March 4, 2020

The Most Important Lead Metric You’re Not Tracking is PCPL: Pipeline Created Per Lead

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As long as there have been sales teams, there have been complaints about the quality of leads. Sales teams can get bogged down in the day to day minutiae of calling, follow-up, emails, and LinkedIn messages, which can warp their sense of the potential of any program.

We have to stop relying on the gut-feel metrics of CPLTMSTAL (cost per lead that my sales team actually likes) and start using the data available to us to understand exactly how each lead touch can pay off over the course of a sales cycle.

You could track common metrics like cost per lead (CPL) or cost per KPI, but these metrics only take you so far. With a little more (relatively simple) math, you can figure out how much pipeline you generate per lead—which can help you better understand the total long-term value of your purchased lead programs.

This article will take you through the steps of calculating the pipeline created per lead (PCPL), a key metric in understanding the true value of your lead programs.

Definitions:

  • CPKPI: Cost Per KPI
  • APV: Average Pipeline Value
  • TPP: Total Possible Pipeline
  • PCPL: Pipeline Created per Lead

Calculating PCPL

PCPL is your advanced metric. It tells you how good your program is at creating pipeline. It tells you the amount of potential revenue you create for every lead contact you make or nurture action you take.

Let’s get started with two example content syndication programs.

two example lead programs

Based on the information in this image, you’d probably say that program B looks better. It has the most conversions and the best conversion rate. That checks out when you calculate the CPKPI.

So let’s take another look at the two programs and compare their CPKPI. Program B still looks pretty good here, with a lower CPKPI.

cost per kpi. the CPKPI of two lead programs.

But if we stopped here, we may not fully understand the long-term impact of going all in on this particular program. In order to see the full financial impact of choosing either of these programs, we want to calculate a couple more metrics: APV, TPP, and PCPL.

To begin, you’ll need one outside metric: your total pipeline generated. Pull metrics for the total pipeline generated per program over the course of at least six months to give you a baseline that takes into account your sales cycle.

Now, let’s calculate average pipeline value (APV). For each of your programs, divide the total pipeline created by the number of conversions. Then compare your two programs again.

average pipeline value. calculated average pipeline value for two lead programs.

By adding these metrics, we can see that while the difference in pipeline created doesn’t feel that big, the APV shows a significant difference in the value of each conversion.

Now let’s add another value to understand scale: total possible pipeline (TPP). You’ll need to ask your provider to give you the maximum volume of leads they can provide in any given month to see your limits.

total possible pipeline. calculated total possible pipeline for two lead programs.

So, while program B looked good at a volume of 400 leads a month, that program starts to falter as we attempt to scale. The differences in TPP for programs A and B are starting to show. But we’re not done yet!

We still need to understand how efficient each of these programs is for your team. To do that, we have to figure out pipeline created per lead (PCPL).

pipeline created per lead. calculated pipeline created per lead of two programs.

The PCPL for these two programs is about the same. But the total pipeline that they’re working towards depends on all the other factors.

Would you rather your team spend time calling out on 500 leads at a $2,000 PCPL with a potential pipeline of $1 million, or 400 leads at the same PCPL that only gets you $800,000 in the end?

PCPL tells your sales team how much each call is worth and, ultimately, which programs they should focus their time on based on data, not on gut feeling.

While your sales team may “know” that they have better success when they call out on individuals that are higher in the org chart, that may be confirmation bias, because it feels like they’re having more success. The leads they call out on from program A may “feel” less successful, but they result in more total pipeline and more revenue.

When you can trace the pipeline, the ultimate value of the work, and the total revenue that the program brings in, you don’t have to work off gut feel.

This blog post has been adapted from a talk that I gave at the Music City Lead Generation Summit in October of 2019.