Click here to learn more about author Juned Ghanchi.
The overwhelming growth of digital data is continuing to emerge as the most promising horizon for techies, analysts, and marketers. A major portion of this data is created by mobile devices; and, as these handheld gadgets continue to take a bigger role in our digital, social, and interpersonal activities, the mobile-generated data will help create more valuable services for mobile consumers. Thus, as the producers of the highest volumes of mobile data interactions they also have to opportunity to benefit most from Big Data Analytics.
The Canadian bank CIBC predicted that there will be more than 50x the growth in data volumes over the next decade. IDC has offered a similar forecast, predicting that there will be a 44-fold increase in the volume of data between 2009 and 2020. While a majority of digital interactions happen now on the mobile web and mobile apps, mobile will play a considerably bigger role in this data explosion and data-driven analytics well into the future.
In conformity with the role of mobile devices in generating data, the impact of a data-driven strategy and analytics on business conversion and revenue will also be huge. While the market is continuing to expand and new technologies are constantly harnessing it, data is playing the role of fuel for this diverse and robust information economy.
Big Data will continue to remain “Big” for all kinds of digital operations. But, the biggest impact will be on mobile marketing. It will shape the way we conceive and practice business marketing and advertising. This blog post discusses why this is bound to happen and how it will turn out.
Creating new value in mobile marketing
Big Data is commonly referred to in connection with three crucial attributes of information growth, namely – volume, variety, and velocity. But, the extent of its impact and the potential it has in store for all of our digital operations, a fourth ‘V’ is likely to be added: ‘Value’. It is more important for the data to be put into meaningful, contextual, and effective use. Managing and analyzing data amounts to nothing if real value is not extracted for the concerned parties. For a mobile marketing business, conversion, user acquisition, user retention, and growth of revenue is of seminal importance and value-driven data analytics should help them in achieving these.
Mobile is more proactive and rigorous in generating and using data
Mobile data has become the largest contributor to Big Data, primarily because of the excessive penetration of the mobile interfaces in all walks of life. Mobile data does not just consist of consumer behavior and usage patterns, but also involves the data created by apps and background services. It is similar to the data generated by the web in general, with the primary difference being that while using mobile devices consumers deliver more diverse and personalized data documenting a variety of contexts, movements, and actions. A mobile device creates insightful data even when the device is not in active use.
Big Data analytics create new scopes for data-driven acquisition
Data-driven analytics make use of a diverse range of user data accessed from different sources like device sensors, session data, mobile app store data, etc. This pool of data can deliver more useful insights when put to use in correlation with other data sources offering demographic, behavioral, social, and economic insights. Often, for new user acquisition, a broader exposure to user specific data can be crucial for generating actionable insights. Traditional data-driven approaches that work with specific data sets seem unequipped in comparison to the broader scope provided by Big Data Analytics. With Big Data, mobile marketers can take their data-driven approach to the next level.
Visual analytics as a force to user retention and analysis
Visual mobile analytics allows the marketers to look at an app through the eyes of the users. The recording of user interactions, behaviors, facial expressions, and actions taken or bypassed all help in evaluating how the app works and can be improved. Visual analytics offer new insights into mobile usability and user behaviors. This new pool of visual user data can be put to relevant use with other data pools corresponding to user persona.
While traditional analytics can only make us aware of the drop-off rate of users, the possible factors leading to drop-offs cannot be known. User behavior recordings in mobile testing environments allow the seeing of factors that cause users to depart or make users remain active.
Visual analytics also get solid insights from the touch heatmaps aggregating various inputs like taps, swipes, pinches, etc. This as a whole provides insights as to where and to what extent users are engaging with the app and what make them take favorable or unfavorable actions.
Big Data for optimizing and personalizing mobile experiences
Mobile Big Data is utilized for addressing a wide variety of purposes, particularly to add personalized effects to mobile services, advertisement, and marketing campaigns. Analyzing diverse data on various metrics, app developers can improve their apps. From personalizing notification messages to custom marketing for specific users, Big Data Analytics can optimize mobile experiences in more ways than one.
Location and contextual data boosting mobile advertising and marketing
While the user preference will continue to remain as a driving force for mobile analytics, typical user needs at specific time and place will give rise to contextual advertising and marketing campaigns. From addressing variable preferences to meeting expectations of usability to allowing ease of accessibility, a focus on user context makes these possible and in doing so a new range of sophisticated location technologies play a crucial role.
Knowing user location data is crucial for marketers to address users in timely and contextual manner. Location data drives marketing campaigns in a more result-oriented manner. Thanks to the use of state of the art location technologies marketing can be more real-time, hyper-local, and target oriented. Location information coupled up with user preference and information on specific user persona can make marketing campaigns more personalized.
Click here to learn more about author Juned Ghanchi.