Browser interactions.
Automatically record clicks, form submissions, search terms, input focus, and input changes when that detail is appropriate for the configured product deployment.
Product analytics for lean SaaS
See product behavior beside the customer context that explains it.
Capture signed-user events and browser interactions, review adoption and activity, then connect the signal to feedback, onboarding, surveys, messaging, and lifecycle automation.
10
The answer first
Product analytics should lead to a decision the team can act on.
Product analytics software records how people use a digital product. It can help a team understand activation, adoption, friction, return behavior, and where a workflow stops. The useful unit is not an event count by itself. It is the decision the evidence changes.
Managani provides focused product tracking for lean teams. The Widget can automatically record common browser interactions, and your application can send stable named events for business outcomes. Activity stays connected to the same signed customer identity used by chat, feedback, surveys, tours, highlights, Web Messages, and automation.
What Managani tracks
Use automatic interaction data and stable product events for different jobs.
Named product events.
Send stable outcomes such as creating a project, inviting a teammate, or publishing a release. Named actions survive interface changes better than selectors.
Customer history.
Review activity beside identity, metadata, feedback, and conversations instead of reconciling an analytics ID with a separate customer database after the fact.
Measurement workflow
Define the decision before adding another event.
- 1
Name the customer outcome.
Choose an activation or adoption action that represents value, not a convenient click. Document what the event means and which product decision it supports.
- 2
Identify the customer safely.
Create the signed Widget token on your server with a stable external ID. Keep customer and account metadata intentional, current, and limited to what the product workflow needs.
- 3
Capture the right level of detail.
Use named events for durable outcomes. Keep automatic interaction tracking only where it helps investigate behavior, and add ignore rules for surfaces that should not be captured.
- 4
Review activity and context.
Filter the tracking view and event stream by time and event details. Open the customer profile when feedback, conversations, or account state may explain the observed behavior.
- 5
Act through the connected loop.
Trigger a survey, adjust onboarding, publish a message, create feedback, or configure a guarded lifecycle rule. Measure again after the change instead of treating the first chart as the end.
Privacy boundary
Do not turn product learning into secret-field collection.
Automatic tracking excludes sensitive field types and known secret categories.
1
Exclude sensitive values.
Password, token, API-key, payment-card, CVC, SSN, and file inputs are excluded from value capture. Add explicit ignore selectors for other product-specific sensitive surfaces.
2
Collect only what changes a decision.
More events create more retention, access, and interpretation work. Prefer a small documented measurement model over an unexplained stream of every interaction.
3
Respect deployment policy.
Review consent, disclosure, retention, residency, and access requirements for every market and customer segment where tracking is enabled.
Limitations
Not a PostHog, Amplitude, or Mixpanel replacement.
Managani does not claim mature session replay, experimentation, feature flags, warehouse pipelines, advanced cohort exploration, arbitrary funnel building, statistical analysis, or proven analytics scale. Keep a specialist analytics product when those capabilities support real decisions.
Where it fits
Focused evidence close to the response.
Managani fits when a lean team needs a clear set of customer-linked events, an activity trail, and a direct path from observed behavior to feedback, survey, onboarding, message, or automation work.
Event quality
Maintain a small measurement contract the whole team can understand.
For each named event, record the customer action, required properties, owner, first supported application version, and the decision it informs. Distinguish a successful business outcome from a button click that merely starts the workflow.
Test events in development and production-like environments with duplicate submissions, retries, offline transitions, and single-page navigation. Confirm stable customer identity before interpreting account behavior, and mark instrumentation changes so a sudden increase is not mistaken for adoption. Review unused events regularly and remove collection that no longer supports a decision. When deeper funnel, cohort, experiment, warehouse, or replay analysis becomes necessary, send a deliberate event model to a specialist platform instead of stretching the lightweight Managani view beyond its stated boundary.
FAQ
Product analytics, answered plainly.
What is product analytics?
It is the collection and analysis of how people use a product so a team can improve activation, adoption, retention, and product decisions. The event model must reflect real customer outcomes.
Does Managani record session replay?
No. It records configured events and interaction data, not a visual replay of the customer’s session. Use a specialist when replay is required.
Can events trigger other Managani tools?
Yes. Named events can trigger surveys and guarded lifecycle automation. Tracking also provides context for onboarding, Web Messages, customer profiles, and product review.
Can I use Managani with PostHog?
Yes. Many teams should keep deep analytics in PostHog and use Managani for the customer-facing loop around feedback, roadmap, release communication, guidance, and follow-up.