There will be little left to chance. Whether that will spur greater sales at lower cost remains to be seen. JL
Lauren Johnson reports in Adweek, Image by Thierry Fournier:
U.S. marketers are poised to spend more than $16 billion on targeted mobile ads this year, reaching $20.6 billion in 2018. What’s more, brands are beginning to invest in location insights outside of advertising and into the burgeoning world of mar tech, where reams of data inform everything from what people are buying and how often they purchase to planning exactly where stores should open.
Marketers have long envisioned a world where millions of people walking by a Starbucks store on a hot day are served an offer for an ice-cold coffee while browsing a website on their smartphone. That scenario, by and large, hasn’t worked out for brands so far due to complexities in ad targeting, challenges around reaching a sizable audience and questions about the accuracy of the location-based firms’ data that relies on bits of information pumped through technology platforms.
Still, there’s a lot of money to be made in location-based advertising. According to research firm BIA/Kelsey, U.S. marketers are poised to spend more than $16 billion on targeted mobile ads this year, reaching $20.6 billion in 2018. What’s more, brands are beginning to invest in location insights outside of advertising and into the burgeoning world of mar tech, where reams of data inform everything from what people are buying and how often they purchase to planning exactly where stores should open.
To dissect the ins and outs of what’s working, what needs fixing and where location marketing is headed, Adweek assembled a panel of six marketers from brands and agencies to hash out the issues for one hour via workplace messaging app Slack. Read on to see how the conversation unfolded.
Lauren 😎 [3:01 PM]: First question: For years, location data has promised marketers granular targeting to hit “the right consumer at the right time.” What are your thoughts about when and how to use location data?
Lisa 📝 : Location data today has many inaccuracies. We use location data with our retail partners as data points to inform decisions at the individual level.
Location accuracy: Measures how closely a company’s data matches to actual location coordinates in the real world.
Abbey: Location data is the digital bread crumbs of offline activity, so we use it in a variety of ways: for insights, segmentation, targeting, analytics and understanding if we drove people to a desired physical location.
Lizzy: I agree. I think everything is still just estimations. You can’t get 100 percent accuracy at any given time. What we have now is better than five years ago or even a year ago, but it’s not perfect.
Warren 🏠 : Nothing is 100 percent accurate. It’s knowing how to use the data and understanding the sources you rely upon.
Brian: Agreed with @Lisa on inherent inaccuracies with location data currently available today, which is why we typically use geofencing to align HotelTonight’s use cases with people who are more likely to have a need rather than target based on a broad DMA location.
Designated Market Area (DMA): A population in a specific geographical area.
Warren 🏠 : Geofencing is likely the most inaccurate of all location data sources. We rely mostly on first-party, app-based IDFA data.
Geofence: A virtual mapped area used by brands to target messages to people at specific locations.
Identifier for Advertising (IDFA): A piece of location-based code within iPhones used for ad targeting.
Brian: Interesting, why do you say that @Warren? It’s been incredibly successful for HotelTonight.
Warren 🏠 : We use geofencing as part of a holistic solution to derive better data. For example, we can determine the difference between an employee and a consumer. Then we can match that user’s ID to ad calls.
Abbey: We used geofencing for an entertainment client to target people at Comic Con because we knew our show’s audience was there. That data drove activation, audience understanding and future targeting.
Lauren 😎 [3:06 PM]: Why is location data inaccurate today?
Adrian 👍🏿 : It’s all dependent on the device, browser and user … all things that are definitionally inaccurate at times. That’s why you mix location data with intelligence data (age, context, sequence, market, etc.). Location is one vector point, not all.
Patrón used three years of drinking data across 12 million users and 100 markets [with Foursquare] to get smarter about what spirits drinkers like. Then we fed that into AI-powered bots, Amazon Alexa and media units. The location data was the building block, but we mixed it with other tools. 🍹
Five to seven years ago, I was just using Foursquare data to get people to check in to stores for badges. Big change!
