Blog Home

Can AI Help You Overcome “No Decision”?

Posted in:  Sales and Marketing Management

Artificial intelligence (AI) may be coming for your job. But debating AI’s impending (or not) domination is blasé and ultimately unimportant for business leaders responsible for driving revenue and growth. Instead, we need to focus our attention on AI’s potential to transform how we sell.

AI is already making waves in sales, from intelligent content recommendations for reps to sales pipeline insights. But an area of significant, untapped opportunity lies in unlocking one of the biggest problems facing salespeople and marketers — “No Decision.”

Forget the shock and awe headlines. The frontlines of shifting buyers from complacency to action is where AI’s potential gets interesting.

“No Decision” Kills Deals. Urgency Revives Them.

“No Decision” is sales purgatory — and the safe haven of customers crippled by an abundance of options and ever-shifting priorities. In the face of uncertainty, it’s often easier for buyers to do nothing.

This type of thinking brings 22% of all deals to a halt. Apply that number to the value of your own forecasted opportunities and “No Decision” could represent millions in lost revenue.

Marketing and sales leaders can confront this phenomena by executing programs that drive urgency, a powerful force that turns leads into customers. One way to frame this is to consider three distinct phases:

  • Prospect evaluation – driving urgency with initial champion
  • Company evaluation – driving sense of urgency across multiple stakeholders
  • Company purchase – helping to establish a critical business imperative

These phases reflect the evolution of a deal: what begins with a single person’s problem often ends with numerous, cross-functional stakeholders confronting a company-wide challenge. As the deal evolves, so should your approach to driving urgency.

Take, for example, the purchase of marketing automation software. A vendor may connect with a director of marketing operations, but the decision to invest will require input from sales leadership, website developers, growth operations, and more. Thus, an effective rep will seamlessly evolve their approach to urgency from specific pain points to a broader business case that encompasses new stakeholders. Ultimately, they must present a compelling solution that convinces all stakeholders the investment will solve an urgent, company-wide problem — without losing sight of the individual’s pain.

Done correctly, urgency creates a bias for action where inertia may otherwise reign. The only complication? Manufactured urgency, like lab-grown diamonds, is inferior to the real thing.

Genuine Urgency Can Be Curated by Hand, But It’s Not Easy

We’ve all had a salesperson try to convince us that we need something we don’t. Usually those conversations don’t end with a purchase. Fake urgency is fragile; simple objections can block a deal because the buyers know they don’t need whatever you’re selling. And they’re right.

Instead, reps must organically develop urgency by attaching product benefits to existing initiatives within the account — for example, a buyer may wish to invest in a CRM rather than marketing automation software; a good salesperson can build urgency by showing the buyer benefits of purchasing both at once.

Unfortunately, the details that authentically build urgency are often buried in Salesforce notes or Gong recordings. Even at startup scale, it would take hours of work to sift through notes, analyze loss calls, and interview account executives to uncover them. Once you’ve done this, it’s possible to create sales plays aligned to the patterns you’ve identified — and then repeat the analysis process months later to see if it worked.

But a manual process like this is essentially a guess-and-check approach, not the kind of adaptive, proactive method that will scale with your business. A deep learning system, however, could analyze qualitative data en masse. Enter: AI.

Use AI to Crack the Code on “No Decision”

AI’s transformation of data into actionable insight currently outperforms traditional analysis methods, revealing customer needs, wants, and habits in ways never before possible.

Just like our example of a manual exploration, AI can analyze urgency-blockers by combing through qualitative data to identify otherwise invisible patterns. The major difference? Where we humans are limited by time, AI can crawl thousands of data points in minutes, pulling insights that can inform your strategy and uncover areas for improvement across your go-to-market operation.

AI excels at finding opportunities to act. In our manual scenario, you must make educated guesses about which prescribed actions will help sales people overcome “No Decision.” With AI, you can feed a machine learning system a data set of no-decision accounts turned customers. The system would then tell you which urgency-driving actions were effective and allow you to correlate these winning approaches by industry, persona, and other important factors.

Transform Inertia into Initiative

Once you set aside the sensationalism surrounding AI, you can start to apply the technology to real business challenges. AI can arm sales teams with content, guidance, and insight into buyer behavior to overcome “No Decision” by creating an overwhelming sense of urgency. The key is to focus on tangible impact, not grandiose predictions. To learn more about actionable steps you can take to set your sales team up for success, read our guide to buyer engagement.