Rouvy: 20% Lower CPA in 30 Days Without Reducing Volume

It wasn’t like any audit I’ve seen—it was a clear roadmap with actionable steps to boost efficiency. We cut our CPA by 20% while keeping the same volume, all in the first month.

Barbora Petrikova

Marketing director at Rouvy

Do you run paid acquisition with a senior in-house team and still ask:
“What can we realistically improve — even by a few percent?”

When you’re spending seven figures on media, a “small” improvement can mean hundreds of thousands in incremental revenue.

That was exactly Rouvy’s situation.

They didn’t expect breakthroughs — just marginal gains.

What happened instead?

• ~20% lower CPA within 30 days, at the same spend
• A foundation that supported 40%+ YoY revenue growth by year-end

The main lever wasn’t new ads or bigger budgets.
It was something most teams — and most audits — overlook.

The Situation

Rouvy wasn’t a beginner SaaS.

• FT 1000: #414 Europe’s Fastest-Growing Companies
• A senior internal paid media team
• A mature experimentation framework
• Clear ICPs, pricing, and business goals

Barbora, the Marketing Director, had seen audits before.

They all followed the same pattern:

“A review of campaigns, some optimizations, a few percentage points improvement.”

At this scale, even a few percent mattered — but expectations were still incremental, not transformational.

The Challenge: When Optimization Is Constrained by the System

On the surface, everything looked solid:

• Right media mix
• Strong creatives
• Smart bidding in place
• Country-specific targets and campaigns

But underneath, the tracking setup was limiting the algorithms..

Rouvy operated across many countries, often in the same language.
However:

• Lifetime value varied significantly by country
• Different CPAs and budgets forced campaigns to stay split
• The algorithm had no early signal to understand value differences

Campaigns were fragmented because the system couldn’t express value early enough.

That’s the kind of constraint most audits never uncover, because it sits:

• Between ads, analytics, and data teams
• Between business strategy and platform mechanics
• Outside the scope of classic campaign optimization

The Solution: A Quarter-Long Growth Roadmap

Instead of tweaking ads, the work started by zooming out:

• Deep understanding of Rouvy’s business model and LTV drivers
• Alignment on growth goals and acceptable trade-offs
• Performance analysis by country, LTV, and scale potential
• A full review of tracking architecture and bidding logic

The output wasn’t a list of fixes.

It was a multi-phase roadmap designed to compound performance over an entire quarter — with strategic consultations continuing through the end of the year.

Tracking Architecture as the Growth Lever

Phase 1: Consolidation Based on Real Value Signals

Campaigns were grouped not by geography, but by similar target CPA and LTV profiles.

This enabled:

• Campaign consolidation
• Higher conversion volume per campaign
• Faster and more reliable algorithm learning

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Phase 2: Making the Algorithm Understand Business Value Early

The core principle was simple:

Platforms don’t optimize for revenue.
They optimize for the signals you give them — early and consistently.

Previously:

• A UK user had ~2× the LTV of a Polish user
• But both looked almost identical to the algorithm at the start

Because that value difference appeared too late, campaigns had to stay split.

The adjustment:

• All users fired a conversion on credit card submission
• High-LTV countries fired an additional conversion after onboarding (often the same day)
• High-value users effectively “counted more” for the algorithm

This allowed:

• Further campaign consolidation
• Better prioritization of high-LTV demand
• Continued use of tCPA bidding that already performed well

Result after 30 days:

• ~20% lower CPA while maintaining the same revenue level

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Phase 3: Value-Based Bidding with Predicted LTV

While phases 1 and 2 were live, Rouvy’s data team worked on predicted LTV models.

The final step was to shift from efficiency-based optimization to value-based optimization:

• Predicted LTV imported into Google Ads
• Offline conversions updated via value restatement
• Bidding evolved from tCPA to tROAS
• Value signals sent immediately after trial start

This removed two major limitations:

• No waiting days or weeks for revenue to materialize
• No artificial inflation of conversions to “hint” value

The system could now optimize for future value at scale, across segments.

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Business Impact

• ~20% CPA reduction within the first month
• Significantly improved scalability and algorithm stability
• A growth foundation that supported 40% YoY revenue growth
• $17M+ revenue by year-end (publicly reported)

This work didn’t replace strong execution —
it removed the structural constraints that were holding it back.

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Why This Worked (When Most Audits Don’t)

From the first interaction, this wasn’t treated as a surface-level review.

Instead of jumping straight into campaigns, Tomas zoomed out:

• Asked deep questions about the business model
• Clarified growth goals and constraints
• Analyzed media mix and GEO strategy
• Evaluated tracking and data integrity

What Rouvy received wasn’t a checklist.

It was a growth system redesign — translated into clear, implementable documentation for internal teams.

According to Barbora, the difference was clear:

• Not tactical-only thinking
• Not isolated campaign changes
• Not generic audit templates

Instead:

• Full-picture business understanding
• Strategy first, execution second
• Clear rationale behind every recommendation
• Practical guidance teams could actually implement

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The Real Takeaway

Rouvy didn’t grow because they tried harder or spent more.

They grew because the system finally rewarded the right behavior.

At scale, growth is rarely blocked by effort.
It’s blocked by misaligned incentives inside tracking and bidding architecture.

Fix that — and performance compounds.