How AdBrains Achieves 35% Better Results Than Other Agencies on Average

Achieving 35% better results than competing agencies on average is a bold claim, and one that deserves a thorough explanation. At AdBrains, we believe transparency is the foundation of any strong agency relationship. In this article, we explain exactly how we measure this advantage, what drives it technically and strategically, and why the gap between AI-powered campaign management and traditional agency models continues to widen in 2026.

Why Traditional Agencies Leave Performance on the Table

Most agencies still operate on a model where a single account manager handles dozens of client accounts, performs monthly optimisations manually and reports via a standard dashboard. This model worked reasonably well a decade ago, but in 2026 it falls structurally short. Google Ads has grown exponentially more complex: more campaign types, more bidding strategies, more audience signals, more asset formats. No human can simultaneously optimise all these variables at the speed and scale required.

The result is that the majority of agencies capture only a fraction of the available optimisation potential. They focus on the most visible metrics, miss subtle signal patterns, and consistently leave budget performance on the table through suboptimal bidding. Our internal analysis of accounts that switched to AdBrains from a traditional agency shows a consistent pattern: within the first 90 days, conversions rise by an average of 28%, cost-per-acquisition drops by 22%, and ROAS improves by 35% on average.

These are not projections or theoretical numbers. They are measured outcomes derived from real client accounts managed under our methodology, compared to their own historical performance in the 90 days before switching to AdBrains.

The Three Pillars of the AdBrains Method

Our advantage does not come from a single clever trick. It emerges from a coherent methodology built on three reinforcing pillars. Each pillar strengthens the others, and together they create a compounding performance advantage that grows over time.

1. Continuous AI Optimisation Instead of Monthly Check-ins

Traditional agencies optimise when an account manager has capacity, typically once or twice per month. AdBrains optimises continuously. Our AI layer analyses thousands of data points per campaign every day: search terms, bids, audience signals, landing page performance, device categories, time-of-day patterns and more. Deviations are detected and corrected immediately, without requiring a human intermediary step.

This means a campaign that starts underperforming on Monday is corrected by Tuesday, rather than at the next monthly check-in. Across an entire year, this difference in response speed compounds into dramatically better cumulative performance. Clients who use our AI-driven approach experience consistently higher quality metrics month over month, rather than the peaks and valleys typical of manual, episodic optimisation.

2. Advanced Signal Enrichment for Smart Bidding

Google's Smart Bidding is a powerful tool, but it only performs well when it receives high-quality signals. Many agencies simply activate Smart Bidding without optimising the underlying data quality. AdBrains connects first-party data, correctly configured conversion tracking and additional audience signals to the Smart Bidding model, enabling the algorithm to make structurally better decisions. Advertisers with enriched conversion tracking report an average of 23% more tracked conversions compared to standard implementations, giving the bidding system richer feedback and leading to better targeting efficiency.

3. Strategic Campaign Structure Aligned to the Customer Journey

The third pillar is campaign architecture. Many agencies use a generic account structure designed primarily for administrative convenience. We build campaign structures that reflect the actual customer journey: from awareness to consideration to conversion. Every touchpoint has its own budget allocation, bidding objective and messaging. This ensures that spend flows to the right user at the right moment, rather than being spread indiscriminately across all intent levels.

Real Results: ToetsJeKennis.nl

A concrete illustration of our methodology is ToetsJeKennis.nl, an online learning platform offering practice questions across multiple subjects and levels. When they moved their Google Ads management to AdBrains, their starting ROAS was 3.1 and they were paying an average of 18.40 euros per new subscriber. After 90 days of continuous AI-driven optimisation, ROAS had risen to 4.8 and cost-per-acquisition had dropped to 14.20 euros. That represents a 55% improvement in ROAS and a 23% reduction in CPA.

The first step was a thorough audit of their existing campaign structure. We found that over 40% of the budget was being directed toward search terms with low purchase intent, while the highest-value queries were underrepresented in bidding. By restructuring the campaign architecture and enriching Smart Bidding with better conversion signals, budget automatically shifted toward the most profitable search segments.

