Sample case study for demonstration. This engagement is illustrative: the scenario is typical of the work Axoria does, and the results are described without figures until verified client data is published.
The situation
A direct-to-consumer home goods brand selling through its own Shopify store had built most of its growth on Meta advertising. For several years the formula had worked: product photography, broad targeting, and a return on ad spend that cleared the margin threshold. Over the previous year that had reversed: cost per order was rising each quarter, the founder no longer trusted Ads Manager, and the in-house team was producing creative without knowing which of it worked.
The brand asked Axoria to take over paid social with a clear priority: profitable new customers, not just orders.
The challenge
The account was suffering from three overlapping issues. Browser-side pixel tracking had degraded after platform privacy changes, so the algorithm was learning from an incomplete picture. Campaigns with no customer exclusions were spending heavily on people who had already bought and would have returned through email anyway, which flattered ROAS while hiding the true cost of a new customer. And creative was judged on gut feel rather than any consistent test design. The question was how much of the reported performance was real new-customer acquisition, and what it would take to grow that profitably.
Research and analysis
We started by reconciling Ads Manager against Shopify order data by customer email and order timestamp. A substantial share of attributed purchases were from existing customers, and a further share were attributed on view-through alone. We segmented historical creative by format, hook and message and matched it to first-order outcomes. A small number of concepts, mostly problem-led video with a demonstrable product benefit, accounted for most genuinely new customers; product-shot statics, which made up most of the output, mainly reached returning buyers. Post-click, social traffic landed on product pages designed for search visitors, with no brand context and no reason to trust it on a first visit.
Strategy
Fix the signal first
Implement the Conversions API through server-side tagging alongside the pixel, deduplicate events, and pass hashed customer data so the platform could distinguish new from returning buyers and optimise accordingly.
Then restructure for new customers
Separate prospecting from retention with strict customer-list exclusions, set targets on cost per new customer rather than blended ROAS, and move retention spend to a small, capped campaign that complemented rather than replaced email.
Creative was reframed as a testing programme. Every concept entered the account with a hypothesis, a fixed budget and a decision rule, and the production calendar was reorganised around what the tests showed.
Execution
Optimization
Once the new-customer signal was reliable, weekly reviews centred on cost per new customer by campaign and the proportion of tested concepts that beat the control. The creative programme iterated on winning hooks rather than winning ads, so a successful problem-led video spawned variants in new formats and openings. TikTok was introduced only once a creative style that worked for cold audiences had been established, and budget scaled in increments tied to whether cost per new customer held.
Results (illustrative)
Figures are withheld until verified, client-approved data is published. Measured in Shopify against the prior period, the movements typical of a programme like this are:
- Cost per order: blended cost per order stabilising and then falling as spend on existing customers was removed and creative efficiency improved.
- New-customer share: the proportion of paid-social orders from first-time buyers rising sharply, the metric the founder cared about most.
- Creative win rate: the share of new concepts beating the control improving over successive cohorts as the team learned which hooks and formats resonated with cold audiences.
What we learned
- Blended ROAS hides the problem. Separating new from returning customers changed every decision in the account. This is the first thing we check in any e-commerce paid social audit.
- Tracking quality is a performance lever. Better event data improved delivery before a single ad changed.
- Test concepts, not executions. Judging creative at the hook level produced more reusable learning than judging individual ads.
- Paid and owned channels need one plan. Coordinating with email removed wasted spend and is a core part of our e-commerce marketing approach.