Digital Reimagined: Context & Predictability in Location Targeting

In association with xAd

Location targeting is experiencing a coming of age. The technological capabilities and marketers’ execution of location-based campaigns have evolved from a somewhat scattergun approach to strategic, measurable, performance-based marketing. In this piece, ExchangeWire reflect conversations that took place at a roundtable event, hosted by xAd, following an exclusive preview of joint research titled: Digital Reimagined: Context and Predictability

Creating a 3D image of consumers

A single piece of location data, taken in isolation, provides a one-dimensional view of a consumer, e.g. current physical location.

However, a collection of data points, including historical location data, real-time location data, and contextual data, creates a 3D image of a consumer allowing marketers to understand preferences and behaviour and, therefore, predict intent and act accordingly.

When it comes to location-based audience targeting, accuracy is top-of-mind for marketers and is today’s golden arrow in the marketing quiver. As data accuracy increases, so does the accuracy of the resulting behavioural predictions that feed real-time ad-decisioning, e.g. the likelihood of a consumer venturing into a particular store.

The dominance of Google and Facebook’s walled gardens is a perennial challenge for marketers. Whilst the duopoly offers marketers scale, it also restricts the data that can be used to plan and target campaigns. Location data, combined with contextual data, provides brands with a tailor-made solution that allows them to break free from Google and Facebook’s walled gardens.

The tipping point

Location is the most ‘honest’ version of a consumer’s behaviour – it is real. Online behaviour is littered with debris; for example, consumers get trapped in YouTube blackholes watching videos about things they’re not really interested in, but can’t seem to stop watching… sound familiar? Or you look at links your friends have sent you, which do not necessarily reflect your own likes and interests.

What this boils down to is that real interest is extremely hard to extract. Substituting online data with location and contextual data is not the answer either; a cross-device solution is best and using the two forms in harmony works most effectively.

Cookies, mashed with location data, give marketers a holistic view of consumers and how to target and influence them.

Justifying mobile ad spend

Measurement is key to the longevity of location and contextual targeting. Footfall justifies mobile location-based spend; however, it’s hard to attribute footfall to ad campaigns, which is why third-party verification, such as comScore Location Lift via xAd, should be welcomed.

Offer redemption is one way, but this tends to only work for FMCG and retail where the price point is relatively low and the option to return the goods is available. But what about automotive or travel? Yes, it’s possible to track footfall to a car showroom, but highly unlikely that those footsteps can be linked to the final purchase, or lack of. But location (especially in car showrooms) is one of the highest indicators of consumer intent; therefore, a measured visit to a car showroom is valuable as they are more likely to purchase through looking at cars in a showroom than if looking at cars online.

Whilst there is merit in driving footfall at scale, especially for relationship-based sales like automotive, from a marketer’s perspective, there is a delicate balance to be struck between more traditional recognised measurements, such as CTR, and newer bespoken visitation measurement, like store visitations for reassurance and, of course, marketers are continually striving to reduce wasted ad spend.

Download the full report here.

The roundtable event this piece is based on was attended by publishers, media buyers, and ad tech professionals.