To celebrate the release of our brand-new user query tool, we’ve taken a deep dive into the burgeoning field of mobile user analytics. Whether you’re looking to maximize bookings through your travel app or you’re seeking ways to improve daily active use and revenue for your gaming app, you’ll find understanding patterns in your users’ behavior has never been easier.
First, Let’s Define Mobile User Analytics
Whenever your app gets launched or re-opened from the background, Appsee counts this as a session. If the app closes, crashes, gets interrupted, or gets sent to the background, this ends the session. If the same user opens up your app a second time, a new session would start.
There are certain events within your app you should always care about, such as first-time registration or a payment screen checkout. But what if you did want to connect all these user sessions together? Maybe you’d like to learn more about the behavior of your high-spending app users in a particular region of the world, who launched your app at least once a week for two years? The reality is that few analytical tools would manage to stitch this information together in a comprehensive way.
But guess what, we’ve done it! Welcome, User Analytics. Appsee’s new user reporting and query-builder will enable you to do just this. Queries are endlessly customizable and provide the means for building multi-layered and complex portraits of individual users since the beginning of time.
Understanding User Properties
With Appsee’s mobile-centric User Analytics, you can make use of a large number of out of the box search query properties. You’ve also got the option to create your own custom properties for even more highly tailored and advanced search queries.
There are three broad options here:
1) Choose to filter users based on specific custom characteristics like ‘paying’ or ‘subscribed’ (setUserProperty).
2) Perform searches based on incrementally growing and numbers-based properties such as. ‘amount paid’ (incUserProperty).
3) Provide further context to your searches with custom-dimensions like ‘subscription type’, ‘gender’, or ‘login method used’.
Mobile User Analytics – Why Care?
As an active player in a mobile app market that’s predicted to grow by 385% through 2021, you can’t afford to be complacent when it comes to delivering a seamless mobile experience. You’re already competing with roughly 10 million apps; CMOs around the globe are increasing budget allocations for marketing technology, and users are becoming ever-more complicated, and quick to abandon a less than ideal experience.
In order to really get to know your users and what they want from your product, you’ve got to get behind the numbers. By now, qualitative analytics is a no-brainer – if you’re not already using a tool that gives insights into behavior and the ‘whys’ behind particular user actions, you’re behind the curve.
User analytics is the next rung on the qualitative analytics ladder. You’ll find it’s the easiest way to run user research for your mobile app – simply log in and drill into any user scenario to learn more about your users’ lifetime of interaction with your product.
User Queries by App Category
To bring our user analytics to life, we’ve put our heads together and come up with the following category-specific scenarios you could plug into our new Appsee User Query Builder. Read on to learn more.
1. Gaming Apps
EXAMPLE USER QUERY: “Find users that have completed 3 levels and up and spent more than $100.00 within my game since January 1st 2018”
In 2018, games accounted for a whopping 74% of all consumer spend in the app stores. Further, mobile games represent the fastest growing sector of the entire games market. The opportunity for monetization is huge but with a growing number of high-profile newcomers like Helix Jump and the relaxing of the gaming freeze in China, competition for user acquisition is likely to heat up.
About the User Query
More than ever, it’s crucial to learn from your Whales, aka most loyal and high-value gamers. Our example user query demonstrates how you could drill into your most habitual and profitable gamers. Perhaps you’ll find these users tend to pay to ‘unlock’ a new feature at a similar moment in their behavioral journey, or typically respond to a particular style, format or timing of messages. These kinds of insights can help to inform engagement pushes and game design iterations in a big way.
2. Business & Productivity Apps
EXAMPLE USER QUERY: “See all users who logged in within the last 3 months and generated a password reset more than 5 times.”
‘Messaging threads’ and apps which support business collaboration and the sharing of information is reported to have been the leading trend for enterprise software in 2018. As constant connectivity and increasingly globalized teams become the norm, the rise of mobile for connecting this way doesn’t seem too surprising. We anticipate mobile app versions of products like Slack and Dropbox will continue to reshape software ecosystems for many businesses.
About the User Query
The number one requirement for most business productivity apps is typically ease of use. If your product proves to be a real efficiency driver, the potential for high CLTV in a corporate setting is huge. If you fail, your app is at risk of becoming “shelfware”. In addition, security and ease of login can represent a difficult trade-off here.
By running a search on users that are logging in but repeatedly generating password resets, you’ll be able to gauge the most likely reasons your customers are having trouble with the login process. It could be that the steps required are unnecessarily complicated.
3. Travel Apps
EXAMPLE USER QUERY: “See all users from Canada who registered in the last month following an Easter promotion, completed a minimum of 5 searches, but made 0 bookings”
The era of travel apps is truly here. In a recent study by Tnooz, as many as 60% of mobile users had downloaded and made use of a travel-related smartphone app. Further, travel research is increasingly happening on mobile – according to Think with Google Travel Trends, there has been a 600% increase in mobile watch time of travel diaries and vlogs over the past two years.
About the User Query
If you’re investing in mobile advertising campaigns for your travel app, you’ll want to ensure your product is working hard to deliver as much advertising ROI as possible. This will require maintaining a focus on the right KPIs and really getting to know your different user segments.
