In a nutshell: Machine learning and artificial intelligence in sales research and practice

Scientific articles contain valuable management implications, but are usually not very easy to digest. We summarize the core results so that you can use the latest research findings for your company. 

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In this article, we focus on machine learning (ML) and artificial intelligence (AI) and their impact on personal selling and sales management. We examine that impact on a small area of sales practice and research based on the seven steps of the selling process. […]
The term [machine learning is generally being used] for the science of getting computers to act without being explicitly programmed. [While] AI refers to the ability of machines to mimic intelligent human behavior, and specifically refers to “cognitive” functions that we associate with the human mind, including problem solving and learning. […]
We hypothesize that selling in future decades will be disruptive and discontinuous, owing primarily to shifts in technology. In other words digitalization of sales functions with the addition of artificial intelligence and machine learning represent a discontinuous change compared to the non-digital era. […] The major difference from mere technological advances is the very close interaction between physical, digital and biological worlds. […]
So far, the greatest impact of automation and technology in sales has been, and continues to be, on all routine, standard and repeatable activities. In these cases, technology acts as a supporting role to make the selling functions more efficient. Going forward, perhaps the greatest impact of digitalization in sales will be in all the activities and efforts that go into understanding customer behavior in order to design and deliver highly customized offerings. Thus, in the future, technology will act as an active decision-facilitator, maybe even a decision maker in some cases, that can act in close collaboration with the salesperson to enhance the latter’s effectiveness. […]
This understanding is critical to the success of sales strategies. […] We suggest that the impact of machine learning and AI on the personal selling and sales management function will be profound.

Key statements

Technologies such as machine learning and artificial intelligence are becoming increasingly important in sales. This article analyzes how these technologies could be utilized in different phases of the sales process in the future:

  • Prospecting: When marketing and sales interact during acquisition, the challenge lies in the identification of promising prospects. With the help of big data, ML and AI can facilitate customer segmentation, allow companies to project overall potential and sales figures, and make it easier to qualify leads, particularly when it comes to digital communication channels.
  • Preapproach and approach: ML and AI can be used to optimize interaction with customers during the presales phase. For example, chatbots can hold simple conversations with customers and transfer them to a member of the sales team as soon as the issue becomes too complex and requires human intervention.
  • Presentation: ML and AI are also driving the development of remote presentations using augmented and virtual reality. Remote presentations are a cheaper option than giving a presentation on site and are more effective than other alternatives such as video conferences. Potential future developments for this technology, such as being able to capture customer reactions in real time, could make remote presentations even more dynamic.
  • Negotiating and closing: When it comes to making a decision on a purchase, customers remain highly skeptical of AI. One way to overcome this in the future could be to combine different technologies to identify potential difficulties early on in the negotiation process.
  • Follow-up: AI-based systems for handling orders are now able to process more complex data and can even provide recommendations for cross-selling. There is further potential in using information that emerges along the supply chain for general process optimizations.

Source:

Syam, N. and Sharma, A. (2018). Waiting for a sales renaissance in the fourth industrial revolution: machine learning and artificial intelligence in sales research and practice. Industrial Marketing Management, 69, 135-146. ScienceDirect