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previously I talked to you about the SAS methodology what I'm gonna do next is match that to the model of the data model and what I'm gonna look at the data model I'm gonna look and a little bit more of a complete model over the past years what we see is that due to all kind of tools data and the depth of data provided is a lot more sophisticated so in this case I'm gonna once again draw the SAS SEALs method funnel we see the down here from left to right down here I'm gonna start with prospects now some of you may be familiar with using suspects and suspects to me are like the phonebook they're literally a list of names it's no correlation that they have to your business those are suspects if we're talking about prospects we're talking about people who have a reasonable likelihood that they can buy your product or service those are prospects moving forward from prospects we have marketing qualified leads if we nurture process with education they may probably end up on our website eventually when they take an action on our website they have become a marketing qualified lead for example they've provided the email address for a download next step that they've become they become a sales qualified lead as a sales qualified lead they are ready and willing to meet with somebody in the sales organization to discuss their needs this is a b2b environment they want to discuss their needs shortly following that they become a sales accepted lead or sales accepted opportunity SILS accepts the lead and from that point forward they are responsible for closing their deal following that if the sales does a good job they get receive mutual commitment with the client a little bit after that following that mutual commitment the team are responsible for all morning them gets the client life which really is where the client starts to first use the product they achieve first usage but also first value they start to see the impact that the solution can have which is called life following recurring use for through the impact stage what we now got down here we essentially get monthly recurring revenue or annually recurring revenue and all at the end if this is achieved over multiple years we get the lifetime value what we see down here is the direction on how are we gonna how are we gonna draw the metrics around this is how I'm gonna draw a few of the metrics here I'm gonna show you how we can do that the metrics first and foremost we are going to consider conversion rate conversion rate conversion rate one is from prospective and to mq conversion rate - it's from mql to SQL now conversion rate 3 is a real important one conversion rate 3 sits right between SQL and SEO for larger deals they don't are aren't as valuable but for high velocity deals these are extremely valuable and ca4 which you may also know as win rate is really what determines how many leads do we need how many deals do we need to win and in this case for example 1 in 4 following that we have CR 5 conversion rate number 5 which is essentially are we losing any clients from the time that they committed to the point that they're on boarded and then following conversion rate number 6 is how many customers achieve and fulfill the commitment of of that contract let's say a 12-month contract we would say expect 12 months in conversion rate 7 what we're going to see is how many how long to achieve what is the rate and amount that people actually achieve lifetime value these are 7 conversion rates these conversion rates are matched with sales cycle lengths with times and so we're gonna have down here T 1 delta T 2 delta T 3 delta T 4 delta T 5 delta T 6 and delta T 7 I know this is I mean I don't even have to mention it seems obvious right these metrics start to give us an idea give us a reasonable idea what's going on now if you're a marketing you may have seen these rates before but you may have called them differently marking combined sometimes this particular matrix and column is calling that lead to opportunity and this is referred to as lead to close I know I'm giving you a lot of metrics and all kind of abbreviations right now I'm quite aware of that but that is in general with a map the mathematical model that we're going to build from we need these numbers because this model allows us to apply and think everything in our business this is the science behind it this is the model the data model as soon as we start pumping data into this model we can see causation what what one one conversion rate causes an x cover conversion rate and it allows us to identify what is right and wrong [Music]