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How can Big Data Boost User Acquisition for Your Mobile App?


With the competition being enormous and the majority of apps struggling to make a consistent user base, new user acquisition and maintaining steady growth in terms of sales has been a challenge for most apps. Mobile app development and marketing thanks to these burgeoning challenges are demanding more expertise and domain knowledge than ever. Moreover, other horizons of new gadgets and devices are coming affront demanding more cross domain expertise and knowledge.

Just like in other businesses, mobile apps are also being benefited through the user insights generated by Big Data analytics.  Thanks to a diverse range of user data sourced through mobile sensors and user sessions advanced data analytics are now capable of producing most relevant insights to drive app sales and user acquisition. So, it is time for marketers to take the opportunity provided by Big Data analytics seriously in order to garner robust sales.

A diverse range of user data sourced from a variety of digital interactions and avenues is providing enterprises, marketers, and mobile app developers grasp the specific user needs and brand expectations. Moreover, the huge pool of user data from a variety of digital sources also helps businesses understand the gap between business practices and consumer interactions and demands. With robust data analytics is in place, it is no longer a challenge to find the issues with user interaction and engagement and address them in a proper manner.

Here we introduce some of the ways Big Data analytics can boost user acquisition for a mobile app.

Addressing users from diverse cultures

For marketers knowing users and audience is not just important, it is an irreversible necessity. But if your app is going to cater to audience belonging to diverse ethnicities and people around the globe, having deeper insights about culture-specific demands and moving factors may be crucial. Well, that is where data analytics can play a big role. Thanks to Big Data you can now have insights about user reactions to your app in different areas. Here are few things that Big Data analytics can do to help to address diverse cultures.

  • Insights about the various cultural and ethnic factors in making apps popular
  • Data-driven insights on preferred design attributes and features
  • Insights on technical issues such as network problems, GPS connectivity and local bans on certain services.

Going deeper into customer opinions

Today customers are coming out openly expressing their opinions about anything on social media and other digital platforms. This actually helped businesses to drive analytics over a huge pool of customer opinions across digital and social media. This obviously results in enhanced marketing maneuvers to drive user engagement, retention, and fresh acquisition. Here are some of the ways data analytics can help in going deeper into customer opinion.

  • Data analytics let us know the opinion of the users on their wished-for features that go missing
  • Through analytics, we can know the major reason for dissatisfaction for users in our target audience
  • Analytics into user opinions and rating data unveils the positive triggers and negative factors

Knowing what works among In-App purchase options

For a vast majority of apps across the niches, the in-app purchase represents the most sought after avenue for revenue. Well, offering in-app purchase options require knowing how it can work best for your app. Mostly, the promise of advanced features, better security and better user experience devoid of promotions and constraints make users go for such purchases. Data analytics can deliver insights about what kind of in-app purchase option works in that category and for respective audience. Through analytics, the following attributes can be laid bare regarding in-app purchase.

  • The revenue generated from various in-app purchase options for diverse categories of apps.
  • The popularity of in-app purchase options across diverse user groups
  • Comparison among in-app purchase options in regard to frequency
  • The popularity of in-app purchase options over time

Determining the revenue model

Which revenue model can be best for your app? Should you put a hefty price tag on it or just should offer a free version along with some gated features for in-app purchase? Or, should you offer separate free and premium versions? Obviously, such decisions can be reached only when you compare competitions and how they have been succeeded with a revenue model. Data analytics can help you grab insights on revenue model in the following ways.

  • Competitor’s revenue model analysis
  • Analysis of receptivity of price brackets and other revenue models among target audience
  • Analysis of ROI versus number of users over time

Marketing for target audience

A marketing can only be successful if it is unleashed for the target audience. Well, how accurately your app marketing can reach your audience with loud and effective campaigns? Or how can you broaden your reach over time? You can target your audience with marketing maneuvers only when you have deeper insights about them and their preferred interactions. Big Data can boost receptivity and acceptance of your campaigns through the following ways.

  • Analysis of potential user preferences across digital interfaces.
  • Analysis of app buying habit and responsiveness to marketing
  • Engagement and frequency of use with certain apps
  • Demographic insights about your target audience

Deeper insights about branding

Branding is after all the original face of a company over and above marketed products. Brand value plays a crucial role in influencing the decision of the majority of users. With data-driven insights concerning what can uphold a brand, you can more accurately position your branding. In the following ways, data analytics can help branding maneuvers.

  • Data reflecting consumer satisfaction and referrals will let you see the position of your brand.
  • Big Data analytics can deliver relevant insights on various competitor brands and their role in creating business value.
  • Analyzing feedbacks and opinions on branding.

Data analytics opened up a horizon of insights based on user data for businesses of all sorts. How can mobile apps be different? With millions of apps competing for discoverability and user acquisition, gaining insights on user activities and reactions is crucial for delivering app up to their expectation.

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