What AI is revealing about the sales process

Recently, my firm commissioned researchers to visit the websites of some 538 companies across nine industries, make a sales inquiry, and ask to be contacted. Surprisingly, fully one-third of the companies completely ignored these seemingly hottest of sales leads. Of the companies that did respond, more than two-thirds gave up following up after only one or two tries, despite proof that more contact attempts yield greater success. On the positive side, 42 percent of responding companies did so within 5 minutes, representing a 36 percent improvement over the previous year. However, despite the relative ease and importance of personalization in contact, over one-third of companies scored poorly in personalizing their replies.

This research points to some interesting things that AI can teach us about sales. Specifically, it shows where sales organizations fall short and points to how solutions leveraging artificial intelligence can fill in the gaps.

Failing to respond to customer inquiries costs companies serious revenue. According to Gartner, businesses spend an average of 10 percent of revenues on marketing. And since marketing’s primary goal is lead generation, ignoring over a third of all leads is a dangerous waste of resources and opportunity. In most organizations, the root cause is a disconnect between the marketing and sales departments. This leads to finger-pointing, with marketing claiming that sales doesn’t follow up, and sales complaining about low-quality leads. This is because, despite today’s technology, lead follow-up is generally manual, laborious, and error-prone. But, unlike humans, AI can accurately and at scale parse what, when, and how customers should be contacted, ultimately putting more leads in the funnel and driving greater sales productivity.

Companies also frequently give up on leads too early. Customer touches are a chance to engage leads and set appointments, but each human touch costs time and money, so typically salespeople follow up only about two times before abandoning a lead. Salespeople behave this way not because they’re lazy, but because they’re savvy and self-interested. They are “spending someone else’s money” for leads, so the incentive is to try once or twice, then move on. This maximizes return on salesperson time and commission, which is good for the salesperson but not for the company. But AI changes the cost/benefit equation when it comes to lead follow-up, reducing the cost per lead and enabling sales to implement best practices, usually 7 to 10 touches. With AI, salespeople are able to pursue hot leads as they would anyway, while fixing the follow-up problem in a scalable and sustainable way.

AI helps drive personalization of responses, which also leads to better sales results. Data shows that personalized messages increase email open and clickthrough rates more than 100 percent and that a greater number of “personalization elements” per email increases sales odds. Using an autoresponder for a first touch, while prompt and easy to deploy, is highly impersonal and therefore tends to cause customers to tune out. Autoresponders also fail to impress today’s sophisticated customers due to a lack of relevant personalization information, such as a reference to the customer’s specific interest. And while it may be infeasible for most sales teams to respond to every lead with a personal message, even automatically generated responses can go a long way if they are thoughtful and individualized using AI tools. More sophisticated systems that leverage AI can go even further by interpreting and specifically responding to the details of a given inquiry, mimicking a human response.

There are many tools available to help sales teams be more effective. But AI doesn’t compete with other sales tools — it competes with the status quo, because lead generation, lead engagement, and sales have been done the same way for decades. Sometimes organizations don’t understand that better ways of doing things exist, and some fear that AI can create job displacement. Yet ironically, early adopters of AI in sales have found the contrary, often having to actually increase the number of sales-related hires in order to handle the increased flow of qualified leads.

Soon, using AI to manage inbound leads will be commonplace and have much broader business implications. The Harvard Business Review quotes Gartner’s prediction that, by 2020, customers will manage 85 percent of their relationship with an enterprise without interacting with a human at all. The most important advice for any organization not already planning to deploy AI is to do something. Sales is usually the best place to start, given the 5.6M non-retail salespeople in the U.S. and the poor lead follow-up in many organizations today. The result will be greater sales and marketing effectiveness and efficiency and, ultimately, greater sales.