Use case · cross-platform ROAS

Compare ROAS across Google, Meta, and beyond — through your agent

Most SMB operators have spend across two or three platforms. Cross-platform ROAS comparison usually means a Looker dashboard and a quarterly review. NotFair lets your AI agent pull live data from each connected platform and synthesize on demand.

Connect Google Ads (live) and Meta Ads (beta) through NotFair
Single-agent view of cost, conversions, and ROAS per channel
Ask the agent to recommend a reallocation

Why cross-platform comparison is so hard manually

Each platform exposes different attribution windows, different conversion definitions, and different reporting cadences. Synthesizing them by hand takes hours and the answer is stale by the time it's ready.

The NotFair workflow

Ask the agent: “Compare last 30 days ROAS across my Google Ads and Meta Ads accounts. Surface the platform with the worst marginal ROAS and tell me what's dragging it down.” The agent pulls live data from each connected platform and synthesizes.

What to do with the answer

Reallocation is the obvious lever, but cheap. The deeper move is identifying whether the underperforming platform has a fixable structural issue (broken tracking, weak creative rotation, bad geo targeting) before reallocating budget.

Connect Google Ads in two minutes

Authorize once at notfair.co. Then open your AI client and ask real questions about your account.

FAQ

Short answers to the most common questions.

Does NotFair support Meta Ads?

Yes — Meta Ads is in beta. See /meta-ads-mcp. The same approval-gated write model applies.

Is NotFair safe to use on a real Google Ads account?

Yes. NotFair separates read tools from write tools. Diagnostic queries run freely, but every write — bid change, negative keyword, ad copy, campaign state — is approval-gated and logged with full provenance so you can audit exactly what the agent did.

Does NotFair support more than Google Ads?

Meta Ads is in beta and GoHighLevel is shipping. Roadmap covers the rest of the SMB ad stack. The principle is the same on every platform: typed primitives, freshness metadata, approval-gated writes.