As more and more brands look to better communicate with their audience and target messaging based on location, a few questions keep coming up. How accurate can I be in understanding where people are? How can I understand what people are doing in those different locations?
These are all good questions, and as marketers are starting to see, location data is very noisy. Whether it is Google Maps showing you in the wrong location, geo-tagging information tied to a photo being someplace you’ve never been, or when you try to check in to Foursquare at your favorite restaurant and it’s the fifth place on the list of options to check in.
In my last column I interviewed Curt Hecht from The Weather Channel about ways marketers can and should be leveraging weather data to understand and target their messaging. For this column, I wanted to get a bit deeper into the data that marketers can collect and understand based on specific locations. So I reached out to David Shim, founder and CEO of location analytics firm Placed, to learn more about what they are seeing from their clients and in the industry overall as well as to share general insight into the quickly evolving location measurement industry. The following are some of the topics that we discussed that I thought would be interesting to share.
Jason Burby: The amount of data available from the use of smartphones is amazing from what people are looking at to where they are physically. When talking about location, how accurate can you get and how do you overcome location-based problems in terms of accuracy that we all experience every day?
David Shim: In early experiments we found that 90 percent+ of the time assigning the closest place to a latitude and longitude resulted in an incorrect match. This level of noise impacts a marketer’s ability to effectively leverage location insights into mobile ad targeting decisions. On the flip side for a publisher the ability to target based on a mobile device’s location is generally limited to 100 meters, the length of a football field.
JB: So how do you overcome that? One-hundred meters can mean very different things in terms of activities or interests.
DS: It takes more than a single latitude and longitude to determine a place. We convert that noise into signal with two distinct approaches, the first around cleaning up location data, and the second focused around contextualizing the places around a location.
To more accurately determine location, Placed looks at a series of features that include latitude and longitudes, location source, accelerometer, gyroscope, compass, etc. By treating location as more than a single value, we are able to cluster sets of data points to infer a more accurate location. This location is then contextualized to a set of nearby places, which are determined by a set of features including proximity, popularity, and category.
The end result is the connection of the digital and physical world, where instead of cookies you now have smartphones, and instead of page views you have places visited in the real world. This level of context not only provides insight into where consumers are consuming your content, but also why.
JB: It reminds me a bit of the early days of web analytics where smart marketers knew there was a ton of value in the data, but struggled to figure out the best way to tie it to their specific business. What are some examples that your clients, or companies you admire are leveraging location data to impact their business?
DS: What we are really talking about is connecting the digital and physical worlds together. A few examples of ways companies are using this information are:
- Consumer insight. Apps with bar code scanning as a feature can implement Placed Analytics to understand what businesses their users were nearby when scanning products (e.g., 18 percent of price scans occur at Best Buy). Additionally we’re seeing publishers tag their content to better understand where their readers were when interacting with their content (e.g., 7 percent of sports content was consumed at Macy’s).
- Media planning. Companies are starting to implement Placed Analytics into their content (apps, websites, etc.) to better understand where consumers are interacting with their brands. This data is leveraged to build out marketing campaigns that take into account location (e.g., location-based ads, out of home, event marketing). This can allow marketers to better target the right message to their audience.
- Inventory availability. As early adopters on the publishing side start to highlight the offline behaviors of their audience, agencies will start asking all publishers for the offline behaviors of their audience, and associated inventory availability. In order to answer this question, publishers are implementing Placed Analytics to understand the places people were nearby when consuming their content.
My conversation with David triggered a number of ideas on ways marketers could leverage this type of information. It was also interesting to consider why CPMs for mobile are so much lower than desktop CPMs. David believes a lot of that has to do with the difficulty in quantifying the impact, like the panels and measurement tools do for TV (Nielsen), radio (Arbitron), and online (comScore, Compete, DoubleClick). Truly understanding and quantifying the value of location that is always changing could be just what is needed to prove the value of mobile CPMs.
When you step back and think about the implications of marketers knowing where people are interacting with their content (not just what state or city they are in, but are they in a restaurant, at an event, in a hotel, or a residential area?) and then tune and target the messaging based on that, the potential is amazing.
Shoot me a note with any questions or other ways marketers can be using this type of information to improve their communication with their customers and prospects.
What are some of the major developments that are likely to shape multi-channel marketing in 2017?
Time is running out to feature your company in our inaugural Mobile Vendor Reader Survey.
Marketers create personas to better understand their target audience and what it looks like. If marketers can understand potential buyer behaviors, and where they spend their time online, then content can be targeted more effectively.
What’s behind a successful data-driven marketing strategy?