developeranalytics [dA] | blog

We had a great time at InterPlay last Thursday! Special Thanks to Bret Terrill for inviting us

Check out the first 25 minutes of our keynote here.

Brief Summary:

• Page View (Impression) Multiple
  average # of page views per daily active user

  To focus the discussion, we introduced this metric in viewing social games.

• Social Gaming is HOT: Compared to Messaging apps (3x page view multiple) and Dating apps (20x multiple), social gaming apps are seeing, on average, a 50x multiple compared to other categories.

• Relative Metric Comparisons Matter: It’s not just about “Daily Active Users” (unique visitors / day). It’s not just about “Page Views” or “Avg Page Views per Daily Active User.” Different gaming apps do better depending on which metric you are looking at. It’s about looking at all these numbers in relation to the rest to see the bigger picture. At dA, we are all about understanding and analyzing the global data set.

• Increased gaming complexity: All apps follow an app life cycle - the rise, the plateau, the fall. The rates of growth and decline vary immensely depending on the nature of the application. At dA, we are seeing more complex, deeper game mechanics develop and evolve over time on the Facebook Platform, all of which are leading to higher engagement.

• Shift in traditional gaming audience: Social games are targeting a much broader audience than ever before. Yes, there is a 37-year-old woman in Ohio who is petting her virtual pet for 3 hours each day.

• Time to focus on Gen 3.0 Games: We talked about Gen 1.0. We’re seeing the rising players in Gen 2.0. Now, it’s time to focus on today and what will be coming in the future.

What’s Next

- We’ll be speaking on June 5th at the Social Media Business School event in LA. Don’t worry - we never give the same talk twice. New insights everytime.
- We’ll be relocating to San Francisco!
- Yes, per the Q&A discussion at Interplay, we are working on something big and an extension of dA to be released in the upcoming months. Stay tuned for the details

We spoke on the analytics panel at the SocialMedia Business School event last week in SF. It was a smaller, close-knit crowd, but there were some great discussions ranging from analytics to brand advertising. Check out this blog post for a summary of notes.

Just wanted to re-highlight a few key points we touched on in this panel:

• Virality (”k-factor) as the new metric: What is fundamentally different between social networks and the web? It’s the power of the social graph and friend relationships in itself. At dA, we measure the “k-factor” of apps. K-factor is the average number of friends invited by each user who already is an app user. So, a k-factor of 1 means that your app essentially is on a path to double (since each user is inviting on average another user).

• Moving the “Referral” stage forward: How do you maximize virality? By focusing on the referral stage as the primary driver for app growth.



At dA, we like to think about traditional “frameworks” in novel ways. In this case, what if you took the “Referral” stage and moved it forward — even before a user is activated? This is essentially what “forced invite” apps on Facebook do, and it’s why they “work.” By doing this, these apps maximize the number of the friends each user touches. Once this stage is maximized, each proceeding stage (retention, for instance) is maximized as well. The more friends that are referred, the more there are to be engaged.

Of course, forced invite apps are no longer permitted on Facebook. Even still, for the new era of apps, moving referral ahead of retention is still a highly effective technique.

• Importance of seed groups for viral growth: At dA, we are also app developers — purely to better improve our analytics product offerings. Why? We believe it’s critical to understand the pain points of developers as well as understand viral / engaging strategies used by applications in order to produce the best tools for developers to use. One case study we did recently was take two identical applications and seed them from two different user bases. The outcome? 20,000 vs 500 daily active users. Bottom line: your users matter.

Last week, we Skyped our way to India to speak with Rajat Agarwalla of Scrabulous. Rajat and Jayant have turned their email version of Scrabulous.com into a very engaging, Facebook game, capturing a large fanbase. They’ve spent a great deal of time on building a strong user community and listening to feedback. For more details behind the Scrabulous story, check out our Scrabulous case study.

In our interview, Rajat shared some of his thoughts on analytics pertaining to the Facebook space.

“Well, in the Facebook space, the number of installs isn’t really that meaningful. Instead, we really track app activity, such as return usage. In fact, even metrics measured on a daily basis really aren’t that useful.”

Bingo! The insight we’ve gathered from testing our own analytics suite at dA has showed very cyclical patterns. That’s why at dA, we are working on changing the way we typically “view” Facebook applications.

Even “daily active users” is not meaningful enough. Because of the viral nature of apps, most daily active users could just be “new” users rather than returning. Our direct measurement analytics tool will be focusing on social networking-specific metrics like virality (”k factor” - for each user, the number of new users resulting from that user) and engagement (return usage). Over the next couple of weeks, we will be sharing more details on this so stay tuned!