Selling in the Digital Age

TL;DR: In this article, the authors address the question: How does employing the classic sales model with customers with greater and lesser preference certainty affect the sales interaction outcomes of (1) purchase probability, (2) sales revenue, and (3) customer satisfaction?

Abstract: Advances in technology have revolutionized consumer buying behavior. The internet has provided customers with a cheap source of information that can help them make informed buying decisions. However, many salespeople are still relying on the classic model of selling, which is based on the assumption that customers are uninformed, uncertain, and undecided when they meet a salesperson. This model suggests that salespeople, as knowledgeable gatekeepers of information, should guide customers through the sales process. For example, solution selling suggests that the salesperson should diagnose customer needs and then recommend the right products/services to fulfill those needs. The challenger sales model suggests that a seller should actively teach customers, tailor the sales process to them, and take control of the customer conversation In this report, authors address the question: How does employing the classic sales model with customers with greater and lesser preference certainty affect the sales interaction outcomes of (1) purchase probability, (2) sales revenue, and (3) customer satisfaction? In their first study, the authors collected data from 356 individual sales interactions in 15 different stores of a U.S.-based retailer of durable goods over four months. They show that customers with greater preference certainty have a lower purchase probability when the classic sales model is implemented. (i.e., from more than 80% to 60%). Further, the revenue from a sales interaction is reduced by more than 25% when salespeople use the classic sales model on customers with higher levels of preference certainty. Finally, when faced with customers who have a good idea of what they want to buy, salespeople may decrease customer satisfaction by using the classic sales model technique. A second, scenario-based experiment corroborated and replicated the first study, using Amazon’s Mechanical Turk. This study found that, under high levels of preference certainty, challenging the customer results in a lower likelihood to purchase during the shopping visit. Further, these findings were found to be unrelated to price. These findings point to a need to transform the way that salespeople interact with customers. The authors offer two ways that managers can benefit from this research, and help their salespeople move beyond the classic sales model. Training. Sales managers can teach their salespeople about the importance of acknowledging the differences among customers along the decision-making process and train them on the appropriate tactic in each stage. Lead generation. Customer relationship management technology now makes it possible to monitor customers’ research behavior and to index prospects depending on their stage in the process; therefore, this technology can assist salespeople in adopting the appropriate sales tactic. Finally, new sales models should revisit and redefine assumptions of the standard paradigm of selling.