and renewal emails come next, and win-back to fully churned users comes last.

  • How do you bring back signups who went quiet?

    Watch a few try the next step and fix where they stall, then test the message with and without the fix against a holdout, and count retained use rather than opens.

  • When should a product-led company add sales?

    A founder can start working accounts where usage is spreading and retaining. A sales team follows once deals need security reviews and procurement that self-serve can't handle.

  • Which self-serve accounts should a sales rep call?

    Ones big enough to pay for a rep's time, with use spreading inside the company and a need self-serve can't meet. Hold some flagged accounts back to check that sales added value.

  • What makes a good north star metric for an early product?

    A retention measure built from how often the problem occurs, the action that solves it and the user it describes, with activation as an input. Drop it if the team can raise it without users getting more value.

  • Should a new marketplace build supply or demand first?

    Whichever side gets a buyer to a completed transaction while giving the supplier a reason to stay. Start in one narrow market and track matches, supplier earnings and repeat buyers.

  • When can a marketplace copy its first city?

    When service holds after subsidies come down, a new manager can run the launch playbook without the founders, and the team knows whether the channel behind market one's demand starts warm or cold in the next market.

  • How should you test a landing page?

    Show visitors what they searched for before the ask, start with the page's first clear funnel drop, and count activated users per visitor alongside signups.

  • Should a startup with a few dozen users stop acquisition?

    Stop broad acquisition but keep a small hand-picked flow from one segment, onboard those users live, and count only return visits nobody prompted.

  • How does a B2B startup find its first paying customers?

    Have founders sell by hand to one narrow buyer, starting with warm intros and asking for payment early. Then check who actually paid, and at what price, before choosing a channel to scale.

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