A cross-channel performance marketing operation focused on scaling e-commerce sales efficiently across Meta, Snapchat and TikTok, while using GA4 as an independent measurement layer to understand on-site behaviour and the ecommerce funnel.
The engagement connected platform execution with independent ecommerce analysis. Media decisions were evaluated at campaign, ad-set, ad-group and creative level while GA4 was used to understand the customer journey after the click.
The objective was not simply to increase media spend. The challenge was to scale sales across three paid acquisition platforms while maintaining acquisition efficiency and identifying where additional growth could come from.
The account included a mix of prospecting, retargeting, catalog, creative-testing and scaling campaigns, with meaningful performance differences between campaigns, ad sets and individual ads.
The operating model therefore focused on identifying what deserved additional budget, what needed further testing, and what should be reduced or stopped. GA4 was used alongside platform reporting to provide an independent view of what happened after users reached the store.
I evaluated performance at campaign, ad-set and ad level rather than relying on blended account ROAS.
I reallocated budget toward structures demonstrating stronger purchase efficiency and scaling potential.
I used GA4 as an independent measurement layer to compare platform-reported attribution with on-site behaviour.
Figures are shown in each platform’s native billing currency. Meta and Snapchat are reported in USD; TikTok is reported in SAR.
Performance varied significantly across testing, prospecting, catalog and scaling campaigns. This created opportunities to progressively redirect budget toward stronger structures instead of scaling the account uniformly.
Campaign and ad-set performance showed substantial variation, with several structures materially outperforming the account average. This provided clear opportunities for budget reallocation and controlled scaling.
TikTok provided substantial purchase volume while individual campaigns and ad groups showed very different efficiency levels. Continuous testing and budget redistribution were therefore central to the scaling process.
Campaign, ad-set and ad-level evidence separated blended account performance from the structures that deserved more budget.
Account, campaign, ad-set and ad evidence supported controlled scaling and pruning decisions.
Purchase volume was evaluated alongside differences in CPA and ROAS between campaigns, ad groups and ads.
Platform reporting was not used as the only source of truth. GA4 was used as an independent measurement layer to understand traffic quality, purchases, revenue and customer behaviour after users reached the store.
Platform-native results and GA4 session-source attribution use different measurement methodologies and should not be expected to match directly. Platform-attributed purchases and revenue are not added to GA4 totals.
Funnel steps are based on active users, while the 11,260 headline figure represents purchase events in GA4. These metrics measure different things and should not be compared one-to-one.
90.59% of users who viewed a product did not progress to Add to Cart. This highlighted an additional CRO opportunity around product-page experience, offer communication, merchandising and conversion optimisation without overstating causality.
Item Revenue and Purchase Revenue are reported from different GA4 ecommerce scopes and should not be interpreted as interchangeable totals. Product and collection names remain intentionally anonymised.
Landing-page sessions, purchases, purchase revenue and engagement rate helped identify entry points combining traffic volume with commercial quality.
Scaling decisions should be made at campaign, ad-set and ad level rather than from blended account ROAS alone.
TikTok contributed substantial volume, while GA4 showed different post-click efficiency patterns between channels.
Platform attribution and GA4 should be interpreted together, not treated as interchangeable datasets.
The ecommerce funnel identified a major CRO opportunity between product view and add-to-cart.
Product-level revenue concentration provided additional signals for merchandising and paid-media prioritisation.
Platform-native attribution and GA4 use different methodologies. They are complementary evidence and are never combined into a single total.
Client, product, URL and account identities are anonymised. Generic campaign structures are retained where they help demonstrate the operating methodology, while all brand-identifying information remains obscured.