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Retailer Evil Villain: Customer Returns

Power BI Dashboard

About this project

As a customer, have you ever ordered specific products through e-commerce and apparently you received the wrong product? have you ever frustrated with the way a retailer processing the order so that it took so long for the products arrived in your place? If the answer is yes, then we both agree that customer satisfaction is number one priority for retailers to sustain their businesses. In the supply chain field, it's called order processing. The process begins with the company accepts the order from retailer then end up with the customer receives the product. Now the question may pop up in your mind, should retailers care about the order processing? absolutely! Here are the reasons:

  1. An effective order processing can help companies to avoid overstocking and understocking issues.
  2. Being accurate on order history and trends can lead to optimal inventory level.
  3. Keep in mind that effective order processing can affect faster inventory turnover and happy customers!

Let's imagine this situation.

You already receive your order after a long wait. Unfortunately, after you are unboxing the package, it's a wrong order! Even worse is the situation that you receive a damaged product. What do we do in those situations? Yup, returning the items. Customer return is an absolute nightmare for retailers. Because customer return can potentially lead to the lost sales. People may possibly not shop again from the same retailer due to a poor return experience.

From the retailer side, what should they do to achieve happy customer and reducing customer returns?

The answer is action.

They need to take action promptly based on data. They need to track every order to achieve happy customers.

In this project, I've developed a sample dashboard to help the retailer gain visibility of every order. This is part of FP20 Analytics Challenge 10 and sponsored by ZoomChart. Here are the measurements used in this dashboard:

  1. Total cost
  2. Average order processing time in days
  3. Average delivery time in days
  4. Return rate (order and product level)
  5. Return impact on profit
  6. Losses - returned items

For retailers, are you ready to embrace your nightmare? It's time to use data in your pocket!

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