According to a recent study, mobile digital media time now constitutes 51 percent of all digital media time in the US.
As more trends continue to lean into the mobile space, mobile is increasingly a business-critical channel in the customer-centric approach competitive firms must take today.
Mobile is the new black—it’s vogue, it’s effective, it’s in demand, it’s everywhere and it is here to stay.
For organizations to capitalize on this digital shift, their mobile app analytics need to be flawless and seamlessly integrate with their web analytics.
Mobile app analytics present many of the same challenges as analytics in the web space—however, extracting and processing user data through a mobile application has distinct obstacles.
Creating a comprehensive and cohesive analysis of the effectiveness of a mobile app isn’t necessarily harder than with a web implementation, since mobile apps give access to much more robust and reliable data points than browser-based applications.
But it is different.
Gathering and evaluating data from a mobile interface requires digital marketers to dig much deeper into the user experience (UX).
The process of really analyzing UX expands beyond the app itself—ranging from the way people discover the app to how consumers actually use the app—and is a frame of mind that revolves around metrics, but never forgets the customer at the center of all business activity.
This blog post examines the metrics you should measure along the life cycle of your app.
Churn, Acquisition, and Defection
In the mobile app world, when it comes to seeing how sticky a mobile application is, we’re primarily concerned with churn, which is somewhat analogous to bounce rate.
The word “churn” refers to the rate of defection.
According to Localytics, 23 percent of apps are only used one time, and 62 percent of users will use an app less than 11 times before defecting. That means that nearly one in four users gives up after the first use, and nearly two-thirds use your app less than 11 times.
Some apps aren’t sticky because of the quality of their content. Sometimes consumers download apps they never intended to use. And certainly churn occurs when the user experience of an app is simply not good.
But with 54 percent of businesses still not using any type of app analytics, according to Adobe, organizations are missing the opportunity to engage and monetize consumers by understanding their behavior.
It is often said that you cannot manage what you cannot measure.
If application owners aren’t measuring what is happening with their apps, then it should come as no surprise that they are losing valuable users due to reasons that they cannot identify.
Challenges of Mobile App Analytics
Many developers and app owners cannot properly track their apps because getting tracking to work with mobile apps can be tricky. Even with the best tools available on the market, it is not nearly as simple as tagging websites.
Keeping tabs on your mobile app implementation presents the following challenges:
- Technical challenges
- Different operating systems
- Challenges with testing
Let’s take a closer look at each challenge.
Many app developers have concerns about implementing analytics because they want to avoid creating what are called “chatty apps”—apps that are constantly sending and receiving networks requests. Adding analytics will inevitably increase the network traffic from the phone, and this will have an impact on the device’s battery life.
Different operating systems
Because the infrastructure varies from one operating system to the next, many companies will use different development groups for different operating systems (e.g. iOS vs. Android), resulting in a fragmentation of code bases. It can be very difficult to tag and extract congruent data from apps that are coded differently. Not to mention inconsistent definitions of metrics between developers.
Challenges with testing
Setting up proxies for mobile apps and ensuring that both the QA personnel and the developers are able to test can be difficult. This slows down the development process because developers are concerned about creating features on their road maps without producing chatty apps, as well as performing unit testing and debugging the analytics solutions.
In spite of these challenges, it is essential to create a mobile app analytics implementation.
There is no more functional way to:
- Measure acquisition of new users.
- Determine how engaged your users are.
- Optimize critical conversions.
- Promote customer loyalty.
- Maximize the value of your app’s life cycle.
Mobile app analytics allow you to interact with your users dynamically, providing the best experience possible for your customers.
The following pages of this blog post provide a roadmap for you to identify which KPIs your analytics implementation should capture over your app’s life cycle.
Where to Start: Tracking and Development Process
The process of developing a plan for implementing mobile app analytics is essentially the same as when creating a web analytics implementation:
Define business objectives
Decide what you want the app to achieve for your business. This may seem a little obvious or tedious, but it is essential. Your goals may be to sell products in an eCommerce store, or to help employees perform their duties more efficiently. Whatever these goals are, record them and determine what success looks like.
Identify Key Performance Indicators (KPIs)
Establish specific metrics of how you will measure your success. These metrics will tell you if you are achieving the business goals that you defined in step one.
Write the code
Insert the tagging elements or write the code that will collect the data you need to measure your success against your business objectives.
Testing and QA
Though technically this entire process is a form of quality assurance (QA), it is still important to audit the final implementation and confirm that the data collection is correct, applicable to your KPIs and providing useful information.
App User Life Cycle
The goal of an app is to create a relationship with the user across the entire life cycle of digital interaction. You need to understand UX over time.
When planning your implementation, consider how you can create metrics to analyze the user experience in each phase of the user life cycle. Each metric will expose one piece of a larger picture.
Potential users search for your app or have any touchpoint with your organization. This can happen in the app store, on your website or even come up in a conversation with friends.
User first opens your app and experiences your offering. You want this experience to captivate your user so they won’t hesitate to return.
