Client & Context

The brand is in a growth phase, operating in a sector where customer loyalty is a major asset. The company already benefits from a solid foundation: customer satisfaction and repurchase rates are strong, meaning that once the product has been tried, customers naturally tend to come back.

However, as with any brand still in the early stages of digital maturity, marketing performance does not follow a linear trajectory, and the challenges surrounding new customer acquisition remain significant.

With a limited purchase history and few learning signals available to feed advertising algorithms, the acquisition model was still fragile and very much a work in progress.

The Challenge

Against this backdrop, the paid media objective was naturally evolving: it was no longer just about generating short-term revenue, but about acquiring new customers.

The growing automation of advertising platforms, particularly Google Ads, introduces a major risk: algorithms tend to favour remarketing and to target already-known audiences, sometimes in ways that are hidden within Performance Max campaigns, at the expense of genuine acquisition.

The challenge was therefore twofold:

• structuring a setup capable of continuously recruiting new customers
• while maintaining rigorous control over the cost of acquisition (CAC)

In other words, without allowing the budget to be diluted on existing customers or on already-conquered brand traffic.

Our Strategy

To meet this challenge, we designed an acquisition strategy centred on leveraging the new customer recruitment features offered by Google Ads, while steering performance using four key indicators directly aligned with the acquisition objective:

• new customer volume
• customer acquisition cost (CAC)
• advertising spend variation
• revenue growth generated by these new customers

The goal was not simply to buy conversions at any cost, but to build a sustainable and incremental acquisition funnel, one capable of continuously bringing new profiles into the brand’s ecosystem, feeding the algorithms with more purchase and value signals, and progressively improving the overall efficiency of the advertising system.

The Actions

To ensure that every euro invested genuinely served new customer acquisition, we implemented a daily CRM export of the brand’s customer base, allowing us to systematically exclude already-known users on an ongoing basis throughout the campaigns.

This continuous exclusion process made it possible to focus advertising investment on genuine prospects, preventing the budget from being captured by remarketing or already-loyal customers.

In parallel, we structured the Google Ads campaigns around new customer acquisition objectives, fine-tuning bids and audiences to maximise reach among unconverted profiles, while maintaining rigorous KPI monitoring to prevent any CAC drift.

Results

Over the analysed period, the advertising budget increased by just +5%, yet this modest uplift in investment delivered particularly significant results.

We recorded a +30% increase in the number of new customers acquired, while reducing the acquisition cost by 19% — demonstrating a clear improvement in campaign efficiency.

Revenue generated by these new customers grew by +30%, confirming that the growth observed stems from genuine, incremental acquisition rather than a side effect of remarketing or loyalty activity.

The new customer acquisition setup acted as a signal accelerator for the algorithm: by generating a steady flow of new buyers, the campaigns increased both the quantity and quality of learning signals, progressively improving the overall efficiency of the system.

This case study demonstrates that even for a brand still in its growth phase, a well-designed, data-driven acquisition strategy centred on signal quality can be both profitable and scalable.