What makes a sales month turn out good or bad? Is your team on track to meet company goals? What behaviors are important to growing your sales team? As experienced sales leaders, Jake Young (VP of Sales at Grow.com) and Kyle Bastien (Director of Sales Training at ProsperWorks) know what it’s like—including what it’s like to not have the answers.
Thankfully, they’ve learned how to ask the right questions, where to find the answers, and how to back it all up with data. In the webinar, they discuss the real sales metrics and equations they use to answer critical sales questions and lead their teams to success.
Below is a quick recap of the six sales metrics you should be tracking (but probably aren’t) discussed by Jake and Kyle. Be sure to watch the webinar for more tips, examples, and insight from these two data-driven sales leaders. And when you'e ready to get serious about your sales KPIs, build a sales dashboard with Grow.
Q: What is the current state of your baseline KPIs?
If you’re on a road trip, you’ll have a hard time reaching your destination if you can’t first figure out where you’re starting from. The same is true with your sales metrics: If you want to know how you’re doing, track your performance, and hit your goals, you have to know your baseline KPIs. Knowing your conversion rates at each stage of the sales funnel shows you where you are, including “leaks” in your funnel that you need to optimize.
A: Revenue Equation
Revenue = Leads → Ops → Wins → Average Deal Size
Q: What rate are my qualified leads growing?
Your MRR, revenue, sales are standard measures of performance, but lead velocity rate (LVR) gives you a look into how you’ll be doing in the future by showing the rate your leads are growing month over month. Lead velocity is one of the strongest levers you can pull to help your team hit your goals.
A: Lead Velocity Rate
LVR = (This Month MQL – Last Month MQL) / Last Month MQL * 100
Q: When should the pipeline materialize?
Revenue forecast is often self-reported by the AE—which means it’s highly influenced by sentiment. To make forecasting more science than art, you should rely on data that can give you a clearer view of how much revenue is likely to come in and when.
A: Revenue Forecast
Revenue Forecast = Weekly Ops Created * Win Rate * Avg. Deal Size * Sales Cycle Distribution
Q: Is a rep on pace for their ramping period?
As Jake has interviewed other sales leaders, most have told him, “I wish I would have focused more on training enablement sooner.” That’s because those sales leaders know that getting new reps to full productivity on schedule helps keep the company on track towards reaching goals. By factoring in a rep’s experience level, you can also more reliably predict the ramp period of a seasoned rep vs. an up-and-comer.
A: Ramp to Full Time Productivity
Ramp-Up = Amount of Time Spent in Training + Average Sales Cycle Length + X
(where X = Sales Rep Experience)
Q: What channels are “closed won” deals coming from?
For Jake, revenue per lead by channel has been one of the most transformational metrics he’s used as a sales leader. It tells him how he’s doing, how the marketing team is doing, how effective trainings are, where to allocate resources, and more. With the added component of retention, you can more effectively ensure that every dollar you invest in new leads will get paid back to you several times over and that your business will grow.
*Correction: The live webinar gave a benchmark of $2-10 of revenue per lead. This should be corrected to 2-10x return per lead.
A: Revenue Per Lead by Channel
Revenue Per Lead = (Revenue from Channel / Leads from That Channel) * Retention %
Q: What actions are truly predictive of purchase?
Though this isn’t exactly a metric or formula, correlation analysis can play a key role in helping you predict retention and purchase. By tracking user behaviors and seeing how strongly they correlate will purchase, you can adjust your strategy to promote those behaviors and increase the “stickiness” of your product.
A: Golden Motions Analysis
Frequency of ‘Motion’ vs. Frequency of Outcome
