Setting up CRM Analytics is a multi-month exercise spanning data ingestion, modeling, dashboard design, and rollout. Plan with an experienced analytics architect; the depth and complexity exceeds what casual Salesforce admins can handle alone. Start with one focused use case before expanding to enterprise analytics.
- Identify analytical use cases and audience
List the analytical questions that standard reports cannot answer well. Sales productivity across many years, multi-org pipeline rollup, service operations metrics, finance close-cycle analysis. Each use case drives data source and dashboard design.
- Provision CRM Analytics and configure connectors
Setup > CRM Analytics > Setup. Enable the product. Configure connectors to Salesforce orgs and external data sources. Plan ingestion schedules based on data freshness needs.
- Build data preparation Recipes
Open Analytics Studio > Data Manager > Recipes > New. Use the visual editor to join, filter, aggregate, and transform source data into datasets. Schedule the recipe to run on the right cadence.
- Create datasets from the prepared data
Each Recipe produces one or more datasets. Datasets are the columnar stores that lenses query against. Review the schema, field types, and dimension/measure designations.
- Build lenses for individual visualizations
Analytics Studio > Lenses > New. Pick a dataset, define the query (group by, aggregate, filter), choose the visualization type. Save the lens for reuse across dashboards.
- Assemble dashboards from lenses
Dashboards > New. Drag lenses onto the canvas. Configure layouts, filters, and bindings between components. Bindings let one lens filter another based on user interaction.
- Embed dashboards in Sales/Service Cloud
Add the Embedded Dashboard Lightning component to record pages. Configure bindings so the dashboard receives the record context. Verify dashboard renders correctly in the embed.
- Configure sharing and roll out
CRM Analytics has its own sharing model. Share apps and dashboards with the right user populations. Train users on dashboard navigation, filtering, and drill-down. Monitor usage and iterate based on adoption.
Salesforce, Snowflake, Redshift, BigQuery, CSV, and other sources. Determines what data flows into CRM Analytics datasets.
Recipes are the modern visual data prep tool. Dataflows are the older JSON-driven alternative. Use Recipes for new work.
Embedded dashboards live in Lightning record pages. Standalone dashboards live in Analytics Studio. Most production deployments use both.
- CRM Analytics is licensed separately. Confirm licensing before designing solutions; consumption-based add-ons for Einstein Discovery and other features add cost.
- Dataset refresh schedules drive data freshness. Hourly refresh costs more compute than daily; pick based on actual use case latency needs.
- Embedded dashboards depend on bindings. Misconfigured bindings produce dashboards that show wrong or empty data when embedded in record pages.
- The query language (SAQL and SQL through Recipes) differs from SOQL. Salesforce admins moving to CRM Analytics need to learn the new query model.
- Migration from older Tableau CRM / Einstein Analytics terminology persists in documentation and community resources. Stay current with the unified CRM Analytics naming.