Congratulations—you’re officially a sales leader! You crushed your number as a seller, your manager saw potential, and now you’ve got your own team to develop.
Then you log into the CRM for the first time as a manager and… oh no. There are 17 sales performance reports you didn’t know existed. Your boss is asking about “pipeline velocity” and “stage conversion rates.” Your sellers are missing quota and you’re not sure if it’s a skills problem, an effort problem, or a territory problem.
Here’s the thing nobody tells you: Having more data doesn’t automatically make you a better leader. In fact, it can make you a worse one if you’re paralyzed by all the numbers.
The best sales leaders don’t track every sales metric. They track the RIGHT things, and they know exactly what to do with what they find.
If you’re a new sales leader trying to figure out which data actually matters and how to use it to help your team perform, then this post is for you.
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Top 3 Sales Performance Metrics
New sales leaders should begin with three core sales performance data types that work together. These three tell you who needs help and what they’re struggling with.
Pipeline Coverage Ratio
Are salespeople building enough pipeline to hit quota? Look for 3-4x coverage as a baseline. This tells you if they have enough opportunities to hit their number.
Conversion Rates by Stage
Where are deals getting stuck? Different sellers will have different bottlenecks. One might be great at getting meetings but terrible at closing. Another might convert demos beautifully but struggle to get past initial outreach.
Sales Activity Metrics
These are the day-to-day: calls made, emails sent, meetings held. This connects effort to outcomes. Low activity with low results is different from high activity with low results—they require completely different sales coaching.
The Weekly Sales Performance Cadence
New leaders should establish a simple weekly routine to assess and convey insights from the data.
Monday: Review pipeline management and stage conversion for each seller. Flag anyone who’s trending off track.
Mid-week: Listen to calls from sellers whose conversion rates are lagging. Come to your one-on-one with specific observations.
Friday: Hold one-on-ones using specific data points. Instead of “How’s it going?” try, “I noticed your demo-to-proposal conversion dropped from 60% to 40% this month. Let’s listen to your last two demos together and figure out what’s changed.”
Sales Performance Quality Signals
Once you know who’s struggling and where, you can look at quality data to understand the root cause—why sellers are falling short.
Call Recordings
Listen to 2-3 calls per seller per month at their problem stage. Are they asking discovery questions? Handling objections? Building urgency? This is where you move from “Jennifer’s demo-to-proposal conversion is 20%” to “Jennifer isn’t uncovering budget authority in discovery.”
Win/Loss Patterns
What separates wins from losses for each seller? Price sensitivity? Competitor losses? Timing issues? Look for patterns. If a seller loses every deal to the same competitor, then that’s a specific competitive positioning problem you can coach to.
Sales Metrics: Red Flags to Watch For
Certain data patterns should trigger immediate action:
- Pipeline coverage drops below 2x (they won’t hit quota without a miracle)
- Sudden change in activity levels, up or down (something’s wrong—burnout, disengagement, or they’re chasing one huge deal)
- High early-stage conversion but low late-stage (discovery problem—they’re not qualifying hard enough)
- Low early-stage conversion but high late-stage (prospecting problem—they’re great at selling but need help filling the top of funnel)
Hypothetical Case Study: TechForge Manufacturing
Here’s how this works in practice.
Sarah was promoted to sales manager at TechForge, a mid-sized industrial equipment manufacturer. She inherited a team of five sellers selling custom automation solutions with six- to nine-month sales cycles.
In her first month, she noticed something odd in the pipeline reports: Her top performer, Mike, had the highest win rate (45%) but was trending to miss quota by 20%. Meanwhile, a middling performer, Jennifer, was on track to hit quota despite a lower win rate (28%).
What the data revealed:
Looking at her diagnostic trio, Sarah found:
- Mike’s pipeline coverage: 1.8x (far too low)
- Jennifer’s pipeline coverage: 4.2x (healthy)
- Mike’s activity metrics: 12 prospect calls/week
- Jennifer’s activity metrics: 35 prospect calls/week
Mike was great at closing but wasn’t prospecting enough. He spent too much time perfecting proposals for deals he’d already won over.
Digging deeper with call recordings:
Sarah listened to three of Mike’s discovery calls. They were masterful—he asked excellent technical questions, understood the manufacturing process deeply, and built strong urgency around downtime costs. No wonder his win rate was high.
Then she listened to Jennifer’s calls. They were competent but generic. She wasn’t uncovering pain points specific to each manufacturer’s production line.
The coaching intervention:
For Mike: “Your close rate is fantastic, but you need 3x pipeline coverage. Let’s block 10 hours/week for prospecting—non-negotiable. I’ll take one proposal review off your plate each week to free up time.”
For Jennifer: “You’re building great pipeline. Now let’s focus on quality. Listen to this call from Mike—hear how he asks about cycle time and scrap rates? Let’s practice that approach on your next three discovery calls.”
The result after 60 days:
Mike’s pipeline coverage increased to 2.9x while maintaining his 45% win rate. Jennifer’s win rate improved to 35% while keeping her strong activity levels. Both finished the quarter at 108% of quota.
The key insight:
Sarah didn’t just look at quota attainment or assume her top performer had it figured out. She used multiple data points together to diagnose specific, coachable problems—and tailored her interventions to each seller’s situation.
Other Sales Performance Data Sources to Consider
As you mature as a leader, you might layer in additional data sources.
Engagement Data
Email open rates, response times, meeting attendance, and proposal view analytics are leading indicators that can predict pipeline health before deals stall.
Win/Loss Analysis data
Structured debriefs on why deals were won or lost, including competitive intelligence. This goes deeper than just the outcome in your sales reports.
Market and Territory Data
Account demographics, industry trends, geographic factors, and total addressable market in each territory. This contextualizes individual performance against opportunity. Your “low performer” might actually be doing great given they have the toughest territory.
Customer Health Scores
Post-sale data such as renewal rates, expansion revenue, and satisfaction scores tied back to the original seller. This shows quality of deals closed, not just quantity.
Tracking the Right Sales Performance Metrics
You don’t need to track everything. You need to track the right things and know what to do with them.
Start with pipeline coverage, conversion rates, and activity. Layer in call quality and win/loss patterns. Use that data to have specific, helpful coaching conversations—not to beat people up, but to help them improve.
The data isn’t the point. Better performance is. And better performance comes from better coaching. The data just tells you where to focus.
Find out how The Brooks Group’s sales leadership training programs can help your team hit their number.
