Google Ads Health

Seasonality vs Trend Separator

Paste daily cost, conversions or clicks and separate the underlying trend from your day-of-week pattern — especially useful for multi-market EU accounts with different holiday calendars.

How to use

1

Paste daily data

Date,value per line — cost, conversions, clicks, whatever you want to decompose. At least 3 weeks works best.

2

We separate trend from seasonality

A rolling 7-day average gives the underlying trend; what is left over is the day-of-week pattern.

3

Read the day-of-week index

See which weekdays run consistently above or below your trend — useful for multi-market EU accounts with different holiday calendars.

Paste at least 14 days of data above.

What this tool does

  • Takes daily date/value pairs (cost, conversions, clicks — whatever you paste) and computes a centred 7-day moving average as the underlying trend line.
  • Compares each day’s actual value against that trend to build a day-of-week seasonal index — e.g. “Mondays run 12% above trend, Sundays 18% below” — useful for multi-market EU accounts where different countries have different weekly and holiday patterns.
  • Needs at least 10 days of data (14+ recommended, 3+ weeks ideal) for the trend and weekday averages to mean anything.

Related tools

Last updated: 19 August 2026 · Built by the CWA Europe PPC team.

Frequently asked questions

What data should I paste in?

Any daily time series — cost, conversions, clicks, revenue — as date,value pairs, one per line. At least 3 weeks of data gives a more reliable day-of-week read than 1-2 weeks.

How is the trend calculated?

A centred 7-day moving average, which smooths out day-of-week swings so you can see the underlying direction. What is left over after removing the trend is the seasonal (day-of-week) pattern.

Is my data uploaded anywhere?

No. All calculations run in your browser; nothing you paste is sent to a server or stored.