Last-click attribution assigns one hundred percent of conversion credit to the final touchpoint before a sale. In a B2B buying journey where a prospect typically interacts with your brand ten to fifteen times before converting, this model does not just understate other channels, it actively misleads the budget decisions built on top of it.
The Practical Problem With Last-Click
Picture a realistic journey: a prospect sees a LinkedIn ad, reads two blog posts over the following weeks, searches your brand name directly on Google, and finally converts after clicking a branded search ad. Last-click attribution credits that branded search ad with one hundred percent of the conversion. Your LinkedIn campaign, which arguably started the entire journey, looks like it generated nothing. Left unchecked, this leads to the LinkedIn budget being cut and pipeline quietly declining a few months later for reasons that look mysterious in the dashboard but were entirely predictable in the attribution model.
Better Attribution Models Worth Considering
Several models distribute conversion credit more realistically across the full buyer journey:
- Linear attribution, distributes equal credit across every touchpoint in the journey
- Time decay, gives progressively more credit to touchpoints closer to the eventual conversion
- Position-based, typically weights 40 percent to the first touch, 40 percent to the last, and distributes the remaining 20 percent across the middle
- Data-driven attribution, an algorithmic model that requires a meaningful volume of conversion data to function reliably
Choosing a Model for Your Account Size
Google's own attribution documentation recommends data-driven attribution once an account has roughly 300 or more conversions per month, since the model needs sufficient signal to be statistically meaningful. For smaller accounts that have not reached that volume, position-based is a reasonable starting point that at least acknowledges first-touch channels without requiring heavy data infrastructure.
It is worth running your historical performance through more than one model before making any decision to cut a channel that appears to underperform under last-click. We have seen channels that looked like dead weight under last-click attribution turn out to be the actual top-of-funnel engine once a more complete model was applied.
Connecting Attribution to CRM Data
The most accurate attribution for B2B does not stop at the ad platform, it connects through to your CRM and tracks which campaigns generate not just leads, but qualified opportunities and ultimately closed revenue. Cost per lead is a vanity metric if those leads never close. Revenue attribution, even if imperfect, is the metric that should actually drive budget decisions, and it is the same lens we apply when reviewing whether retargeting investment, covered in retargeting in Google Ads, is genuinely earning its budget rather than just appearing to.