In the last part of our pricing series, you read about the added value that the use of Artificial Intelligence can deliver to merchants in the context of pricing. With the right application, online merchants can achieve significantly higher profits with minimal price increases. In the following article you will read how merchants can use Next-Best-Offer to learn about their customers‘ spending habits and intensify customer loyalty over the long term in order to differentiate their market position from the competition.
Meaning of the term „Next-Best-Offer
Companies are learning that using analysis and getting to know their customers on an individual level is the best way to significantly increase sales and customer loyalty. This means that retailers see greater success when they work with detailed and dynamic information about each individual customer rather than aggregating them as members of a broad segment at a specific time. The crucial point is direct interaction with the customer when it is relevant. What steps are necessary to transform new customers into loyal existing customers? The answer: General random offer recommendations must be replaced by individual personalized recommendations. This ultimately leads to customers buying so much more than planned in the online shop.
A few years ago, cost-intensive call centers were used in customer relationship management to tap cross-selling and up-selling potential. „Next Best Offer“ is a much more mature variant: if there is a risk that a customer should migrate, the focus is not on pulling a lot of money out of the customer’s pocket in the short term, but on keeping him there for the long term by addressing him correctly.
Predictive analytics methods are necessary to record the behavior, preferences, background and purchasing history of an individual customer. These include the black box, for example, purchase probabilities or article groups that are of particular interest to the consumer. This results in coordination at the right time with the right product for the individual customer. A continuous learning process is created with data-supported real-time analyses.
Advantages of the „Next Best Offer“
Even if the online shop comprises a five-digit number of products, „Next-Best-Offer“ automatically assigns each individual interested party the products they would most likely buy. The result: more satisfied customers. They feel valued because their wishes are recognized and they are addressed individually, separated from the broad customer segment.
Marketing specialists use the insights into the behavior of their customers (so-called customer insights) to promote sales, bind customers to the company in the long term and maximize customer lifetime value. By defining the next best step in the sales process for each individual customer, retailers exceed customer expectations and deliver the best possible customer experience.
Summary
The larger the online store’s product range, the more retailers benefit from Big Data analysis. As the product range increases, it becomes increasingly unlikely that a product will be included under the random offer recommendation that actually meets the individual customer’s requirements. For this reason, you can use the development of the Next Best Offer from Dastani Consulting to find the right offer for every customer. Even with limited resources, our analyses can help you to place individualized advertisements and to address customers in a decisive manner. The optimal presentation of the products leads to increased contribution margins in marketing and sales.
The choice of a customer-oriented approach with „Next Best Offer“ is the ideal way to significantly increase the conversion rate and turnover in e-commerce through optimal product presentation.
Companies that rely on machine learning and a data-driven business model are better positioned. They are able to take over relevant market shares from their countless competitors in online trading and thus specifically avoid the price war with other traders.
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