January 19, 2017

January 11, 2017

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Generate realistic data on shopping habits

March 1, 2017


 The brief


Create a dummy data set which shows realistic shopping habits and customer preferences.For example, a data set which shows the following assumptions as insights:

  • Estimated income related to age - generally older people have higher incomes.

  • Amount spent on goods related to income - generally people with higher incomes spend more.

  • Various choices that customers make, such as product purchased and method of payment, are related to income and age - generally younger people shop more on their phones.


How we created the dummy data


We generated the data set in DataBake using the following variables, as columns:

  • Address

  • Age (18-65)

  • Gender 

  • Estimated Income (>£10k)

  • Retail Purchases (Jeans, T-shirt, Jumper, Coat, Shirt, Trousers, Shorts)

  • Amount Spent on Goods

  • Method of Payment (E-Commerce, In Store, M-Commerce)





This is what our realistic dummy data looks like when visualised.




View and download 1000 rows of this data set.



Think you can bake a more insightful dummy data set?

Grab a byte at app.databake.io


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