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How and Why to Use Analytics to Upsell your Business

Rohan Kulkarni
November 12, 2021 |
why to use analytics

Introduction

Getting more in return from what you already have is one key principle of upselling products as a merchant. By obtaining deeper analysis from your customer information you’d be able to get new hidden insights that would certainly increase the possibility of more revenue from your store’s existing consumer base, as now you would be able to offer them the products that are relevant to their needs.

Key techniques to upsell products

Analyze and segment your customers:

Before any analysis of your store’s customers for cross-selling can be done, your store data must first be divided into segments, based on shared attributes, such as average spend, location, or purchase habits. This process is very crucial and requires detailed data mining techniques to correctly decide how and where the segments should be created. Once complete the data view will help track which customers might buy more, and also what they might buy, and when.

With vizB you need not worry about any of these as within just a few clicks your store customer data will be prepared and segmented into sections such as AttentionSeeker, ChurnBestCustomer, Churn Customer, Likely to Churn, LoyalCustomer, NewCustomer, PotentialLoyalist while also providing you insights on customer lifetime value and other deeper analytics.

Use Predictive Analytics

Customer behavior data can be used to predict the likelihood of responding to a cross-sell or upsell offer. Input data can include the products or services that are commonly purchased by your customer.  This data can be further analyzed to identify which customers bought, as well as the dates when the purchases were made.

This information can bring valuable insights for your product marketing team to make data-driven decisions and build product and pricing bundles with more analytical information rather than just simple guesses. Techniques such as market basket analysis and association rule mining will help your team deliver products that have hidden sale patterns amongst them.

vizB helps your marketing team to derive optimal product prices by proving them with insights on demand, predicted seasonal demand, and discounted prices for the products in your store.

Identify your slow-moving products to promote them to a higher audience

It is important for a store owner to manage products and improve inventory performance.  slow-moving products occupy your inventory space for longer, due to the slowness in selling the goods hence having a large number of products with LTR ( low turnover rate) can be harmful to your business.

With vizB, you can identify such products and better manage them. At times all a product needs are some attention which could make these slow-moving products your best-selling product in no time.

Benefits of cross-selling and upselling to your business 

  • Upselling helps generate additional revenue for your business more effectively than selling to new customers. Lead generation at most times is expensive hence it is more efficient and more profitable to upsell to your existing customer.
  • Upselling helps build stronger customer relationships and is not just a sales tactic to generate more revenue for your store but if done correctly, it can help your customer derive more value out of the purchases they make. It helps your team to build better customer experiences and stronger customer relationships.
  • Helps to increase Customer Lifetime Value (CLV) upselling and cross-selling are great ways to increase your customer’s profitability over time and keep them coming back for more.

Conclusion

With access to customer data and the use of techniques derived from machine learning, customer analytics will give your store opportunities in cross-selling and upselling thereby building new paths to generate additional revenue for your store.

By taking a data-driven approach, customer-centric businesses can ensure that upsell and cross-sell offers are not sent to merely achieve a marketing goal, but to help customers achieve their own goal and build a stronger customer relationship with the eCommerce store.

Rohan Kulkarni

My passion to automate and build solutions on AI's ability to absorb/ interpret information dictates my work as an AI engineer. I enjoy building and experimenting with classical machine learning algorithms and deep learning models. I like reading on new tech while for fun I play CSGO and hunt for stories/ patterns in my surroundings.

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