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How To Use Location Data To Map Consumer Intent

Intent marketing produces a high ROI by paying attention to the consumer and, these days, consumers reveal their proclivities through data. Thanks to new technologies, location-based data can be used to measure intent and drive sales.

If you’re a marketer trying to gauge a consumer’s habits and likelihood to purchase, location data could tell you what you need to know and become a valuable asset. But why?

We spoke to Benoit Grouchko, CEO & co-founder at Teemo, who shared his insights on this topic. Grouchko is based in Paris, France and his company has created a  location-based marketing platform that aims to boost in-store traffic.

It’s new and exciting

“If you think about the history of digital advertising, intent-based marketing has been mostly driven by web browsing,” Grouchko said. As smartphones came onto the scene, location data became a new way to improve the accuracy and relevancy of marketing campaigns.

It’s a stronger signal

In the past, marketers were limited in their attempts to reach a specific audience with specific intent. They would often target based on browsing history. If you are reaching out to people who have shown a strong intent around cars, it might be better to target people who visited actual car dealerships as opposed to auto-related websites, Grouchko says. This physical interaction provides a stronger signal. The consumer took their quest into the real world, and moved away from  hypotheticals

Travel data is valuable

“When it comes to trips, it would really depend on the kind of advertiser that you would want to engage with,” Grouchko said. “So if you think about people who are in the traveling industry, what you want to leverage there, is, basically — how did that person travel over the last twelve months? Is the person a frequent business traveler? Which routes is that person usually flying? Is the person an actual tourist? Okay, what kind of destinations, and when do those travels happen? When do the purchases happen?”

Consumer intent can be determined by looking at the underlying patterns. The consumer could be a frequent business traveler, but might only travel to the Caribbean when on holiday, at a consistent time of year. They may research tours, and book, at particular times of year.

“So that’s another strong signal,” said Grouchko. “And then you combine all of that, and you’re like ‘okay, when is the right time to reach out to that user, to that individual, and what is the most efficient way to reach out?’”

If a business traveler flies back and forth from Boston to San Francisco on a weekly basis, a marketer would obviously want to engage that user with an offer along that route, since it would have more relevance than a random, untargeted offer.

“You wouldn’t be able to do that if you didn’t have the information. So that’s one way of engaging the users. Another one is the hotel industry,” Grouchko said.

Location data might reveal whether a traveler tends to stay in luxurious resorts, or in cheap, roadside motels. Marketers can target them with relevant offers accordingly.

Download our eBook: The Rise of Intent Marketing — Best Practices for Data and Personalization

Shopping partners are revealed

“If you are a high-end luxury fashion retailer, you probably want to engage with users who have recently visited or who frequently visit high-end luxury brand fashion retailers,” said Grouchko.

Consumer shopping habits can reveal an affinity for particular brands. That same data can also be used to conserve capital.

“If you realize that that user is usually going shopping at a particular mall every Saturday, if you don’t have a shop in that mall, it’s not that interesting to engage with that user, because that user is much less likely to go to your shops,” Grouchko explained.

Additionally, it can be valuable to look at the time of day. By looking at both the where and when, marketers can engage with the user at exactly right time, based on their individual patterns.

“There are loads of signals that you can get with location,” Grouchko said. “So basically, what you can do is take all the signals together, put them in the engine, and then automatically target users based on their intents.”

Campaigns can be tested for efficacy

In addition to measuring intent, a marketer could also use location data to measure the performance of a campaign.

“So that’s where you can actually apply some pretty sophisticated machine learning, because as you have the feedback loop of who you targeted and who went to your stores,” Grouchko said. “You can keep on optimizing, optimizing, optimizing, to keep driving more visits and engage with relevant users.” 

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