Case Study: Predicting Sales with E-receipts Data – Children’s Place
One of the most common use cases of our e-receipts data is to serve as a proxy of companies’ revenues and sales. When we have access to a consistent email receipts data panel, as the one Measurable AI offers, we are able to generate predictions after the end of each quarter based on historical data, given our data updates frequently on a weekly basis.
Following a Bayesian approach first tested by De Rossi, et al in 2017 with Amazon e-receipt data, we employ Measurable AI’s very own email receipts data for a case on company Children’s Place (NASDAQ: PLCE).
To summarize, the approach aims to estimate the growth rate by calculating the posterior distribution using the e-receipts data, with sales management guidance as prior information.
Based on Measurable AI’s e-receipts data sample from 2020 January to 2020 June, we get the number of total sales for both Q1 and Q2, which results in an estimated growth rate of 1.43 (43%)
We then used the public estimated revenue figures from Bloomberg as the sales management guidance, which falls between 1.27 to 1.65. Following the methodology by De Rossi et al, we take 1.43 as the final estimated growth rate for Q2.
Finally, the actual Q2 sales for Children’s Place turn out to be 368M. This means the actual growth rate is around 1.44, which proves our estimation with e-receipts data is accurate.
Talk to us for for more interesting datasets on food-delivery industry.
Charlie Sheng is a serial female entrepreneur, and a dedicated communicator for technology. She enjoys writing stories with Measurable AI’s very own e-receipts data. You can reach her at [email protected]
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*Reference research: Guida, T., De Rossi, G., Kolodziej, J. and Brar, G. (2018). Big Is Beautiful: How Email Receipt Data Can Help Predict Company Sales. In Big Data and Machine Learning in Quantitative Investment, T. Guida (E.).