According to Localytics, 75% of all app users churn within 90 days. Measure the level of engagement so you can take action in your marketing and app design, transitioning users into the next phase of the app’s life cycle.
Conversion occurs when your business goals are fulfilled, and is often connected with monetization. This indicates loyalty. A high stickiness factor will not only help you maintain current users, but it will also motivate them to participate in customer advocacy, helping you acquire new consumers.
In addition to considering the different phases in the life cycle of a user, it is also important to consider the overall experience for that user.
Considering these phases helps you understand what a user is experiencing, but stepping into the shoes of the user helps you understand what the user expects to experience.
Does your application meet those expectations? How will that affect the app’s design?
Mapping Mobile Metrics
The different phases in your app’s user life cycle are the framework for identifying which metrics you will use in your implementation.
Consider these examples of acquisition metrics:
- Number of downloads
- Ratio of downloads to visits in the app store
- Plays per page
- Number of users generated from downloads
- App store ratings
One of the biggest factors in achieving your business goals is app store optimization. Around 60 percent of new app discovery happens as a result of general browsing in the app store. Apps that are listed as the most popular apps comprise 30 percent of new app discovery.
Because ratings and rankings in the app store are extremely important in acquiring new customers, you want to remain aware of how your apps are performing in this context.
Engagement analytics for mobile apps are a significant tool for you to gauge how involved users are with your app. Standard measurements of engagement are usually counted in the form of frequency ratios, or ratios of events to time.
Ratio of users to time
Ratio of users to time illustrates how many and how often people use your app. An app meant to help people manage their daily activities will consider daily usage as an important indicator. Understanding how your app fits into somebody’s lifestyle can help shed light on frequency ratios.
Average visits per month/week/day
What is the total time spent in your app per user during each temporal period? This can help you judge the intensity of the app’s usage.
Time in app per visit
How long is the duration of each visit? Insights into your user’s behavior in an app can open up important questions to consider. If your app offers a substantial amount of quality content, but time in app is stunted, it might suggest a navigational or usability issue. Or, if you notice that session length begins to consistently decrease over time, it may mean that you need to add new content to keep your users engaged.
A common misconception with this indicator is that more screen views demonstrate higher engagement and therefore higher satisfaction. However, sometimes the successful use of an app means that users quickly get the information they need, avoiding unnecessary screen views. If your user loads a bunch of screens in a futile search for information, they may be hiking your screen views metric but having a negative experience. You don’t want to count a frustrated user as a success just because they loaded a bunch of screens before they deleted your app.
Intra-page events measure how much users are interacting with the elements within a page. These elements may include:
- Text Fields
- Dropdown Lists
- Buttons and more
These events show that your user is engaged with the application.
Critical conversion points
Critical conversion points measure the completion of an objective you hope users will complete within the app. These are often tied to revenue activities.
- User logins
- Soft conversions
- In-app purchases
- Account status screens
Pro Tip: The predictive value of intra-page events is critical to providing a dynamic experience for your user. If you can use intra-page events to predict what a user will do next, you can more fully personalize their experience, either improving that experience or mitigating the risk of defection.
The critical thing is to get users to keep using. You want them to come back a second time and repeat their user journey. You are much more likely to churn a user after the first use than any other use. Strive to understand the characteristics of the people who use your app only one time in order to make that critically important first impression.
You need to map all the above behavior against time. How do these usage patterns curve out over the next 30, 60, 90 days? This will help you see how sticky your application is.
Just as with web analytics, conversion analytics for mobile apps let you focus on the highest value conversion points in your app, such as completing a transaction with a minimum purchase amount.
When an app user performs any action in your app that you have defined as a goal, your analytics should record this as a conversion. There are two foundational places to begin when considering how to define and measure your conversion performance.
Customer lifetime value
Customer lifetime value (CLV) is usually represented as the average revenue per user, abbreviated as ARPU over time. This metric provides insight as to whether or not the average user is providing enough revenue across his or her lifetime to make your app profitable.
When calculating CLV, some analysts also take into account retention as a function of churn rate. Consider the following questions when evaluating your app’s ability to convert:
- How do your customers contribute to your mobile revenue?
- Do they create ad impressions or subscriptions or in-app transactions?
- How engaged are customers with your app?
- How long is the average customer life cycle?
- How many more customers will that one customer bring in?
Drop-off and completion rates provide insight as to whether or not users are experiencing friction as they interact with your app. A faulty button or a functional error in your app could be the cause of people dropping out of their user journey.
- Which screens are they visiting?
- How many screens are they visiting?
- How many screens do they need to visit to come to a conversion point?
- How many people have the same user journey?
- Where do people drop off along the journey?
- How high is your drop-off rate?
- How are your call-to-action click rates?
Optimizing Critical Conversion Points
Gaining a holistic view of the user experience via your conversion analytics reports, as well as A/B testing, allows you to then optimize critical conversion points and improve the customer experience.
Insight to help you reduce points of friction could be the difference between retaining and losing a user.
