The world is awash in data, much of it created by mobile devices, and it can be used to help create more valuable services and advertisements for the mobile consumer.
CIBC, a Canadian bank, predicts that information-generation growth will increase 50 times over the next decade. IDC, a market research firm, similarly forecasts a 44-fold increase in data volumes between 2009 and 2020. Mobile is playing a large part in driving this explosion in data.
What’s the use for all that data? Is it just noise?
Many mobile executives are starting to get their arms around mobile-generated data and applying it to shape customer retention and marketing decisions. In an an environment like mobile, personal and intimate, personalised campaigns and hyper-targeted messages are key. And those can only be created with the help of big data.
Could data be the paradigm that anchors the next mobile marketing revolution? Many think so.
In a recent report from BI Intelligence on Big Data and Mobile, we define big data, examine mobile’s connection to it, analyse its potential, its practical applications and pitfalls, look at how it’s collected, and answer some of the most frequently asked questions about big data and mobile.
Here’s an overview of the relationship between big data and mobile:
- First, big data needs to be defined:Big data is most commonly defined as data sets that meet three attributes, known as the three “Vs”: volume, variety, and velocity. But there is something more to it. “I like to say there’s a fourth V: value,” says Kipp Jones, vice president of product at Skyhook. In order for data to be meaningful at all, it needs to be captured and stored efficiently. Then someone has to manage the data, analyse it, and extract value from it. Data, big or not, doesn’t add up to anything worthwhile if it doesn’t have value to someone.
- Mobile is particularly well-suited to a big data lens: Mobile big data isn’t only a function of smartphone penetration and consumer usage patterns. The data is also created by apps or other services working in the background. Technically speaking, its not that different from data created using the traditional Web. The difference is that consumers are just producing more of it as we shift our behaviour to digital channels, leaving a trail of data documenting our movements and actions. Even when we are ostensibly not using our phones, we are still creating reams of data.
- This data can be used to optimise and personalise mobile experiences: Mobile big data can be used for a dizzying variety of purposes, but it is often used for the optimization and personalisation of mobile services and marketing campaigns. App developers, for example, might use Flurry’s analytics to improve their apps. Retention is a key metric for developers. Developers can compare their user retention numbers with all other apps and apps within their own categories, to gain insight into how they stack up, and what they might have to change to improve their numbers.
- Or to help drive an explosion in mobile advertising and marketing: Location data is an essential component of mobile big data — perhaps the primary data type that differentiates mobile from Web-based big data. Location data is expected to help transform the mobile advertising and marketing industry. The ability to deliver real-time hyper-local, targeted advertising represents a potentially momentous evolution of the ad market. Data from social media, paired with location data, can also be used to drive personalised campaigns.
As our personal and business lives migrate into mobile, there’s virtually no end to big data applications.
- Defines what big data is
- Examines mobile’s connection to big data
- Analyses big data potential, practical applications, and pitfalls of collecting and applying data insights on mobile devices
- Looks at how big data is collected
- Answers some of the most frequently asked questions about big data and mobile marketing