New technology is emerging that does more than just look at mobile devices‘ locations — it tracks how a company’s mobile app is performing in comparison to its competitors’ mobile apps. The resulting analytics give insights into the specific vertical market and product performance.
“We initially built a big data platform that collected information and processed it into an aggregated data store that mobile carriers and cable companies in the US could use,” said Alexander Zaidelson, vice president of product management for wefi, which delivers analytics on mobile app access and performance. “We collected a lot of information about what was going on in an individual user’s mobile device, and we focused this information gathering around three dimensions: the location of the device, the networks that the device was connecting to, and the applications that the user of the device was accessing and using.”
At this point wefi realized there were companies in many different industry verticals that would potentially be interested in the information.
“You could use this information to determine how many users were using Facebook — or if you were a media publication like The New York Times, you could query the information to determine how many New York Times subscribers were accessing Facebook or The Washington Post from Central Park at 3 pm,” said Zaidelson. This type of competitive intelligence would then provide insights into the end user experience, and how long (or exclusively) you were capturing your customers’ mobile application market share.
Other use case examples for mobile apps’ analytics
Let’s say you are a transportation company like Uber, and you want to understand the similarities and differences in customer behaviors in different US cities. You look at the mobile app access numbers of your users, and also look at the number of times they are using their mobile devices to access competitors’ applications. You notice that usage patterns for customers in San Francisco and New York City are very similar, but that you’re winning fewer customers in Austin, Texas. From here, you can move the data into marketing for more detailed analytics and strategy work for Austin.
You can also predict the likelihood of when a user will stop using your mobile app; this is particularly useful in the gaming industry, where the competition between game purveyors for market share is very intense. By monitoring mobile access to different games, gaming companies can use these big data analytics to predict when it is most probable that they could risk losing a customer. A typical scenario occurs when you see from incoming data that a customer has installed three new games; this is a situation where the customer is likely to stop using your original game, and an opportunity to connect with him via a message that can help to ensure his continued engagement with you.
The importance of customers’ engagement rates
“Looking at the engagement rate of customers is extremely important,” said Zaidelson. “For example, when we look at online media, on any given day the Bible is the most popular source that mobile devices are accessing. After this, you see publications like dictionary.com or Amazon Kindle. If you are a publication like The New York Times, you can superimpose your audience on these statistics to see if your readership reflects these tastes, or if their tastes are different. The analytics can tell you a lot about your readers’ preferences, and also assist you in improving the relevance of your product.”
Note: TechRepublic and ZDNet are CBS Interactive properties.