A sales KPI dashboard is supposed to answer one question. Are we going to hit the number? Most dashboards do not answer that question. They show 40 metrics, none of which roll up to a clear forecast or a clear action.
This post covers the 12 metrics that actually matter, organized into four buckets. For each metric you get the definition, the formula, a sensible target, and what good versus bad looks like. The free Excel dashboard at the end pulls them together.
What a sales KPI dashboard is for
A dashboard is not a scorecard. A scorecard tells you who is winning. A dashboard tells you what to do next.
A working sales dashboard does three things. It shows whether the number is in reach. It surfaces the leading indicators that will move that number. It points to the team or rep that needs attention this week.
If your dashboard cannot do those three things, it is decoration.
The 12 metrics below are organized into four buckets. Activity metrics are leading indicators. Pipeline metrics show coverage. Conversion metrics show efficiency. Retention metrics show whether the wins are staying.
Activity metrics (the leading indicators)
These metrics answer the question, are reps doing the work that will create future pipeline.
1. Outbound activity per rep
Definition. Number of meaningful outbound touches per rep per week. Calls, emails, LinkedIn messages, video messages.
Formula. Total outbound touches divided by number of reps divided by weeks in period.
Target. Depends on motion. SMB SDR teams might run 80 to 120 per day. Enterprise AE outbound might be 15 to 25 per day. Set the target based on what your top performers actually do.
Good vs bad. Good is consistent week over week, with rising reply rates. Bad is a spike in volume followed by a crash, or volume without any pipeline coming out of it.
2. Meetings booked
Definition. Number of qualified first meetings booked per rep per period.
Formula. Sum of first meetings booked across reps. Track by source: outbound, inbound, partner, marketing.
Target. Tied to your pipeline coverage requirement. Work backward from quota and conversion rates.
Good vs bad. Good is meetings that hold and convert to qualified opportunities. Bad is meetings that book but do not hold, or meetings that hold but never advance.
3. Meetings held
Definition. Of the meetings booked, how many actually happened with a qualified buyer.
Formula. Meetings held divided by meetings booked.
Target. 70 to 85 percent for outbound. 85 to 95 percent for inbound demo requests.
Good vs bad. A no show rate above 25 percent on outbound means qualification is weak. Above 15 percent on inbound means the booking flow has friction or the response time is slow.
Pipeline metrics (coverage and health)
These metrics answer the question, do we have enough pipeline to hit the number, and is it healthy.
4. Pipeline coverage
Definition. Total qualified pipeline divided by quota for the period.
Formula. Sum of open opportunity amount in stage 2 or later, divided by quota.
Target. 3x to 4x for most B2B motions. Higher for transactional motions. Lower for enterprise motions with very high win rates.
Good vs bad. Good is coverage hitting target by the start of the quarter, with stage distribution skewed toward later stages. Bad is 4x coverage where 80 percent of it is in early stages.
5. Pipeline created (new business pipeline)
Definition. Net new pipeline added in the period.
Formula. Sum of opportunity amount entering qualified pipeline in the period. Net of any pulled or downgraded amounts.
Target. Tied to your historical conversion. If you win 25 percent of qualified pipeline and need 10M next quarter, you need 40M in new pipeline this quarter.
Good vs bad. Good is steady week over week creation that matches the math. Bad is heavy reliance on one or two big deals that have not been pressure tested.
6. Average deal size
Definition. Average ACV or TCV of closed won deals.
Formula. Sum of closed won amount divided by count of closed won deals.
Target. Specific to your business. Track trend more than absolute value.
Good vs bad. Good is steady or rising deal size with stable win rates. Bad is rising deal size with collapsing win rates, which usually means reps are chasing whales they cannot close.
Conversion metrics (efficiency)
These metrics answer the question, how efficiently are we turning effort into revenue.
7. Win rate
Definition. Percentage of qualified opportunities that close as won.
Formula. Closed won count divided by total closed count in the period. Or closed won amount divided by closed amount.
Target. 20 to 35 percent for most B2B motions. Higher for warm inbound. Lower for cold outbound enterprise.
Good vs bad. Good is stable or rising win rate at stable deal sizes. Bad is rising win rate driven by a flood of small deals that mask a falling enterprise win rate.
8. Sales cycle length
Definition. Average days from opportunity creation to closed won.
Formula. Average of (close date minus created date) for closed won deals.
Target. Specific to motion. SMB might be 30 to 60 days. Mid market 60 to 120 days. Enterprise 6 to 18 months.
