CRM Analytics · Salesforce · dashboards · analytics apps

CRM Analytics reporting that leads from a result to action in Salesforce.

I design interactive dashboards using sales, service and external data. Users see the KPI, its drivers and record detail in the environment where they already work.

CRM Analytics is the current name of the former Einstein Analytics and Tableau CRM. Tableau Next is a separate product, so the scope follows the organisation's actual Salesforce environment.

Describe the report and Salesforce environment See the solution structure
Reporting available in Salesforcedashboard, analytics app and record context
Analysis-ready dataCRM objects, external sources, recipes and datasets
Role-appropriate accesslicences, permissions, app sharing and security predicates

When CRM Analytics makes sense

Standard reports are not enough for cross-process analysis.

CRM Analytics becomes useful when teams need to connect objects, analyse history and result drivers, or enrich CRM with data from outside Salesforce.

Pipeline shows value, not risk

Historical movement, opportunity quality, activity and signals requiring attention are missing.

Data is spread across objects

Account, Opportunity, Activity, Case and custom objects are difficult to combine reliably.

Context sits outside CRM

Plan, billing, product or marketing data is needed to explain sales and service outcomes.

KPIs have several definitions

Conversion, pipeline coverage and forecast differ across reports and spreadsheets.

Refresh status is invisible

Recipients cannot see the data period or owner of a failed job or dataset.

Access was not designed

App sharing does not replace record-visibility design and security-predicate testing.

Reporting product

From Salesforce objects to an analytics app used in daily work.

I separate data preparation, analytics logic and the recipient experience, turning the dashboard into part of a managed reporting environment.

01 · Sources

Salesforce and external data

Standard and custom objects, files, connectors and optionally Data 360 data.

02 · Preparation

Recipes and datasets

Joining, cleaning, aggregation, calculated fields, schedules and job control.

03 · Analysis

Lenses and dashboards

KPIs, queries, filters, interactions, drill-down, record detail and device layouts.

04 · Use

Analytics app and Lightning

Organised assets, sharing, Salesforce embedding and a path to action.

The report answers a questioneach page has an audience, decision and detail level
The dataset has an ownerdefinitions, refresh and changes are accountable
Security is testedfeature permissions and data visibility are separate layers

Example product

The Sales Performance App connects monitoring, analysis and CRM record work.

This is an illustrative structure. Pages, queries and detail follow the sales process, data model and audience roles.

CRM Analytics appSales Performancemanagement · sales ops · manager
OverviewOutcome, target and forecast

Revenue, pipeline, coverage, win rate, trend and primary variances.

Pipeline healthOpportunity quality and movement

Stage aging, inactivity, close-date movement and values at risk.

ConversionFunnel and outcome drivers

Stage conversion by team, segment, source and product.

AccountsCustomer and record detail

From aggregate to account, opportunity and the next action in Salesforce.

Data and refresh

I design new data preparation in recipes and retain dataflows where they remain justified.

Recipes provide the more convenient path for new preparation processes. Existing or technical scenarios may continue to use dataflows without an automatic rewrite.

Input

Objects and connections

Required fields, relationships, history, sync frequency and external data.

  • Salesforce and connected objects,
  • CSV and available connectors,
  • direct data when architecture permits.
Transformation

Recipes and datasets

Logic designed to stay understandable, testable and maintainable.

  • join, append, aggregate and filter,
  • calculated fields and value standardisation,
  • output to the right dataset.
Operations

Data Manager and jobs

A report is credible only when refresh status is visible.

  • sync and recipe-job order,
  • schedule and error logs,
  • an owner and response for failed jobs.

Process

From business questions to reporting embedded in the team's workflow.

  1. 01

    Audience, decisions and current reporting

    Roles, Salesforce reports, spreadsheets, apps, licences, problems and expected actions.

    Outcome: needs map
  2. 02

    Sources, KPIs and dataset model

    Objects, grain, relationships, history, external data, metric definitions and system of record.

    Outcome: reporting model
  3. 03

    App and dashboard prototype

    Pages, information hierarchy, widgets, filters, interactions, drill-down and record path.

    Outcome: accepted prototype
  4. 04

    Recipes, datasets and views

    Transformations, queries, lenses, dashboard designer, layouts, performance and schedules.

    Outcome: test version
  5. 05

    Sharing and security

    Licences, permission sets, apps, roles, groups, security predicates and test scenarios.

