A “CHANGE AGENT” has historically been defined as a person from inside or outside of an organization who assists in optimizing or transforming how functional areas within the organization operate. Their primary role is not to manage the change, but rather to support, inform, and inspire the key stakeholders within the organization who will champion that transformation.
In sales, this role is especially needed because we live in a very dynamic world that is constantly changing, and the need to be agile is a business imperative. To demonstrate just how much change is bombarding sales organizations, Sales Mastery conducted a change assessment study, surveying more than 225 business-to-business (B2B) companies. The chart below summarizes the input we received.
Here we see that change takes many forms, and it comes in two flavors: change that impedes sales performance, or change that enhances it. The thing to note here is the cumulative impact of change on sales. Whether positive or negative, change requires that companies adapt to achieve gain or remove pain. But how does a person effectively monitor all these aspects of change at the same time to continuously facilitate transformation? The answer: They can’t. So perhaps we need to widen our definition of what constitutes a change agent to include CRM, specifically in the form of artificial intelligence/machine learning (AI/ML).
Over the past few years, through our sales enablement initiative’s benchmarking efforts, we have increasingly been finding examples of sales organizations using AI/ML to continuously assess various aspects of change in sales. For example, InsideView’s AI-based Apex decision engine allows you to constantly monitor changes in the customer’s marketplace and determine the industries and geographies on which to focus selling efforts that will yield the highest success rates.
Salesforce’s Einstein can analyze millions of customer records to determine new customer needs. Einstein’s algorithms perpetually adjust what to look for based on the feedback they receive on the outcome of previous recommendations; as changes in customer expectations are surfaced, the system makes new recommendations to uncover new sales opportunities.
Bridgei2i leverages AI to continuously perform win-loss analyses. One of the results of this process is that it can generate competitive heat maps for all your company’s competitors. It can quickly provide feedback on which competitors you are doing better or worse against, and why. And it also provides insights into how to exploit an advantage or minimize a threat.
Aviso constantly scans internal and external data sources for factors that could impact the sales forecast. As it detects changes in deal status, it alerts sales management to opportunities that are at risk, along with suggestions on how to get the deal back on track or replace it with another deal in the pipeline that is progressing faster than previously assumed.
The key in each of these examples is that AI can process huge amounts of data, look at things from more unique perspectives, and do all this at speeds that are impossible for humans to match. Pair that with the judgment a human change agent can bring to the equation and you have a formula for more successfully helping an organization sell at the speed of change.
