Big Data and Importance of Data Driven User Acquisition Strategy for Mobile Apps

As business analytics is increasingly becoming crucial to get insights on users and trends, marketers should now concentrate more on how data can be effectively used for new user acquisition. The availability of huge pool of digital data and rigorous analytics apparatus to analyze and get inroads into this data pool opened a new vista of opportunity to drive user acquisition campaign based on the insights gathered from Big Data analytics. Basically data driven attribution strategy is to eliminate the faulty guesswork out of your mobile app marketing strategy and replace it with a clear and detailed view into the customer profiles and their lifecycle.

The Role of Big Data in Data Driven Acquisition

Data is already a crucial part of analytics, whether for web or for mobile app. But this data mainly refers to the user data accessed from the correlative mobile sources like device sensors, user session data, app store data, etc. This immediate pool of user data is undoubtedly crucial but they have limited potential to reveal the deep underlying trends and user specific insights. The Big Data analytics comprising huge pool of unspecified and unstructured digital data can further replenish mobile apps with diverse social, economic, consumer and behavioral insights. The real time device driven analytics coupled up with the Big Data analytics can further equip app marketers in identifying opportunities for new user acquisition. For more relevant and actionable insights the reach of app analytics must incorporate bigger insights derived from diverse sources along with the immediate device and platform produced user data.

What is Data Driven Acquisition?

Advanced and sophisticated algorithms used in data driven acquisition help one determining the touch points that play key roles in influencing users. App marketers can now easily see the best friction opportunities and accordingly drive a strategy to maximize the engagement and conversion rate.

Gaining business intelligence from a robust data analytics apparatus can just give marketers further boost in this respect. Larger the scope of data analytics you can utilize better a strategy you can device for acquisition.

How Data Driven Strategy Works as Part of Existing Analytics?

It is very likely for any marketer that he is already replenished with overwhelming volume of marketing and advertising data. Actually that helps in adapting to the new strategy where data analytics delivers insights for your user acquisition.

As for assessing your success at the end of a campaign, data driven strategy let you see the performance and result of each tactical move quite clearly. Thus you can always sharpen your tactical moves in each new campaign. Moreover, each new user acquisition unveils the definite friction points that played crucial role in influencing users.

In case of ecommerce and business apps mobile CRM coupled up with app analytics can just accentuate this strategic decision making. Mobile CRM data corresponding to business transaction, contact, user feedback and session can deliver actionable insights that can further be judged in the light of customer profiling done by app analytics. The input from mobile CRM can make your user acquisition campaign more result oriented and complete.

Using Big Data for new Customer Acquisition

While Big Data is often understood vaguely by many app marketers and campaigners there are too many close-in-hand scopes of gaining insights into user data and accumulatively they are part of Big Data analytics. For instance, data retrieved from existing customers is a crucial piece of data for new user acquisition.

Cross channel user data is another source that can play a vital role in gaining insights. The business apart from its mobile ecommerce app may have wide range of user data that can be retrieved from its stores, web or connected social interactions. Deciphering the parts of the marketing strategy that worked is always crucial for marketers to device new acquisition strategy and all these pools of data from diverse sources play a decisive role into that.

Where is the scope of further improvement? What maneuvers and touch points helped generating most user interests? What is the platform users prefer most to be reached on? Is there any potential attribute detested by most users?  What parts need improvement? What techniques generated the most new users? Big Data analytics help to answer to all these questions and boost app performance.

More Target Oriented Promotions by Combining Diverse Sources of Data

As valuable customer insights are increasingly becoming accessible business institutions now enjoy more power to customize messages to target new customers. Traditional data sources like transactional history, profile demographics and user behavior patterns apart now business institutions have the access to customer data over an array of digital platforms including social media. By combining these diverse sources of data and their capacity in drawing actionable insights now business organizations and their respective mobile apps can now orchestrate new user acquisition campaign in a more personalized and effective manner. This race among business organizations to get closer to the customer is increasingly being decisive to achieve business goals. But such a personalized approach to user acquisition would not be possible without the input provided by Big Data analytics. Simple customer data within organizational framework and database is not enough now. A combination of traditional sources of data coupled up with other sources of digital data will be the guiding force for drawing customer insights.

Finally, any app cannot ensure a growth path by only focusing on new user acquisition. New user acquisition will only deliver business growth if user engagement and retention are also given sustained focus. Just as in user acquisition campaigns both traditional and new sources of digital data corresponding to users can play too important a role for customer engagement and retention.

While offerings based upon the usage patterns can engage customers better, addressing customers based upon individual behavioral analytics can help retaining customers on board. Today’s business focused mobile apps have to take acquisition, engagement and retention all as part of the data driven value chain for growth.