Main Metrics. Sticky Factor
What is Sticky Factor or Stickiness Factor, how to measure it in a game, how to improve it and evaluate users’ loyalty.
Published
27.11.2019
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devtodev

New users install your app every day. Some of them will never use the product again, but some will do it every day. Your income highly depends on how they are going to behave in your app and how much they are interested in it. Because the more loyal they are the more they tend to pay.

We can evaluate users’ interest, loyalty and degree of engagement by using a number of metrics and Sticky Factor or Stickiness Factor is one of them. We can use this metric to evaluate how stable our user base is and how regular they go to our app. We usually calculate it as a number of Daily unique Users divided in a number of Monthly unique Users.

 Sticky Factor = DAU / MAU * 100%

But sometimes we use DAU/MAU ratio.

Sticky Factor graph

Let’s take a closer look at how this metric works.

Let’s assume that 1 000 unique visitors open an app every day. It means that DAU of this project equals 1 000. If these are different visitors every day then project’s MAU is going to equal 30 000 and the Sticky Factor will equal 1 000 / 30 000 = 3%. This is the lowest value this metric can accept and it shows that users do not stay in the app and that it’s Retention Rate is, most likely, low and it doesn’t have a user base required to generate income.

Read more: 70 links to become a better game analyst

The reverse situation is when people use the product every day and then its DAU equals 1 000, MAU - also 1 000 and the Sticky Factor = 100%. This is a dream that will never come true of course and this metric usually highly depends on the product's genre and it’s intended use. For games, for example, Sticky Factor around 20% is considered to be good, but for social networks and messengers it is often around 50%.

 In devtodev we previously analyzed games’ Sticky Factor and we found out that it varies between 4 and 37%. On average it makes exactly 18%.

Sticky Factor, as well as Retention Rate, characterizes audience retention and shows the probability of a newly acquired user to stay in the product. It also shows how good this product retains or “hooks” users.

Read more: Man Metrics. ROI

It is reasonable to control this metric after certain time periods for each product to evaluate the impact of changes made, compare it for different users’ segments and estimate it during A/B tests (video) to get a better understanding what elements influence users’ interest.

 If you want to increase Sticky Factor, you can apply the same measures you use to improve Retention Rate because your task is to get a user interested in the product and to make them use it again and again. The following can be helpful:

  • Acquire target audience initially interested in your product and its functions.

  • Create valuable and up-to-date content stimulating a user to come back to the project again and again.

  • Provide convenient interface with lots of useful instruments and features.

  • An app should have something for sharing and somebody to share and discuss it with.

  • Reminders about the product and useful changes (in the form of e-mails or push notifications).

and so on.

Despite Sticky Factor is not directly associated with income, it characterizes audience’s loyalty and activity, which, in turn, directly affects monetization and income. It means that the more stable and involved your user base is the faster product’s audience forms and grows. The bigger it is the more payments users make and hence the product income grows. devtodev research shows that there is a correlation between Sticky Factor and income (it accounts for 50-60%), which supports the idea of this metric’s influence on product’s financial metrics.

Read more: Main Metrics.Download

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About devtodev

devtodev is a full-cycle analytics solution developed by games industry professionals specifically for game developers that helps you convert players into paying users, improve in-game economics, predict churn, revenue and customer lifetime value, as well as analyze and influence user behavior.