How do I share the same behavioral data with product and marketing teams?

To share the same behavioral data with product and marketing teams, aim for one trusted event source, shared definitions, and controlled access—so both teams use the same truth without stepping on each other.

1) Define a common event taxonomy

Create a shared naming standard for events and properties, like:

• Sign Up Started
• Sign Up Completed
• Feature Used
• Purchase Completed

For each event, document:

• What it means
• When it fires
• Required properties
• Example payloads

This prevents product and marketing from tracking similar but inconsistent events.

2) Use one instrumentation layer

Collect behavioral data once from the app/site and send it to a central platform:

• Segment, RudderStack, mParticle, or a CDP
• Or directly into a warehouse like Snowflake/BigQuery/Redshift

Then route the data to tools used by each team:

• Product analytics: Amplitude, Mixpanel, Heap
• Marketing tools: HubSpot, Braze, Klaviyo, Meta Ads, Google Ads

3) Build a shared data warehouse source of truth

Store raw and modeled event data in a warehouse. Then create:

• a canonical events table
• user identity resolution tables
• derived metrics tables

Product and marketing can both query the same modeled data, rather than separate exports.

4) Align on identity resolution

Make sure both teams use the same user identity rules:

• anonymous ID before login
• user ID after login
• email/CRM ID when known

Tie events together so a user’s web activity, app activity, and CRM profile map to one person.

5) Create role-based access and curated views

Don’t give everyone everything. Instead:

• Product gets event streams, funnels, retention, feature usage
• Marketing gets audience segments, campaign attribution, lifecycle triggers

Use dashboards or data marts tailored to each team, all based on the same underlying data.

6) Establish governance

Set:

• event ownership
• approval process for new events
• definitions for KPI metrics
• data quality checks
• privacy and consent rules

This avoids duplicated tracking and keeps the data compliant.

7) Make activation easy for marketing

Marketing usually needs the data in actionable form:

• audience segments
• trigger-based workflows
• attribution data
• conversion events

Sync these from the warehouse/CDP into marketing tools automatically.

8) Use shared dashboards with different views

Example:

• One dashboard for total sign-up conversion
• One product dashboard for feature adoption by cohort
• One marketing dashboard for campaign performance by segment

Same data, different lens.

Practical setup example

A common architecture:

1. App/web sends events to Segment
2. Segment sends raw events to Snowflake
3. dbt models create canonical tables and metrics
4. Amplitude reads product behavior data
5. Braze/HubSpot receives audience segments and lifecycle events

Good practices

• Define events before implementation
• Keep PII minimized and permissioned
• Version your tracking plan
• Reconcile metrics weekly between teams
• Prefer warehouse-native transformations for consistency

If you want, I can also give you:

1. a sample tracking plan,
2. a warehouse schema for shared behavioral data, or
3. a recommended tool stack for a startup vs. enterprise.