Customer Experience across Touchpoints along the Customer Journey. A Text Mining Analysis

To extract data from Foursquare, we wrote a Python script that uses the Foursquare Developers API to collect relevant data. The Foursquare API refers to physical stores in a city as “venues” and the user-written reviews of the experience in the stores as “tips”. To extract the tips for the venues, we used the “venues search” functionality of the API (Foursquare, 2020), which allowed us to search for "venues" within a certain radius (The maximum supported radius is currently 100,000 meters) from the center of a specific city. We selected Alpha and Beta, cities from the United States (New York, Chicago, Los Angeles, Washington, Boston, and San Francisco), the UK (London), Canada (Toronto), and Australia (Melbourne, Sydney) based on the “Global City Index”.

Using the Twitter Search API through a Python script with the Tweepy library, we initially collected 3,114,924 anonymized tweets, which mentioned 75 retail brands between September 27th, 2018, and April 10th, 2019. This data represents a broad cross-section of English-written tweets on the retail brand’s categories in the United States.