Data Viz Done Right

October 19, 2017

Workout Wednesday: Market Basket Analysis

5 comments
For week 42, Emma set us a task to conduct some market basket analysis. Essentially she asked us to figure out which product sub-categories cross-sell the best. This is a very, very common question, especially in the retail sector.

Emma indicated that you would need to use a PC and I'm on a Mac. This, however, didn't pose a challenge.

STEP 1: Join the data to itself

The idea here to join the two Orders tables by Order ID. This self-join allows us to see the cross selling of each line item in each Order ID with all other line items with the same Order ID.



STEP 2: Filter out sub-categories that are the the same in both data sources

The goal of this filter is to remove any product sub-category that joins to a product sub-category with the same name. To do this, I created a simple boolean calculation, then added it to the Filters shelf and selected False.



STEP 3: Create a Total Sales calculation

This is pretty straight forward. Simply take the two sales measures and add them together.



STEP 4: Combine the sub-categories to get a list of the products that sold together

You could do this with a combined field, I merely prefer to write the calculation.


STEP 5: Create the Top N parameter and show the parameter control


STEP 6: Build a bar chart of the sub-categories purchased together sorted by Total Sales


Notice that I now have every combination of product sub-categories purchased together duplicated. I'll need a couple table calcs to fix this.

STEP 7: Check if the current row matches the previous row

With this calculation, I'm checking for duplicates. If I get "True" back as a result, then that means it's a duplicate. Notice here that I'm rounding the sales. I had to do this because Tableau wasn't matching the sales for some reason.


By excluding the "True" results with a table calc filter, I now have removed the duplicates.


STEP 8: Filter to the top N sub-categories

Again, I need a table calc filter. I need to rank the total sales, but since I have twice as many records (the previous table calc filter essentially just "hides" the other rows), I need to take twice as many rows as I indicate in the parameter.


Drag this calc to the Filters shelf and choose True and I have the results I want.


STEP 9: Build the final dashboard


5 comments :

  1. Nice job! Maybe put it in a dashboard with heat map matrix at top with highlight actions between both charts?

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    Replies
    1. Go for it! That wasn’t the challenge posed though.

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  2. Hi Andy,

    Great article, may be you can also try all records in x-axis from one data-set and others in y-axis from other data-set. I tried it a couple of months ago and it give a great approach to data. I am unable to upload any JPEG here :( otherwise shared the snapshot

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  3. To get rid of the duplicates, I used INDEX()<=2*TopN rather than RANK(). It works, but I'm always curious about application outside of this specific example. Are there any issues with using INDEX rather than RANK?

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    Replies
    1. Index is a counter. It’s the same as Rank_Dense not Rank.

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