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“Analyzing customer behaviors is like studying a living process—it’s constantly changing,” Jason Wiegand, manager of digital analytics and optimization at WestJet, explains.
Mobile users behavior is not an exception. The influx of apps has created challenges for their vendors in ensuring apps popularity and users commitment.
Read this article from Belitsoft (an offshore app development company) to know how mobile analytics can help to build an app strategy that will bring you the biggest bang for your buck.
What is mobile analytics?
Mobile analytics is the practice of tracking and measuring user behavior data from app usage. Contrary to the popular belief, analytic data can be a valuable tool not only for revenue and app popularity tracking. The right data analysis helps to understand users’ intents, as well as find and fix the weak points to increase app performance and user retention.
Who needs mobile analytics?
QA teams and developers
As the Dimensional Research survey reports, users have little tolerance to glitchy apps.
- 61% of users want their apps to start in 4 seconds or less;
- 49% expect their apps to respond in 2 seconds or less;
- 53% will delete a mobile app with crashes, freezes or errors.
- 37% lose interest in a company’s brand because of mobile app bugs.
While most businesses have already understood the value of testing, many are missing on the potential mobile analytics data can provide.
It is impossible to predict every single action a user can perform within an app as well as all factors that can affect user perception. QA team can only guess within their cultural and educational background and presumptions. Applying mobile analytics adds to smarter test cases, as the data shows how an app is being actually used.
Analytic data can be particularly useful for QA when measuring usability, performance, and reliability of an app.
Usability is about the ease with which people interact with an app. Analytics collects information about the time between the screen taps and whether the task has been completed correctly. The data can also help to identify spots where users get confused and hesitate to make progress.
Performance can be gauged based on the speed with which specific screen combinations occur. When extracting data from servers takes longer than is acceptable to users, it is time for some fixes.
Reliability is a measure of how correctly the system performs the tasks it is asked to. The proportion of the requests done and the times it was completed without error shows the stability of an app. Analytics can also give an insight into the context and circumstances that have led to crashes and identify their causes.
Mobile marketing is associated with app promotion, users conversion, engagement, and retention.
Today it is not enough to count app downloads to understand the productivity of your efforts, although the numbers undoubtedly matter for new apps. Successful marketing campaigns are built on comprehensive data obtained from analytic metrics. Some of the most valuable include:
Retention and churn rate. On the market, where 71% of all app users tend to churn within 90 days, increasing customer retention rate by just 5% can give a 25% to 95% increase in profits.
Customer acquisition cost and lifetime customer value. As the name implies, this metric gives you an idea of how much does it cost to attract a new user. The system matches media expenditures depending on the source channel with revenue induced by each consumer and calculates marketing ROI.
Lifetime customer value determines how much an average customer gives your app in monetary terms. The goal of the most marketing campaigns is to keep these figures higher than the cost of getting those customers.
Daily/monthly active users and sessions. This insight will show how dedicated your users are. The analytics platform counts the number of individual visitors per day and the number of sessions per those users. The lesser the discrepancy between the daily and monthly active users stats, the higher the engagement.
User personas. In-app collected data can show such data as age, gender, location, device type, activity time etc. It helps to divide customers into cohorts and shape marketing campaigns accordingly. For example, knowledge of the time users open your app most often gives an understanding of their typical time patterns. It can help marketers to adjust efforts like push notifications to the time they are most likely to be noticed considering also time zones.
How do customer recommendations affect my success?
How to properly deal with negative feedback
How can I provoke positive recommendations?
Exceed customer expectations
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UX/UI designers make mobile apps attractive, consistent and smooth. No doubt the innate sense of style prompts them to create good-looking interfaces and user journeys. Yet, interactive data can provide feedback on how compelling these arrangements are.
Heatmaps visualize every gesture, screen interaction, and engagement of users with your app. Knowing what your users are most interested in provides awareness of what features and screens are crucial. Right data interpretation shows also what precedes both app installs and conversions and allows to detect critical bounce points.
Analysis of A/B testing data is another treasure trove for UX/UI professionals. A successful app is not one with an uncountable amount of features, but one that provides polished experience in every detail. A/B testing helps to bring out the intuitive background of user actions and optimize not only a functional performance but also psychological. Messages, descriptions, color patterns, screen transitions, layouts are some of the detailed to be perfected with mobile analytics.
Mobile analytics is a powerful tool in the hands of an app creators. All of them rely heavily on user behavior data and customer preferences.
QA teams can apply analytic data to see how app functionalities are used and run smarter tests. Usability, performance, and reliability can also be easily measured and then fixed by developers.
Marketers get a valuable insight into retention and churn rates, customer acquisition costs and lifetime value, number and time of sessions and user personas.
UI/UI designers apply analytics to understand how users actually interact with an app. A/B testing helps to refine user experience from both functional and physiological sides.