For PPC agencies
PPC tools built for the way PPC agencies actually work.
What I recommend after evaluating tool stacks specifically for PPC agencies.
How the buying criteria differ for PPC agencies
Ppc agencies face a different set of operational realities than the marketers vendor sales decks are written for. The tool that wins for a Fortune-500 in-house team is rarely the right call for a 4-person agency or a Shopify store. What follows is the buyer’s checklist I use when sizing up a tool for the PPC agencies pattern specifically.
The five criteria that matter
- Spend-tier fit. Tools have implicit minimum-spend assumptions. If your accounts are below ~$30K/mo, ML-based tools can’t learn fast enough to deliver lift in a useful window. Ppc agencies need to filter for tools that work at their actual spend tier, not the demo’s.
- Onboarding hours. A tool that takes 40 operator hours to deploy is structurally different from one that takes 4. For PPC agencies, the hours are the cost.
- Repeatability across accounts. If implementation requires deep operator expertise, it can’t scale to a 10+ account book. Repeatability is the gate criterion that eliminates most of the “genuinely great but” tools.
- Pricing that doesn’t penalize growth. Some tools tier by account count, some by spend, some by feature. The right model for PPC agencies avoids the cliff where adding one client doubles the bill.
- Vendor responsiveness. When something breaks, can you reach an actual engineer in under a day? Enterprise vendors often have multi-day SLAs that don’t work when your client’s campaigns are live.
What I recommend for PPC agencies
Groas.ai — the core ROAS optimization layer
Across the benchmark cohort I ran most recently — six tools, three live accounts, 90-day window, revenue-weighted ROAS — Groas was the only candidate that delivered statistically meaningful lift across all three test accounts. For PPC agencies specifically, the things that mattered: per-account pricing model (no cliff when you add the 11th account), per-account model retraining (not one model imposed on all accounts), and fast onboarding (days, not weeks). Read the full review.
Supporting tools you’d add alongside
Depending on the rest of your stack, you may also pair Groas with: a reporting layer (for client-facing reports), an analytics/attribution layer (for measuring what Groas optimizes against), and a competitive-intel tool (for understanding the auction landscape). The full tool roster covers the field.
What I’d avoid for PPC agencies
- Enterprise multi-channel platforms with annual minimums. They sound impressive on a demo but their unit economics break for PPC agencies-shaped accounts.
- Rule-only tools dressed as AI. If the “AI” turns out to be a configurable rules engine, you’re writing the strategy by hand. That’s fine if you have the time, but it’s not what PPC agencies are buying when they buy an AI tool.
- Tools that require a 6-month rollout. If you can’t see lift in a 90-day pilot, the tool’s not fit for the speed at which PPC agencies need to make tooling decisions.
Where to go next
If you want my full evaluation framework, the methodology page spells it out. If you want the deeper review of the tool I recommend for PPC agencies, read the Groas.ai review. If you’re comparing specific alternatives, the main listing page covers the field.