Budget Recommendations

Ad budget allocation, decided on what each channel returned

Every channel returns something different, and the monthly decision usually goes to the loudest number rather than the best one.

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The problem today

  • Most marketing budget allocation arguments are really arguments about measurement.
  • Media mix modeling that skips that step produces a confident recommendation on numbers nobody trusts.

How it works

  1. Spend and results are pulled per channel
  2. Return is computed the same way for each
  3. Scenarios are modeled
  4. A recommendation is written
  5. You decide

What you get

  • A budget decision with a number behind it
  • Channels compared on the same basis
  • The recommendation in a form a client will accept
  • The same figures feeding your client report

What it connects to: Google Ads, Microsoft Ads, Meta, Windsor.ai, HubSpot or your customer system, and Google Sheets.

Is this the right fit for your firm?

How far back does it look?

Far enough for the pattern to mean something, and it says when the history is thin.

Does it move money?

No. Ppc budget management stays a human decision.

Does this feed the client report?

Yes, the same analysis drives the recommendations section.

Start with the task your team repeats every week

Bring it to a free one-hour Claude 101, on Claude, the AI assistant made by Anthropic, and see what can be set up to take it off their desk.

Book a free Claude 101
Book a free Claude 101