A media planner agent that
sees all channels at once
Splitting a budget across Meta, Google and TikTok by gut feeling is how most plans still get made, because building a real cross-channel model by hand takes longer than the planning cycle allows. We build an agent that reads your actual attribution data and proposes the split, with a person approving the plan before any spend moves.
The role today
A quarterly media plan usually gets built the same way: last quarter’s split, adjusted by whoever’s gut feeling was loudest in the meeting, with a vague sense that one channel is “probably” outperforming another. Building a real cross-channel attribution model by hand takes longer than most teams have between planning cycles, so the plan ships on intuition and gets revisited only when a channel’s cost clearly spikes. The channels that quietly underperform in a way that does not show up as an obvious red flag keep getting funded at the same level, quarter after quarter. The cost of staying with gut-feel splits is rarely visible as a single bad decision; it shows up as a slow, compounding underperformance across several quarters, a channel that should get 10% more budget stays flat, one that should shrink keeps its allocation out of habit, and nobody notices because no single quarter looks obviously wrong on its own.
What the agent takes over
The agent reads your actual spend and sales data across channels and builds an attribution read that accounts for the fact that a customer rarely converts on the first channel they touch. From that, it proposes a budget split with its reasoning shown, this channel is pulling more of its weight than its surface cost suggests, this one less, and models what a given shift would likely do before you commit to it, so a 20% move is a modeled scenario rather than a bet. Each month the plan refreshes against new data, and a plain-language summary explains the recommendation for whoever in the room does not read attribution models for a living.
The model’s memory of past scenarios, what a 15% shift from search to social actually did last time it was tried, means a new proposal is grounded in your own account’s history rather than a generic assumption about how channels typically behave. That history also surfaces when a channel’s past performance may no longer be a reliable guide, a platform changed its algorithm, a competitor entered the space, which a founder relying on last quarter’s intuition alone would have no way to notice on their own.
What stays with humans
Deciding the overall marketing budget, approving the proposed split before spend moves, and making the call on a new channel to test stay with your team. The agent builds the model and proposes the plan; people decide what the business can afford and is willing to try.
Guards
No plan changes live spend without approval; the agent proposes, a person decides. Every recommendation shows the data and reasoning behind it so it can be checked rather than taken on faith, and the model explicitly flags a channel with too little data for a confident read instead of assigning it a number anyway. A kill switch reverts to the previous plan in one message. A new attribution model is run in a dry run against last quarter’s actual results, checking whether it would have recommended something sensible in hindsight, before it drives a live budget decision. If planning moves in-house, we hand over the model, its assumptions and the full scenario history, documented for your own analyst.
Price and timeline
| Option | Price | What it covers | Timeline |
|---|---|---|---|
| Agency runs it | from $3,200 | Built, launched and supervised by us, plus a monthly support plan | 3 to 5 weeks |
| Full control, handover-ready | from $5,450 | Same agent, deployed on your infrastructure with full documentation to run it yourselves | 3 to 5 weeks plus 1 to 2 weeks for handover |
Running cost is usually $20 to $150 a month in model usage, depending on volume.
Related
See the full package breakdown on the AI agents service page and performance marketing, analytics. Pair this with ads optimizer agent, creative testing agent, analytics narrator agent inside the same Marketing & Content group, or with the narrower marketing mix attribution, ad budget allocation automation. For real numbers, see ai media buyer meta ads, media buying latam 30k installs.
Ready to put this to work on your team? Get in touch and we will map it against your current process on the first call.
FAQ
How much does a media planner agent cost?
From $3,200 for a cross-channel model covering up to three ad platforms plus your sales data, live in 3 to 5 weeks. A monthly refresh and ongoing scenario modeling usually runs from $1,200/month.
How long does it take to go live?
Three to five weeks: the first two to three build the attribution model against your actual historical spend and sales, the rest validates it against a real budget decision before it drives anything live.
Which channels and tools does it work with?
Meta, Google and TikTok Ads are standard; other channels with exportable spend data (offline, affiliate, email) can be folded in to see the fuller picture rather than treating paid social as the whole budget.
What if it gets something wrong?
A proposed split never executes on its own; it goes to a person as a plan with its reasoning shown, and the model flags when a channel does not have enough data yet for a confident attribution read rather than guessing at its contribution.
What about our data and security?
Your ad spend and sales data stay on your own accounts and warehouse. The attribution model is built for your business specifically, not benchmarked against other clients' numbers.