How to turn device fragmentation from a challenge to an opportunity

This article is brought to you by Lotame. It’s hard to imagine life before smartphones. In under a decade, they have transformed the way we live our lives, from how we keep up with friends and interact with brands, to the way we discover deals and navigate around new cities. According to eMarketer, by 2015 there are expected to be 2.04 billion smartphone users worldwide, and 15 countries will have reached at least 50% smartphone ownership.The continued rise in mobile usage has transformed the way that brands need to target and engage consumers. However despite all the focus on mobile, there continues to be a significant gap between the amount of time spent on mobile devices and the percentage of ad spend that mobile commands compared to other channels.According to a Millward Brown study, daily time spent on mobile devices is now outpacing TV for the first time.  Globally, in 2013, mobile devices (smartphones and tablets) accounted for 47% of all screen time daily. Despite these statistics, however, mobile advertising makes up only 4% of total media spend worldwide.While factors such as a lack of standardised, impactful creative formats on mobile, and poorly optimised mobile content experiences undoubtedly play a part, at the heart of the disparity between time spent and media spend is targeting.The absence of cookies across mobile apps and many mobile browsers has sent ripples through the digital advertising industry, and is forcing marketers to rethink their approach to audience targeting. In the absence of cookies, audience data across mobile is collected via device IDs. While data collection through device IDs is arguably more effective than cookies due to the more uniform and persistent nature of device IDs, this methodology has one major limitation: there is no easy way to link mobile device IDs with desktop cookies.The effect of this is that brands are limited to data gathering, ad delivery, and measurement in silos. This leaves no clear understanding of frequency of ad delivery across screens, and no way to tell sequential brand stories. This limitation also means that the rich third party data ecosystem that has been established across the desktop web over the last decade can’t be leveraged across mobile devices.Lotame Cross-Device has been developed specifically to address these challenges. The new solution uses probabilistic and deterministic algorithms to determine relationships that exist between billions of signals flowing from desktops, smartphones and tablets. Through this patent-pending technology, different devices can be accurately mapped together creating significant opportunities for advertisers and publishers including:-          Cookie-based audience segments can now be targeted across mobile, and mobile-based audience segments targeted across desktop. This increases reach for advertisers and monetisation potential for publishers.-          Advertisers can use the technology to tell sequential brand stories across screens, increasing the impact and effectiveness of digital campaigns.-          Ad delivery can now be frequency capped across screens, reducing wastage and avoiding negative consumer experiences.-          Cross-device consumption patterns can be used to underpin custom content delivery and ad creative, helping increase ad engagement and the stickiness of publisher properties.Making the match: deterministic and probabilistic matching explainedDeterministic matchingA deterministic (or direct) match is established when there is known information that connects different devices together, such as user login information. A consumer, for example, may login to a website to access certain features or content, and may also login to the same publisher’s mobile app to access content on the go. This login data, which is encrypted to strip it of any PII, can then be passed through the Lotame platform to establish a direct link between different devices.Probabilistic matchingWhere known data linking devices isn’t available, probabilistic matching can be used as a powerful alternative. Probabilistic matching takes signals from different devices and uses statistical analysis to identify links between them. These signals could include consumption signals (IP address, location, day parts, time stamps), visitation signals (frequency of visits and time between events), or device signals (device make, model, OS, screen size and resolution). Over time, the algorithm analyses enough signals, and sees enough patterns between them, to tie different devices together with a high degree of confidence.http://vimeo.com/107481376Lotame Cross-Device can help transform your data management strategy and ensure you keep pace with consumers’ fragmented media consumption habits. To find out more about this powerful new solution, visit: www.lotamecrossdevice.com or download our free whitepaper: http://pages.lotame.com/whitepaper-cross-device.html[Image: Shutterstock]