Ozzie Sport

If you haven’t figured out in my many posts, I’m not Australian; I’m an American. More specifically, I’m an American from the Chicago area with friends and family who live there. Of late, I’ve been interested in Foursquare check in patterns. (What’s the value? What’s the potential ROI? Are there patterns that appear that could be useful for using a campaign on? Is there another way to measure success beyond say coupons on site?) Rather than look at local patterns, or Australian patterns that could possibly be construed as research that might have copyright implications beyond my control, I decided to look at patterns for Chicago at one of my favorite chain restaurants. That was Subway. (Added bonus: Local to home research based on my sport methodology research, that could help me get a job back home [if I want to go back].)

I found a list of about 47 Chicago based Subways. Most of them appear in the loop. In at least one location, there appears to be a duplicate location. A script I had assistance with in developing checks those locations everyday at midnight US CST. It then records the total checkins and total people at the location for that day, compares the difference from the previous day and gives me the total checkins and total people for the past 24 hours. This process, once started, relatively easy. (If you have some business in the US Central Time, I could start getting that data for you tomorrow.) Every day, I get an e-mail with the total daily checkins in csv format. I put that data into an Excel file so I can process it. Fun stuff.

One of the patterns that has emerged is that there appear to be more weekday checkins to Chicago Subways. In fact, 15 Subways of the 47 have more weekday checks. 6 Subways have more weekday checkins. 25 of those locations are tied for checkins between weekdays and weekends. I believe with one exception, they have zero checkins across the five days looked at. The remaining Subway had a negative checkin and I slotted it into its category. Not sure why/how that happened that led to a negative checkin day.

The fact that these locations are mostly Loop locations probably explains a lot of what is going on with this data set. The Loop is the business district. Office workers would go to Subway during the week. They checkin during those times. Fewer workers in the city on the weekend, fewer checkins.

These patterns likely would be different for other businesses in Chicago (probably not as much in the loop) and elsewhere depending on that location and business type. More data on more businesses would be interesting. The holidays coming up will skew things for a bit because Christmas Eve, Christmas Day, New Years Eve, New Years Day are likely to be non-normal business days. I’d love to look at some of this data beyond my limited sample in order to better grasp how people are using the service and what the business implications are. (Is anyone really looking at total daily checkins for certain classes of businesses? If so, would be something I’d love to read!)

Anyway… on with the data!

Related Posts:

• 2011 Cricket World Cup: Foursquare Checkins to date
• Most popular AFL teams across social media sites (February 14, 2011)
• Australian Sport Foursquare Data Visualized
• Australian sport Foursquare checkins: December 27 – January 2: A-League leads