    Outcome: controlled access
  6. 06

    QA, publication and adoption

    KPI reconciliation, job tests, documentation, audience training and report-development process.

    Outcome: maintainable solution

Use cases

Reporting for sales, service and CRM process owners.

Management

Executive sales cockpit

Outcome, forecast, pipeline coverage, movement and key risk.

Sales

Pipeline and conversion

Stages, velocity, aging, conversion, lost opportunities and funnel quality.

Managers

Team performance

Team results, activity, opportunity portfolio, coaching and priorities.

Customers

Account 360

Sales, activity, products, service cases and account potential.

Service

Service performance

Volume, SLA, backlog, resolution time, channels and recurring contact drivers.

Sales operations

CRM process quality

Data gaps, inactive opportunities, date movement, adoption and process consistency.

Security

I test what a user can do separately from which data they can see.

Licences and permission sets expose features. App sharing controls asset access, while security predicates may restrict dataset rows.

01

Licences and permissions

Who can view, explore, build dashboards or manage recipes and dataflows.

02

Apps and sharing

Which groups, roles and users access apps, dashboards, lenses and datasets.

03

Row-level security

A security predicate defines dataset rows visible to the signed-in user.

04

Control scenarios

Salesperson, manager, director and administrator are tested against specific records.

Acceptance criteria

The report must reconcile with CRM, remain understandable and be secure.

Criteria follow the process, data, licences and decision frequency.

KPIs reconcile with the reference systemdefinition, grain, filters and tolerances are documented
The dashboard leads to explanationresults can be decomposed by meaningful drivers and records
Jobs complete within the required windowsync, recipes and datasets have schedules and monitoring
Each role sees the right scopepermissions, app sharing and security predicates pass tests
The view works at its destinationAnalytics Studio, Lightning and device layouts are accepted
The solution has ownersdataset, app, dashboard, job and definitions are accountable

Honest limitations

What CRM Analytics does not solve automatically.

  • Not every report needs CRM Analytics.A simple object list or summary may remain a standard Salesforce report.
  • Licences and edition matter.Feature scope, data volume and audience size affect the solution.
  • A dataset does not repair CRM quality.Missing fields, stale stages and inconsistent process require source-level work.
  • Recipes need operational oversight.Sync, job order, errors and schema changes require handling.
  • Security does not end with app sharing.Dataset visibility requires appropriate predicates and role tests.
  • Tableau Next is a separate scope.It requires Data 360 and a different architecture from a classic CRM Analytics app.
Krzysztof Surowiecki

Reporting and business analytics

I connect KPI design, data preparation and clear report use.

I work with management reporting in Salesforce CRM Analytics, Tableau, Power BI and Looker Studio, matching scope to the client's environment rather than moving simple reports into a more complex tool without a business reason.

20+years of experience
150+analytics and data projects
50+clients

Figures refer to the broader analytics and data practice, not only Salesforce CRM Analytics implementations.

Before we talk

Frequently asked questions.

Is CRM Analytics still the current name?

Yes. It is the current name of the product formerly known as Einstein Analytics and Tableau CRM.

Has Tableau Next replaced CRM Analytics?

No. They are separate Salesforce products. CRM Analytics remains relevant for organisations that need analytics embedded deeply in Salesforce.

When is a standard Salesforce report enough?

A simple summary on one or a few well-related objects may be faster and easier to maintain. CRM Analytics adds value for history, multiple sources, advanced transformation and interactive analysis.

Recipes or dataflows?

I normally start new preparation flows with recipes. Dataflows can remain appropriate in existing or technical solutions and do not require automatic replacement.

Can reports combine data outside Salesforce?

Yes, depending on connectors, licences and architecture. Data may be prepared in CRM Analytics, loaded through files or connectors, or accessed through supported direct mechanisms.

How is data restricted by user?

The design covers feature permissions, app sharing and dataset row-level security. Security predicates require tests with actual roles and records.

First step

Describe the current Salesforce reports and three questions the team cannot answer.

I will follow up on licences, objects, external data, roles, refresh frequency and where the dashboard will be used.

Discuss the reporting need View management reporting

More context

Choose the right reporting layer.

Management reportingan example path from KPI to insightView reporting Tableau implementationanalytics for a broader data environmentExplore the service Data Governanceownership, definitions and access controlExplore the approach