Pairing Human and Artificial Intelligence for Lead Qualification

Every sales representative wishes for a bluebird—that fabulous sales opportunity that out of the blue drops into their lap. But the reality is that most leads require a lot of time and effort before the sale is closed.

The best place to start is with lead qualification. However, the problem is that lead qualification may be the most hotly disputed aspect of any sales and marketing process. So hostile is this disagreement over what constitutes a good lead that typically sales reps reject well over half of the marketing-qualified leads (MQLs). What’s more, almost 80% of marketing leads never convert to sales. 

With the introduction of artificial intelligence (AI), the lead qualification war may finally be coming to an end. A Harvard Business Review study finds that AI-powered systems may double lead generation while cutting qualification call time by as much as 70% and reducing costs by more than half.

But before you envision a machine-only, lead-qualification process devoid of human intervention, let me suggest that it takes the pairing of human intelligence (HI) and AI to turn raw leads into high-quality sales opportunities.

As the opening line in the old television show The Six Million Dollar Man goes, “We have the technology to rebuild this man…we can make him [or her] better.” Here’s how.

The Problem with Lead Qualification

Lead qualification is messy, complicated and expensive. It includes dead ends and follow-up calls to determine if a raw lead is worth pursuing. It’s also slow, which is why traditional lead qualification is hard on your ROI.

Lead generation may thrive on quantity, but good lead qualification is all about quality. And the process requires sifting through every raw lead that signed up online for information, attended a webinar, or dropped a card in a fishbowl at a tradeshow to find prospects and, ultimately, opportunities.

The process of separating the wheat from the chaff has only become more challenging with online marketing. Inbound leads are seldom clean and complete. Intentions can be unclear. And it’s hard to know exactly where a lead falls in the buying cycle. Furthermore, connecting one lead (signup) with another by the same person or company in a complex, multi-touch marketing environment can require a lot of cross-checking.

Of course, this is where technology shines. And AI-enhanced lead qualification is the difference between wasting sales time on tire kickers and identifying prospects with the need, budget and intent to buy.

Many marketing and sales programs can clean up dirty data, provide missing contact information and cross-reference leads across multiple campaigns. However, it takes smart, well-crafted algorithms for AI-powered systems to provide context and intent and determine whether or not a lead is a prospect worth pursuing.

In short, AI algorithms can analyze a lead from three perspectives:

  • The prospective buyer

It does so by analyzing the frequency of contact, likely position in the buying cycle, budget and even the words used in an inquiry.

  • The vendor

AI uses demographics and firmographics to determine whether a lead is a good fit with the products and services sold and how it matches the ideal customer profile.

  • Marketing campaigns

AI analyzes key performance metrics of marketing campaigns.

From Tinker to Evers to Chance

In the early years of the 20th century, the Chicago Cubs baseball team boasted an infield notorious for robbing many a slugger from scoring a run. From shortstop Joe Tinker to second baseman Johnny Evers to first baseman Frank Chance, it was the perfect double play. It’s also the perfect metaphor for how AI and HI can work together.

Leads go through a three-part qualification process. The marketing department designs its lead generation campaign with a particular outcome in mind: large numbers of raw leads that meet specific demographic and firmographic criteria (e.g., industry, company size, location and budget). The leads come in and are passed to sales as MQLs.

But instead of leaving it to a sales development rep (SDR) to find the proverbial needle in a haystack full of leads, AI takes over. It provides the quantitative analysis that finds the leads that qualify as good prospects based on virtually any criteria you want to program into the algorithms.

Human Intelligence Delivers the Qualitative Analysis

Once AI systems have poked, prodded, cleaned and prioritized leads into a list of viable prospects, your SDRs can provide the human insight and intellect to identify a prospect as a highly qualified opportunity.
Only another person can hear the tone in a prospective buyer’s voice and use it to determine readiness and the next steps. Similarly, it takes a person to overcome a sales objection with a quick story or case study.

When the follow-up call feels right, and the SDR confirms the buyer is open to taking the next steps, they can begin to nurture a new relationship into a hot opportunity and, ultimately, pass it along to a field rep.

By pairing AI with HI, you can refine your lead qualification process while freeing up your SDRs to do what they do best…start the sales process.

AI shouldn’t intimidate or even threaten your people with obsolescence. That’s because it complements HI and makes everyone on your sales staff more productive. With your sales team free to focus only on the best prospects and opportunities, it’s easier to scale output and increase ROI.

Call us at +1 813-320-0500 (US) or +39 06 978446 60 (EMEA), or contact us online for help meeting your sales goals.

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