Monday, January 25, 2016

Basket Analysis Made Easy

This article is aimed at technologists who hear about Basket Analysis and need a simple explanation with examples. Basket Analysis used to be the preserve of high cost specialist providers. Now we have OLAP technology and hardware that makes Basket Analysis available at commodity prices. Everyone involved in retail analytics should understand Basket Analysis. Essentially, Basket Analysis supports analysis of sales by the combinations of items purchased.

To elaborate, I will provide two classic examples of Basket Analysis.

1. Menu Trim
The business would like to remove a couple of low value items from the menu (product list). A smaller menu generally supports lower operational cost and inventory investment. Candidate items might be the lowest by sales value or gross profit contribution. We observe that the lowest value items are Frozen Yoghurt and Fruit Salad, which we can find by a simple slice of items and their sales/gross profit. However, this does not take into account whether customers come in to buy the product on its own, or whether they are buying lots of other products too. We can see from the Basket Analysis query below, that Frozen Yoghurt customers buy lots of other products with their Frozen Yoghurt. Basket Analysis can sum all the products the customer buys with Frozen Yoghurt, which we call Affected Net Sales. This suggests that we can remove Fruit Salad from the menu we only risk the $15,414 of sales, but if we remove the Frozen Yoghurt, we risk $1,899,151 of sales. We say that it is "at risk" because the customers might be coming in especially for the Frozen Yoghurt, and purchasing other products while there. Without Frozen Yoghurt these customers might go elsewhere for their entire basket.

2. Attracting Large Value Transactions
Your business might have a strategy to increase sales by promoting menu items that tend to be involved in large value transactions. Basket Analysis can help you do this by identifying menu items (product items) involved in large transactions. In the example above, Avocado Toast has a high transaction average of $105, while the average transaction for all items is $45. So, the business strategy might be to discount and/or promote Avocado Toast to attract these high value customers.The marketing geniuses will work out a way to attract these customers, which might be by discounting Avocado Toast, offering a discounted side item, promoting quality/health features, inter-company coupon, etc. Once the campaign starts, Basket Analysis can very succinctly report on the success of the campaign. One of the key indicators will be the transaction average of Avocado Toast transactions during the campaign. The sales of Avocado Toast might increase two fold, but if the Transaction Average is halved, you are probably only attracting customers who purchase Avocado Toast alone. Ie, you are not attracting customers with large transaction value. In the chart below, we can see that the Avocado Toast promotion has been successful in increasing Avocado Toast transactions, however, these additional transactions have been small value transactions. The marketing geniuses might need to try a new strategy!

I hope this has shown how Basket Analysis can help business' create better strategies and measure how well these strategies are working. This is just two simple examples of an infinite number of possibilities, only limited by your creativity. Basket Analysis has become a commodity feature in retail analysis and is becoming an essential tool for successful retail strategies.

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