Each product is different, even those that appear to be the same. I'd try and stay away from comparing yourself to others and instead look at the data the right way. Then I'd compare yourself to yourself each day and week and do things to improve the numbers.
Instead of looking at it this way, I'd instead look at it on a cohort basis over time. A product can have a really bad (total active users)/(total signups) rate historically but actually be in really good shape after iterating for a while. For example, you might be working on your product for 6 months, have 3,000 signups to date, and 300 active users. It would be unfair to measure how things are going by taking 300/3,000 (10%). If you were to look at the same data on a cohort basis, you might find that some group of recent users is stickier than others (because your product changed, or product positioning changed, or something else), and the rate might be something more like 90%.
Products like Mixpanel and Amplitude handle cohort analysis well. You can send in a couple events (Sign Up and some authentic usage metric you define depending on your goals) and pull a cohort analysis. An example: http://aacook.co/retention.png
This chart tells you quite a bit about how you're doing. Week/week acquisition (number of new users signing up) is in the first column, new user activation in the 2nd column (number of new signups who reached a moment of value) and a basic form of retention (number of users coming back at week N).
Instead of looking at it this way, I'd instead look at it on a cohort basis over time. A product can have a really bad (total active users)/(total signups) rate historically but actually be in really good shape after iterating for a while. For example, you might be working on your product for 6 months, have 3,000 signups to date, and 300 active users. It would be unfair to measure how things are going by taking 300/3,000 (10%). If you were to look at the same data on a cohort basis, you might find that some group of recent users is stickier than others (because your product changed, or product positioning changed, or something else), and the rate might be something more like 90%.
Products like Mixpanel and Amplitude handle cohort analysis well. You can send in a couple events (Sign Up and some authentic usage metric you define depending on your goals) and pull a cohort analysis. An example: http://aacook.co/retention.png
This chart tells you quite a bit about how you're doing. Week/week acquisition (number of new users signing up) is in the first column, new user activation in the 2nd column (number of new signups who reached a moment of value) and a basic form of retention (number of users coming back at week N).