#gooley

Meet Stonehead and Gooley!

See Shaffy above.

slime cuties are pretty top tier.

If most of your users are consistent returning users, as you increase the period from 7-days to 14- and 30-days you'll probably see the number of sessions and active minutes increasing. This is because your users may be active in your app for 30 minutes in a week, 45 minutes over 2 weeks and 90 minutes in a month. Think of Facebook-type usage - where a single user is consistently returning day after day and week after week so the per-user time is adding up. If most of your users are new or infrequently-returning users (e.g. many e-commerce sites or crowdfunding sites) then you will probably see a similar time and number of sessions as you expand the period. This is because you don't have much overlap for users across long periods of time. For example, I visited Kickstarter once this week to fund a campaign and spent probably 10 minutes, but in the past month I've still only visited Kickstarter once for 10 minutes, and in the past quarter I've probably still only spend 10 minutes on their site. So the per-user time isn't adding up even though there are many users in any given week.

You may notice that we removed the total event count from each of the rows. The only metric that's less useful than the total count of an event might be a count of total pageviews. For the rare events where a total count is directly related to the success of your business, it's likely that those events either have a revenue component or are tied to billing in some way (e.g. messages sent in a marketing automation system) and those events are included in other analysis sections. Instead you should be focused on the portion of your active users who are triggering the event, and how many times the average person uses it.  These numbers, coupled with looking at the change from the previous week or month, show you explicitly how user behavior is changing in your product and help to eliminate deceiving results.  In the example above looking at a 7-day period of activity, we can see 3 red areas of concern. First, the portion of users who are downloading preview images decreased by over 5%. We're not looking at the absolute decline in number of users downloading, but rather a decline in the percentage of active users who downloaded. This is important because most businesses are steadily growing week over week and will nearly always have more users triggering events, but as behavior changes the proportion of users who use one feature compared to another may be changing. That's what we aim to highlight for you, instead of just showing you an all green dashboard because you've added 10% more users this week. The other two red areas of concern are in the per user metrics for downloads and purchases. We can see that this week, the average purchaser bought a single image - but last week your typical purchaser purchased two images. A single week may be too short of a period to get concerned for this decline and you may zoom out to a 14- or 30-day period, but if you recently made changes to the purchase flow or other potentially significant interfaces, you may want to take a closer look.

In the example above, you can see that about 2600 users across 1100 accounts viewed at least one report this week. The typical user viewed 3 reports in a week, but the median for accounts is actually 12 reports per week. This will help you to discover the distribution of activity on a user-by-user basis as well as account-by-account. For instance, you may see certain features which are being used by many users, but only a handful of accounts. This should highlight an opportunity to spread the word about that ability of your app - because the accounts that have discovered it are using it heavily. It's also a good opportunity to chat with those accounts to learn why they're power users, so you can leverage those real-world benefits to promote among your other accounts.

You can now build and share dynamic reports for your people or accounts. Simply click the New Report button at the bottom left of the Preact app and go to town. Some ideas for reports: users who haven't yet used a new feature, most engaged users who were active in the past day, users who have started an activity but never finished it, your oldest users who have been active within the past week, etc.