How to get your Amazon DSP data ready for agentic AI

Amazon DSP holds some of your most valuable business data — programmatic ad campaigns, audience targeting, impressions and spend across inventory types, product-level ad performance, and the geo and device context behind every placement. 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 audiences delivered the lowest cost per conversion across our Amazon DSP campaigns last quarter" in seconds rather than days. Fivetran + dbt Labs delivers the complete data foundation agents need — Fivetran moves Amazon DSP data reliably into your warehouse or data lake, and dbt transforms it into trusted, AI-ready tables.

Why Amazon DSP data is critical for agentic AI

Programmatic campaigns generate performance signals continuously — across audiences, ad formats, inventory sources, geographies, and devices. A media buyer trying to understand which combination of factors actually drove results today pulls reports from the Amazon DSP console, exports spreadsheets, and manually stitches campaign data to product and sales data elsewhere. That process takes hours, and by the time it's done, budgets have already moved on to the next flight.

This is exactly the gap agentic AI closes, but only if the underlying data is centralized and ready to query. Without it, teams make decisions about where to shift spend, which audiences to pause, and which creative is underperforming on partial information, or they delay those decisions until the weekly report lands. That's infrastructure built for agents, not just analytics — and most teams don't have it yet. The data sits in Amazon DSP, disconnected from the sales and inventory data a team needs to evaluate it against.

What agentic AI can do with Amazon DSP data

Once Fivetran centralizes Amazon DSP data alongside the rest of a business's data, an AI agent changes what a media buyer or retail media manager can do in a single request.

A media buyer can ask which audience segments produced the strongest return across campaigns this month, and get a ranked answer instantly instead of building a pivot table. A retail media manager can ask how ad performance for a specific product line compares across geographies, and pull an answer that blends campaign, product, and geo data without touching three separate exports.

An agent can also flag campaigns where spend is concentrated in underperforming inventory types before the flight ends, giving the buyer a chance to reallocate budget mid-flight instead of learning about it in a postmortem. And because device and platform context syncs alongside campaign data, a growth or media team can ask how performance differs between connected TV, mobile, and desktop placements — a question that used to require manually joining data from separate reports.

None of this requires a data team to build a new report first. The agent answers directly, because the data foundation is already in place.

How Fivetran gets your Amazon DSP data ready for agentic AI

Amazon DSP data in its raw form is fragmented across campaigns, audiences, inventory, product, and geo, and it lives inside the DSP console, disconnected from the rest of a business's data. That fragmentation is exactly what makes it unreliable for agent workloads — an agent can't answer a cross-campaign question if half the data it needs sits in a separate system.

Fivetran solves this by moving Amazon DSP data reliably into a central warehouse or data lake, keeping it fresh, complete, centralized, cleansed, and governed so agents can query it with confidence. Fivetran syncs campaign, audience, geo, inventory, and product data on an ongoing basis, capturing new records as they appear so the data never goes stale between reporting cycles.

From there, dbt Labs — part of Fivetran — transforms that raw data into clean, trusted, AI-ready tables. dbt's modeling, testing, and documentation capabilities turn scattered campaign and audience records into governed data an agent can trust, without teams having to build transformations from scratch. For teams standardizing on an open, interoperable foundation across ad platforms, the Fivetran Managed Data Lake Service keeps Amazon DSP data in an open format alongside other advertising sources.

What your Amazon DSP data unlocks for your team

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

• Cross-campaign performance analysis — compare spend, reach, and outcomes across every active campaign without pulling separate reports.
• Audience-level optimization — identify which audience segments consistently convert best and which underperform.
• Product and geo intelligence — connect ad performance directly to specific products and regions for sharper targeting decisions.
• Inventory and device insight — see how performance shifts across inventory types and device contexts to guide budget allocation.
• Faster mid-flight decisions — catch underperforming spend early instead of waiting for end-of-campaign reporting.

FAQ

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

It means your campaign, audience, geo, inventory, and product data from Amazon DSP is centralized in a warehouse or data lake, modeled into clean tables, and governed so an AI agent can query it accurately. Without that step, the data stays locked in the DSP console and disconnected from the rest of your business data.

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

Media buyers and retail media managers can ask direct questions about campaign performance, audience effectiveness, and product-level results, and get answers immediately instead of waiting on manual reporting. Teams can also catch underperforming spend mid-flight rather than after a campaign ends.

Is Amazon DSP data ready for AI agents out of the box?

Not without preparation. Fivetran + dbt Labs must centralize, model, and govern Amazon DSP data before an agent can query it reliably.

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

No. Fivetran automates the data movement, and dbt's modeling framework gives teams a fast path to AI-ready tables without a dedicated engineering buildout.

How does Fivetran get Amazon DSP data ready for AI agents?

Fivetran moves Amazon DSP data reliably into your warehouse or data lake, keeping campaign, audience, and product data fresh and complete. dbt Labs then transforms and governs that raw data into clean, AI-ready tables using its full modeling and testing capabilities. One company delivers the entire stack, from movement to transformation.

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