Americans are consuming more coffee than ever before. In Q1 of 2018, coffee giant Starbucks posted over $6.1B in revenue1. With nearly 14,000 locations in the United States alone, it is common for Americans to see the green and white logo in their daily travels.
A team of analysts contacted us expressing frustration while attempting to manually acquire data for specific Starbucks locations. For several days, the team worked continuously to harvest location data for several cities. The greatest difficulties this team encountered were the inaccuracies in data and loss of time and resources.
Go Get It
By using Atlas, Intuli helped the analysts achieve their data needs while significantly reducing the costs and inaccuracies. In the same amount of time it took the team to harvest several cities, a single developer using Atlas harvested data for nearly 14,000 Starbucks locations across the United States.
The analysts approached this problem by using Atlas to navigate and extract information from the Starbucks website. Starbucks' site is set up to facilitate a customer search for the nearest location, within a small geographical area. This structure makes it time-consuming and cumbersome to gather data on a broader scale. With Atlas, the developer was able to automate the collection of data. It took less than a week to collect a nation-wide data set without the inaccuracies from traditional harvesting methods.
Additionally, Atlas provided the ability to continuously update the data set. This allowed the analysts to gather current information without sacrificing time to check for new locations. Furthermore, with the transformation tools in Atlas, the analysts had the ability to format the data into structured model.
At the beginning of the project, the analysts were limited to small subset of data covering just a few cities. With the help of Atlas, the analysts were able to capture a nationwide representation of a major corporation. From their results, the analysts were able to produce the heat map shown In Figure 1, accounting for nearly 14,000 locations harvested by the developer.
With the initial success of harvesting data from Starbucks, the analysts had the resources to include other major coffee chains. By using Atlas, the analysts were able to capture and maintain data sets from the key players in the coffee industry such as Dunkin Donuts, Tim Hortons, Caribou Coffee, and Peets. Figure 2 is a breakdown by company of all the locations harvested. At the end of the project, the analysts obtained comprehensive insight into a dynamically changing industry.
Major Coffee Chains
Locational information was harvested from 5 major coffee chains
In 101,041 page loads, 24,308 unique locations were found
In under a week, the team of analysts were able to complete 101,041 page loads.
What started as an endeavor to gain insight on an individual coffee chain turned into a view of a major United States market. Atlas drastically reduced the time it took to accurately harvest up to date information. Due to the efficiency in harvesting with Atlas, the team can capture new information and maintain their current data sets.
Curious to learn more about data harvesting and how Atlas can help your company?
Contact us to obtain an in-depth view on how the data was harvested and how Atlas can enhance your data capabilities.
1 Geekwire - https://www.geekwire.com/2018/starbucks-posts-6-1b-q1-revenue-mobile-order-ahead-usage-grows-slightly-11-u-s-transactions/