Imagine your typically high-performing Canadian geo had failed to convert users following an annual Easter promotion. By launching a query to show users attributed to your Easter campaign who had run travel searches but failed to book, you’ll be able to dive into these sessions and identify previously undetected points of friction. Maybe your app failed to display the correct currency which put users off, or the promo code didn’t work. Whatever the reason, you now have a ready-made pot of users for a future re-engagement campaign. Could a further promotional push move the conversion needle for these users?
4. Educational Apps
EXAMPLE USER QUERY: “Monthly paying customers who haven’t logged in for at least 1 month but previously reached course 7.”
Educational technology is transforming the way children and adults are learning around the world. According to Excellent Webworld, the global e-learning market is predicted to reach $243 billion by the end of 2022. Educational apps are a key factor in this overall market growth as mobile learning through tablets and phones start to replace more traditional teaching methods in the home, in schools, and workplaces.
About the User query
Gamification and cultivating habitual use are key factors for ensuring your educational app becomes and stays successful. You’ll want to make sure your most engaged users (especially if they’re paying money to use your app) continue to see the value of your tool. By formulating the search query example provided here, you can dive into the sessions of all paying users who had progressed to a significant course level but whose habitual use had trailed off.
5. Retail Apps
EXAMPLE USER QUERY: “Users who made their first purchase through your app during Black Friday after tapping on a Black Friday email promo code link, then made another purchase within the following 3 months”
By learning more about the initial behaviors of these users and how their habits have changed over time, you’ll be better placed to target this particular group with a re-engagement campaign. You may wish to add more rewards for loyalty at this point, or assess the difficulty level of this stage – if the level is too difficult or easy, this could be putting your engaged users off.
As reported by App Annie, November 2018 was the biggest mobile shopping month of all time in terms of time spent. Further, time-spent in shopping apps correlated strongly with e-commerce sales. Given that mobile shopping is set to comprise nearly 75% of all total e-commerce transactions by 2021, getting in-app engagement right and improving stickiness represents a massive opportunity for driving revenue.
Mobile fueled flash sales and shopping events like Black Friday continue to help mobile break all kinds of e-commerce sales records. In 2018, this one day saw a 50% growth increase in sales, and we’re sure this will increase even further over the next few years.
About the User Query
The ideal scenario for you as a retail app owner is to win a new lifetime customer off the back of a campaign promotion like Black Friday. By making use of Appsee’s integration with Appsflyer, you can search for users that were attributed to a particular promotional campaign like Black Friday, and even the promotional links they clicked on.
The ideal scenario for you as a retail app owner is to win a new lifetime customer off the back of a campaign promotion like Black Friday. By making use of Appsee’s integration with Appsflyer, you can search for users that were attributed to a particular promotional campaign like Black Friday and identify campaign ROI at the user level in a clear way.
With this information, you can filter further to understand more about these particular customers. How did these users behave across sessions? What retail categories of item did they look at? Were their sessions longer on average? All of these insights will help to inform future design iterations and campaign pushes, so you can do more of what is working well.
6. Food & Beverage Apps
EXAMPLE USER QUERY: “Show me users in Australia who have spent more than $500, left a 1-star review in the last 6 months and haven’t logged in again for the last 6 months”
Food and beverage apps grew across the board in 2018, with certain regions like France, Australia and South Korea, witnessing particularly dramatic growth in this category. User retention is likely to be a key aim for food and beverage apps everywhere, explaining the prominence of loyalty campaigns incentivizing repeat orders and personalized offers across this category in particular.
About the User Query
As an app owner, the last thing you want is for a poor in-app experience to lose your business real revenue in a high-performing region of interest. In the user query example provided here, you could filter users based on the custom properties of the amount spent and poor reviews.
If you find user engagement and spending in your app has ceased since the user left a bad review, you’ll want to first ensure this wasn’t caused by friction points in the UX, like slow time to load or failure to recognize a promotional code. Once you’ve investigated the cause(s) of app abandonment, you’ll then want to consider methods of re-incentivizing these lost users to engage and spend with you again.
7. Health & Fitness Apps
EXAMPLE USER QUERY: “Find users that log more than 10,000 steps of walking a day and have a wearable device enabled”.
In a recent survey, wearable technology, and mobile exercise apps were named as top fitness trends for 2019. In the USA particularly, digital health tools have really taken off – almost 90% of respondents said that they made use of at least one such tool. As major companies like CVS Health begin to ramp up their digital health capabilities, the challenges for this app category will be to show the tangible benefits of using an app early-on and to foster loyalty by preventing users from hopping from one app solution to another.
About the User Query
The example user query provides the perfect means for learning more about your model fitness app users. By exploring the history of their engagement with your product, you can explore factors such as how long it took them to get to this stage, whether they were daily users from the start, how long they spend in your app per session on average, and if they responded to particular in-app messaging in a positive way. You’ll then be able to extrapolate from these insights for future advertising and loyalty pushes. You’ll also have a ready-made segment if you decided to reward these particular users for commitment to their fitness goals.
Until now, app owners may have struggled to formulate an in-depth understanding of their users from a qualitative point of view.
Appsee’s user analytics enables you to run in-depth user research from the comfort of your desk – all it requires is a few clicks and a curious eye. Our powerful new User Query builder is one of the most advanced in the industry and the use cases for apps across a range of categories is clear.
It’s your job to get to know your own app’s users – this is the only way you’ll be able to deliver a product that empathizes with their needs and fulfills a tailored value proposition. To start building detailed portraits of your own app’s users, signup for a free-trial here.