In our technology-driven world, marketers need to be creative with their advertising strategies this holiday season. The retail landscape has evolved a great deal over the past few years with new mobile advances, but consumers are still making the majority of purchases in store, including 53 percent of tech savvy millennials. While online browsing patterns are valuable, they are not always the best indicator of purchase intent. The places consumers move about in the physical world tell a better story of consumer path to purchase.
MediaMath, in collaboration with Factual, provides media buyers with rich, global location data to deliver relevant advertising to mobile users through their omnichannel platform. I spoke with Heather Blank, GM, Audiences at MediaMath, to dive into our partnership and explore recent trends in location data usage across the industry that will span into 2018.
Leighann Terraforte: What do you believe has played a major role in the growth of demand for location data? What do you hear from clients?
Heather Blank: Two big trends are driving the interest in location data. One, the continued shift of the consumer from desktop to mobile. Consumers are using their phones/tablets more, which means there is more data available and that data is a better signal. And two, the continued need from clients for more relevancy. Clients know that recent site visitors are one of the best converting segments for advertising. Being able to create segments based on recent offline location visits is extremely interesting to clients.
LT: How have you seen top client brands use location strategically within MediaMath?
HB: Using location data to better target users based on interest and shoppers has been one of the most common trends. We have seen a lot of interest in running ‘always-on’ retargeting campaigns based on offline visits – but limited scale has been a barrier to growth on these strategies. I think some of the most strategic use cases have been around expansion of location data into the B2B space. For example, targeting users of specific conferences to determine job function.
LT: What do you look for in terms of data quality when evaluating a partner?
HB: The biggest thing for us when evaluating what partners we want to work with on internal product development is deterministic matching. It is important that we work with partners that are deterministically assigning attributes and segments – we are less interested in modeled out segments or attributes.
LT: How do you see location data playing into your mobile growth for 2018?
HB: Location data is a big focus for our mobile growth next year. We believe that location data converted to interest and shopping attributes, is a great signal for better performing audiences. We would like to use more location data in our machine learning products for better targeting and optimization.
LT: How do you see the use of location data growing and playing a role beyond targeting and measurement?
HB: At MediaMath we are also hoping to use location data as part of our optimization products. For example, having AI/machine learning use location data to determine the optimal bid price in real time. We might learn that users are more responsive to ads when they are at certain locations vs. others.
There is no doubt, consumers are increasingly spending time on their mobile devices. The ability to target people based on where they go in the physical world is extremely valuable, and advertisers recognize the opportunity to use location data to reach users with contextually relevant messaging. The mobile market continues to grow and according to eMarketer, mobile location ad spend is expected to increase 120 percent from 2016 to 2021.
Originally published on Medium
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