5 B2B sales funnel statistics you need to master

We need data to drive our businesses. But more statistics won’t necessarily deliver a better business. There are five sales funnel statistics that you simply must know (and manage).

 

In earlier blogs I have argued you need only four statistics to build a back of the envelope model of your funnel. In this brief blog, I’ll shift to measurement, and detail the five sales funnel statistics that you need to know, sweat, and improve.

 

In ‘How to size your funnel on the back of an envelope’ I argued that you need to know just four statistics from your current sales funnel to work out what your future sales funnel was likely to look like, and to model improvements. Just to refresh your memory, I argued you need to know:

  • How long it takes to move a buyer from each stage in the buyer’s journey to the next stage
  • Your success rates from lead to proposal
  • Your success rates from proposal to closed deal
  • How many meetings each progression took.

And in How measurement can align Marketing and Sales I drew on our earliest alignment report (2003/4) to point out why leading companies measure Marketing on the propose to close ratio, and measure Sales on lead to proposal. It’s a weird bit of logic, but compelling. Check it out if you haven’t already.

 

So let’s assume you have worked out what your funnel needs to look like, and are now measuring the delivered reality. What are the sales funnel statistics to focus on the most? You will see a link with the modelling data, but I’m going to need to get a little more granular.

 

For each lead source and for each BDM, you need to know:

  • Leakage rate per stage
  • Lag per stage for deals you won
  • Lag per stage for deals you lost
  • GP per deal you won
  • Cost per win

Let’s deal with each of these.

Leakage rate per stage

This is pretty simple, and the case is clear. If you know how often you fail to progress buyers through each stage for each lead source, and for each BDM, you can unlock all sorts of value. For example, find out why BDM number 1 has a 20% leakage (vs. an average of 30% for other BDMs) and get them to share that tactical approach with others.

 

Or compare a campaign that has a disproportionate of it’s leakage very late in the journey, and identify why. Then make changes to that campaign to ensure that those buyers who have these traits leak earlier. Maybe qualify more aggressively, or use language in your early-stage communications that lets those who meet the profile shown by the ‘late-leakers’ qualify themselves out. “Wow, this might not be for me” is a horrible conclusion late in the buyer’s journey, and a wonderful one early on.

Lag per stage for deals you won

Time really is of the essence. Know how long it takes a buyer to navigate this stage, and compare it with…

Lag per stage for deals you lost

…how long it takes a buyer to navigate this same stage, from this same lead source, for a buyer who does progress, but then leaks at some later stage. You might find, as many do, that “lag is death” (a slow buyer is a non-buyer). But you might also find that rushing cruels your win rates from your sales funnel statistics also. Contrasting the win pattern with the loss pattern for each lead source, or each BDM (or a matrix of both if you have enough data) will tell you more about your funnel than a thousand hours of a clever consultant ever will.

GP per deal you won

If you know how much gross profit (GP) a typical win is worth for each lead source and for each BDM, than you can feed that back up the funnel to identify what a lead is worth. Let me use some crude maths to make the point. If you need 20 leads to make one sale, and you generate $20k of GP from each sale, then leads are worth $1k of GP each. Does that mean you should be willing to spend a grand per lead? You need one more data point to answer that question.

Cost per win

Make sure to include marketing costs as well as sales costs when you calculate your cost per sale. Meetings can be an very effective proxy for cost. Just take the total cost to run your sales force and divide it by an estimate of the number of meetings (include lengthy phone meetings) had by the sales force each year, and you have a cost per meeting good enough for this measurement purpose. Now count how many meetings are used up on average for each of these types of win. After applying the cost per meeting, you have a pretty good sense of the sales cost for each win type.

 

For marketing cost, apportion environmental marketing (‘EM’ is roughly synonymous with branding and positioning – for a better definition check out How much energy should you spend on branding? – evenly across all deals. So, if you spend 5% of your total GP every year on Environmental Marketing, then for each lead source or BDM, your EM will be GP times 5%. Do the same for Channel Readiness (sales enablement). Now, demand generation spend should be easy enough to apportion narrowly to each lead source as your campaigns will usually be distinct.

 

Net, net, let’s say that if you have a sales spend of $10k per win, and a marketing cost of $5k, then we can now answer how much you should be willing to spend on each lead. The $20k of GP we used in the earlier example needs to be reduced by this $15k of sales and marketing spend. So in the hypothetical business in this example, each lead is worth $250.

 

…unless you want to make a profit. GP, or gross profit, is the profit that gets applied to your overheads and then your interest costs, and then shareholder profits.

 

This blog was not intended to be a lesson in business models, so let’s get back to why we want this data.

 

If you find that campaign 1 costs $250 per lead (break even), and campaign 2 costs $200 per lead, then clearly you should double-down on campaign 2 and stop campaign 1. Remember though that the cost per lead in this example might reflect cost, or it might reflect closure rates, so do you abandon campaign 1 or do you fix it?

 

I said there were only 5 measures. I didn’t say the decisions would be easy.

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