A quick primer
The key method here is comparing against the same period a year ago, not just the previous stretch within the current season, since that's exactly how Google's own tool for spotting seasonality is built: the year-over-year comparison checks the last 28 days of search volume against the same 28 days a year earlier, built specifically to separate a recurring market shift from something specific to your account. If a channel's rise or fall matches the same pattern from last year, that's seasonality. If there's no matching pattern from last year, it's more likely something new and specific to the current campaign.
Inside the channel performance report itself, there's a direct tool for this too: the time series chart shows how channel mix changes over your selected date range and helps pinpoint the exact moment of a shift, for example when a video was added or goals changed. Pick a long enough range that covers the equivalent season last year, and you can visually compare this year's channel-distribution curve against last year's.
What to check before you touch anything
- Do you have data from the equivalent period a year ago. Without it, telling seasonality apart from decline by eye is very difficult.
- Does the current channel-mix shift repeat the same shape as last season (a rising Display share before the holidays, for example). A match in both shape and timing points to seasonality.
- Does the shift line up with an external, documented trend in search trends, not just your account's own numbers.
- Did internal changes (new assets, a bid strategy switch) happen at the same time as the seasonal window. If so, the two effects may be layered together and need to be separated.
- Are you looking at a long enough period. A few days won't reveal a seasonal pattern; you need a range spanning both the current and last year's season.
Possible approaches
- Use the year-over-year comparison in search trends as your primary, purpose-built tool for separating seasonality from an internal issue.
- Overlay this period's time series chart against the same period a year ago (comparing two exported reports manually) to see whether the shape of the channel-distribution curve repeats.
- If the pattern repeats year after year, treat the current shift as expected seasonality and avoid making manual budget changes in reaction to it.
- If there's no matching pattern from last year, that's a stronger case for looking at an internal cause: assets, signals, bid strategy targets, or the competitive environment.
- Keep your own record of seasonal patterns as you accumulate data across multiple years. The more cycles you have, the more confidently you can tell a repeating pattern from something genuinely new.