As a recent graduate of business school, it was inevitable that I was going to force you to read some kind of case study. It’s what we “business school people” do. And as you all know, I am a big believer in the value that analytics can bring to any organization no matter what size. So, today’s lesson will be:
A case study in how a small retail shop can use analytics to increase business.
While I know some of you may not own or manage retail businesses, hopefully, you’ll still be able to find some ways in which you can apply analytics within your businesses.
Ann’s Pie Shop (a fictional name that in no ways implies any connection with any real business of the same name) was experiencing a slowdown in business. Ann attributed this mainly to two factors: 1) the time of the year, June, and 2) the fact that everyone seemed to be on some kind of low-carb diet. So, Ann was looking for ways to boost her business.
In the past, she had always used the same methods of marketing her business: word of mouth, flyers with specials, occasional radio ads, and partnerships with restaurants and non-profit organizations. She thought it might be time try something different, so she did some research and decided to apply some analytics.
Her first thought was to increase more foot traffic into her business, which was located downtown. But she didn’t know how many people walked by her business, and at what times of the day. So, to gather that data, she put sensors in her store windows to count traffic based on day of the week and time of day. What she discovered was very interesting. While she always assumed that evening rush hour would be the highest traffic time, she found that many people were stopping in front of her building in the afternoons around 2:00 (what I like to call the corporate afternoon break). Using this new information, she determined that this would be a good time to advertise her delivery service – so when they were out on their afternoon break, if they wanted a pie but didn’t want to buy it and take it back to the office, they could have it delivered to straight to their home. The result – Ann not only grew her business during this time of the year, she also increased awareness of her delivery business throughout the entire year within the corporate worker demographic.
Next, Ann used analytics to learn more about her pie distribution. She had always had a “gut feeling” for which pies sold well in which seasons but had never really taken the time to understand the numbers. When was peach pie popular? Was there a better time to stock peanut butter pie, or banana cream pie? Ann was determined to find out. She started to record what pies were purchased and when. She tracked as much data as she could – time of day, day of the week, demographics – and how they all affected which pies sold when. She even did some experimental baking to see how new types of pies would sell. This enabled her to not only better plan her daily baking, but also her seasonal baking. By knowing who bought what kinds of pies and when, she was not only better able to keep the right pies in inventory, she was able to boost revenue and reduce the expense of unsold pies.
These are two simple, but reasonable examples of how you can use analytics to approach business problems. Look at your numbers. Think about what they can tell you about your business and how you can improve.
If you’re interested in my thoughts, or how analytics might be able to deliver value in your business, feel free to reach out anytime. We could even work up a case study for your business.
And, if you’re wondering about the pie case study, yes… her last name was Alytics.