#inactive users

[welldonna]

Pro-tip: If you go under your "Following" tab on your blog, you can see how long ago someone has updated. And if the blog has "-blog" at the end of it, that's a good indication that it is inactive. I'm seeing blogs that have not been active in 4–6 years. Yikes. 😬 Will probably log in at a later time to delete them.

I really don't know why social media apps don't have a feature that automatically deletes inactive accounts after a certain about of years.

[lookalikeswithdifferenthardware]

Artificial Intelligence - If someone is deemed missing their records are essentially being automatically deleted as they are not acquiring results when attempting to index them

[ngodingkode-blog-blog]

Inactive users eTwinning

Results of the eTwinning Survey: Inactive Users amongst Maltese eTwinners

View On WordPress

[nuzzlenarry]

Xkit doesn't seem to work with finding inactive followers. And it takes ages to find people who haven't been online for maybe more than 2 weeks. But, I have something that makes it a little bit easier than checking every blog. If you go to your followers, just press ctrl+F and you get the search thing. Just type in week, and if it becomes red you can skip to the next page, it still takes a lot of time but like that you don't have to check every single one!

[cardboardisforjumping]

Finding it really hard to push the unfollow button to any Hiddles related blogs, even though some of them have been inactive for months

[poppa-soju]

me on mangabullet: can i touch ur butt?

mangabullet:

[hoista]

How to use analytics and segmentation to find value from users with no account

 I was reading this blog post by Fred Wilson and it occured to me that engaged users are not just about people who create accounts, regularly log in and contribute. But also about the different cross sections of people who are engaging with your app on their first visit, or returning visits on a passive level.  The gist of the linked blog post is about twitter and how many people visit it in a month.

400M active users per month

100M users who log in

60M users who tweet

Usually, the 300M people who didn't create an account are not measured as active users or engaged users. If we ignore it, we are missing out on the potential insights of those 300M users if we are not measuring correctly. If we look only at the drop-out points along the account creation funnels and see them only as failed conversions we are ignoring them as active users and failing to utilise the value they are gaining from just observing. These 300M should be segmented further (e.g. to returning and non-returning visitors) and we should analyse what they are doing to give us insights into their behaviour.

How About Mobile Apps?

One key difference between websites and mobile apps is re-discoverability. For many people, if they don't like an app, they will delete it. For website, a new blog post, a link from a trusted source, a search engine can bring people back to the website, but for apps, once you have deleted it, the hurdles to re-find the app and re-install it are much higher than for websites. This poll shows that 26% of people uninstall an app after only using it once.

For mobile apps that require an account before being able to use the app, this can be a problem. The app could be redesigned to provide value to a user before they created an account. Then we can segment the groups and do some deeper analysis, and potentially reduce the number of app uninstalls. This opens up the chance to retain these "unconverted" users.

What are we measuring?

We are segmenting the users into different levels of engagement, in a similar way to how games can segment people into different 'levels' based on their progress in a game. This way we can discover different types of behaviours and insights to potentially convert to higher value actions.

The segments we are effectively using here are

Used the app once only

Used the app more than once (or on multiple days) but never created an account

Created an account

Contributed to system 

These segments gives us insights into the behaviour of each group, and allows us to optimize the app for each group to increase retention. Engagement is the key, changing the engagement into a revenue event or some other high value event can come later. The more people you keep engaged in these channels the more possible high value events that can occur. An example is referral, people who may not have created an account but are regular passive users may go on to contribute to its organic growth.

Secondarily, high value events for each of these segments may be very different. They are different user groups with different behaviours, what they find high value may be different for each group.

How do I track it and what actionable insights can I get?

Check the number of people who return to your app. Some analytics tools, such as Flurry can provide you with the number of users who are one-session users. Compare this with each iteration of your app and see if you can reduce the % of people who are one-session users. Segment this group so you can drill down into their behaviour. What events are they doing?  What events are they not doing when compared to returning users who have not created an account?  Can you improve the app to make one-session users less likely to leave? Some examples of things you may want to optimize based on what you discover -

Improve ways for non-account owners to refer your app or content.

Increase visibility of non-account owners to account owners. 

Increase accessibility of public contributions by account holders to non account holders

Just by providing more value at the beginning of your app, can help you to retain users and refer users. By identifying, segmenting and drilling down into their behaviours and comparing their behaviours to 'active users', it should give you insights on what to focus on to improve your app (or website). By engaging 'non-active' users, it's possible to increase value to 'active' users as well.

Image courtesy of Flickr, Ed Yourdon