Lisa 📝 : @Adrian Agree 💯. Triangulation of data is critically important in the digital landscape. Not all location data is inaccurate. However, precision and accuracy is key to scale, and using location data in a silo will not deliver the best consumer experience. In addition, the location of an individual might detect they are near or in a particular store. However, you have no idea [if there is an] intent to purchase.
Triangulation: The process of using multiple pieces of data to verify the accuracy of one piece of data.
We have many retailers that utilize location data in addition to other data sources to deliver the right product mix and creative messaging to their consumers. As an example, an outdoor clothing retailer would customize their messaging strategy differently for someone in Florida versus New York.
Lizzy: I almost see location data like 🍪🍪. Most advertisers still use cookies and they aren’t always accurate. It helps guide your targeting. I also find issues with location data with search advertising. A lot of the accuracy is reliant on your patterns of behavior, which may or may not build a reliable profile. I think a huge differentiation now with campaigns versus five years ago is having the option to track foot traffic based on locations. Any step toward attribution with mobile in particular is huge.
Attribution: Determining that a piece of media drove a conversion.
Lauren 😎 [3:14 PM]: With vendors all pitching their own sets of data, what do you look for in location data?
Warren 🏠 : We look for users who were exposed to ad messages in out of home, digital and TV, and then we can retarget, track them or create look-alikes.
Look-alikes: Piecing together anonymous data to create mini-profile groups that have the same characteristics as an advertiser’s goal.
Abbey: We look for partners to allow us to action against their data across as many platforms as possible and to be merged with as many additional data sets as possible. So for us, the best partner is a flexible one.
Lizzy: Agreed with @abbey. I look for a partner that can optimize based on their data that is frequently updated if not in real time. The data is useless unless I can optimize against it while the campaign is live.
Adrian 👍🏿 : Facebook and Google offer varying degrees of both, but it’s hard to use data outside their ecosystem, of course.
Lauren 😎 [3:18 PM]: @abbey Are you seeing more location firms open to sharing and mixing their data? A few years ago it seems like that would have been a no-go because it’s a competitive advantage.
Warren 🏠 : We see this now. The data market is getting very crowded, so we are seeing partners selling and buying each other’s data in order to dimensionalize their offerings. Sort of an “if you can’t beat ’em, join ’em” mentality.
Abbey: Honestly, that often comes down to us doing the due diligence of looking at data 📊 side by side and triangulating 🔺 it. What we really like are when partners don’t just make their data available on their own networks, but also unbundle it so it’s not just packaged with media. That’s a big plus for us.
Lauren 😎 [3:23 PM]: 👍🏼 Alright—which company has the best location data?
Warren 🏠 : Freckle IOT. It’s all first-party, fine-grain data. We also like NinthDecimal.
First-party data: Data collected and stored directly by a company.
Third-party data: Data collected by another firm that’s used as an additional source for verifying location.
Abbey: One source we like is Foursquare as it not only looks at lat/long data, but also looks at height and depth. When I’m somewhere like [New York City’s] High Line, other location-based services might show the High Line, the office building above it and the restaurants below—Foursquare will know where you are on the High Line.
Lat/long data: The horizontal and vertical coordinates on Earth for an exact location.
Brian: +1 on Foursquare—they’ve come a ways since their pivot.
Lisa 📝 : I think Google wins in this area. They own the software and have some of the best location data with the least amount of limitations. Their map assets also allow them to track start and end points versus just a snapshot in time like others.
Lizzy: Google has the power of their apps, but also additional phone data from Android phones. Facebook has [a] large volume [of data], but Google has the volume and the leg up on having so many different apps and devices that can provide that info. I do a lot of campaigns with search, DoubleClick Bid Manager and custom audiences from Google data and it seems to be the most versatile for me within the last year or two.
Warren 🏠 : Google gets my vote from a consumer point of view, but they own their sandbox and have rules that limit how you can partner—Google is far too restrictive from an agency point of view.
Lauren 😎 [3:36 PM]: A lot of firms now pitch themselves as more of a data source with dashboards rather than advertising players. Why are so many location firms trying to get out of serving ads?
Lizzy: It probably depends on what is profitable. If you don’t have to pay for a large sales team to push advertising and you can sell tech and data to other companies pushing the ads for you, then why not? In the end, many of the companies pushing ads are using the same tech providers and data. It’s all incestuous.
