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§ Agent · Twitter Ads

The Twitter Ads data agent that acts the way you would.

It keeps an eye on your Twitter Ads spend alongside the revenue it drives, on a schedule you set or whenever fresh data lands. When a campaign drifts, it tells you, or handles it the way you'd want.

D
DefiniteAPP9:14 AM · #growth-alerts
⚠️ Spring Launch line item burned 41% of budget at 3x your target CPA

Two line items in Spring Launch spent $6,800 in the last 24 hours but drove only 9 signups, well off your ~$74 blended CPA, while their CTR held flat.

Review & approve Dismiss
Twitter Ads Line Item + Campaign + Performance Metrics (Analytics) · joined to Stripe conversions · audit log

How an agent works

An agent watches one thing and acts on it. Not a workflow, just a standing watch that usually does nothing and acts the moment it should.

◄ repeats on the schedule you set ►

You stay in control

An agent does what you'd do, and only what you've authorized.

The same trusted numbers

It acts on the same governed metrics as your dashboards, and every action is logged and traceable.

You approve anything that writes

It alerts and recommends on its own; anything that changes data is yours to approve.

Try it on a test channel first

Point a new agent at a throwaway channel and watch its judgment before it touches anything real.

No false alarms

It remembers what it already flagged and waits before acting again, so it won't alert you about the same thing twice.

What you can put an agent on

Blended CACACROSS YOUR SOURCES

Tie your Twitter Ads spend to the revenue it actually drove

It joins your Twitter Ads spend and conversions to the closed revenue in your warehouse, so you see blended CAC and payback by campaign, not the in-platform conversions the Ads dashboard reports to itself. You find out a channel stopped paying back before the next budget review, not after.

CampaignLine ItemPerformance Metrics (Analytics)Conversion Tracking Tag
Spend

Catch a line item burning budget off-target

When a line item's CPA breaks its trend or it's pacing to blow its budget, it tells you which campaign and creative are responsible and how much you've already spent off-target. It lines up the pause or the cap for you to approve, before the day's budget is gone.

Line ItemCampaignPerformance Metrics (Analytics)Funding Instrument
Creative

Flag creative fatigue before it drags the campaign down

When a promoted tweet's engagement and CTR slide while frequency climbs, it surfaces which creative is fatiguing and what it's costing you in wasted spend. You get the rotation flagged while there's still budget left to move.

Creative AssetPromoted ContentTweetPerformance Metrics (Analytics)
Custom

Run any Python it needs to get the job done

Beyond alerts and write-backs, an agent can run arbitrary Python, so it can do whatever the task actually requires: call an API, kick off a job, reshape the data, or wire into your own tooling. The action space is yours to define.

Why not just build it yourself?

You could rig one of these with a cron job and a Slack webhook in an afternoon. The watching is the easy part. Here's what you'd own forever, and don't, here:

  • The cross-source join: not one tool's data, but it reconciled against the rest of your stack
  • A trusted, consistent metric: the same number your dashboards use
  • The investigation into why, when something fires
  • A full audit trail of everything it did
  • The upkeep, when the schema drifts or the script breaks at 2am

The data it works from

Every Twitter Ads object, modeled and query-ready the moment you connect.

Ads Account
marketingrevenue_finance
Campaign
marketingrevenue_finance
Line Item
marketingrevenue_finance
Targeting
marketing
Creative Asset
marketingengagement
Promoted Content
marketingengagement
Tweet
marketingengagement
Custom Audience
marketingcustomer
Conversion Tracking Tag
marketingrevenue_finance
Performance Metrics (Analytics)
marketingrevenue_financeengagement
Funding Instrument
marketingrevenue_finance

It runs on your real Twitter Ads account (paused line items, half-tagged conversions, naming drift and all), not a tidy demo.

Where it acts

Slack

A message in the channel you choose, with the context and a button to act on it.

Email

A summary in the inbox of the people who need to see it.

Webhook

A payload to your own systems, to wire the agent into whatever you already run.

Warehouse write-back

A flag written back to your warehouse for everything downstream to pick up.

Hand off to Fi

Kick the question to Fi to investigate the why and propose the fix.

MCP

Expose it to your own agents and tools over MCP, and drive it from your stack.

Run it in your own VPC or fully self-hosted. Everything it does is pure SQL and Python you can inspect.

Build your agents with Fi

Fi is your AI analyst. It helps you build and customize everything in Definite, including the agents that watch and act.

Fi

Your AI analyst. Ask questions in plain English, and let it help you build and customize everything in Definite, including your agents.

Meet Fi →

Agents

The watchers and actors. Once you've built one, it runs on its own, keeping an eye on what matters and acting the way you would.

Autonomous agents →

Get started

  1. 1Connect Twitter Ads, and the sources it needs to reconcile against. Synced and modeled in an afternoon.
  2. 2See the numbers tie out to what you already trust.
  3. 3Put an agent on one thing you can't afford to miss. Fi helps you build it.
§ FAQ

Common questions

You set the schedule, and it also re-checks whenever fresh Twitter Ads data lands. Each agent watches the one thing you point it at, nothing else.
It alerts and recommends on its own. Anything that writes, whether to a tool, your warehouse, or a customer, is yours to approve. You can also point a new agent at a test channel first and watch its judgment before it touches anything real.
When something fires, it can hand off to Fi to investigate, drilling into the data it has across your connected sources to find what's behind the move, and showing its work.
Those watch Twitter in isolation against in-platform conversions, and act only on rules you hard-code. This watches continuously, reasons across your spend plus the revenue in your warehouse, and hands off to Fi to investigate why, so you act on real payback, not the platform's own scorecard.

Your answer engine
is one afternoon away.

Book a 30-minute call and watch us build your first dashboard live, with your own data.