Thanksgiving Analytics: From Cobbler to Mall Stampedes

Thanksgiving Analytics: From Cobbler to Mall Stampedes

Thanksgiving is about gathering with loved ones and not only showing appreciation for each other but to also express gratitude for what we normally take for granted. Not to mention all the welcomed food comas we’ll be in, because nothing beats Grandma’s mac and cheese...

But Thanksgiving also marks one of the biggest days for retail companies across America. That is why each year hundreds of billions of dollars are spent navigating crowded stores to find the best deals. To give you a perspective of how big this day is for retailers; in 2018, the average consumer spent $1,007.24 during Black Friday, which is a 4.3% increase from the previous year. This is a staggering 717.5 billion generated in one day for the retail sector of America.

Here at Keyence, we love digging deep into the data and understanding the meaning behind it to give us that data first approach. So, instead of running my typical sales projects, I decided to have a little Thanksgiving fun. That’s why I asked Ki; what drives the American consumer to go out and chase these deals?

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The Data

For this project, I used data from a survey offered by SurveyMonkey that asked Americans a list of questions about their typical Thanksgiving Day, which can be viewed here. I then asked Ki, based on this survey, to increase the total amount of people that responded “Yes” to the question, “Will you shop any Black Friday sales on Thanksgiving Day?” Ki then told us a very interesting story about the correlation between people attending the biggest shopping event and how they spend their thanksgiving day!

The Results

The first insight generated pointed to the regions of the US that took part the least in the annual shopping day. Ki pointed out specifically that the Pacific region had only participated on Black Friday 16% of the time while the West South Central participated the most.

The next insight Ki found was that there was a direct correlation between the respondents’ age and if they participated in Black Friday shopping or not. Who would have guessed the youngest were brave enough to attend the event and sometimes quite literally fight for those deals!

Finally, Ki found something shocking. People who work in Retail tend to attend the Black Friday festivities. How shocking! People who work inside these retail stores will be working most likely and buying! Not really... Ki found specifically that the Americans who did not work in retail were the most important to increasing the participation in Black Friday. But more specifically Ki found that from this segment of Americans who do not work in retail that they would go to Black Friday if they watched the Macy’s Day parade that morning.

Along with watching the Macy’s day parade, Ki also mentioned something interesting. Well, let’s just say if we got that segment of Americans to choose more apple cobbler for desert we would see an increase in Black Friday shoppers! A correlation between a hot gooey, crumbly, sweet desert can correlate whether someone will bust out their wallet late thanksgiving night.

The Viz

We then put together a targeted dashboard highlighting the increase we need in both viewership for the Macy’s Day Parade and how much apple cobbler we need them to consume. Our goal for this dashboard was to increase the participation for this segment of Americans from 21.68% to 26%. This would bring in billions of more dollars for the retail community! To achieve this goal we would have to bring our apple cobbler intake from 11% to 40% and our Macy’s Day parade viewership from 53.46% to 60%. This insight could be turned into action by possibly making more advertisements for Apple Cobbler during the Macy’s Day Parade.

Now, while this may be a good example of how insights are limited by the amount and quality of your data, it’s still fun to run! Come back to see what we feed Ki next. From everyone here at team Ki, enjoy the Holiday weekend and do not forget to eat some desert and tune into the parade.

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