No two sales teams are the same and they all need managing differently. However, keeping an eye on these metrics should put you in good stead to help your team perform at their best.
1. Win/Loss Ratio
The ratio of won to lost opportunities. This measures the productivity of a sales rep or team. The higher the percentage of won deals, the more effective the team is performing. Comparing a single rep to the team average gives you an idea of how an individual is performing. So you can share the best practices of your top performers and provide some extra support to the people who need it.
N.B. Always judge a rep's sales productivity (based on their win/loss ratio) in relation to the overall team/industry average. For example, if your team is selling a freemium product, they'll likely have a significantly higher loss ratio.
2. Average Deal Size
The average deal size is a great proxy for measuring a rep's ability to qualify leads and delay gratification. It's also an absolute MUST for accurate forecasting!
You can use this number, together with your team’s win/loss ratio, to provide new starters with a concrete number of qualified opportunities they’d need to start the quarter with if they were to meet their quota at the end.
Opportunities Needed = Quarterly Target /Av Deal Size x W/L%
e.g. If your team’s win/loss ratio is 35% and your average deal size is $12,000. A rep with a £150,000 target for the quarter should start the quarter with...
150,000 / 12,000 x 0.35 = 36 Opportunities
N.B. The overall team number is a good starting point here. You should be able to work out your reps' individual win/loss ratios and use those for better accuracy.
3. Forecasting Accuracy
There are two different ways of thinking about this. Both, however, are a good measure of how realistic reps are about their pipeline.
Forecasting accuracy as % of goal (a.k.a. margin of error)
From a sales management standpoint, it is very important to have a good understanding of your team's margin of error. If a rep has consistently missed goal by say 5% that probably isn't cause to put them on a performance plan immediately. However, if this is a common occurrence across a large sales team, those percentages could start adding up. Knowing what the overall impact here could be, will save you a lot of headaches when setting up quarterly forecasts and later reporting "up the chain". On the flip side, if a rep is consistently above target, it's a good indication that their quota could be increased.
Forecasting accuracy as variance of close date
This is the difference between expected and actual close date measured in days. It is common practice for salespeople to pick the last day of a month/quarter as the expected close date for the bulk of their opportunities. In such cases, knowing that rep A's deals take on average 10 extra days to close from their original forecast day is invaluable.
4. Pipeline Tenancy
This metric shows you the average number of days a deal spends in a given stage of the pipeline before it closes. As a sales manager, you want to be mindful of the pipeline stages that deals tend to get stuck in. This is a great way to decide on training content and what individual reps need help with.
Knowing your team/reps' pipeline tenancy is the best way to spot staling deals.
e.g. If you know that on average rep A's deals take 5 days to move from Proposal to Verbal Agreement and a deal has now been sitting in Verbal Agreement for say 2 weeks, that should tell you that something is not quite right. (Hint: Don't wait for 2 weeks to pass if the tenancy for a stage is only 5 days).
5. Probability of Closing
The actual likelihood of a deal being successfully closed based on the stage of the pipeline it’s currently in. The further down the pipeline a given deal is, the higher that percentage is. This percentage will tend to vary from rep to rep and is a great way to spot who needs help with what.
This is the single most important metric when it comes to building a reliable sales forecasting system based on weighted averages.
Any sales professional who has used Salesforce.com will be familiar with using weighted averages to forecast. The difference here, however, is that to have a reliable model, you need to account for the fact that the probability of closing will (significantly) vary for different salespeople. Knowing the numbers for your individual reps is the difference between a good and a great forecasting model.
Pro Tip: If you really want to take your team's sales forecasting to the next level, then you should consider not only what the actual probability of a deal closing is at a given stage, but also how it ties to remaining pipeline tenancy. This could be a bit hard to wrap your head around at first so here is an example:
A deal (worth $8,000) is expected to close in 6 days. It's currently sat in Proposal Shared. The probability of closing at Proposal Shared for rep A is 85%. Standard weighted average forecasting will put this deal at $6,800. Things start looking different if you know that it takes on average 10 days (4 more) for that deal to travel through the rest of the pipeline. TL;DR - the probability of closing, in that case, will be less than 85%. More importantly, it will continue decreasing as time goes on. This is what we call Dynamic forecasting and we'll cover in a different post.
Hopefully by keeping track of these data points you'll be better informed and help your team to perform better.
If you need some help digging into the data, Heresy will show you these metrics and more! Head over to heresy.io to learn more or to sign up for your (free) account.
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