We Know Which Suburb Eats More Pizza by Analyzing Data from 15 Million Australians

In his interview with AdNews, Shobhit Shukla talks about how we help brands, enterprises, and publishers make smarter business decisions with human mobility data.

Want to know where Australia’s busiest supermarket is or which suburb eats more pizza than any other? Near, a Singapore-based human mobility platform company analyzing the physical movement of 15 million Australians each month knows. Woolworths at Westfield Bondi Junction is the busiest supermarket in Australia and recently Sydney’s Macchiato Wood Fire Pizza on Pitt Street became the busiest pizza joint.

Media companies are making good use of the movement data, offering advertisers finer slices of audiences to reach highly qualified prospective customers for brands. News Corp Australia in March announced, as a part of a string of enhancements to better define audiences, a deal with Near. MCN, the media sales house for Foxtel and other content brands, says it is integrating Near data to provide richer post-campaign reports including audience profiles and brand affinity attributes.

“Looking to the future, we are currently working through how we can match our Foxtel audience across not just digital but also our broadcast platform with location data to give us a single view of our consumer,” Nev Hasan, MCN’s director of advanced advertising, told AdNews.

“This will allow us to not only understand our consumers better from an insights point of view but allow us to be more targeted when engaging with them – which then presents a truly unique opportunity for attribution modeling across our platforms.”

Near’s data, available in 40 countries, is married with local census and map information. The data collected is being used to understand how people behave in the real world, not online, but offline — where they visit and what they like to do.

“That can actually help us solve a lot of interesting problems, ranging from advertising to development, smart city planning, and understanding traffic movement,” says Near co-founder Shobhit Shukla.

“Near is the largest human mobility platform. We are collecting data on how people move around.”

Movement data gathered from apps

Near provides this anonymous mobile location information by tapping data collected by apps, mostly of the free variety such as weather, gaming, or maps.

“Now for the first time we have an opportunity to understand the behavior of users, not just based on the content they’re consuming, but also the places they’re visiting, and the behavior they exhibit in the real world, “ says Shukla.

“When you merge the two, you get a much better picture of a person’s behavior.”

“For example, a car dealership will want to know who might be interested in buying a Tesla. To find them, the dealership could go to a social networking site and see who’s interested in an electric car. But if you look at people who actually visit a Tesla dealership for a test drive, we would argue that’s probably a stronger signal of their intent to buy,” he says.

Shukla argues that brick and mortar store visits are a very strong signal of consumer buying, “Digital attribution has been very well defined so if you go online and buy something, everything is measured. if someone saw an ad and then actually ended up walking into a store and buying something because of that ad, then the publisher should get credit for that. So we’re also bringing performance metrics and measurability to the large publishers who have traditionally have been about premium content. And if you marry premium content with performance metrics and measurement, then you have the best of both worlds.”

Spatial Insights in Allspark

In Australia, Near has data on about 15 million monthly active users. “We don’t really have a service or a consulting model, we don’t share any raw data with any partner or any customer. All of the data gets surfaced and visualized through the software, and that’s partly also for privacy reasons because we want to make sure that when we get consent from our users to utilize the data, “ adds Shukla.

Near started as a company in late 2012 in Singapore. Most of its research and development is done out of Bangalore in India and San Francisco in the US.

MCN’s plans

MCN describes the ability to add real-world audience insights based on location as amazing.“We have been using location data in various ways across not only our digital platform but also TV to allow us to provide more targeted and relevant solutions for advertisers and brands,” says Hasan at MCN.

“Traditionally location targeting efforts have been focused on proximity, by reaching users close to a location like a casino or a restaurant and serving them advertisements. Over the last 18 months, we have also seen a shift to looking at where users have been rather than where they are and this is when the opportunity expands.

Historical behavior or locations are a unique proxy for future behavior and information – something that is extremely valuable for clients to segment key audiences across the board,” adds Hasan.

Near’s ability to look at historical behavior helps to deliver deep consumer insights, while also being used to measure business outcomes.

“For example, we can look at footfall uplift studies comparing multiple stores over various for consumers who were exposed to advertising vs non-exposed,” says Hasan.

The data takes the analysis further, such as people who have been to footy stadiums during the season and what other locations are these fans likely to visit, and whether they are likely to be gym junkies, passionate cinema-goers or frequent flyers.

“This information is interesting both to a sports codes governing body, but also to major sports advertisers who want to gain deeper insights into how to reach their core audiences,” says Hasan.

Published in AdNews.