Brandet Premium Stores: a fashion e-commerce brand that measures what it sells

Results at a glance

Every figure on this page is a rate, share, or relative comparison — Brandet’s media budget and order volumes stay confidential. Visitor-to-cart runs at 6.6% on a premium fashion catalog, and the clients-seeded campaign produces the majority of orders.

The challenge

Brandet Premium Stores, a premium fashion e-commerce brand in Lebanon, needed more than a store and some ads. It needed a growth system in which every visitor, cart, and order was measured, every campaign had a defined job, and every change to the site could be proven to help — or reverted.

A measurement foundation first

Before a dollar of media, we built the tracking layer: Meta Pixel with server-side Conversions API, so purchases are recorded even when browsers block scripts; Google tag and GA4 with detailed e-commerce events (view, add-to-cart, begin-checkout, purchase, with item and value parameters); Google Ads conversion tracking tied to the same events; and disciplined UTM tagging on every paid, social, email, and WhatsApp link. Audiences — viewers, carters, checkout-abandoners, purchasers — accumulate from day one, so retargeting and exclusion lists exist before the first campaign needs them.

A catalog that reaches everywhere

One product feed connected to Meta (powering Advantage+ catalog campaigns), Google Merchant Center (Shopping and Performance Max), and a WhatsApp catalog — the channel Lebanese shoppers use to browse and order. One inventory, one source of truth, wherever the purchase decision happens. Dynamic retargeting then shows a shopper the exact item she considered, on whichever platform she opens next.

Four campaigns, four jobs

• New-customer acquisition — engaged audiences and purchasers excluded, so the budget can only buy genuinely new people. The only way to know the true cost of a new customer.
• Advantage+ catalog — dynamic product retargeting from the feed, converting product interest into orders.
• Cart abandoners — shoppers who added to cart, with purchasers excluded; short windows, closing the checkouts that were left open.
• Clients-seeded — Brandet’s customer list used as the seed for Meta’s audience expansion, so the algorithm finds shoppers who look like proven buyers and re-engages the buyers themselves. The account’s most efficient campaign.

Each campaign is optimized for cost per purchase and monitored continuously; budget moves toward whichever job is producing purchases most efficiently that week. Branding and awareness campaigns run alongside to keep filling the top of the system. The payoff shows in the ratios: the clients-seeded campaign delivers purchases at 58% lower cost than new-customer acquisition, cart abandoners at 53% lower, catalog retargeting at 35% lower — and the blended cost per purchase lands 44% below cold prospecting.

Frequency as a budget signal

Retargeting budgets are usually set by feel. We set them by frequency. The cart-abandoners audience is finite — the people who added to cart and haven’t purchased — so ad frequency tells us exactly how saturated it is. When frequency rises, the budget is chasing the same shoppers and should hold or drop. When frequency decreases, the audience has expanded (more carts upstream), and the budget can grow effectively — reaching new abandoners rather than re-hitting old ones. Budget follows the audience, not the calendar.

Funnel analytics and friction removal

With people-level funnel tracking in place — unique visitors, shoppers who carted, checkouts started, orders placed — the leaks became visible: healthy engagement with the catalog (6.6% of visitors added to cart) but a steep loss between cart and checkout.

The response was a conversion program, not a redesign. Friction points in the cart-to-checkout path were identified and removed one at a time, and each change was released to a percentage of users first, with conversion tracked daily for exposed and unexposed groups, so impact was measured rather than assumed. Within two weeks, the cart-to-checkout rate climbed from roughly 12% to over 30%, while checkout-to-order held at 45% — the fixes brought more shoppers to checkout without bringing weaker ones.

AI discoverability

Search is moving into conversations. The store was structured to be found when shoppers ask ChatGPT, Gemini, or Google’s AI results for what Brandet sells — machine-readable product and brand information, answer-shaped content, and consistent entity signals. A compounding, unpaid channel most stores in the region have not yet claimed. See AI search optimization.

What made the difference

• Tracking before spending — pixel, server-side, GA4, and UTMs shipped first.
• A catalog that follows the shopper — Meta, Google, and WhatsApp from one feed.
• Campaigns with one job each, and cost per purchase deciding where the budget goes.
• Retargeting budgets set by audience frequency, not by the calendar.
• The discipline to test every site change on real users before believing it worked.

Download the white paper: From Pixels to Purchases (PDF)

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