Stop comparing features. Compare behaviour.
Two platforms can both list "AI budget optimisation," "predictive audiences," and "automated reporting." One sends you a suggestion; the other moves the money itself; a third needs you to hand-build every rule. The feature names are identical. What they do in production is not. Evaluate on behaviour, not vocabulary, and the field sorts itself quickly.
Score each criterion below from 1 to 5 for every platform on your shortlist. The ones that matter most for you carry more weight, but a platform that scores low on governance or reversibility should worry you no matter how it does elsewhere.
The nine criteria
1. Execution depth
Does it recommend, run rules you wrote, act autonomously, or act inside limits you set? This is the first question because it frames every other one. A recommend-only tool needs little governance and gives little leverage; an autonomous one needs a great deal of both. Read the full breakdown in the execution-depth spectrum, then place each platform on it honestly.
2. Governance and guardrails
If a tool can act, the only safe version is one where you set the limits: spend caps, brand exclusions, change thresholds, and approval gates that must pass before anything runs. Ask to see where those limits are configured and who on a non-technical team can change them. No guardrails is not "more powerful." It is unbounded risk. See guardrail-driven automation for what a real control layer includes.
3. Data access model
How does it get your data, and how much access does it demand? Read-only or view-only access (it can see but never change account settings) is the responsible default. Be wary of anything asking for admin rights it does not need. Ask what it can touch, and whether access is revocable.
4. Where it acts — integrations
An action is only real if it reaches your account. Check how the platform connects to Google Ads, Meta, GA4, and your CRM — through documented APIs and protocols, not screen-scraping or copy-paste. Thin integrations are where "automation" quietly becomes "a list of things for you to do manually."
5. Proof of impact and auditability
For every change a platform makes, can it show you the trigger, the action, and the measured result, in a log you can export? This is the difference between a system you can defend to a CFO and one you have to take on faith. Our Trigger / Action / Impact framework is one model for what that record should contain.
6. Reversibility and blast radius
When something goes wrong — and it will — how much damage can one action do, and how fast can you undo it? Ask for the largest change the system can make without human approval, and whether it captures a before-state so any single change can be rolled back. A tool that cannot reverse itself is a tool you cannot run unattended.
7. Pricing model
Seat-based, usage-credit, spend-percentage, and flat-fee models behave very differently as you scale. Credit-based pricing in particular can produce surprise bills the month a campaign goes well. Map the real cost at your expected volume before you sign; our pricing guide breaks down the trade-offs.
8. Ownership
When the engagement ends, what do you keep? With some platforms you rent access to a black box and walk away with nothing. The better answer is that you own the workflows, the rules, and the configuration, and can run them with or without the vendor. Ask the uncomfortable question: if we leave, what do we lose?
9. Human-in-the-loop
Where does a person stay in control? The strongest platforms do not remove humans; they move them up a level — from doing the work to setting the bounds and approving the exceptions. Look for explicit approval gates above a threshold you choose, and clear ways to override or pause anything.
How to weight the scorecard
Not every criterion matters equally for every team. If you are buying a recommend-only analytics layer, governance and reversibility matter less. The moment a tool can act on your accounts, criteria 2, 5, 6, and 9 — governance, auditability, reversibility, and human oversight — become non-negotiable, and a low score on any of them should knock a platform off the list regardless of its features.
One more weighting rule that buyers miss: the best platform in the world will underperform on a weak foundation. If your conversion tracking is broken or your team cannot self-serve data, no amount of AI fixes that — it just automates on bad inputs. Score your own readiness before you score the vendors.
Is your foundation ready for AI that acts?
The free Readiness Score checks the inputs every platform depends on — data access, tracking, structure, governance, and tooling — and tells you the one gap to close first. Four minutes, no login.
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