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eCommerce & Retail Case study

Up to 10.68x ROAS Across Four Peak-Season eCommerce Campaigns

How we delivered 5.12x to 10.68x ROAS across four seasonal Meta campaigns for an eCommerce food brand, with 748 purchases at a blended 7.1x ROAS.

Line-art of a gift box connected to a calendar with four highlighted days, a shopping bag and a rising bar chart
Industry
eCommerce & Retail
Services
Meta Ads, Facebook Ads, eCommerce Marketing, Conversion Optimisation
Client
Kept confidential
Published
June 2026
Purchases (4 campaigns)
748
Blended ROAS
7.1x
Peak campaign ROAS (Father's Day 2025)
10.68x
Higher ROAS on the best campaign vs the four-campaign blend
50%

01

The Challenge

Our client is an eCommerce food brand whose sales are highly seasonal. The big revenue moments arrive in tight windows around Valentine’s Day, Father’s Day, Halloween and the Black Friday / Cyber Monday (BFCM) period, and the difference between a good year and a great year comes down to how well those few weeks are executed.

The brief was simple to state and hard to do well: turn each seasonal spike into a profitable, repeatable Meta advertising play rather than a one-off scramble.

02

Our Approach

Instead of treating each promotion as a fresh start, we built a repeatable seasonal playbook and ran it across the calendar.

  1. Step 1

    Creative Built for the Moment

    Each campaign led with season-specific creative and offers (gifting angles for Valentine’s and Father’s Day, themed bundles for Halloween, and clear discount messaging for BFCM), tested across multiple variations so the algorithm could find the winners quickly.

  2. Step 2

    Leveraging Meta’s Andromeda Algorithm

    We structured campaigns to feed Meta’s newer Andromeda delivery system the signals it needs: consolidated ad sets, broad-but-relevant audiences, and clean conversion tracking through to purchase. This let the algorithm scale spend into the best-performing creative during each short selling window.

  3. Step 3

    Retargeting and Funnel Capture

    A retargeting layer recovered browsers and abandoned carts during each peak, and the Shopify funnel was tightened so the paid traffic landed on pages built to convert rather than generic category pages.

03

The Results

Across four seasonal campaigns, the brand generated 748 purchases at a blended 7.1x ROAS (Meta-attributed purchases and purchase value).

CampaignROASShare of revenueShare of ad spend
Father’s Day 202510.68x12%8%
Valentine’s Day 20267.86x62%56%
Halloween 20255.35x6%8%
Black Friday / Cyber Monday 20255.12x20%28%

The most efficient was the Father’s Day 2025 campaign at 10.68x ROAS, 50% above the four-campaign blend, bringing in 12% of the combined revenue from 8% of the combined spend. The biggest was Valentine’s Day 2026 at 7.86x ROAS: it took the largest share of the budget and still returned more than the blend, bringing in 62% of the combined revenue. Black Friday / Cyber Monday took a larger share of spend than of revenue, and its ROAS was the lowest of the four. Even so, every campaign cleared 5x ROAS, and the best returned about twice the ROAS of the weakest, showing the playbook holds up across very different seasons rather than relying on one lucky month.

04

Key Takeaways

  1. 01

    Seasonal peaks reward preparation

    The brands that win Valentine’s, Father’s Day, Halloween and BFCM are the ones with creative, offers and tracking ready before the window opens.

  2. 02

    A repeatable playbook beats one-off campaigns

    Reusing a proven structure across seasons delivered consistent 5x to 10x ROAS rather than unpredictable results.

  3. 03

    Feed the algorithm clean signals

    Consolidated campaigns and accurate purchase tracking let Meta’s delivery system scale into winners fast during short selling windows.

  4. 04

    Retargeting protects the peak

    Recovering browsers and abandoned carts during high-traffic periods materially lifts return on ad spend.

For seasonal eCommerce brands, the opportunity is not just running ads during the busy periods, it is treating each one as a repeatable system that compounds year on year.

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