| page.title=Understand the Value of Your Users |
| page.metaDescription=Understand what makes users come back to your app and improve retention. |
| page.tags="analytics, user behavior" |
| |
| @jd:body |
| |
| <p> |
| In-App Analytics will help you understand user behavior and ultimately user |
| value over time. Fundamentally, users are people — and no two people are |
| exactly alike. You can explore what makes your different groups of users |
| unique and, in turn, how these groups respond to your app content, features, |
| and monetization strategies. The more you understand about what your users |
| respond to, the better you can tailor your apps to meet their needs. |
| </p> |
| |
| |
| <h2 id="cohort">Assign Value to User Goals</h2> |
| |
| <p> |
| Different types of developers value their users differently — and |
| different types of users have different values. Google Analytics gives you |
| the power to value your users in the way that makes the most sense to you. |
| </p> |
| |
| <p> |
| By using Google Analytics goals, you can define specific actions in your app |
| that mean the most to your business: perhaps it’s important that your users |
| reach a specific screen in your app or that they spend a designated time |
| playing your game. Perhaps you define a goal based on whether or not a user |
| completed a certain event (like completing a level). |
| </p> |
| |
| <p> |
| Whatever the method used, you can assign a monetary value to a goal in order |
| to put a dollar value on an action. Perhaps it’s worth $3 if a user completes |
| a given level or $.50 if they sign up with an account. By assigning value to |
| given behaviors, you can really dig into the data to understand your most |
| valuable users. |
| </p> |
| |
| <p> |
| Google Analytics also lets you view Revenue per User for transactions in your |
| app (such as in-app purchases). Pair this data with segments to drill down to |
| find your most valuable users. |
| </p> |
| |
| |
| <h2 id="audiencereporting">Know your users with Audience Reporting and Demographic |
| and Interest reports</h2> |
| |
| <p> |
| Google Analytics’ <strong>Audience Reporting</strong> section highlights a |
| wealth of data about your users’ characteristics: what app versions they’re |
| using, what devices they’re on, where they’re from, and what they're |
| interested in. Among these, the Active Users reports highlight how users come |
| back over time. |
| </p> |
| |
| <div> |
| <img itemprop="image" src="{@docRoot}distribute/analyze/images/active_users.png"> |
| </div> |
| |
| <p> |
| Google Analytics’ <strong>Demographics & Interest</strong> reports highlight |
| information about your users gathered using Google Analytics’ extensive reach |
| in apps. See the Gender & Age breakdown to discover the demographic |
| characteristics most common among your users, or take a look at the Interest |
| reports to see what interest categories entice your users. |
| </p> |
| |
| <div> |
| <img src="{@docRoot}distribute/analyze/images/demographics.png"> |
| </div> |
| |
| <h2 id="change">All Things Change with Time, and So Do Your Users</h2> |
| |
| <p> |
| Getting users to install and open your app the first time is a big accomplishment; |
| however, it’s only the first step of what is hopefully a long and prosperous |
| relationship. The best apps aren’t just the ones with the most downloads, they are |
| the ones that have users coming back day after day, month after month, and year |
| after year. |
| </p> |
| |
| <p> |
| Google Analytics takes a user-centric approach to reporting to help you explore what |
| keeps users coming back. <strong>Cohort Reporting</strong> allows you to see which users |
| come back over time and when usage tends to fall off. You can easily take this same |
| information and overlay it on any other report. |
| </p> |
| |
| <div> |
| <img src="{@docRoot}distribute/analyze/images/cohort_reporting.png"> |
| </div> |
| |
| <h2 id="measure-value">Measure Value over Time</h2> |
| |
| <p> |
| Analyzing retention is a great way to ensure users stick with your app and come back day after |
| day. With <strong>Lifetime Value</strong> reporting, you’ll get a full picture of these users’ |
| value over time. To get the most out of this report, it’s important to start with a clear |
| definition of what a user’s value means to you based on your business objectives. |
| </p> |
| |
| <p> |
| Once you’ve defined the value, you can access the report to measure certain variables such as |
| revenue per user and number of screen views per user over a period of 90 days. For example, if |
| the goal of your app is to get users to purchase virtual or material goods, you’ll want to use |
| this report to get a clear view of when they make a purchase and how much they are spending in |
| your app over time. |
| </p> |
| |
| <p> |
| Lifetime Value is a key metric to use to measure the effectiveness of your acquisition |
| campaigns. If your cost to acquire a new user is higher than the average value over time, |
| you might want to optimize your campaigns to meet the lifetime revenue they generate. Lifetime |
