It is projected that mobile advertising will grow by 128% by 2018 – an increase of $64 billion over the next three years.
However, mobile devices have not just been used as a new advertising bandwagon but has recently become a primary source of data in all device campaigns. Many popular data platforms such as Lotame and AdChina have added mobile DMPs to their platform in the last few years. Below are a few upcoming data sources that have are derived from user behavior on mobile devices.
Mobile Location Data
- Factual provides advertisers a new way to geo-target consumers by providing customizable location data and geo-fencing capabilities. Location based targeting analyzes and segments people based on where they go and segments them based on brand affinity, behavioral, and demographic characteristics. These segments can be used as audiences within Factual. With geo-fencing, advertisers have the ability to target users in a radius around specific place categories in the database. This targeting has the ability to be quite granular with the polygon tool which reaches users in precisely specified areas such as parking lot vs. building.
- Placecast is a mobile DMP that standardizes and de-duplicates location and other data for many enterprises today. They make this data available through their DSP or as a separate entity.
Mobile Application Data
- Push Spring is audience data that is powered by mobile applications which can be obtained through personas or custom segmentations. Personas include mobile audience targeting with life stage, intent, and activity dimensions. Custom segments can be built from personas, app genres, app ownership, and device type.
Cross- Device Targeting
- Cross-device targeting is a first-party data source and enables retargeting with mobile impressions. It is used to market the same user who saw an ad on a mobile device with another one of their devices. This cross-device data can either be deterministic or probabilistic. Deterministic data uses digital properties of web applications (such as a login name) to track users across devices; therefore, deterministic data is quite precise. Probabilistic data aggregates data sources and is devised with less of a technical science – it has been estimated that this data from ad tech companies is generally 60 to 99 percent accurate.