The User Stickiness card appears in the Engagement Overview report in Google Analytics 4. It shows you how often people are coming back to your site or app over different time periods: daily, weekly, and monthly. Instead of just telling you how many users you have, it gives you insight into user retention and how frequently people return.

Think of it like this:

• If a user visits your site once and never comes back, that’s not a sticky experience.

• If they return daily or at least weekly, your site or app is more “sticky”, meaning it’s engaging or valuable enough to bring people back.

GA4 calculates stickiness by using three ratios that compare active users over different timeframes:

1. DAU/MAU – Daily Active Users over Monthly Active Users

2. DAU/WAU – Daily Active Users over Weekly Active Users

3. WAU/MAU – Weekly Active Users over Monthly Active Users

Each ratio gives you a different angle on how frequently users return.

The 3 stickiness metrics explained

1. DAU / MAU – Daily Active Users divided by Monthly Active Users

What it shows:
This tells you what proportion of your monthly users are also active in a single day.

How it works:
Let’s say you had 3,000 unique users in the last 30 days (your MAU), and 300 users were active today (your DAU). That means 10% of your monthly users were active today. So your DAU/MAU = 10%.

Why it matters:
This ratio reflects how often people are using your product on a daily basis. A high DAU/MAU ratio indicates that people find your site or app valuable enough to visit nearly every day.

Use case examples:

• A banking app, fitness tracker, or social media platform would expect a high DAU/MAU ratio, daily use is normal.

• For an ecommerce site, daily usage may not be expected, but a low DAU/MAU could still show that users only shop once and don’t come back until months later, which could indicate an issue with retention.

Benchmark (rough guide):

• 10%+ = Reasonably healthy daily engagement

• 20%+ = Very strong daily user retention (typically only seen in apps or tools with daily utility)

2. DAU / WAU – Daily Active Users divided by Weekly Active Users

What it shows:
This measures what proportion of your weekly users were active today. It’s a shorter-term measure than DAU/MAU and helps you assess daily engagement within a 7-day window.

How it works:
If you had 700 users active in the last 7 days (your WAU) and 100 of those were active today (DAU), your DAU/WAU = 14.3%.

Why it matters:
This is useful for spotting patterns in shorter-term engagement. If this percentage is low, it may suggest that even your engaged users aren’t checking in daily.

Use case examples:

• If you publish blog posts every weekday, you’d expect some level of daily engagement, but not necessarily from all users every day.

• If you’re running a week-long promotion, you might use this metric to gauge how many of your interested users are actually coming back each day during that period.

Benchmark (rough guide):

• 15–30% = Fair to strong engagement

• Lower than 10% = Users are browsing less frequently, possibly only once per week or less

3. WAU / MAU – Weekly Active Users divided by Monthly Active Users

What it shows:
This metric tells you how many of your monthly users are also active in a typical week. It focuses on weekly return rates.

How it works:
Let’s say you have 3,000 monthly users (MAU), and 1,500 of those visited at least once in the last 7 days (WAU). WAU/MAU = 50%. That means half of your monthly users visit at least once per week.

Why it matters:
This ratio reflects how consistently users are coming back, if a large portion of monthly users return weekly, it’s a good sign that your content or product is useful or interesting enough to drive repeat engagement.

Use case examples:

• A newsletter site or ecommerce store might not expect daily visits, but weekly engagement is more realistic.

• For B2B service providers, this could show how consistently people check back for new information, support, or tools.

Benchmark (rough guide):

• 40–70% = Strong sign of ongoing engagement and user interest

• Less than 30% = May suggest a lot of “one-and-done” users who visit once but don’t come back until the next month (or not at all)

What does success look like? (benchmarks for user stickiness)

There’s no universal ‘perfect’ number, it depends on your industry, product type, and business model, but here’s a general breakdown for context:

If you’re running an ecommerce or content site and you see low DAU/MAU but a decent WAU/MAU, that’s not necessarily a problem, it means people return weekly, which is still valuable. However, if all three metrics are low, it may mean that most users are bouncing after a single visit or aren’t finding a reason to return.

Task: Based on the above information about each of these stickiness metrics and benchmarks, try having a look at the screenshots we shared above to see if you can see any issues or areas to improve (even without knowledge of what these sites/apps are).

How should marketers use this data?

Here are a few ways to take action based on what you see:

• Low stickiness across all metrics?
  You may need to focus on retention strategies like email follow-ups, re-marketing ads, loyalty programmes, or fresh content.

• Good monthly traffic but poor DAU/MAU?
  You’re getting people in the door, but they’re not coming back. Consider user journey mapping to see where drop-off happens and improve your value proposition.

• Strong WAU/MAU but weak DAU/WAU?
  Users are coming weekly but not daily, it could be that that’s normal for your business. However, if you’re aiming for daily engagement (e.g. through blog posts or offers), review how often you give people a reason to return.