Once you have gathered your conversion analytics data, you should look at two specific groups of interest:
1. The group that achieved the desired objective or conversion
2. The group that could not overcome friction in the app and defected
It is important to consider both of these groups—the first because it is critical to understand what drove this group to continue in spite of any friction, and the second because you want to help reduce friction in order to increase your rate of usage.
Understanding the goals of the first group can help you maintain those aspects of your app and reduce friction for the second group.
Group #1: The converted
Beware of confirmation bias.
We all suffer from something called confirmation bias. This is where we expect a certain type of result, so we go looking for evidence of that result.
This is the frame of mind that might cause you to think that a lot of screen loads indicates high engagement, when, in fact, it might indicate a frustrated user struggling to find the information he or she is looking for.
Make sure to consider the activity of your most engaged users objectively because it is easy to make false assumptions as to why they are using your app successfully. Try to consider them in the following manner:
- What are their characteristics?
- How can we segment these users?
- Are there important subgroups within these successful users?
- What separates these users from everyone else?
Keep in mind that the indicators that you might use to segment your users may not be purely behavioral.
These indicators may be determined by a variety of factors, such as engagement scores where you measure the number of screen loads or the number of clicks on a specific button.
You can also consider workflow points, where your users increase their scores as they reach certain milestones along the user journey.
Once again, beware of confirmation bias. You have to let the data from your analytics inform the critical points.
There are certain characteristics that make some users more likely to get over their initial indecision and start making those critical first in-app purchases. Identify the catalysts that help your users get over that hump and initiate a pattern of purchasing.
Group #2: The defectors
Once you have identified the elements of your app that increased a user’s chance of converting, consider those users who defected:
- What are some of the friction points users experienced along the way?
- Where did they experience this friction?
- How can you lubricate the process to make it easier for users to accomplish their goals?
Sometimes apps are designed around the structure of their database, or they might have the same functionality as a corresponding website. This can be problematic.
Mimicking website or database structure (such as a high number of form fields or passwords with special characters) can complicate the process for a mobile app user.
Critical conversion points are important milestones for a user and essential to the objectives of your app. It should be your priority to simplify the conversion process and reduce friction for the user.
Loyalty analytics allow you to assess the level of commitment users have towards your app. They include metrics such as:
- App reviews and referrals
- Social media endorsements and interactions
- Customer rewards and promotions within your app
Loyalty analytics can really illuminate the elements of your app that most resonate with your users, providing actionable insight into how to engage across multiple channels.
As you analyze your data, it is important to not only consider the overall numbers, but also to segment them down according to various engagement and conversion criteria.
Consider the entire life cycle of a user as you work in campaign attribution.
Traditional analytics have been very focused on immediate conversion. As a result, analysts tend to attribute a conversion to the last piece of content the user saw. This way of thinking discounts the rest of the experience of the user, detracting from the value of the content that the user encountered along the way.
It is important to remember that, ideally, the user is engaged in a long-term relationship, so identifying the specific positive experiences across the entire life cycle of a user will help you nurture that relationship and really increase the ROI of your applications.
Requesting reviews, rating, and referrals
Asking users to recommend your app to their friends the first moment they launch will probably only get you a bunch of two-star ratings.
You want to make sure that you are prompting people to engage socially with your app when they have been successful with it. When people have a high level of satisfaction they will give more positive feedback.
Rewards and in-app promotions
Anyone who has worked in a direct response marketing capacity will tell you that there is a sweet spot for conversion.
When it comes to mobile apps, getting the user to pop the bubble and make that first in-app purchase is critical. Once that happens, one purchase leads to another. A follow-up promotion prompts the next purchase and it moves forward.
People are creatures of habit and promotions like rewards programs help create habits around your application.
But in order to build this type of loyalty, you have to understand the user’s experience with your app. If they are having a negative experience, offering promotions and rewards won’t get you very far.
Beyond measuring the behavior of your users, it is important to continually monitor your app as well as your analytics implementation to ensure functionality.
Mobile app analytics allow you to continuously perform quality assurance following the release of your app. Consider the following metrics for measuring the overall user experience.
- How performant is the app?
- How long are startup load times?
- How long are inter-screen load times?
- How long are load times for calls-to-action?
- Does the app have chatty analytics that cause battery drainage?
- Do we receive reports of when our app crashes?
- Does our app function on all devices?
User journey functionality
- Can users get from beginning to conversion seamlessly?
- What roadblocks do users face along the way?
Collect the Right Data, and Collect the Data Right
Gathering data isn’t worth anything if the data isn’t correct. Ensuring that your data accurately reflects user behavior and experience is crucial to making effective data-driven decisions.
Automated validation tools like ObservePoint’s AppAssurance help you keep your data accurate and preserve the functionality of the user journey.
There is nothing more important than keeping the user happy, and AppAssurance can help you ensure that your data is accurate and actionable. That way, you can make informed decisions towards better configuring the user experience across the entire life cycle.
Learn more about how ObservePoint can help you with your analytics testing by scheduling a demo today.
About the AuthorLinkedIn More Content by Sun Sneed