Accepted Instances of Meeting Type which contribute to revenue carry a Value, this value is often referred to as the Average Meeting Value or AMV. If the AMV for a given Meeting Type is known, and number of Accepted instances which are impending of this Meeting Type are also know. Calculating the forecasted revenue is relatively simple.
How many Instances of a given meeting type must be "Accepted" in what period of time to hit our closed won target?
Example: A quarterly closed won target for a given team is $1M
• 60 Days Deal Cycle from Qualified to Closed Won
• $0 of Existing Pipeline
• Single Revenue Generating Meeting Type of "X"
• "X" has an AMV of $2K
• "X" has a 35% Accept Rate
• Deals are only sourced from Kronologic scheduled meetings of "X"
If it takes 60 days to close a deal from the point it is qualified and given that there is $0 in existing pipeline then we need to have all of our accepted instances of type "X" scheduled within the first 30 days of the 90 days quarter. Please appreciate the distinction between when an instance is accepted and when an instance is scheduled. These two very different events are distinguished as the time-stamp of when an instance was accepted by the recipient, and the actual Start Time of the instance. In this example we mean that the Start Time of accepted Instances of "X" must be within the first 30 days.
If each accept of type "X" is worth $2K in Closed Won, then we divide the $1M target by $1K and get 500. So 500 accepted instances with a start time occurring within the first 30 days of the quarter are required to hit the $1M target for the quarter.
However, assuming $0 in existing pipeline is not remotely realistic. So let's assume pipeline exists and is steady state. If the pipeline already exists to support this closed won amount the more interesting question becomes;
How many accepted Instances of type "X" are required per month to maintain a $1M per quarter revenue output?
We already know that 500 accepted instances of type "X" are required to support $1M in Closed Won. If there are 3 months in a quarter, then every month we must have 167 instances of type "X" scheduled to maintain $1M in quarterly revenue output. Interestingly, given the 60 day Deal Cycle from Qualified to Closed Won 2/3rd of instances of supporting a given quarter's $1M in revenue will have Start Times in the previous quarter.
Steady state pipeline assumption allows us to ignore the difference in the timestamp of an instance's acceptance & Start Time. 167 instances must have Start Times and 167 instances must have accepted timestamps each month to achieve our goals. Note: these two cohorts of instances are likely to members which exist in both groups for a given month.
If 167 instances of Type X must be accepted monthly to maintain $1M in quarterly revenue, how many instances must be activated each month? Our example says that Type X has an accept rate of 35%, so the algebra here is easy. We just need to answer the question 35% of what is 167? We divide 167 by 35% which is about 477 Instances must be activated each month to maintain our $1M quarterly revenue output.
To put that in real world terms, if meeting type "X" is a Demo this means that 477 monthly demo requests are required to support $1M is revenue quarterly. These numbers become much more intuitive when applied against a team. If there are 10 members of a team taking Demos, on average they must take around 17 demos each month. Which is a very reasonable number
Ultimately we care about the probability of a deal closing before a given meeting is had and the probability of the same deal closing after. Knowing these two variable is all that is needed to calculate the value of any given meeting. Regardless if a given meeting is scheduled automatically our manually, this is the only way to gauge the effectiveness of a revenue generating meeting. All meeting math follows this basic format.
Let's take a look at two examples.
Example A: The Demo
Let's say historically contacts who request a demo and never get a demo convert to closed won at 0% but contacts that do receive a Demo convert to closed won at 16.8% the +16.8% difference is multiplied by the average closed won contact value to $11,905 to give an Average Meeting Value of $2K
Example B: The Proposal Review
Now let's say historically unreviewed proposals convert to closed won at 40% but contacts that do receive a Proposal Review convert to closed won at 70%, here we have a +30% difference, which is multiplied by the same average closed won contact value from the example above of $11,905 to give an Average Meeting Value of $3,571.
Scheduled Meeting Types represent known quantities of work that will be accomplished. We measure work as the progress made toward toward a goal. This is not unlike how "work" is measured in the field of physics, where the work is considered the force applied to an object multiplied by its displacement. or its movement toward a goal.
A sales team, for example, spend their efforts closing deals. Many, if not most of these efforts are not spent in a meeting of a known meeting type. Like a demo or a Proposal Review. Does this mean the efforts of a member of the sales team are wasted? Absolutely not. This is apparent in Example B: The Proposal Review. If a member of the sales team did not have a Proposal Review the probability of that unreviewed proposal evolving to a closed deal is 40%. What causes it to be 40%? We are unsure. Could be emails from the sales team, could be the efforts of marketing, or could be a late monsoon season in the Sahara. Meeting math does not care to understand the effects external to specific scheduled meeting types on value production. Again, all that we are concerned about are the progress that was made toward closing because of a given the occurrence of a given meeting. And in the case of the Proposal Review, the progress was increasing the probability of closing the team by 30%, or $3,571 in statistical closed won revenue.
If 500 demos per quarter are required maintain $1M in quarterly revenue, how many demos are required with the addition of 90 Proposal Reviews?
In the Example B we discovered that Proposal Reviews are worth $3,571, if we have 90 of them we simply multiply to get $321,429 in new forecasted revenue. We can subtract this from $1M to understand the amount we need to get from demos. $1M – $321,429 = $678,571. Then we divide by $2,000 for the value of a Demo, which gives 339 Demos.
In a Demo only scenario 500 Demos where required per quarter to maintain $1M in revenue, however with the addition of 90 Proposal Reviews only 339 demos were required, for a total of only 429 total accepted meetings. More interesting is the the drop in the number of required demo requests needed to support $1M in quarterly revenue. If the accept rate is 35% about 1428 demo request were originally required, this amounts drops to which drops to 969 per quarter wit the addition of the Proposal Review.
When using calendars to forecast revenue becomes tricky with the introduction of multiple meeting types. For this reason reporting and optimization should be practiced using the forecasted value by meeting type.