The AI-Driven Sales Process, Part 1: A Lead Generation Revolution

“What did the AI tell us?” asked no salesperson ever.

Actually, that’s not true. Although it once might have seem far-fetched for someone in sales — a role that is often based on gut-feel and human intuition — to trust the input from an artificially intelligent database, help from such digital assistants is quickly becoming commonplace. Earlier this year, for instance, market research firm Forrester released a report which said sales departments, along with their counterparts in marketing, now lead 50% of all AI-related initiatives in business.

For that other 50 per cent, though, there’s clearly still a learning curve of sorts to overcome. Hopefully by now salespeople know AI won’t be able to replace them, but sussing out the real value amid all the hype and speculation about AI’s benefits is another matter.

To help clear up any misconceptions and get at some of the answers, we’ll be running a three-part series that looks more comprehensively at what AI can bring to what are arguably the biggest areas that face any sales team. This includes lead generation, closing a sale, and the overall management of sales, from time management to performance evaluation and more. Thanks to Einstein, Sales Cloud from Salesforce can be a huge game-changer in each of these areas.

Given how much time sales often spend prospecting — particularly on prospects that aren’t worth the effort — it makes sense to start with AI in lead generation first.

Nurture-Worthy Leads

If you think about it, a lot of the information sales gets about a lead may not amount to much. If they filled out a contact form before downloading a web site or other asset, for example, the sales team might get details such as name, title, company and an email address.

This leaves sales pros with two options: start researching — with sometimes-random queries on search engines and the like — or just ignore the leads in favour of trying to wring extra businesses out of their more established clients.

AI could do that research a lot faster and more efficiently by looking at the data that’s already in Sales Cloud, as well as third-party sources to “think” through factors like:

• How do firms in the same vertical market as this lead tend to behave when they have an actual intent to buy?

• How does a job title such as the one from this lead match the kind of person who is the key decision maker vs. an influencer in this kind of account?

• What are the most likely products and services that will get a lead through the door to an actual sale, based on their digital activity across the company’s site and even other sites?

Then, almost like a CEO who receives a regular list of the most profitable and valuable customers that he or she should know, the sales rep gets a run-down of the leads that are “nurture-worthy.”

Orchestrated Outreach

Sometimes people know that they’ve become a lead. After passing over their contact information they may be bracing themselves for that inevitable email message or call from a sales rep who “noticed” they’ve downloaded an asset or filled out a form. This is a delicate moment in prospecting, and it’s all too easy to ruin it.

Dedicated reps might have solved this in the past by writing as personal and specific an e-mail message as possible. Those efforts are laudable — they’re just not always practical when you’re trying to cover off a large territory and have multiple leads to follow up on at once.

Let AI take over some of this grunt work without reducing the result to a canned-sounding message that leads automatically read and think, “automated.” Just as reps think about the specifics of the person to whom they’re writing, AI can look for things like:

• Tone: Based on job titles, for instance, are there certain ways of communicating that make sense? Perhaps something more formal for a senior executive, for instance, versus a more casual written “voice” when you’re communicating with a more junior manager.

• Keywords: When we do an online search we all tend to put certain terms forward. The same logic applies to communicating with a lead. What kind of industry-standard terminology or even company-specific jargon might get them to take notice?

• Topics: If you’re selling to chief marketing officers, they may be looking for ways to get better results from digital campaigns. If you’re selling to someone in health care, the priority might be about improving the patient experience. The better you can position your outreach, the more likely you’ll get an actionable response.

Painless Prep

You may be so busy you think you deserve your own admin assistant, but the reality in your company may be that it’s just not possible to hire one for you. AI, however, means that such a hire may not be necessary or effective, given that the technology can access information from the lead that would be too time-consuming otherwise.

Let’s say a lead actually accepts an offer to connect for an in-person pitch. Put AI to work:

• scanning e-mails and integrating with calendaring systems to find mutually-agreeable dates without a lot of back and forth.

• gathering spec sheets, buyer’s guides and other mid-funnel content the lead may want to look at after the meeting. Having this early makes you look super-prepared.

• pulling together a customized version of a pitch deck based on the most appropriate products and services, bundles with customized pricing and/or eligible discounts.

When a lead turns hot, sales reps can’t wait to get out the door. AI not only gets them out the door faster but ensures they’re walking through the customer’s door armed with everything they need to be successful.

Of course, lead generation is just one aspect of sales. In our next post we’ll look at what AI means for that most critical of stages: getting to “yes” and actually closing a deal.

Are you prepared for an AI world? A cutting edge CRM solution can help. Learn more in our ebook, “AI for CRM: Everything You Need to Know.”