The channel that gets credit is the channel that gets budget, and for most brands, the default model is quietly rewarding the wrong one. Google deprecated last click, first click, linear, time decay, and position based models in 2023, making data-driven attribution the only rule-based option left[1]. If you have not rethought your measurement strategy since then, your budget allocation is based on a model that no longer exists.
Why the Old Models Failed
Last-click gave 100% credit to the final touchpoint before conversion. It was simple, and it was systematically wrong about discovery. Brands using it consistently underfunded top-of-funnel channels because those channels never got credit for starting the journey. First-click had the opposite problem: it valued discovery and ignored everything that actually closed the deal[1].
Linear, time-decay, and position-based models tried to split the difference. Position-based assigned 40% to the first touch, 40% to the last, and spread the remaining 20% across the middle. Time-decay applied a 7-day half-life, weighting recent touches more heavily. All of them were arbitrary, and none of them used your actual data.
Data-Driven Attribution Is the Only Default Now
Google Ads switched to data-driven attribution (DDA) as the default in 2023 and deprecated all rule-based alternatives[2]. DDA uses machine learning to analyze your actual conversion paths and assign credit based on which touchpoints genuinely influenced outcomes. Accounts with enough conversion volume (typically 300+ conversions and 3,000+ interactions in 30 days) get the most accurate models[3].
The practical impact is significant. DDA frequently reveals that channels you thought were underperforming were actually driving assists. Cutting a channel that looks weak under last-click but strong under data-driven attribution is the single most common budget misallocation in paid media.
Where Attribution Still Breaks Down
DDA solves intra-platform attribution but not cross-platform measurement. Google's model only sees Google touchpoints. It cannot credit the LinkedIn ad that started awareness, the podcast mention that built trust, or the organic search visit two weeks before the branded click that converted.
View-through conversions in display and video are another blind spot teams routinely overlook. A user who sees your YouTube ad, does not click, and converts via branded search the next day gets zero credit for the video impression under most default setups. Enabling view-through tracking closes that gap.
How Scanner Helps
Accurate attribution depends on accurate tracking, which depends on a well-structured site. Broken tags, slow pages, and redirect chains all create gaps in conversion data. Scanner audits technical site health so your attribution model has clean signals to work with.