A quick primer
Google's own troubleshooting documentation names this pattern directly, calling it cross-channel dynamics: with last-click attribution, a channel can look like it has a low ROI when it's actually playing an important role earlier in the path to conversion, since last-click often fails to capture the full contribution of channels engaging users earlier in their journey. That's a direct official acknowledgment that a low channel ROAS under last-click attribution isn't always a diagnosis; it's often an artifact of the measurement method.
Google's own recommendation for this exact scenario is to move to data-driven attribution, which spreads credit for a conversion across every touchpoint in the user's path instead of assigning it entirely to the last click. That's a direct way to reveal a channel's real contribution when it only looks weak because of the attribution model. It's also worth keeping the marginal ROI principle in mind: even a segment with a lower average ROI can be the most valuable traffic, carrying the highest marginal return in specific auctions, so a low average by itself isn't a final verdict even without switching attribution models.
For video inventory specifically, there's a further, officially documented layer for measuring upper-funnel contribution: engaged-view conversions, which get viewer skips clicking but watches the video and converts later. Part of a video channel's upper-funnel value is invisible in the standard "Conversions" column and only shows up in this separate metric.
What to check before you touch anything
- What attribution model is being used in the account. With last-click, a channel's contribution earlier in the funnel is systematically undercounted.
- Is data-driven attribution available, and have you compared it against last-click for this same channel. The difference between the two models is itself a diagnostic signal.
- Are engaged-view and view-through conversions being counted separately from the main column, especially for video inventory, where this is an officially documented, distinct source of conversions.
- Are you judging a channel by average ROI in isolation from the marginal cost optimization principle. That criterion alone can be misleading regardless of the attribution model.
- Is there enough data accumulated for a meaningful comparison between attribution models. On a small number of conversions, the difference can be statistically unstable.
Possible approaches
- If you're on last-click attribution, switch to data-driven and re-compare the channel's ROAS or contribution. A rise in the figure after that switch confirms an upper-funnel effect.
- If the channel is video inventory, add the Ad Event Type segment to see engaged-view and view-through conversions separately before concluding there's no value.
- Don't cut a channel purely for a low average ROI under last-click attribution. Rule out this specific, officially documented distortion first.
- If, even after switching attribution and accounting for engaged-view and view-through conversions, the contribution is still low, that's a better-grounded reason to reconsider the channel's role.
- Check both angles (attribution model and engaged-view metrics) as a standard part of every channel evaluation, not just when a problem is first suspected. Make it routine rather than reactive.