Digital health
Where does a sensitive care or wellness onboarding flow lose people?
Measure completion and drop-off without making each participant’s readable interaction history available to the analytics service.
Learn what users need without watching everything they do
Privacy-first product analytics for sensitive workflows
See which steps drive activation, where users drop off, and what to improve next without building a readable history of every user behind the trend.
Privacy should not leave your product without analytics
Privacy kept analytics out
You chose not to add product analytics because tracking cookies, SDKs, and readable user histories were the wrong trade-off for your users.
Your current stack still sees the user
Consent gates, masking, access controls, and retention policies govern the history. They do not stop your analytics tool from reading it.
The alternatives still force a trade-off
Use simpler analytics and lose product context. Self-host the same readable history or build with privacy tooling, and your team inherits more infrastructure.
Keep the funnels, adoption signals, and product feedback. Make individual activity private
Bring the sensitive journey you left unmeasured. Stoffel turns protected events into a clear view of activation, conversion, and drop-off.
Onboarding
Track the moments that answer the product question
Define the journey and metrics once. Stoffel protects those event values before analytics can turn them into a user history.
- Guided workspace and source setup
- Typed event names and descriptions
- Schema simulation before implementation
Insight setup
Build the funnel your team already knows how to use
Choose the events, order, conversion window, comparison, and breakdown that answer the product question.
- Ordered funnel steps
- Conversion windows and date ranges
- Comparison and breakdown controls
Data basis
Review what the insight can reveal before your team uses it
See the approved event schema, private submission path, aggregate computation, and opened metric behind the product view.
- Approved typed event schema
- Direct submission to configured MPC services
- Opened aggregate returned to your product
Your product insight
Know which product moment needs attention next
Bring activation, conversion, and drop-off into one view your team can use after every release.
- Activation and stage-level drop-off
- Previous-period comparison
- Save or add the insight to a dashboard
Get the product signal your team has been missing
Bring one sensitive journey. Leave with a product view your team can use.
Use cases and industries
Start where readable product histories create the most risk
Stoffel fits product questions that need a shared adoption, conversion, or drop-off signal—but not a browsable story about each person.
Financial products
Which verification or account-setup step blocks activation?
Use protected event values to produce an approved funnel across a sensitive financial journey.
Enterprise and B2B SaaS
Do invited teams reach the first value moment?
Give your product team the shared activation pattern without a browsable history of named customer users.
Cryptocurrency wallets
Which setup, backup, or transaction step blocks wallet activation?
Measure activation and feature adoption without giving the analytics service a browsable history of each user’s in-product wallet activity.
Keep broad exploration. Add privacy-first analytics where it matters
Use your existing suite for the journeys it can safely hold. Use Stoffel when your team still needs the signal but the readable history is the wrong trade-off.
Why teams add Stoffel Analytics to the product stack:
- Predefined product journey metrics
- Sensitive journeys without a central readable event history
- Dashboard insight for your team
- Works beside the analytics stack already in place
| Capability | Stoffel AnalyticsPrivacy-first product analytics | PostHogProduct analytics suite | AmplitudeProduct analytics suite | MixpanelProduct analytics suite | MatomoPrivacy-positioned analytics suite | AWS Clean RoomsData collaboration | Snowflake Data Clean RoomsData collaboration |
|---|---|---|---|---|---|---|---|
| Predefined product journey metrics | |||||||
| Sensitive journeys without a central readable event history | |||||||
| Dashboard insight for your team | |||||||
| Works beside the analytics stack already in place | |||||||
| Person-level replay and investigation |
Compare all 7 products
| Capability | Stoffel AnalyticsPrivacy-first product analytics | PostHogProduct analytics suite | AmplitudeProduct analytics suite | MixpanelProduct analytics suite | MatomoPrivacy-positioned analytics suite | AWS Clean RoomsData collaboration | Snowflake Data Clean RoomsData collaboration |
|---|---|---|---|---|---|---|---|
| Predefined product journey metrics | |||||||
| Sensitive journeys without a central readable event history | |||||||
| Dashboard insight for your team | |||||||
| Works beside the analytics stack already in place | |||||||
| Person-level replay and investigation |
Privacy-first product analytics FAQ
The technical questions your team should ask before changing the data relationship
Clear answers on privacy by design, cookies, self-hosting, individual activity, compliance, and current availability.
What is privacy by design in product analytics?
It means designing the measurement path around an explicit product question, collecting only the selected events, and deciding what may be revealed before analysis begins. In Stoffel Analytics, selected event values are protected in the client and the analytics workflow receives an approved product metric rather than a readable event history for each user.
Which privacy by design principles apply to product analytics?
The practical principles are data minimization, purpose limitation, privacy by default, explicit authorization, and controlled outputs. Stoffel applies them through predefined event schemas, approved metrics, minimum-participation rules, and repeated-query controls. Your team still owns consent, lawful basis, retention, access, and governance decisions.
Can product analytics work without cookies?
Yes. Stoffel’s current protected event path does not depend on tracking cookies. But cookie-free analytics is not automatically private: an SDK or server can still retain linkable user histories. Stoffel changes what the analytics service can read, not merely how a browser identifier is stored.
How is privacy-first product analytics different from self-hosted analytics?
Self-hosting changes who operates the infrastructure, but it can preserve the same readable event model. Stoffel protects selected values before they enter the analytics path and returns approved aggregate metrics. Self-hosting can still be useful; it solves a different custody and operations question.
How does privacy-preserving product analytics protect individual activity?
For the current Stoffel path, clients send typed private event values directly to configured MPC services. The product keeps public configuration and receives the opened aggregate. Thresholds, authorization, query policy, and composition controls are still required because even aggregate outputs can reveal too much when a group is small or repeatedly queried.
Does privacy-first product analytics replace session replay or user-level debugging?
No. Replay, support, fraud review, and debugging can require an identifiable journey. Keep those workflows narrowly governed in the tools that need them. Stoffel is for product questions where your team needs adoption, conversion, or drop-off without unrestricted person-level drill-down.
Is privacy-first product analytics automatically GDPR compliant?
No product architecture creates automatic compliance. Stoffel can reduce the readable data exposed to an analytics service, but your organization still needs an appropriate lawful basis, consent where required, clear notices, authorization, retention rules, security controls, and legal review for its use case.
What can teams evaluate in Stoffel Analytics today?
Early access currently covers the Rust client path, predefined event schemas, count, sum, and average metrics, the dashboard lifecycle, and CSV export. Production browser and mobile support and broader exploratory product analytics remain active product work.
Learn from the journey you have been forced to ignore
Join early access with one sensitive journey. We will help you turn it into a product view your team can use.