Tracking Mobile Ad Effectiveness With Real-Time Data
The volume of mobile data and the speed at which it is created continues to increase as the global population increases, as mobile device penetration rates rise, and as the consumer usage rate for social media grows.
When analyzed effectively, this data can provide business insight on user sentiment, behavior and even physical movement patterns. Due to the sheer number of mobile devices in use, Big Data practitioners can tap mobile Big Data analytics to better understand trends across vast populations and sub-segments of users. This understanding helps business to improve engagement tactics and to optimize the delivery of services.
Mobile device data becomes particularly useful for analytics purposes when combined with extended data from outside sources. For example, weather and economic allow practitioners to correlate macro-level trends to a targeted set of users. These consumer segments have traditionally grouped users together based upon similarities. However, industry is increasingly focusing upon targeting towards individuals based upon their interests or upon their past behaviors.
Below you will find a number of ways you can apply real-time data analytics to your mobile marketing and advertising campaigns.
- More Personalized and Targeted Ads
Big data allows brands to better target users with more personalized interactions that drive engagement. We increasingly see ads featuring products and services we might actually want to use to make our lives better. These more personalized, more targeted ads are all based on massive amounts of personal data we constantly provide. Everywhere we go nowadays, we leave data crumbs. Following these trails reveals information about what we we’re doing, saying, liking, or sharing. Thanks to our mobile devices, this data trail now also hints at where we’re going.
- Hyper-Localized Advertising
The proliferation of mobile devices, primarily smartphones, has created a major opportunity for marketers to deliver contextual advertisements. These mobile-specific ads target the right people at the right time. For instance, through the combination of social data and location data, stores that shoppers are near and might be interested in can send out ads offering percentage discounts or other incentives. Delivered by shops to their shoppers in real time, these ads get consumers to walk through their doors. Hyper-localized advertising has been shown to increase customer engagement and conversion rates.
- Leveraging Attribution to Achieve Mobile Engagement
Leveraging Big Data about user behavior helps brands more accurately and completely quantify the effectiveness of their mobile marketing initiatives. Big data helps marketers determine whether their campaigns are creating the desired results. The ways users respond to branding assets can be used to literally create “rules of engagement” for each user or for each type of user. Marketers optimize their results through understanding varying levels of consumer engagement and through understanding the contributions of different campaigns across the path-to-purchase.
- Real-Time Data Analytics Across the Complete Mobile Lifecycle
In the past, conventional database solutions could be relied upon to effectively manage and analyze massively large data sets. But they did so at a snail-like pace, taking days and even weeks to perform tasks that often yielded “stale” results. By contrast, the big data analytics platforms of today can perform sophisticated processes at lightening-fast speeds, allowing for real-time analysis and insights. Shorter time to insight allows marketers to make real-time decisions and take immediate action based on fresh, reliable and relevant information.
- Flip Traditional Consumer Profiling Upside-Down
In the context of ubiquitous, real-time consumer data brands can now ask the data who their customers are. Contrast this to the erudite consumer profiling where consumers are targeted towards based upon their goodness of fit into an expected consumer picture. Rather than relying upon arcane consumer characteristics, instead we can now quantitatively choose targeting characteristics based upon the congruence of these characteristics with the desired call-to-action.
Brands are in desperate need for solutions that will help them understand the impact of their mobile advertising spend in the grand scheme of their broader marketing plan. This requires brands to go well beyond the click-through to be able to attribute their spend to in-store visits and better yet, sales.