We also implemented a dedicated remarketing layer targeting visitors who had viewed the product page but not yet subscribed. This audience converted at a CPA 38% below the campaign average after our remarketing strategy was applied. Finally, we analysed historical conversion data to identify timing and device patterns. ToetsJeKennis.nl showed a strong spike in mobile searches on weekday evenings, a pattern their previous agency had completely ignored in bidding strategy. By targeting this segment more aggressively, evening conversions increased by over 41%.

AdBrains vs. Traditional Agencies: A Clear Comparison

What Makes Our Approach Technically Different

Beyond strategy, several technical elements set AdBrains apart from the average provider. These elements are less visible from the outside but have a direct impact on campaign performance.

• Enhanced Conversions: We implement Enhanced Conversions as standard across all client accounts, capturing an average of 15-25% more conversions that would otherwise be lost due to cookie restrictions and ad blockers.
• Audience layering: By adding multiple audience segments as informational layers to campaigns, the bidding algorithm learns which user profiles deliver the highest conversion value, and adjusts bids accordingly.
• Asset testing at scale: Our AI continuously tests different ad variants and automatically adjusts display frequency based on statistically significant performance measurements.
• Search term hygiene: Weekly analysis of search term reports with automated flagging of irrelevant queries ensures budget always flows to relevant, high-intent searches. Properly managed negative keywords alone can improve campaign efficiency by 10-15%.
• Seasonal and trend corrections: Our AI recognises seasonal patterns and proactively adjusts bids ahead of predicted demand shifts, rather than reacting after the fact.
• Landing page analysis: We connect campaign performance data to landing page metrics and automatically signal when a page is leaking conversions, enabling rapid remediation.

How We Measure and Validate Our Results

A claim like "35% better" only has value if it is rigorously measured. We apply a three-layer measurement protocol. The first layer is a comparison with the client's own historical performance in the 90 days before switching to AdBrains, adjusted for seasonal variation and market changes. The second layer is a benchmark comparison against industry averages for the relevant segment. The third layer is an internal performance comparison across all client accounts.

The 35% figure represents the weighted average ROAS improvement across all accounts that have been with AdBrains for a minimum of 90 days. The spread is wide: some accounts improve by 20%, others by 60% or more, depending on the degree of underoptimisation in the starting situation. But the weighted average consistently converges around the 35% improvement mark. We are transparent about the limits of our methodology: in markets with very low conversion volumes (fewer than 30 conversions per month), the AI layer is less effective simply because there is insufficient signal to learn from. In those cases, we combine our AI approach with more hands-on strategic guidance. More details about how we structure our service are available on our approach page and our FAQ.

Frequently Asked Questions

How quickly do new clients see improvements in campaign results?

Most clients see measurable improvements within the first four to six weeks, particularly in search term relevance and budget distribution. The larger gains in ROAS and CPA typically appear after 60 to 90 days, once the AI layer has collected sufficient campaign data to make robust optimisations. The exact timeline depends on the conversion volume and complexity of the account.

Does your approach work for smaller advertising budgets?

Our methodology is scalable, but the AI component performs best with a minimum budget of around 1,500 to 2,000 euros per month. At lower budgets, conversion feedback per unit of time is too limited for optimal AI-driven management. In those cases, we use a hybrid approach where strategic manual guidance carries more weight. Information about which setup is right for your situation is available on our pricing page.

What makes you different from agencies that also claim to use AI?

There is a significant difference between agencies that claim to "use AI" by simply switching on Google's Smart Bidding, and agencies that have built a complete AI-driven methodology around data quality, signal enrichment and continuous optimisation. Most agencies do the former: they activate Smart Bidding and report that as "AI optimisation." We build a full data infrastructure around the bidding algorithm, feed it with first-party signals and monitor it daily with automated anomaly detection. That is the fundamental difference between a tool and a system.

How exactly is the 35% improvement calculated?

The 35% figure is a weighted average of the ROAS improvement clients achieve after a minimum of 90 days with AdBrains, compared to their performance in the 90 days before switching. We adjust for seasonal influences by indexing the comparison period against historical market movements in the relevant segment. The range runs from approximately 18% to over 60% improvement depending on the degree of underoptimisation in the starting situation. Accounts that start from an already well-optimised baseline will naturally see a smaller percentage gain, but even for those clients, our continuous approach adds structural value compared to episodic manual management.