How Sales AI Improves Pipeline Management
The pipeline is the lifeblood of sales teams. And how you manage the pipeline of opportunities is a critical factor in rep and team success. Focus on the right deals and probability of success is greatly improved. Focus on the wrong deals and success is unlikely.
Pipeline management is both art and science—as with many things in sales. It’s difficult for less experienced sellers and even some experienced players. Without a doubt, one of, if not the biggest, determinant of sales success is where reps spend their time. And spending time and effort on the right opportunities is a big chunk of that equation. So, let’s break this challenge down.
For this article we’re going to focus on the science of pipeline management. Specifically, how Sales AI can uncover patterns and assist sellers in doing a better job moving opportunities through the pipeline.
Pipeline Management or Opportunity Management
Jason Jordan, in his book Cracking the Sales Management Code argues that there’s really no such thing as “pipeline management.” He claims that you really don’t manage your pipeline, you manage the opportunities in your pipeline. Okay, fair enough Jason. By the way, if you haven’t read Jason’s Cracking the Code, read it. It’s one of the best books on sales management out there.
So, opportunity management. Let’s break this down. To manage our pipeline effectively we have to understand the opportunities in our pipeline.
There are 3 key aspects when we look at an opportunity.
- The company or division of the parent company. This is really the account for most teams. Is it a good fit? An industry you have experience with and can support? Does it match up with your ideal customer profile [ICP]? Or at least come close.
- What does the opportunity—the deal itself—look like? Is it big enough, or at least have room for expansion? Who’s involved in the buying team? Is there some mass [the right personas and number of buyers] behind the initiative? Or is it two interns kicking the tires? What’s the true pain behind the initiative, driving the buying team to look for a solution?
- Finally, what’s the urgency level? Does the buying team seem motivated to move? Is there a timeline? Are they willing to communicate and provide the information you need to help? Are they willing to attend meetings to move the initiative forward? Or will this take a ton of education and convincing before they become motivated?
These 3 dimensions allow us to qualify and rank the opportunities in our pipeline. Now we can prioritize our efforts and invest in the right deals. And this is not a one-time qualification event. It’s constant and must be systematically reevaluated on a regular basis. This takes a lot of work and is where Sales AI can help immensely.
How Sales AI Helps Evaluate and Rank Opportunities
Sellers have a hard time with continuous, systematic opportunity qualification. But machines don’t. Sellers have lots of other things to do, like talk to buyers, uncover needs, and build relationships. Continuous, systematic evaluation of opportunity data is where machines and sales AI really excel.
Sales AI cranks through opportunity data at crazy-fast speeds, scoring various aspects of the deal and activity data. It tirelessly evaluates every opportunity looking for patterns, risks, and positive buying signs. As it evaluates and scores the pipeline of deals, it sends alerts and notifications to reps and managers when situations need action. It ranks and prioritizes opportunities, so reps know which are most valuable and where to focus effort.
Where should I focus: on early, mid, or late stage opportunities?
The answer is yes. To maintain a healthy pipeline, you have to put forth effort across the pipeline. Okay, before you label me as Captain Obvious, let’s dig a little deeper. Let’s get scientific here.
As a healthy deal progresses from early to mid to late stages in the buying cycle, the frequency of communication—the energy between buying and selling team—increases.
So, this means we’ve got to spend a disproportionate amount of time on the late stage opportunities in order to close them. Buyers expect it. And there’s no getting around it. As buying teams gain greater confidence and clarity in their buying decision, they spend more time with their vendors of choice, ultimately spending the most time with their finalist. It’s only natural as they need to confirm and validate their selection.
So, for a seller, what’s the optimal mix of effort to put forth on early, mid, and late stage deals? Each selling team is different of course, but a good rule of thumb is a 50-30-20 percent mix. Or in other words, 50% of time on late stage deals, 30% on mid stage, and 20% on early stage opportunities.
Here’s a quick breakdown.
Early Stage [20% effort]: more opportunities to assess, but many few buyers to communicate with.
Mid Stage [30% effort]: fewer opportunities to assess and service, but more buyers to communicate with as you expand your reach on buying team.
Late Stage [50% effort]: many fewer opportunities to work, but lots more demand from the buying team as buyers come out of the woodwork to see, feel and touch—and get their say before the purchase decision is made.
How Sales AI Helps Optimize Effort Across the Pipeline
Sales AI analyzes your pipeline and helps you determine how to spread your effort across the various opportunities in your pipeline. Because it constantly evaluates each opportunity and the buying team responses and behaviors, it can help identify the deals most likely to move forward. Thus, help you pick the opportunities that need your focus.
Sales AI can see the buyer behavior patterns we as humans often miss. It can help you decide the best opportunities in each stage so you can spend the bulk of your time investment with right deals that show propensity to move forward.
In addition, it can identify gaps or weaknesses in your pipeline. For example, if you have plenty of healthy opportunities in late stages, it can suggest more effort at the top of the funnel to prevent a dry spell two quarters from now.
Pipeline management, or managing the opportunities across the pipeline is not easy for anybody—even experienced reps. It takes analysis and planning. Sales AI can help immensely because it’s good at this type of systematic pattern analysis. In the end though, Sales AI is here to assist, not decide. Sellers are in charge. But Sales AI can definitely help turn good sellers into better sellers.
Hope you have your best year ever.
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