High-quality data drive accuracy and precision; both are crucial to mobile marketing’s success.
I am in London.
This statement is accurate. It’s also true.
And, some would agree, it’s a statement of value. However, it’s extremely broad. An advertiser knows my demographic data: professional male, works in media, aged 30–40. But, how many other professional males who work in media, aged between 30 and 40, are in London today?
One definition of accuracy is this: to what degree does a measurement correspond correctly to a known or standard location? The measurements we get, however, can be as broad as 111 kilometers or as narrow as 1 meter. And it’s this wide spectrum that creates challenges across our industry.
I am on Great Chapel Street, London, at 9 a.m. with a 1-meter confidence-measurement that I am in the Verve London office.
This statement is both accurate and precise, and it’s here that the value of winning in location-based marketing begins. Precision provides granular intelligence to the accuracy measurement. Many platforms simply state the importance of accuracy alone when utilising location intelligence. And while there is no disagreement that accuracy is important, a fundamental way to drive success in strategic mobile marketing is to properly marry the concepts of accuracy and precision. The fusion of the two provides the connective thread between people, places, and purpose, delivering better campaigns results via movement science.
And so, how can brands exploit the accurate-and-precise model? How can they realise the full potential of movement intelligence? As we’ll explore in the next section, it all comes down to data — the quality of the data involved.
Quantity and Quality: More Data Doesn’t Mean Better Data
The mobile consumer is the largest driving force behind media consumption, with the average young Brit checking their mobile device on average 85 times per day, according to a recent multi-author study. Additionally, research by Verve discovered that Mobile Prodigies — a grouping of Millennial and Gen Z consumers — are spending 80% more time in mobile apps than they were a year ago, with the same percentage expecting ads that are tailored to their individual interests.
However, when utilising exchange data, it’s difficult to define individual users with any real precision. In fact, location data today is sometimes perceived as “dirty” or “wrong.” We find this impression across the news, with industry experts such as Jeff Devlin, chairman of WPP, a global leader in communications services, stating that 80%–90% of mobile-ad inventory has incorrect or imprecise location data attached to it.
Yet location is an evolving science; precise but not perfect and new techniques are being explored every day. Teasing out high-quality data and leveraging them in appropriate ways depends on an advertiser’s particular objectives. Additionally, when it comes to location, an under-discussed topic is that of its application within stages of attribution, profiling, and targeting.
For attribution, we need the most precise location signals: these help us determine whether someone is actually inside a building or defined area. High-quality data are critical in this circumstance.
For profiling, we need consistency of location signals over time so that we can build a picture of the device user (where they go, etc.). Precision is required, but not all the time and certainly not in real-time.
Finally, for targeting, there is a trade-off between precision and scale, and for that reason precision is often de-emphasized depending on the needs of a given business. Considering our example at the start of this article, when serving an ad, does it matter that someone is literally inside the Verve office when they receive it? Or is it just as helpful to know that the person goes to the Verve office often, allowing us to infer a great deal about who that person is and what behaviors they represent. Again, the more precisely we understand a device user, the less precisely we need to target them based on their exact location.
Relevance is critical to targeting, and relevance extends far beyond real-time location — although real-time can be a crucial starting point. In the midst of all of these factors, as we seek high-quality data to fuel precise and accurate targeting, there emerges a light at the end of the tunnel, an approach to data that brings with it certain assurances. It is the SDK location model.
The SDK Advantage: Location-Smart and Permissions Granted
Location-smart SDKs are transforming the way mobile marketing is employed. The technology is integrated directly into a publisher’s app, extracting location intelligence that is both accurate and precise to inform profiling, audiences, and attribution. A good SDK not only provides accurate data, it also produces consistency of location data — enabling better understandings of consumers and improving marketing’s ability to reach the right people within an advertiser’s media budget. When a mobile consumer engages with an app, their location services enabled, the data extracted can pinpoint that user, transforming how advertisers tell their stories.
Direct integration with apps not only provides the ability to move with the user throughout their entire day’s journey (when location services are enabled), it also allows the user to opt-in when brands and publishers ask to use their data. This trusted bond between consumer and app provides advertisers with highly granular insights into where their users travel, where they have been, and the context surrounding every location.
App environments are growing dramatically in popularity. Advertisers and publishers need to embrace the precision-plus-accuracy challenge to realise the untapped opportunity presented to them. Using the best-case datasets to better pinpoint mobile consumers will empower that breakthrough, one SDK integration at a time.
Reposted from author’s originals article appearing on Medium.com
Originally published on PubNative.net