Predicting Product Returns in E-Commerce

1) Introduction

Everyone wishes they were wizards, where they could just say ‘Accio’ and stuff would appear out of nowhere. The ecommerce sector has come closer to making this dream a reality. People cast ‘Accio’ when they place an order, and a few days later, their wishes are granted through the delivery process.

But, when the customer isn’t satisfied with the product, you may have to make a lot of effort to ensure a safe yet hassle-free return. In order for you to establish an optimal supply chain to facilitate this, predicting product returns becomes absolutely crucial.

The ecommerce sector is a unique blend of technology and innovation. Most eCommerce companies use third-party services to formulate their supply chain to serve their customers. The logistics supply chain is an integral part of the ecommerce fulfillment process.

But, the logistical supply chain is known for its complexities. Therefore, ecommerce companies have to optimize their fulfillment process and order delivery cycles to ensure a seamless delivery experience.

The delivery of products in ecommerce can be a linear process once you have established your supply chain. The ecommerce returns process can be dynamic due to the higher probability of exceptions.

Therefore, ecommerce companies need to optimize their returns process as they drive the supply chain in ecommerce. One of the advantages of having an ecommerce business is that you don’t have to collect data compared to other fields.

With the advancements in AI/ML in the modern age, you can use this data to get an insight into customer behavior. You can even use it to predict product returns. These insights can be used to formulate your returns process and design a supply chain that can optimally handle your requirements.

You can use returns management solutions like ClickPost, which integrate with your existing fulfillment, and WMS software to help you integrate your supply chain in a single-window dashboard for your convenience.

As you provide a seamless returns experience to your customers, you are expected to see a rise in retention rate and increased ticket size on your platform.

In this blog, we will discuss how you can use the evolving technologies of AI/ML to evolve your ecommerce returns process.

2) Why do you need to predict product returns in ecommerce?

The ecommerce returns process is already a loss-making process for ecommerce businesses. Therefore, it is optimal for businesses to incur a minimum loss in the process.

To achieve this, these businesses focus on optimizing their returns supply chains. When optimizing a process, it is crucial to analyze available data and patterns to design strategies that suit the needs of your business.

Since the entire experience of the ecommerce sector is online, it becomes easier to collect data from different touchpoints with minimal effort. You can use the data to predict product returns for your ecommerce business.

This can help you design your returns process around customer behavior, which will solve a wide array of operational problems for you.

You may face the following problems if you do not predict product returns in ecommerce:

2.1) Pseudo-sales

This term is generally used when a product has a high return rate. It means that the product has good sales numbers but a higher than anticipated return rate. This can create a severe inventory issue as you may end up ordering unnecessary inventory.

2.2) Inventory Lag

When you do not predict product returns in ecommerce, you may have to tackle the issue of inventory lag more frequently. Inventory lag is a term used to describe the gap in the inventory figures due to the number of products currently in reverse transit. These products have not been logged in the inventory yet, but some will be restocked and resold.

2.3) Mismanaged Supply Chain

When you enter a new geography or introduce a new product on your platform, you must make appropriate operational arrangements to handle the order fulfillment process.

Just like you use sales projections to manage inventory and supply chain, you will have to predict product return rate. If you do not do so, you will be left with a hazed supply chain. This will increase your cost as you will have to sort the issues that may arise and, at the same time, affect your order fulfillment speed.

3) How can you predict product returns in ecommerce?

Data intelligence technology is no less than a magic spell. Just as you cast a spell and something happens, the data intelligence takes data and provides you with insights by analyzing the data. As advancements are made in the field every day, these technologies become more and more accessible for everyone.

The way that this works is you will use a general framework that uses the principle of Hypgraph to predict the customers' intentions regarding the products in the cart. This will help you predict the product's return rate even before the customer has completed placing an order.

The principles of the graph will be used to train a machine-learning model on data sets like shoppers' preferences, personal attributes, product reviews, and product history on the platform.

You can use these insights to install necessary operational measures to optimize your returns process. You can even implement a strategy called ‘demarketing,’ where if the likelihood of a customer returning the product is too high, you can suggest other recommendations to avoid the loss of sale. You can even develop a quick local model with the help of the internet.

Alternatively, you can use artificial intelligence returns management software like ClickPost that provides these services in their suites. The advantage of using third-party software for this purpose is that you won’t have to dedicate technical resources. You can just use the data insights provided by the software to predict the return rate for your ecommerce platform.

4) Benefits of Predicting Product Returns in Ecommerce  

Statistics have been at the core of every development for ages. Kings used it to forecast war outcomes; Engineers to calculate efficiency, scientists to calculate probability, and so on. The ecommerce sector has been booming in the post-internet era.

The convenience provided by the industry has almost spoiled the modern-day customer. Now that we understand the why and the how of the ecommerce return rate predictions, it is essential to understand the value of going through this hassle.

But, the business model of the ecommerce sector is not straightforward. You must manage the complex supply chain and fulfillment operations behind the scenes without affecting the customer experience. Return is an integral part of this process and an essential feature in regard to customer experience.

Therefore, just as you forecast sales before launching a product, you must predict product return rates in ecommerce so that you can design an operationally optimized ecommerce returns process. Here are some of the benefits of predicting product returns in ecommerce:

4.1) Improved Supply Chain

One of the best ways to optimize ecommerce returns operations is to make the ecommerce returns process a part of your primary supply chain. When you predict product return rates for a particular area, you can make necessary arrangements operationally to handle the returned products optimally.

4.2) Easier Inventory Management

Since you have already predicted product return rates, you can now easily manage your inventory. This allows you to avoid ordering unnecessary merchandise and keep you aware of pseudo-conversions. Predictions can also help you in ensuring optimal inventory management across multiple warehouses.

4.3) Better SLA terms

As an ecommerce business, it is more likely that you will not be handling the logistics and delivery process yourself. The cost of ecommerce returns is mainly the cost of reverse logistics and restocking. You can leverage your volumes and the predicted ecommerce return rates to leverage better SLA terms with your third-party partners.

5) Conclusion

It is so beautiful to watch so many gears work in complete harmony that allows a machine to perform a particular function. The ecommerce supply chain machinery is made of various gears- logistics, delivery, shopping experience, customer experience, order picking, order fulfillment, and many more.

All these gears should work in perfect harmony at the click of the customer’s button. But, this is only possible if we use the spell of mathematics to make it work. You need to be ready for every scenario possible. That isn’t easy in a supply chain as complex as ecommerce.

One of the ideal ways to tackle these complexities is to predict these expectations before they happen. With the advancements in AI/ML, you can now predict customer behavior and intention in ecommerce. Ecommerce returns are an essential part of every ecommerce operation.

Predicting product returns in ecommerce using data intelligence can help you improve your supply chain and inventory management systems. 

With the help of AI models, you can now predict the intention of the customer regarding the items in the cart before they even place an order. This will help you maintain optimal inventory levels and incorporate the returns process as a part of your primary supply chain.

6) FAQs

6.1) How do I predict product return rate in ecommerce?

The ecommerce return rate is calculated by dividing the number of products returned by the number of products sold and multiplying it by 100. You can use various data insights from machine learning models trained on customer behavior data, or data intelligence returns management platforms.

6.2) Can I avoid returns by predicting the return rate in ecommerce?

The AI/ML models will predict the intention of the customer before the customer places the order. Suppose the return probability of a particular product is too high. In that case, you can use a strategy called ‘demarketing.’ In this strategy, you would recommend similar products with lower return rates to the customers to reduce the likelihood of the customer returning the product.