How Burger King used data science to attract McDonald’s clients in Philadelphia

Who wouldn’t like a cheesy soul full-filling burger at Burger King? But how can Burger King increase its customer base? Given the number of street food outlets in Philadelphia and their competitors, Burger King has to have its presence felt where there are customers, even if that is in the competitor arena.

Now, one way to approach the customers might be to advertise where Mcdonald’s outlets are present. McDonald’s has a good customer base and attracts new visitors as well. Burger King could take this to their advantage and sell their items at distinguished spots for increased visibility. According to a CNBC report published on December 4, 2018 — Burger King took a big step with the launch of 1$ Whopper. All you had to do was get within 600 feet of any 14,000 McDonald’s restaurants, and you are unlocking a whopper for 1$ on the Burger King app. That is turning every McDonald’s into a Burger King restaurant.

Burger King also piggybacked on McDonald’s popularity and goodwill with a ‘Day Without Whopper campaign. As part of the campaign, they stopped selling their top-selling ‘Whopper’ burger for a day in Argentina to increase sales of McDonald’s Big Mac burgers. The reason being that the proceeds from every Big Mac sold were donated to Children with Cancer.

In this article, we shall see how using the data, Burger King can put their advertisements by locating the McDonald’s outlets.

Data Sources

The datasets used in this article have been imported from:

• OpendataPhilly
• Opendata
• Google Maps

Google Maps APIs (Application Programming Interface) has been used to provide traffic data. The dataset is an open data set and is available to the data science community.

Data Analysis

The data has been analyzed using Python and visualized with Power BI.

Data Analysis Meets Billboards Advertisement

Did you know that data analysis and billboards have a connection? Based on a lot of data points, McDonald’s created two temporary billboards — that teased their competitors Burger King. This article takes inspiration from interesting content that readers can find here:

https://www.thedrum.com/creative-works/project/tbwaparis-mcdonald-s-france-directional-billboard

As part of this case study, we will be doing what can be described as Data Science Meets Billboard Advertisement.

Getting Philadelphia Billboards data

First, we shall need data. If Burger King is going to have their presence around McDonald’s they need McDonald’s’ data as well as Billboards data. They also want to know which Billboards are best to put advertisements on since advertisements have their cost. This goes on to show how data points procured from Google Maps can help quantify traffic which eventually helps price traditional billboards based on traffic. The data is located at http://data.phl.opendata.arcgis.com/datasets/5eb34bd14d3e4cc996168a1a1c026e0e_0.csv. For more information, check out https://www.opendataphilly.org/dataset/outdoor/resource/5a384091-f83d-4b78-89c1-b2f498fb1802 for more information.

Getting McDonald’s data

Getting McDonald’s’ data is a bit challenging. But we can take help from Google Maps for the same. Once you have all the requirements satisfied you can use the url to fetch the data. Make sure you correctly enter the API key.

Plotting McDonald’s Data

First, let’s plot the data we have for the McDonald’s data. We need to use the Google Maps API to get the numbers.

Using Google Data, there are some 60 McDonald’s outlets in Philadelphia at the time of writing this article. In the future, this number may change.

Distance Between McDonalds and Philadelphia Billboards Data

Now that we have both the McDonalds and Billboards Data, it’s time to do the magic. We need to know the distance between the closest billboard to any Mcdonald’s outlet. For our purposes, we shall be using 0.5 KM as the least distance.

Using the Haversine distance we calculate the distance between two points. That means, we use the angular distance between two points on the surface of a sphere. While the first coordinate of each point is assumed to be the latitude, the other is supposedly radians.

The advantage of doing this is, Burger King can save the cost of ineffective advertisement and can invest only where there are McDonald’s outlets, effectively reaching out to potential customers.

Color Codes

Blue: Shows the locations of the billboards that are within the distance of the McDonalds

Red: Shows the locations of the McDonalds.

Notice that as we decrease the distance, we get more precise Billboards.

100 Meters

When we set the distance at 100 meters, there are 15 billboards that can be utilized as they are near a McDonalds’ outlet. However, since these billboards are very near, they are overlapping on the map.

250 Meters

When we set 1/4th of a kilometre, (250 meters), we get 109 billboards.

Half Kilometer

When we set the distance at half a kilometre, we get 259 billboards.

One Kilometer

Setting 1km some 688 billboards can be utilized.

Summary

After analyzing all the data, we draw the following conclusions:

1. Burger King can advertise close to McDonald’s by leveraging the power of Data Science. By doing so, Burger King can gain very loyal customers and achieve a return on investment.
2. If we look at the data, it seems like billboards with a 100m radius are the best choice since the target focuses on McDonald’s customers.
3. McDonald’s is the direct competitor of Burger King; hence if Burger King utilizes the billboards within 100m, it will help them gain loyal customers.
4. Besides the 100m setup, 250m is also a reasonable distance since the number of billboards increases. However, they are far from the eatery. Advertising beyond a 250m radius is not a good idea.
5. If you were a Business Analyst for McDonald’s, you could further build your results. How?

1. Data sets can help you look for which way the traffic faces the billboard.

2. Is there a convenient way to take a detour to the closest Burger King location for a customized billboard?

3. Check if the billboard is digital and whether you could customize the message by the time of the day or the weather?

4. Are there other billboards in the same location? What are their dimensions and exact position?

Code

All the codes used here are available at GitHub and can be found here https://github.com/Mindtrades-Consulting/How-Burger-King-used-data-science-to-poach-McDonald-s-clients-in-Philadelphia-

This analysis was conducted by www.mindtrades.com, a data analytics consulting company.

References

1. Catherine Clifford, “You can now head to McDonald’s to get a Burger King Whopper for 1 cent — here’s how”, December 4, 2018
2. TBWA/Paris, “McDonald’s France: Directional Billboard by TBWA\Paris”, March 6, 2016
3. Megan Tyce, “Burger King stops selling Whoppers to help McDonald’s cause: but does it make BK look better than McD’s?”, October 16, 2019