Leads generated per unit of time
You may wish to define this more strictly as “marketing qualified leads (MQLs)” that meet specific criteria. Consider splitting into the following sources:
- Inbound leads generated by source (consider tracking inbound lead response time)
– organic
– SEM
– referral - Outbound leads
Activity metrics
I generally avoid delving into activity metrics since doing so can lead to bad behavior (ex: lack of pre-call prep) and is demotivating to reps. Hence, only inspect to find the root cause of underperformance.
- Emails (# per unit of time)
- Calls (# per unit of time) [benchmark=56] and talk time; connect rate [benchmark=9%] is not in reps’ direct control
- Meetings (# scheduled; touch-to-scheduled rate ; held-to-scheduled rate)
- % of time spent selling (this is nearly impossible to measure accurately)
- Collateral and enablement tool usage
Opportunity conversion rates
- Lead-to-opportunity
- Touches-per-opportunity [benchmark = 32]
- 1st meetings-to-opportunity
Pipeline quantity, value (weighted & unweighted), and duration by stage
- Point in time
- Change over time
Deal Success metrics
- Win rate = (# closed won) / (# closed won + # closed lost)
- Sales cycle (average total days for closed won opportunities; possibly broken down by stage) [benchmark = 60 to 90 days]
- Deal size = (total revenue) / (# closed won deals) [benchmark = $166K field & $19K inside]
- Gross margin
Retention rates
- Uncapped wallet retention (generally best to measure at the parent account level)
- Binary retention (parent account or individual user)
Executive KPIs
- Compensation cost of sales [benchmark = 7.9%];
- OTE [benchmark: field ~$200K and OTE inside ~$80K]
- Revenue growth (or, rarely, market share growth)
- Quota attainment [benchmark = 65% achieve or exceed]; average quota [benchmark: $2.7M field & $1.0M inside]
- Forecast accuracy