Data is the foundation of good marketing. A recently released Econsultancy report, tells us that 92% of digital marketers know that analytics drive actionable recommendations that make an impact. So, as a marketer, you know that data is important, but there’s a clear understanding that the devil (or insights in this case) is in the details (analysis).
In today’s data-rich world, marketers are left to find answers in mountains and mountains of data and often require the help of specially trained data analysts to glean any type of real insight. Once you start talking mobile, the problem only becomes more challenging. The nature of mobile adds more data to analyze that it is fundamentally different than data from other channels. And, it is important - mobile apps are expected to hit $70 billion in annual revenues by 2017 - that is just around the corner!
So, as a digital marketer how can you leverage the right insights from your mobile analytics to improve your marketing efforts? What data should you care about? What are mobile marketers even using analytics solutions to learn about?
Know Where Your Users Spend Their Time
Before we get into how to use a mobile analytics solution, let’s take a step back and understand where consumer spend their time while online.
According to comScore (as reported by Business Insider), time spent on digital devices is growing at a rapid pace, 24% year over year. Almost all of that growth comes from mobile, which saw a 50% jump year over year in the U.S. from 2013 to 2014 (52% for apps).
Of the time spent in mobile, 86.5% is spent inside of mobile apps. Consumers have spoken - they prefer to interact with your businesses via mobile apps. Using a solution built for mobile, that ingests the right data and makes it accessible for your marketing efforts is a critical first step in getting your marketing right.
What Other Marketers Use Analytics to Discover
As a marketer, you primarily use analytics to understand what your customer is doing in your apps or website. It should come as no surprise to learn that marketers want the following in an analytics solution (Econsultancy Survey, July 2014):
- 56%: Tracking behaviors across devices and channels
- 53%: Personalization and targeting
- 49%: Identifying valuable clusters / segments of customers
- 44%: Evaluating the overall customer experience
Tracking Behaviors Across Channels
Attribution of user behavior across channels is the holy grail for most digital marketers. This will allow you to build a single user profile, defined by the behaviors and actions of each per channel, that can be used for great data mining, improving customer experiences, personalized customer interactions, and precise targeting.
For example, if a customer first interacts with your company on a website, but then goes to a mobile device to complete the transaction - does your app, acting off of the information gathered by your analytics solution know this? You should be able to leverage this information about an abandoned cart and tailor an app experience that both delights the customer and improves your revenue.
Personalizing and TargetingMobile analytics solutions allow you to gather large amounts of mobile-specific information that is incredibly useful for precise targeting. We see four types of information typically gathered:
- Mobile Descriptors: These are data points endemic to the channel - things like a user’s geographic location, the default language chosen on a device, device hardware used, the quality of data connection, the operating system, and the version of app.
- Mobile Behaviors: These are uniquely measured for mobile devices and include things like number of sessions (open/close of an app), date of the first session, date of the last session, time spent in an app, and amount of money spent on virtual items (think subscriptions sold via app stores or gold coins found in games).
- App Events: These are events, usually specific and important to your application. For a mobile game, examples could include things like tutorial started, tutorial abandoned, tutorial completed, and level completed. For a retail app, it could include things like item viewed, item saved to cart, cart abandoned, or purchase completed. The possibilities are endless and entirely custom to an individual business and app.
- User Demographics: These are the standard like age, gender, zip code, income, etc.
With such a wealth of data, you can see how easy it would be to build precisely targeted marketing campaigns to virtually any relevant segment of user you care about.
Identifying Valuable Clusters / Segments of Users
Now that you have this information, it is important to be able to use it to find relevant groups of users. And what is great about mobile is that you can get really specific, really quickly just by combining the groups above.
For example, if you are marketer at the Gap and need to grow revenue with the women’s line, you may build this segment (to target later with a mobile marketing campaign): Women / Users in San Francisco / Who opened the app last Saturday / Have spent more than $50 / Viewed items.
Evaluating the Overall Customer Experience
Mobile app experiences are defined by actions taken in the app - things like clicks, swipes, specific pages visited. Mobile analytics solutions can help you identify which of those events or combinations of events will lead to good or bad user behavior.
For instance, you can compare and A/B test things like onboarding, tutorials, or shopping flows. Knowing how different parts of your app contribute to things like app abandonment, failed purchases or infrequent use are key to improving the overall customer experience.
Comprehensiveness Is Key
Above all, marketers need to be able to act on this data. Analytics alone is not enough. You must be able to marry insights to specific marketing tactics. The key to making the most of mobile analytics is knowing that it is not a siloed intellectual exercise. Segmentation without targeted marketing campaigns is a wasted exercise that does not move metrics.
To learn more about how to gain better insights from your mobile analytics, download our whitepaper: 7 Tips for Turning Big Data into Smart Data