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How to upsell and cross-sell better with Predictive Analytics
Whenever you go to a restaurant after the meal the waiter may come and ask you "Would you like to order some dessert ?". This offer is a classic case of cross-selling.
Businesses have been cross-selling and upselling for a long time to maximize their sales and profit. But it is in this age of online business the concept of upselling and cross-selling has taken a new meaning and relevance altogether for eCommerce.
Amazon has reported that 35% of its revenue comes from upselling and cross-selling. The reason why Amazon does so well with upselling and cross-selling is due to its highly personalized and relevant product recommendations. Amazon has mastered the art of cross-selling and upselling, all thanks to the technology of Artificial Intelligence and Predictive Analytics.
What is the difference between upselling and cross-selling?
Upselling and cross-selling are closely related but differ very much in both meaning and process.
Upselling is when you recommend a customer to buy a higher-priced option of the product he has selected. The recommendation could be a more expensive model in the same category or an additional feature such as a warranty. The below example shows a higher-priced alternative with an added item.
Cross-selling is when you recommend a related product that compliments the customer's existing purchase. This additional product could be of a different category but will be fulfilling a need unsatisfied in the original purchase. The below example shows the recommendation of products that the customer may need in the future.
How Predictive Analytics works for Cross-selling and Upselling?
Cross-selling and upselling recommendations are neither based on intuition nor on some general rule that fits all transactions. Predictive Analysis and Artificial Intelligence use some of the following customer data to cross-sell and upsell effectively:
past purchase history
assessment of his purchasing power from his annual CTC package on the glassdoor profile
demography and social status
frequency of shopping
Predictive Analytics can help you ace the game of upselling and cross-selling. Enterprises must realize that already there is an extensive amount of customer data available, and all they have to do is make use of this data with Predictive Analytics tools to sell more and grow more.
4 steps to win Upselling and Cross-selling with Predictive Analytics
Know the customer's behavior - Today the majority of customers tend to check the online price of a product while shopping for it in a physical store. Customer behavior is changing rapidly; for businesses to know what will work with a particular customer and what will not, they have to have an all-around understanding of customer behavior.
Predictive Analytics and Artificial Intelligence help to understand the overall customer behavior based on the following fields:
The kind of Content that engages the customer such as blogs, personalized emails, live chats, etc. Knowing the right content and channel is the key.
Customers' Social Media Activity, his sharing habits, and indulgences.
Customers' responses to Campaigns such as email marketing campaigns, social campaigns, etc.
How the customer engages in Advertising on various platforms such as social advertising, display, or search advertising.
Data on his shopping history, purchasing power, and product preferences.
Customer Profiling - Artificial Intelligence and Predictive Analytics tools can help businesses to segment customers based on years of data of purchasing history, product usage, offline v/s online purchases, etc.
Identifying and segmenting customer in the following categories can help you do better with upselling and cross-selling:
Promotion Seeking Customer: This segment of the audience falls for steep discounts and personalized promotional offers.
Controlled Spending Customers: This set of customers shop for the fixed budget, and they will not increase their spending even if they buy additional products.
Service Demanding Customer: These customers have a habit of overusing customer support channels. They tend to reach out for customer support even for the small issues that occur.
Revenue Reversing Customers: This set of customers is bad for business. They tend to return purchased products, terminate contracts pre-maturely, etc. With the more they buy, they display this behavior more frequently.
Product Recommendation with Predictive Analytics -
Predictive Analytics sums up the likelihood of a customer's response towards upselling and cross-selling. Predictive Analytics proves a highly potent tool for marketing teams to bundle the right product and services to maximize sales and revenue.
Measure the success of Upsell & Cross-sell with Predictive Analytics -
Customers today prefer a highly personalized shopping experience. The inability of businesses to meet this need of customers can cost them dearly in the form of revenue and customer loyalty. A large part of the success of upselling and cross-selling lies in providing highly personalized recommendations. There are several triggers on the customer's journey of purchasing the product. Predictive Analytics and Artificial Intelligence help to measure the customer's response at the various stages of the purchase pipeline and how the customer can be further engaged to push him closer to hitting the "Buy" button. Recommending the right product at the right time through the right channel is what every business looks for conversion.
It is far cheaper and easier to cross-sell and upsell, rather than generating a new lead to create a sale. With Predictive Analytics and Artificial Intelligence tools, we have the right infrastructure and insights to maximize cross-selling and upselling. Offering the right recommendations to cross-sell and upsell will improve customer loyalty and help you to create a higher customer lifetime value for your business.