Signal Rebuild

A UAE fashion e-commerce retailer selling across the Emirates was spending heavily on Meta and TikTok, yet the platforms, GA4 and the Shopify backend all reported different sales numbers. ROAS had drifted down for three quarters, and nobody trusted the dashboards enough to move budget with confidence. This is an example engagement that illustrates how we work; the client is anonymised and the figures are illustrative.

Rebuild the measurement foundation so ad platforms optimise on real orders, then restructure TikTok and Meta around creative testing in time for White Friday, the biggest sales window of the year. The target was a blended ROAS above 3x at a stable or lower cost per acquisition, measured against backend revenue rather than platform-reported numbers.

Tracking came first. Only once the signal was clean did we touch budgets or creative.

• Server-side tracking: server-side Google Tag Manager, Meta Conversions API and TikTok Events API with deduplication, plus Google Consent Mode v2 and PDPL-aligned consent records.
• Backend reconciliation: a daily check comparing platform-reported purchases with Shopify orders, so the gap stayed visible.
• Account restructure: fewer, broader campaigns on Meta and TikTok, giving the algorithms enough conversion volume to learn.
• Creative matrix: weekly tests of hooks, UGC-style try-ons and Arabic and English variants, with fatigued ads retired on a fixed rule.
• Seasonal plan: a White Friday budget ramp that protected the learning phase instead of resetting it.

In a scenario like this, clean signal and disciplined testing compound quickly. Over twelve weeks, blended ROAS in this illustration rose from 2.1x to 3.4x, cost per acquisition fell 32% and Meta event match quality climbed from 5.8 to 9.1 out of 10. More importantly, the team could finally see which campaigns made money, so budget moved to winners within days rather than at month end.