| Value is particularly valuable if you offer in-app purchases, but it can be applied to |
| discovering many other useful insights, such as number of times they open your app, total |
| number of screens and goal completions. |
| </p> |
| |
| <h2 id="cohort">Segment Your Data</h2> |
| |
| <p> |
| Looking at aggregated data helps you understand overall user behavior trends, |
| such as how their purchase patterns change over time. However, in order to |
| understand why purchase patterns changed you need to segment your data. |
| </p> |
| |
| <p> |
| Segmentation allows you to isolate and analyze subsets of your data, based on |
| specific attributes. For example, you might segment your data by marketing |
| channel so that you can see which channel is responsible for an increase in |
| purchases. |
| </p> |
| |
| <p> |
| Drilling down to look at segments of your data helps you understand what |
| caused a change to your aggregated data. All reports in Google Analytics |
| provide for segmentation of your traffic. For example, each row in your |
| Language report shows how a specific segment performed. This lets you compare |
| different segments and understand which languages are bringing in the highest |
| value traffic. |
| </p> |
| |
| <div> |
| <img src="{@docRoot}distribute/analyze/images/language-report.png"> |
| </div> |
| |
| <p> |
| Here are some common segments that you might want to consider when looking at |
| your own data: |
| </p> |
| |
| <ul> |
| <li>Date and time, to compare how users who visit your site on certain |
| days of the week or certain hours of the day behave</li> |
| <li>Device or app version, to compare user performance on different |
| operating systems or app updates</li> |
| <li>Marketing channel, to compare the difference in performance for |
| various marketing activities</li> |
| <li>Geography, to determine which countries, regions or cities |
| perform the best</li> |
| <li>Customer characteristics, such as repeat customers vs. first-time |
| customers, to help you understand what drives users to become loyal customers.</li> |
| </ul> |
| |
| <p> |
| To use segments, click <strong>Add Segment</strong> above the report on any |
| data set you’re interested in breaking up. See the 15 System segments that |
| come with any app profile; these are default segments that allow you to do |
| basic analysis on elements like New Users, Android/iOS Traffic, or Tablet |
| traffic. If you need to dig deeper into your data, you can build a custom |
| segment by clicking <strong>+New Segment</strong> in the top right. Using any |
| combination of dimensions and metrics, you can create segments specific to |
| your business. The combinations of criteria are so extensive, hundreds of |
| thousands of permutations are available. |
| </p> |
| |
| <p> |
| For example, for a report across all sessions in a date range you may choose |
| to include only users whose cumulative revenue across all sessions in a date |
| range is greater than $100; or only users who viewed a specific screen, then |
| completed a specific event, but never actually made a transaction. |
| </p> |
| |
| <p> |
| Alternatively, you could include only sessions that were the result of a |
| specific advertising campaign or only sessions that resulted from a specific |
| campaign AND resulted in a goal completion. |
| </p> |
| |
| <p> |
| Another way to generate segments is to import from the gallery. When you |
| click Add Segment, click Import from gallery (next to +New Segment). Using |
| the Gallery you can import segments that other businesses have found useful |
| — maybe you're interested in importing segments that pertain to |
| engaged traffic or mobile commerce. Choose from hundreds of segment packs |
| to find the ones that make sense for you. |
| </p> |
| <div> |
| <img src="{@docRoot}distribute/analyze/images/segmentation.png"> |
| </div> |
| |
| <p> |
| Segmentation is a powerful way to slice and dice your data in order to unlock |
| insights about users and their behavior. Use this information to improve your |
| app and find more people that resemble your high-value users. |
| </p> |
| |
| <h2 id="cohort">Understand What Makes Your Users Tick with Further Analysis</h2> |
| |
| <p> |
| Using the power of segmentation, you can perform very sophisticated analysis |
| on the types of users using your app — are your buyers concentrated in |
| a particular geographic area? Are users who visit a certain screen getting |
| stuck and abandoning your game? Are there certain behaviors that lead to more |
| conversions? What crashes are having the most impact on your revenue? |
| </p> |
| |
| <p> |
| Understanding what properties make up an engaged and monetized user base is |
| important for developing a strategy to find similar users and for building |
| users’ experiences based on their behavior. |
| </p> |
| |
| <div class="headerLine clearfloat"> |
| <h2 id="related-resources"> |
| Related Resources |
| </h2> |
| </div> |
| |
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