26/ Attribution Model Comparison, Google + Meta

What it does

Runs your conversion data through different attribution models side by side, last click, first click, linear, time decay, position based, and data-driven. Shows you how credit shifts between campaigns depending on the model so you can make better budget decisions instead of over-investing in last-touch campaigns.

How it works

Claude takes your multi-touch conversion path data and applies each attribution model to the same dataset. It then compares how each campaign's attributed conversions and ROAS change under different models, highlighting campaigns that look great under last-click but contribute nothing at first-touch (and vice versa).

Practical example

Under last-click attribution, your Google Brand campaign gets credit for 420 conversions at $18 CPA, making it your "best" campaign. But when Claude runs first-click attribution, Brand drops to 31 conversions, most of those users actually discovered you through Meta prospecting (which jumps from 89 to 340 attributed conversions). Linear attribution puts Meta prospecting at 215 and Brand at 190, giving a more balanced picture. Claude recommends shifting 20% of Brand budget to Meta prospecting, which is actually originating most of your pipeline.

What you get back

• Side-by-side conversion and ROAS comparison across all models for every campaign
• Campaigns most affected by model choice (high variance = their role is misunderstood)
• Upper-funnel campaigns being undervalued under last-click
• Lower-funnel campaigns being over-credited under last-click
• Budget reallocation recommendations based on a blended attribution view
• Recommended "working model" for your specific account based on funnel length and touchpoint patterns