In this analysis, I answered 5 questions my client had. The goal was to help establish their upsell strategy. You’ll find the answers to the first 2 questions in this extract.

Here is an extract of the anonymized transactional data. The original data was in excel, I uploaded it in the software used to create this report (Rstudio):
date product userId
2012-08-15 Orange 2
2013-11-04 Pear 3
2013-04-04 Kiwi 5
2015-05-30 The whole fruit basket! 6
2014-09-15 Mango 7

Question 1: What is the share of repeat customers?

There are 10286 distinct customers. Out of which 873 bought more than one product. Therefor, the ratio of customers who bought more than one product is 8.5%

Question 2: When oranges are bought first, what is the most common second purchase? What is the latency between first and second purchase?

Let’s first look at the sales data:

First Purchased Product Second Purchased Product Number Of Cases Share Of Cases (%) Purchase latency
Orange Apple 249 67 25 weeks
Orange Mango 85 23 10 weeks
Orange Pear 17 5 35 weeks
Orange Kiwi 14 4 27 weeks
Orange The whole fruit basket! 4 1 50 weeks
Orange Orange 1 0 0 weeks

67% of second purchases are Apples. Half of these Apples are purchased in the first 25 weeks after purchasing Oranges. Example users that follow this pattern are: 7006, 10726 and 12385.
23% of second purchases are Mangoes. Half of these purchases are made in the first 10 weeks after purchasing Oranges. Example users that follow this pattern are 4764 and 13029.

Let’s then look at the distribution of second product purchases:

Each bar in this graph corresponds to a 5 week period.

Apple sales peak at the beginning (first 5 weeks) and then slowly decrease. Mango sales peak at the beginning (first 5 weeks) and then drop very sharply.

Based on this distribution, I would offer Apples once in the first 5 weeks. And continue offering them every 5 weeks for a year. Or maybe every 10 weeks if 5 feels too intrusive. As for the Mangoes, based on the distribution in question 3, I would offer them as the client is purchasing oranges.

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This report was generated with the awesome R software (it is free). It is a data analytics software. This report was focused on the latency between first and second purchases. It would be very easy to add the latency to 3rd, 4th and 5th purchases.