Find where new signups get stuck
See which setup step loses the most people, inspect the numbers, and review a change that could help them continue.
Your first result: A breakdown of where people stop and a draft improvement to the step worth investigating first.
What you need: Connect your product analytics. Add Stripe if you also want to follow signups through to paid subscriptions.
Example
Sample data · A fictional reporting app
240 people signed up. Only 96 connected their data. Scout shows you where they stopped and prepares a clearer setup screen.
The numbers
First 14 days after signup · the same 240 people
| Where to look | People at this step | Continued | Share who continued |
|---|---|---|---|
| Connect their data | 240 | 96 | 40% |
| Create their first report | 96 | 72 | 75% |
| Become a paying customer | 72 | 24 | 33.3% |
Start here: 144 people stop at the data connection step—the biggest drop in this sample. Start by making that step easier to understand.
Connect their data
240 people signed up, but only 96 connected a data source. That leaves 144 people without the data they need to see a report.
Suggested change: Make the benefit of connecting clear
Current version
Configure your workspace
Choose an integration to continue.
Button: Add integration
Scout’s draft
See your first report
Connect the analytics tool you already use. We’ll import your data for you.
Button: Connect my data
How to check whether it helped: Check whether more than the current 40% of new signups connect their data within 14 days, and whether they go on to create a report.
Create their first report
Of the 96 people who connected data, 72 created a report. The other 24 got through the connection step but never saw the product’s main result.
Suggested change: Give people a starting report
Current version
Your reports
No reports yet.
Button: Create new
Scout’s draft
Your data is ready
Start with a weekly overview. We’ve selected your connected source so you can see a report right away.
Button: Create my first report
How to check whether it helped: Check whether more than the current 75% of people with connected data create a report within their first 14 days. Confirm that the report contains useful data.
Become a paying customer
24 of the 72 people who created a report subscribed. First inspect why the other 48 did not continue; seeing a report does not mean everyone needs a paid plan.
Suggested change: Explain what the paid plan is for
Current version
Upgrade
Unlock Pro to continue.
Button: Upgrade now
Scout’s draft
Keep your reporting history
Save your reports and compare performance over time. Review the plan and billing details before subscribing.
Button: See the paid plan
How to check whether it helped: Check subscriptions among people who created a report, using the same 14-day window. Also watch refunds and cancellations so a higher signup count does not hide a worse customer experience.
These are sample numbers, not customer results. A clearer screen is a proposed test, not a promise of more subscribers. In your project, Scout checks which events and payment records can actually be connected.
How do you find a trial activation drop-off?
Define the first useful result a new customer should reach, then follow the same eligible signups through the required steps for the same amount of time. Inspect the step with the largest relevant loss and the screen behind it before proposing a change. Add payments only when recorded identities and payment lineage connect them to that cohort.
Activation is specific to your product. A reporting app might use a first report; a collaboration app might use a completed shared task. A login, page view, or integration button click does not automatically establish that someone received value. Keep the owner's selected objective and choose supporting steps that explain it.
Prepare the evidence
Create a project for your product, then connect PostHog and optionally Stripe. Inspect the intended project, event names, source freshness, and historical coverage after sync. Installing a connector does not create missing completion events or recover unrecorded historical identities.
Record the measurement definition before reading a rate:
| Decision | What to record |
|---|---|
| Population | Which new accounts or trials enter, and which recorded conditions exclude a record |
| Required steps | The actual completion event for signup and each necessary setup action |
| Identity | The subject and scope that link events; say when records cannot be joined |
| Ordering | Whether each later step must occur after the preceding step |
| Completion window | How long each entrant has to reach activation |
| Payment outcome | The qualified settled payment and trial relationship, when both are observed |
Use the existing project's measurement definition rather than inventing new names for the same events. Measurement methodology explains why separate daily totals do not establish a funnel. PostHog also documents funnel ordering, denominators, and incomplete conversion periods.
Ask Scout for one reviewable improvement
- Ask: “Where do new signups stop before reaching our first useful result? Check the recorded events, identities, coverage, and completion window. Show the eligible population, completions, and source references for each required step. Preserve my selected objective.”
- Inspect the source references. A missing step is a measurement gap; an immature cohort still has time to complete. Keep unmatched Stripe activity separate from the product funnel.
- Have Scout read the screen or public page associated with the suspected drop. Consider errors, unnecessary requirements, waiting time, and unclear instructions as competing explanations.
- Ask for one concrete draft and its measurement plan. The count shows where to investigate; it does not show why people left.
- Review the draft, affected audience, and execution scope. Analytics read permission does not authorize a rollout or a change to your product.
Reproduce a baseline with your own data
Choose an entry period whose entrants have all had the declared completion window. Save the source report or receipt, filters, definition, and observation date. For each step, retain the number eligible to attempt it and the number completing it. Distinguish conversion from the first step from conversion relative to the preceding step.
In the fictional example above, 96 of 240 signups connect data: 40%. Seventy-two then create a report: 75% of connected users, or 30% of all signups. Those rates answer different questions. They are sample arithmetic, not TractionScout or customer results.
After a reviewed change ships, record its date and let the next comparable cohort mature. Track the affected completion and the next useful outcome; also inspect cancellations or refunds if payments are in scope. If practical, use a properly configured randomized experiment. A before-and-after difference can also reflect audience, price, instrumentation, or other product changes.
Continue from the result
Use acquisition channel activation to investigate whether a source brings suitable users. If people do not reach the site, inspect Google searches and clicks or ad spending. The example above uses labelled sample data and does not forecast a lift.