AI offers tremendous promise to help sellers become much more efficient. A lot of the tasks that take seller time can be more effectively handled with AI tools. Properly used, with the right prompt engineering, AI can help us better understand potential issues our customers face.
We can, for instance, ask it for issues facing certain roles. We can ask it to look at certain industries/markets, or types of companies. We can even provide financial reports and other data, that can be incorporated into the analysis and recommendations.
We can invest a lot of time in refining our prompts, feeding the LLMs reports to analyze to refine the insights provided (and these tools are supposed to save us time?). The LLMs will provide ideas, insights. They may get us closer to issues that might be a concern to our customers, but they only get us (and everyone else doing similar things) to a certain point.
There’s always a gap. In the old days of Telecom, it was called the “last mile” problem. The “last mile” represented issues unique to the customer. Where every vendor was relatively undifferentiated up to the last mile–they could provide a full range of telecom services, band width, and other capabilities, the real differentiation was with the ultimate connectivity to the customer–the ability of the provider to address the issues specific to the customer and their needs. It was this “last mile” that provided the greatest differentiation. Controlling this “last mile” also impacted any other choices the customer might make in their overall telecom implementations.
The “last mile” problem exists in all sorts of industries. For example, Amazon has little problem moving products from distribution center to distribution center. It has little problem in predicting what each distribution center stocks. It’s bigger challenge is getting specific orders from the distribution center to the right customer, and doing this as effectively and efficiently as possible.
Data scientists struggle with the “last mile” problem within their own organizations. They conduct very complex analysis, build models to help organizations better understand things. The problem is connecting the right data, the right models and presenting it in an impactful way to address executive concerns at this moment. Some of it is a problem with their ability to present the data in a meaningful way, much of it is a problem on the receiving end–the executive ability to understand and take action on the data and models.
The problem with “last mile” problems is that it is not solely in control of the provider, it requires cooperation, collaboration, and alignment with the receiver. And these are unique to each receiver.
The selling “last mile” is the most important and most difficult challenge to sellers. The issues we encounter are issues that AI cannot, at least for some time, address. These issues are specific to the customer situation. Specific to an individual at a moment in time. These issues change from individual to individual, even within the same organization. The individuals change their perspectives from moment to moment. Today, they have certain priorities and issues, tomorrow those may change.
Then there are those messy feelings and emotions. “How do they feel about what they are doing? How confident are they? What can we do to help build their confidence?”
AI can’t help us on Linda Jone’s concerns about the project right now. It can’t help build John Smith’s confidence that he and his team are doing the right thing. It can’t incite Jill Johnson to think differently about the strategies she is prioritizing for her organization and how the organization should address the risks to those strategies.
This gap, the “last mile,” is uniquely human. It can only be filled by sales people. It can only be solved by sellers working closely with the customers—the individuals, not abstractions of the roles.
The problem is, “Are we equipping our sellers to successfully manage the ‘last mile’ problem?”
Are we providing our sellers the customer and business acumen critical to addressing these issues. Are training them in leading collaborative conversations, helping the customers navigate their problem solving/change process? Are we training them in how to help build the confidence of the customers making the decision? Are we training them in helping groups of buyers align around goals and manage consensus through the process?
Selling success is about connecting impactfully with buyers–individuals–at a moment in time. For some time, AI will not be able to help us with these unique interactions at moments in time. It’s people that do this.
How are you equipping your sellers to address the “last mile” problem?
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