Good vs bad. Good is shrinking or flat cycle length with rising deal sizes. Bad is cycles getting longer without deal sizes growing, which usually means more stakeholders and more friction without more value.
9. Sales velocity
Definition. A composite metric that measures how fast revenue moves through the pipeline.
Formula. Number of opportunities times average deal size times win rate, divided by sales cycle length in days.
Target. Trend matters more than the absolute number.
Good vs bad. Good is rising velocity quarter over quarter. Bad is rising velocity driven entirely by one variable while another is collapsing. For example, win rate up but deal size down by the same factor.
10. Stage conversion rates
Definition. Percentage of opportunities that advance from each stage to the next.
Formula. Count of opportunities that exited a stage to the next stage, divided by total entering that stage in the period.
Target. Map your historical baseline. Then watch for drift.
Good vs bad. Good is stable conversion across the funnel. Bad is one stage collapsing while others hold steady. That is usually where the coaching opportunity lives.
Retention metrics (the wins that stay)
These metrics answer the question, are the deals we close actually creating durable revenue.
11. Net revenue retention
Definition. Recurring revenue from your existing customer base over time, including expansion, contraction, and churn.
Formula. (Starting ARR plus expansion minus contraction minus churn) divided by starting ARR. Measured over 12 months.
Target. 100 percent is flat. 110 percent is healthy. 120 percent plus is best in class for SaaS.
Good vs bad. Good is NRR above 110 percent driven by expansion, with churn below 5 percent annual. Bad is NRR at 105 percent propped up by a few expansion deals masking underlying churn.
12. Logo retention
Definition. Percentage of customer logos retained over a 12 month period.
Formula. Logos at end of period divided by logos at start of period, excluding new logos added.
Target. 90 percent plus for mid market and enterprise SaaS.
Good vs bad. Good is high logo retention paired with high NRR. Bad is high NRR but falling logo retention, which means a few big customers are propping up the number while many small customers are leaving.
Building the dashboard in Salesforce
Most of these metrics are in your CRM already. The build is mostly about choosing the right reports and putting them on a single dashboard.
Activity metrics. Use Activity reports filtered to last 30 days, grouped by user. Add to dashboard as bar charts.
Pipeline metrics. Use Opportunity reports with date filters. Coverage is a calculation comparing pipeline amount to quota. Some teams use Salesforce Forecasts; others build the calculation in a custom report.
Conversion metrics. Win rate is a standard report. Stage conversion needs a historical opportunity report or an analytics tool. Sales cycle length is a formula on the opportunity record.
Retention metrics. NRR and logo retention require account level snapshots over time. Either build with Snapshot Reports or pipe to a BI tool.
A working dashboard fits on one screen. If you need to scroll, you have too much on it.
Building the dashboard in Excel
The free template at the end of this post is built for teams that do not have a CRM yet, or for sales leaders who want a clean view independent of the CRM.
It has four tabs aligned to the four buckets. Each tab has a target column, an actual column, and a delta column. The summary tab rolls everything up into a one screen view with red, yellow, and green status indicators.
You enter the data manually or paste from a CRM export. It is not a real time dashboard. It is a structured weekly review tool.
How to actually use the dashboard
A dashboard is not for daily checking. It is for two specific moments.
The weekly pipeline review. Open it before the meeting. Identify the top three things off target. Go into the call ready to discuss those, not the green metrics.
The monthly business review. Open the trend view. Look at six month trends, not week over week. The signal is in the slope.
If your team is opening the dashboard daily and reacting to small movements, you have built a stress machine, not a management tool.
Common dashboard mistakes
A few patterns to avoid.
Tracking too many metrics. If you have 40 KPIs you have zero priorities. Twelve is the upper bound. Six is better.
Tracking output without input. Tracking closed won without tracking pipeline created is how you get blindsided next quarter.
Setting targets without history. Round numbers are seductive and wrong. Use your own historical baseline as the floor, then push from there.
Letting the dashboard drift. Definitions change. Stages change. Quotas change. The dashboard has to keep up. Audit the formulas every quarter.
Download the template
Get the free Excel sales KPI dashboard with all 12 metrics, formulas, targets, and a one screen rollup view.
Download the sales KPI dashboard
Related reading
Bring this into Salesforce with CRUSH
A KPI dashboard tells you something is off. It does not fix the off thing. The fix lives at the account level: which account is at risk, which deal needs a champion, which whitespace play has not been activated.
CRUSH layers account plans, relationship maps, and mutual action plans on top of the data your dashboard already shows. The metric tells you where to look. The plan tells you what to do.
