Marketing & Agency
A Meta Ads agency does a lot more than launch campaigns and check Ads Manager once a week. The real work is an account audit, an account structure built around your catalogue, a running creative testing process, audience strategy, budget pacing, conversion tracking that's actually correct, and reporting that ties back to real revenue — not just platform ROAS. Here's what each of those actually involves.
Before touching a live account, a competent agency reviews what's already there — campaign structure, historical spend and performance, existing creative, audience overlap, and whether tracking is actually reporting correctly. This matters most when taking over an account someone else built, where the audit is often what surfaces the real problem: sometimes it's weak creative, but just as often it's broken tracking making a healthy account look worse than it is, or the reverse.
Campaign and ad set structure should reflect your catalogue, margins and customer journey — not a generic template copied across every client. This includes decisions like how prospecting and retargeting are split, whether campaigns are organized by product category or by objective, and how much budget consolidation makes sense for Meta's algorithm to have enough data to optimize well, without creating so few campaigns that testing becomes hard to isolate.
Meta ad performance degrades as creative gets stale — the same ad shown to the same audience for weeks eventually stops converting as well, regardless of how good it once was. A running testing queue — new angles, formats and hooks entering rotation on a regular cadence, with clear criteria for what gets scaled and what gets cut — is core to the job, not an optional extra. Whether the agency produces that creative itself or directs a client's creator relationship, this strategic direction is the agency's responsibility either way.
Meta's targeting has shifted heavily toward algorithmic, broad, and Advantage+ audiences over the last few years, away from the granular interest-stacking that used to define account management. Part of the job now is knowing when broader, signal-driven targeting genuinely outperforms manual audience building, and when specific exclusions or retargeting windows still need manual control — and testing that, rather than assuming either approach automatically works better.
Moving spend between campaigns and audiences based on what's actually converting, on a set review schedule rather than reactive day-to-day tinkering that doesn't give the algorithm time to learn. This also covers pacing around promotional periods, monitoring for delivery issues or learning-phase resets caused by too-frequent budget changes, and deciding when scaling spend is actually supported by the data versus when it would just be spending into diminishing returns.
An ad can do everything right and still convert poorly if it sends traffic to a product or collection page that doesn't match the ad's promise, loads slowly, or has a confusing checkout path. Agencies typically flag these issues and suggest specific changes — sometimes even build a dedicated landing page for a campaign — but actually implementing site changes is usually a client or developer responsibility unless it's explicitly part of the scope.
This is the part that separates agencies that understand measurement from agencies that only understand campaign structure. It covers the Meta Conversions API running alongside the browser Pixel — see Pixel vs CAPI for how the two work together — with correct event deduplication so purchases aren't double-counted, and Event Match Quality monitored as a signal of how well events are matching to real Meta users, not treated as a vanity score to maximize for its own sake.
An agency that can't explain what CAPI does, why deduplication matters, or what EMQ measures is optimizing a campaign structure on top of numbers it doesn't actually understand — which is a real risk regardless of how good the creative testing process looks on paper.
Regular reporting that explains what changed and why — not just a screenshot of Ads Manager's dashboard. Good reporting checks Meta's reported numbers against actual Shopify orders, since Meta's attribution window and reporting logic routinely differ from what actually shipped. If a report is only ever Meta's own numbers restated, that's worth questioning.
A high platform-reported ROAS number can still coexist with a business that isn't making money on its ad spend once real margins, discounting, and returns are accounted for. Agencies that only chase the ROAS number in Ads Manager can end up optimizing toward a metric that doesn't reflect actual profitability. The more useful conversation is about what spend level and channel mix actually grows the business profitably — which requires looking past the platform's own reported number, not just requesting a higher one.
Worth naming plainly, since overpromising here is common across the industry.
We manage Meta and Google Ads with the same focus on measurement, tracking and actual business performance described in this guide.