For local ad campaigns on social media, a user's location data is critical. But how accurate is this information, whether it is self-reported or pulled via technology?
Before jumping to issues with location data, it's helpful to recognize that there are a variety of ways locations are recorded and reported on social media. 140 Proof lists some of these collection methods:
- People on all social platforms add real or vanity locations to social profile bios
- Foursquare and Facebook users check in at locations on platforms
- Twitter users elect to attach GPS location data to their posts
- Apps use IP addresses to distinguish their users
As self-reporting may be the least accurate of these methods, the study differentiates between a user's stated location ("I'm in NYC.") and their recorded observed location (You're really in Hoboken.). The stated location data stems from self-reported location in social media profiles and check-ins, and requires an action from the user. The observed location data happens without direct action from the user, and is typically pulled from GPS tagging or IP address. Misrepresented location data from social media data often lies within geographic drift, defined as the difference between a user's stated location and their observed location.
"Take Chicago, for example. Of all social users who say they’re in Chicago, more people were observed outside of Chicago’s blue circle than inside it. Put another way, people who say they’re from Chicago are often not even near Chicago. By stark contrast, the geographic drift for most who state their location as Jackson, Mississippi is much more tightly confined. The same principle applies to this part of the chart — more people who say they’re in Jackson are observed outside the circle — but the drift is much less."
This drift may occur for a variety of reasons. One simple explanation may be clarity, as the location "New York" is more recognizable than "Hoboken", users are more likely to self-report their location at New York for practical purposes. Drift can also be attributed to commuting, especially in a city such as Los Angeles which is known for heavy traffic. Other factors reported by the study include credibility and social graph distribution.
In contrast, there are locations which experience little drift and offer more accurate data. One example from the report is Napa, California. Known for it's wines and tourist attractions, the locals are true locals including retirees, families, and local business owners who are all less likely to travel frequently or long distances.
What does all of this research mean for marketers? In AdWeek, 140 Proof CTO John Manoogian said:
"Location had previously been considered a single set of data. This suggests it’s at least two. We need to be considering exactly where this person is. And we have to consider how location affects them as a person and how is that coming into the campaign. There are certain sorts of campaigns that are focused on hyper-local and there are others about my state of mind or my identity.”
Local marketers now need to understand how location data is reported and collected on particular social networks before launching a targeted geographic campaign in order to make the most of social marketing efforts.