How We Increased Cloudvisor’s Pipeline Quality by 130% Using PMax

Step 1: Establishing the Right Foundation

Before adjusting the campaign itself, we needed to align the data infrastructure with :

• Mapped the full sales funnel, from initial form submission to MQL, SQL, Opportunity, and Closed-Won.
  
  
• Integrated key conversion events from HubSpot into Google Ads, ensuring the algorithm could optimize for signals beyond the surface level.
  
  
• Audited lead qualification logic and refined status definitions (e.g., Top-Tier SQL) to capture quality early.
  
  

This was critical. With Google continuing to invest in AI-driven systems like PMax, campaign success is increasingly dependent on the quality of the feedback loop. In short: you cannot scale what you cannot measure properly.

Step 2: Narrowing the Optimization Goal

At launch, the campaign was set to optimize for general lead submissions to allow the system to collect baseline data.

But within two weeks, we transitioned the optimization to target only Marketing Qualified Leads  — leads that met basic business validation criteria and showed intent to engage.

This shift significantly improved lead relevance.

Result: Conversion Rate (MQL → SQL) increased by 33.33%.

Step 3: Moving Toward Full-Funnel Optimization

One month in, we extended optimization across the full customer journey — incorporating not just MQLs and SQLs, but also Opportunities (Lead → MQL → SQL → Opportunity)

This allowed us to prioritize leads that were not only qualified, but had a higher probability of becoming revenue-generating customers.

Results 4 weeks post-implementation:

• CR (MQL → SQL) increased by 130.3% in comparison to the week of implementation.
  
  
• Opportunity volume grew by 50%.

Step 4: Optimizing for Custom Signals (Top-Tier SQLs)

To further improve campaign accuracy without sacrificing algorithm training volume, we collaborated with Cloudvisor to implement custom conversion stages:

• Top-Tier SQLs: Leads that had passed internal qualification and were likely to progress through the sales funnel.
  
  

By assigning different values to these conversion types in Google Ads, we provided clearer signals on what success looks like — enabling the system to optimize not just for quantity, but business impact.

The result was a continued increase in SQL and Opportunity, outpacing the cost growth — a clear indicator of improved performance.

Key Takeaways

Performance Max Requires Strategic Input

While PMax offers powerful automation, it does not replace strategy. Without the right signals, it will default to optimizing for volume — which, in most B2B funnels, results in high CPLs and low close rates.

To use it effectively, advertisers must define quality benchmarks early, implement clean CRM tracking, and pass this data back consistently.

Sales Funnel Alignment Is Essential

None of this would have worked without a well-defined sales funnel implemented by Cloudvisor’s team. By structuring the campaign around real sales milestones — not superficial metrics — we ensured alignment between spend and high quality lead generation.

The Value of Collaboration

Cloudvisor’s team was proactive and transparent throughout the process, which made it possible to iterate quickly, validate changes, and make optimization decisions based on full-funnel visibility. This level of partnership was fundamental to success.