How to get your Marketo data ready for agentic AI

Marketo holds some of your most valuable business data — every lead's demographic profile and score, every email send and click, every campaign and program outcome, and the full history of how each prospect moved through your funnel. Getting it ready for agentic AI means giving AI agents access to a centralized, cleansed, and governed version of that data, so they can answer questions like "which campaigns are actually driving sales-ready leads this quarter?" in seconds rather than days. Fivetran + dbt Labs delivers the complete data foundation agents need — Fivetran moves Marketo data reliably into your warehouse or data lake, and dbt transforms it into trusted, AI-ready tables.

Why Marketo data is critical for agentic AI

Marketo tracks the full story of demand generation: who your leads are, how they engage with email and campaigns, and which programs move them toward a sale. But that story is scattered across leads, activities, campaigns, programs, and email performance data that no single person can piece together fast. Marketing ops teams spend hours each week pulling campaign reports, reconciling lead scores, and manually stitching together which programs actually influenced pipeline. By the time a report reaches a CMO, the data behind it is already days old, and the next campaign decision gets made on gut feel instead of evidence.

The volume compounds the problem. A single active Marketo instance generates activity records — email opens, clicks, form fills, program status changes — far faster than any team can review manually. Without a centralized, current view of this data, agentic AI has nothing reliable to work from. Getting Marketo data ready means building infrastructure built for agents, not just analytics — so questions get answered the moment they're asked, not the next time someone builds a dashboard.

What agentic AI can do with Marketo data

Once Marketo data is properly prepared, an AI agent turns raw lead and campaign activity into instant answers. A demand gen manager can ask which lead sources produced the highest-scoring leads over the last 90 days and get a ranked answer immediately, instead of waiting on an analyst to pull it together. A marketing ops lead can ask an agent to flag every campaign with declining email engagement before the quarterly review, rather than manually comparing open and click rates across dozens of sends.

An agent can also trace a lead's full journey — every program it joined, every email it opened, every status change — and summarize which touchpoints correlated with becoming sales-ready, giving a lifecycle marketing leader a clear view of what's actually converting. Instead of waiting for a monthly program performance report, a CMO can ask an agent directly which programs delivered the lowest cost per qualified lead and get a straight answer, drawn from real engagement history rather than a static spreadsheet.

These capabilities all come from data the Marketo connector already captures — lead records, activity history, campaigns, programs, and email performance — organized so an agent can reason across all of it at once instead of one report at a time.

How Fivetran gets your Marketo data ready for agentic AI

Marketo data in its raw form is not something an AI agent can use directly. Lead and activity records live across dozens of interrelated tables, activity volume grows constantly, and Marketo's own data retention limits mean older activity history can disappear before anyone analyzes it. Without a system pulling this data out consistently, it stays fragmented, stale, and impossible to govern at scale.

Fivetran moves your Marketo data reliably into a warehouse or data lake, keeping it fresh, complete, and ready for agents to query. It fetches your most recent leads and activity first, so current engagement is always up to date, while continuing to backfill historical activity in the background. It applies incremental updates as records change, captures deletions and merged leads accurately, and adapts automatically to custom campaigns, programs, and event tables specific to your Marketo instance. For teams using the Fivetran Managed Data Lake Service, this same data becomes part of a broader, centralized data lake alongside other sources.

Fivetran + dbt Labs then takes this a step further: dbt transforms and governs raw Marketo data into clean, trusted, AI-ready tables — centralized, cleansed, and governed for reliable agent use. Prebuilt quickstart dbt models give teams a fast starting point for lead, campaign, and email performance analysis, and dbt's full modeling, testing, and documentation capabilities extend far beyond those quickstarts to keep the data governed as your marketing stack grows.

What your Marketo data unlocks for your team

With Marketo data in a central warehouse, AI agents unlock capabilities your team couldn't access before.

• Instant campaign performance answers — ask which campaigns and programs are driving the best results without waiting for a report.
• Full lead journey visibility — trace every lead's activity history and program membership to see what's actually influencing conversion.
• Faster lifecycle decisions — spot declining engagement or stalled leads before they fall out of the funnel.
• Cross-source reasoning — combine Marketo data with sales and revenue data on an open, interoperable foundation, rather than working from Marketo in isolation.
• AI-ready reporting — replace manual, recurring reporting work with agents that answer questions on demand.

FAQ

What does it mean for Marketo data to be AI agent-ready?

It means your lead, activity, campaign, and program data is centralized in a warehouse or data lake, cleansed of duplication and fragmentation, and governed so an AI agent can query your full marketing history accurately and combine it with other business data on demand.

What can my team actually do with AI agents and Marketo data?

Teams can ask an agent direct questions about campaign performance, lead engagement, and program ROI and get immediate answers, instead of waiting on manual reporting cycles or building new dashboards for every new question.

Is Marketo data ready for AI agents out of the box?

No. Raw Marketo data needs to be centralized, modeled, and governed before an agent can query it reliably and act on it with confidence across campaigns, programs, and email activity.

Do we need a data engineering team to set this up?

No. Fivetran handles the data movement automatically, and prebuilt dbt quickstart models give teams analysis-ready tables without writing transformation code from scratch.

How does Fivetran get Marketo data ready for AI agents?

Fivetran moves your Marketo data reliably into your warehouse or data lake, keeping leads, activities, and campaign data fresh and complete. dbt Labs then transforms and governs that raw data using its full modeling and testing capabilities, and prebuilt quickstart models give teams a fast path to AI-ready, analysis-ready tables.

Start building your data foundation for agentic AI

Fivetran + dbt Labs give your team the centralized, governed Marketo data agents need to answer real marketing questions instantly, not days later.

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