From maturity to growth
Context
As the B2B arm of the leading insurance comparison platform, Assurland Pro is specifically aimed at professionals, the self-employed and businesses. In this highly competitive market (professional liability insurance, building warranty, mutual insurance for the self-employed), the model remains the same: generating qualified leads for insurance partners. However, costs per click (CPC) are significantly higher here, making every irrelevant click very costly.
Although the account was performing well, it suffered from a dual structural problem typical of B2B in 2025:
- Inaccurate targeting: The strict application of Google’s ‘best practices’ (mixing Broad and Phrase match within the same ad groups) diluted relevance. Despite well-crafted adverts, the alignment between the user’s query, the advert and the landing page was not optimal, leading to significant budget wastage
- Conversion blind spot: As the signing cycle concluded “offline” (phone call, finalised quote later), campaign management relied on conversion imports. However, this process lacked reliability: the absence of strict conversion deduplication sent noisy signals to the algorithm (a single click generating several ‘false’ conversions), skewing Smart Bidding.
Objectives
The challenge was not simply to increase volume, but to ensure sustainable growth. We needed to improve the technical infrastructure (tracking) to enable the algorithm to optimise based on actual business performance, whilst identifying new sources of leads through a more refined semantic strategy, all whilst maintaining an ROI of over 1.
Achievements
We implemented a two-stage strategy, addressing both the cause (the data) and the effect (the delivery):
- Restructuring and alignment: To counter high CPCs, we moved away from a generalist structure towards strict segmentation. By isolating Exact Match and developing ad groups based on precise semantics, we ensured perfect alignment between ad, keyword and landing page. This automatically boosted Quality Scores and reduced costs.
- Offline Tracking Correction (Data Integrity): This is the cornerstone of success. We audited and corrected the offline conversion import process. By implementing a rigorous deduplication system through successive export/import tests, we succeeded in sending only ‘genuine’ unique conversions back to Google. Result: The bidding algorithm now works with clean data, favouring profiles that actually convert.