Lisa 📝 : I think location-based companies got over their skis a bit in the beginning. There is not a lot of differentiation between these players and if you can add insights, dashboards and analytics to your mix, you can begin to create more use cases and efficiencies for location-based marketing.
Adrian 👍🏿 : Seventy-five cents from each digital dollar goes to Facebook or Google, so why fight for ad scraps when you can power the platforms, campaigns, clients and agencies? I’ve used both media and data products and think it really depends on what outcome you’re driving.
Abbey: There’s a move toward self-service and making the data accessible to be able to buy through demand-side platforms that are under contract that many location providers had to unbundle.
Lauren 😎 [3:40 PM]: Snap recently acquired Placed for $135 million. Are you more likely to spend money with Snapchat because of the location measurement?
Warren 🏠 : It will help them for sure. It was a smart move.
Lisa 📝 : I have several retailers looking at location measurement and attribution, so I think it will definitely help Snapchat.
Lizzy: Until Snapchat has a better offering of ad products and targeting, it won’t change anything for my clients. In the end, if you aren’t trying to reach a teen or 20-something, Snapchat isn’t the best bet right now anyways.
Lauren 😎 [3:43 PM]: With Verizon and AT&T pushing more into advertising, what are the marketing implications with telecoms getting into location targeting? Can Verizon’s location data turn Oath into the third biggest player in digital advertising after Facebook and Google?
Warren 🏠 : The carrier data is massive and really good. Very eager to see what AT&T does—they hired some really smart talent. I suspect they will also become another walled garden [because] there are huge privacy issues with carrier data.
Lisa 📝 : Each provider can’t grow beyond their own network, which is roughly one-third of the population (maybe more). So they will always be challenged with scale. The jury is still out on Oath.
Lizzy: I typically come across [telecoms] trying to sell their digital inventory when I’m working on TV 📺 buys. It’s a case of digital trying to take a priority from those providers when what I’m there for is TV. They are never on my top list of priorities, specifically from cable telecom.
Lauren 😎 [3:49 PM]: Let’s talk beacons 🚨. It seems like a lot of the hype around beacons and in-store location technology has died down over the past two years. True or false?
Adrian 👍🏿 : We’ve prototyped some really cool beacon-based technology for in-store use at retail. It’s very cool but not ready for prime time. Reminds me of augmented reality—until it can scale without tons of requirements, it’s hard to justify the spend.
Abbey: One challenge with beacon technology is that it’s less scalable because people have to have the device on, transmitting, etc. So while there are some promises around beacons, there are also limitations that are keeping it from becoming highly scaled.
Lizzy: I would say that it has fallen flat. Not as many people are going to stores, period. The potential for a pool of data is likely dramatically lower with the increase in online shopping rather than brick and mortar 🏬.
Lauren 😎 [3:55 PM]: For a while, firms pitched super-precise targeting—like being able to target someone in a mall instead of someone in the parking lot. Is that level of insight as important as it was a few years ago?
Brian: Yes, it is. For example, we message New York Yankees ⚾️ fans to stay for extra innings and book on HotelTonight, so we wouldn’t want to target users who’ve already left the game and are at the subway station already. We only message to users who are at the stadium, not at the station.
Lizzy: For retail and restaurant clients I work on, it is still important. It is often the difference between having the right offer served in the ad for someone already in the store versus just driving by.
Lauren 😎 [4:01 PM]: Last question: What’s the No. 1 thing that you want to do with location you’re not doing now?
Adrian 👍🏿 : Insights are greater than data, so I’d like to have a more efficient way of garnering true insights quickly since this information is so critical. The value of location data is proportional to the insights derived.
Lizzy: I would use it as a heavier portion of brand studies. Brand studies are often broader to be able to get a stable sample, but more granular uses for research purposes would be on my list.
Abbey: It’s a little out there, but we would love to use information about a consumer’s location to influence more relevant real-world consumer experiences, not just more relevant experiences that live on a phone . How do we use location data to unlock greater creativity and relevance, writ large?
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