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RedBubble Sales Analysis Using Python

I’ve created a notebook that will allow RedBubble artists to do basic analysis on the sales data from their RedBubble page(s).

RedBubble is a print-on-demand service that does all the hard work for you in return for you hosting your designs on their website and accepting a tiny commission on each sale. They do the printing and the marketing for you freeing up your time to focus on making good designs and helping people find them.

RedBubble help their creatives track their progress by providing a Dashboard of how people are visiting their pages. If that’s not good enough, artists can download the Sales History and do further analysis themselves.

Why not use Excel for this?

Excel is great for manually moving data around and you can do everything here in Excel if you have the required skill. The good thing about Python is that you can automate the dragging and dropping of the data more easily

What will this Notebook do?

The aim is to be able to simply upload a CSV from RedBubble (Sales History) and mass run all the functions that produce useful insights that matter to you personally.

Why are using Google Colab?

It is the most accessible Python Notebook application alongside Kaggle and Jupyter Notebook. All you need a Google account and you can download a copy onto your Google Drive.

If you’re here, you’re probably looking to learn Python — can I recommend DataCamp which have interactive courses and more Python notebook templates like this to allow you to explore datasets and perform machine learning tasks with ease.On another note, where do you design your merchandise and have you heard of Canva or Placeit? Combining these two will allow you to create new, unique designs that appeal to your niche audiences.

Download your Sales History from RedBubble:

Go to https://www.redbubble.com/account/sales/by_sale

Upload the downloaded CSV to your copy of my Google Colab file

Copy the filepath into the required code box as shown in the Notebook and run through each block of code to see your insights.

The main sections within the Notebook are:

  • Uploading the Sales History CSV
  • Converting the Sales Dates to the correct format
  • Summary Tables
  • Trends and Pattern Graphs

These charts will be most valuable to artists including:

  • Line Graph of Total Sales Growth by Month
  • Bar Chart of Highest Selling Designs (Works)
  • Bar Chart of Highest Selling Product
  • Stacked Bar Chart of Highest Selling and Most Profitable Categories
Total Sales Growth by Month

You may want to look out for whether you’re not as profitable but you’re selling more low value units or vice versa. This way you can adjust your strategy.

Highest Selling Works

I feel a lot of people will have similar split of sales where you’re selling mostly through a small margin of products.

Highest Selling Products

I don’t mind showing you the ratio of products I’m selling :)

Profits from Product Categories Per Month

Here the Google Colab Notebook. Make a Copy and run your own Sales History through it.

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