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With Big Data Come Big Responsibility
As data swelling continues, the challenge becomes extrapolating the most important metrics and interpreting their insights

Startups collect data. They collect pageviews, visits, downloads, clicks, conversions, registrations, users, active users, uniques, time spent on site or in-app, content created or consumed, sessions, purchases, upgrades, subscriptions, shares, likes, tweets, posts, pins; the list goes on. As these numbers grow the data becomes big, it begins to swell. As the swelling continues, the challenge becomes extrapolating the most important metrics and interpreting their insights.

The scope and scale of analyzing and sharing these metrics is seemingly endless. Often, the tendency is to rely on top-line numbers to communicate trends and themes. However, these top-line numbers do not always communicate the full picture. Instead, when presenting data, companies should focus on the combination of metrics that are core to their business and give a deep understanding of their products and their audiences.

At the D10 conference last week Mary Meeker presented her annual Internet Trends report. With the report, Meeker uses some incredible metrics to outline a number of undeniable trends impacting the Internet.The metrics on each slide are calculated and deliberate. Diving deeper into the numbers, one of the slides that piques some interest is the following, slide 27:

 

Examining the slide, the definitions of Monthly Active User (MAU) and Daily Active User (DAU) are important:

  • MAU — any unique user who uses the Facebook app in a given 30 day period
  • DAU — any unique user who uses the Facebook app in a given 24 hour period

Even more important is how DAUs relate to MAUs, which is very often represented as DAUs as a percent of MAUs ratio.  This ratio tells us about an app’s retention rate. The following two extreme scenarios are illustrative:

  1. Every single user of the app is using the app every single day. This would represent a retention rate of 100% and a DAU/MAU ratio of 1.
  2. Every single user uses the app only once and never again. This would represent a retention rate of 0% and would initially show a DAU/MAU ratio of 1 (Day 1) but rapidly progress towards a ratio of 0.

Slide 27 above shows Viddy’s Facebook MAUs and DAUs, with the heading “Facebook Open Graph Distribution — Examples of Onboarding 17MM New Users in 7 Days!” The headline is pretty impressive and the massively up-and-to-the-right blue line looks pretty positive. However, the yellow line is seemingly telling a different story. If users were coming back every day, the yellow line would track the blue line closely. However, the fact that each day’s DAU numbers track closely to the daily increase in MAUs suggests that users are rarely coming back.

Here’s the chart of DAUs as percent of MAUs over nearly the same period, starting when Facebook began to highlight Viddy in the news feed:

 

The trend here is looking much more like scenario #2 than scenario #1. As a frame of reference games like Farmville, CastleVille and Zynga Poker routinely maintain a DAU/MAU ratio of between 18% and 25%. Facebook itself has a DAU/MAU ratio of about 57% (as of December 2011).

The right metrics are unique to every company and the responsibility of communicating great engagement can be more difficult than collecting the data itself. As this data swells, it’s easy to get lost in its abundance. All this is to say that metrics can tell many stories and often they can be deceiving.

____

This is a cross post with DigitalPuck.ca by Bram Sugarman, who can be followed on Twitter @bramsugarman. Bram is a member of the investment team at OMERS Ventures. Prior to joining the team at OMERS Ventures, Bram spent time working  as a software engineer, product manager, and data analyst at Electronic Arts, CryptoLogic, and Uken games.

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