Visitor Retention

Visitor Retention shows how many of the visitors who first came to your store in a week or month came back in the periods after.

How It’s Calculated

Each row of the grid is a cohort: the visitors whose first session in the date range started in that week or month. Visitors is the size of the cohort. The columns count periods since then: Week 0 or Month 0 is the period of the first session, Week 1 or Month 1 the period after, and so on.

Each cell is the share of the cohort that had at least one session in that period. A visitor who comes back in weeks 1 and 3 counts in both columns, and not in week 2. The first column is always 100%.

Cohorts are weeks for a date range of up to 93 days, such as Trailing 2 months, and months for longer ranges, such as Trailing 3 months. Trailing 1 year is the default.

A row under the grid shows the average for each column. A cell is blank when no visitor from the cohort came back in that period, or when the period hasn’t started yet.

A visitor’s cohort is the period of their first session inside the date range. Someone who visited before the range counts in the cohort of their first session in it, so the early cohorts hold some returning visitors. A longer date range reduces this.

Visitors are tracked with a browser cookie. The same person on 2 devices, or in a private window, counts as 2 visitors. Treat the percentages as a guide.

What Counts

• Visitors who declined analytics cookies, or who opted out of the sale or sharing of their data while Require Sale-of-Data Consent is on, aren’t recorded. Known bots are left out.
• Only events inside the date range count, in your store’s time zone.

This report is a grid. It has no summary cards, no Live switch and no Compare, Segment, Sales Channel or Filters control. It offers the long date ranges only.

What Good Looks Like

There’s no target. The first column is 100% by definition, so look at the drop after it. A row that fades fast means mostly one-time visitors.

A row that levels off shows a group that keeps coming back.

Read down a column to compare cohorts. A newer cohort with a higher Week 1 than older ones is a sign that more visitors return.

What to Do About It

• A steep drop after Week 0: give visitors a reason to come back, such as an email sign-up or a loyalty offer.
• One cohort much higher than its neighbors: look at what you did that week, such as a campaign or a launch.
• Retention falling across newer cohorts: check which channels brought them in Sessions by Source & Channel.

Retention by Cohort shows the same view for customers who bought.

Where to Find It

• Visitor Retention: open Reports and look under Web Analytics.