Marketing Cloud Intelligence · Migration Service
Salesforce Marketing Cloud Intelligence (MCI, formerly Datorama) has been a strong platform for marketing analytics — but for many organisations, the cost structure, row limits, and absence of any AI roadmap are making it harder to justify staying.
Decision Foundry has been working on this platform for over 13 years. We know what it can do, where it falls short, and what a well-architected migration looks like — regardless of where you're moving to.
The Reality
Four reasons we hear repeatedly when teams ask us about moving off MCI.
MCI charges by rows of data. At 20–40M rows you're paying ~$60K/year. At 100–300M rows, that climbs to $100K+.
Every drill-down to keyword, device, or country level costs more rows. Teams end up aggregating data they should be keeping granular.
MCI sits outside Salesforce's Lightning environment. No Agentforce access, no natural language querying, no roadmap to change this.
The platform has no active development behind it. Staying means betting on infrastructure with no forward investment.
What We Do
End-to-end migration coverage — from initial scope to AI layer.
We assess your setup, data sources, tech stack, and pain points to recommend the right migration path.
We evaluate all options and explain the trade-offs so you can commit to the right destination with confidence.
We manage the end-to-end build across data ingestion, transformation, harmonisation, and reporting — validated at every phase.
We build AI capabilities directly into the new stack — from Snowflake Cortex to Power BI Copilot to a broader agentic layer.
We stay engaged post-launch to refine the setup and surface opportunities to get more from the new platform.
Where You Could Move To
Two broad paths, each with different trade-offs. The right answer depends on your team, your data volumes, and how much flexibility you want post-migration.
Path A
Low-code, easier for marketing teams to manage. Best when your team wants MCI's bundled feel with fewer of its limits.
Path B · Recommended for high-volume setups
More flexible, easier to evolve over time. Each layer is independently swappable.
The key advantage: if you ever want to change your reporting layer, you switch one component — your data warehouse and all your data stays intact. With an all-in-one tool like MCI, everything moves when you move.
Still on MCI?
See the full migration breakdown — costs, timeline, AI capabilities, and what you gain on the other side.
The Process
Seven phases from first conversation to optional AI layer. Each phase has clear deliverables — no black boxes.
A low-commitment session to understand your current setup, migration goals, and outcomes needed from the new platform.
We map out every migration path available, explain what each one means for your team, and recommend the one that fits your situation best.
We map exactly what needs to be built, what transformations are required, and what the reporting architecture should look like.
We connect all your data sources using pre-built API connectors via Fivetran or Airbyte where possible.
We apply your business rules, standardise naming conventions, and unify data across sources before a single dashboard is built.
We build dashboards and reporting layers — from executive-level views to granular marketing performance breakdowns.
Optional final phase: we layer in AI querying, anomaly detection, or advanced analytics on top of the core reporting stack.
Who Benefits
Buyer
User
Influencer
Why Us
We've been working on this platform since the Datorama days. We know the ins and outs, the workarounds, and the limitations better than most. That means we scope migrations accurately and don't over-promise.
Whichever tool you're moving to, we've almost certainly worked on it. Power BI, Tableau, Looker Studio, NinjaCat, Adverity, Supermetrics, Snowflake, BigQuery. We have hands-on experience across the full landscape.
We are a certified Snowflake partner, which matters when Snowflake is often the recommended data warehouse destination for MCI migrations.
We work with media agencies, e-commerce teams, healthcare organisations, and financial services firms. We understand what your marketing and analytics teams are actually trying to do with the data.
We recommend what's right for your situation, not what's easiest for us to implement.
Ready to start?
We'll assess your current MCI setup, map the options, and give you a clear picture of what moving looks like — timeline, architecture, and cost.
Book a Free MCI Migration AssessmentCommon Questions
Yes — it's the term most used in the industry when moving from one analytics platform to another, and it's what clients typically call it. Some teams use "re-platforming" or "modernisation," but the work is the same: getting your data and reporting off MCI and onto a new stack with no loss of historical fidelity.
No. The discovery phase is specifically designed to help you figure that out. We assess your needs first, then recommend a destination. See Alternatives to MCI for the menu of options we evaluate against.
In some cases yes, but we assess this during discovery. Often a clean migration is more cost-effective than a hybrid setup — keeping MCI alive for a subset of work means you keep paying its row-based fees and supporting two stacks. The deep-dive technical discovery makes the call clear.
This is exactly the scenario where a bespoke modular stack (Snowflake / Fivetran / dbt / Tableau or Power BI) typically makes more sense than a like-for-like tool. Row-based pricing breaks down at this scale. We scope the right architecture for high-volume setups during the deep-dive discovery — and we have Snowflake partnership credentials for the warehouse layer.
No, preserving historical data is a core part of how we approach every migration. We plan for this explicitly in the deep-dive discovery phase — historical extraction strategy, transformation parity, and validation against MCI's existing reports before cutover.
It depends on the complexity of your current setup and your destination. A straightforward migration can be completed in 8–12 weeks. More complex, multi-source setups typically take 16–24 weeks. The deep-dive discovery gives you a calendar-week plan before you commit to the build phase.
MCI to Tableau Migration is the destination-specific service for teams who've already decided on Tableau. This page is for teams who haven't decided yet, or know they want a different destination — Power BI, Looker Studio, a bespoke Snowflake-based stack, NinjaCat, Adverity, or something else. The discovery phase here is what helps you pick the right destination.
Two reasons: (1) 13+ years on MCI / Datorama means we scope migrations accurately and don't over-promise. (2) Cross-platform expertise across every destination tool — Tableau, Power BI, Looker Studio, NinjaCat, Adverity, Supermetrics, Snowflake, BigQuery — so the recommendation isn't biased toward what we know better. We're vendor-neutral on tool selection.