Salesforce Marketing Intelligence guide
Marketing Intelligence is Salesforce's marketing analytics and attribution product. Here is what it does and what to plan for.
Marketing Intelligence is Salesforce's analytics and attribution product for marketing, presented as the marketing analytics layer on the Marketing Cloud page. It was previously called Marketing Cloud Intelligence, and before that Datorama. It brings performance data from campaigns and channels together so teams can see what is working and where to spend.
What it is for
Marketing teams often have spend and results spread across ad platforms, email tools, web analytics and CRM. Marketing Intelligence is designed to combine that data, standardise it and report on performance and attribution in one place.
Core capabilities
| Area | What it covers |
|---|---|
| Data consolidation | Bringing marketing performance data from several sources together |
| Reporting | Dashboards on campaign and channel performance |
| Attribution | Understanding which activity influenced results |
| Intelligence+ additions | Paid Media Optimization, Segment Intelligence and Flexible Attribution |
How it connects with other Salesforce products
Marketing Intelligence complements execution products such as Marketing Cloud Engagement and Marketing Cloud Next. Existing customers can renew into Intelligence+, which Salesforce says adds Marketing Cloud Next capabilities, including the features listed above. For wider business analytics, Salesforce also offers Tableau and Tableau Next.
Who it suits
- Organisations with significant paid media spend across several platforms.
- Marketing operations teams that spend too long building reports by hand.
- Leaders who need consistent cross-channel performance figures.
Questions to answer before you buy
Analytics projects succeed or fail on clarity rather than tooling. Before you evaluate Marketing Intelligence, agree answers to a few questions with marketing, finance and sales:
- Which decisions should the reports support, such as budget moves between channels or campaign go and stop calls?
- Who owns campaign naming and taxonomy, and how will it be enforced across agencies and regions?
- Which figure is the source of truth for revenue or pipeline: CRM, finance or the ad platforms?
- How often do people need the data refreshed to act on it?
Written answers make configuration faster and stop the project becoming a dashboard-building exercise.
Planning an implementation
- 01
List data sources
Record every platform, account and file that holds performance data.
- 02
Agree definitions
Standardise campaign naming, channels and key measures first.
- 03
Choose an attribution approach
Decide what questions attribution must answer.
- 04
Build core dashboards
Start with a small set used in real decisions.
- 05
Review regularly
Check data freshness and accuracy each reporting cycle.
Common mistakes
- Connecting sources before fixing inconsistent campaign naming.
- Treating attribution output as exact truth rather than a decision aid; see measuring marketing impact honestly.
- Building many dashboards that nobody uses.
How GeekMidst can help
Our marketing analytics and reporting service helps you define measures, naming standards and dashboards. Our data engineering services can prepare source data, and our Marketing Cloud consulting team can help you decide how analytics fits with the rest of your marketing stack.
Questions we hear
Is Datorama still a product?
What does Intelligence+ add?
Is Marketing Intelligence the same as Tableau?
Which data sources are supported?
Related reading
Connected campaigns and attribution
Attribution basics in Account Engagement
→Using data views for reporting
Engagement reporting in Marketing Cloud
→Marketing Cloud overview
The full Marketing Cloud family
→Need clearer marketing reporting?
Tell us where your data lives today, and we will help you plan a reporting approach.
