There’s a raging debate on whether Nairobi residents can sustain the mid to high-end businesses being setup in malls and other “middle class” neighbourhoods. What better way of tracking purchasing power of Nairobians than monitoring the conspicuous consumption of coffee 😉 .In the spirit of being humorous and factual, I give you The Espresso Index – a tracker for the number of customers indulging at Java House Africa outlets.
As a coffee addict, I kept most of my receipts from Java House. Within the receipts, there is a number succeeding the letters CHK that indicate the number of customer you are at the time of purchase. Although the number sometimes overlaps between days, we can the estimate number of customers per day through data normalization and extrapolation.
Let’s get started with Java Junction which I do have a good number of receipts. The process would be to get the CHK number, estimate number of people served per hour then add CHK number to number of hours remaining in the day multiplied by no of customers per hour. The following graph (index) is born.
The graph looks ragged because of very little data used – with more data, it should smoothen out and show trends. However, we can still deduce that the outlet serves on average of 650 customers a day. If each customer spends on average Kshs 500, that translates to Kshs 325,000 a day and Kshs 9.75 million a month.
Take this analysis with a grain of salt, a lot of assumptions and estimates have been made. Example the outlet processes 20 customers an hour and customer arrival is uniform across the day (which isn’t usually the case).
Inspired by Caffe Con Leche Inflation Index
Are you an influencer looking to utilize your skills or a brand seeking connection to the right influencer ? Blue Bear App matches businesses to online influencers and provides an analytical platform to manage online campaigns. Engage them today of their portal https://www.bluebearapp.com/