Quantifying Intangible Sales Factors Using AI with Rob Käll [Episode 744]

Rob Käll, CEO of Cien, Inc., joins me on this episode.

Key Takeaways

  • Cien, Inc. is headquartered in Miami, Florida. Cien means 100 in Spanish. The name refers to reaching 100% of quota. Cien offers AI for SaaS businesses that are scaling.
  • Rob tells of working in SaaS and not seeing revenue scale with the sales team’s growth. In 2016, Rob and a business partner addressed the problem of scaling sales revenue by starting Cien.
  • Cien is a web app. A prospect can get a Hidden Revenue Assessment to start the conversation. Hidden revenue refers to reps who are not making quota.
  • AI identifies the root causes of that hidden revenue by analyzing a prospect company’s anonymized sales data. Then the prospect can sign up to start using the Cien AI product. The tool is designed for sales leaders.
  • Most sales coaching today is not structured or measured. AI can help leaders and coaches address the problems using a value chain. Rob explains ‘value chain’ and how to measure ‘inferred work ethic’ instead of activity metrics.
  • Rob talks about evaluating communication skills and engagement ability. Cien AI allows for individual characteristics. You can’t clone sales stars but you can improve reps’ skills in using effective sales tools.
  • The reason most sales reps do not hit quota is that they are failing in one or two core attributes. Sales managers are also causing by stacking the deck against some reps. AI demystifies sales.
  • Rob explains the procedures Cien AI uses to analyze sales data and provide solutions to problems. Cien accesses CRM data, emails, and phone calls. The more data is seen, the better the assessment will be.
  • AI analyzes the time reps are spending on various activities. It also analyzes if sales leaders have been distributing leads unevenly. Rob explains how Cien implements the process for their clients.
  • The more time reps spend talking with their prospects about the prospect’s core problems and needs, the more engagement and selling opportunities they will have.
  • Rob talks about scoring opportunities by value. What about the value delivered to the prospect? That can be inferred from the opportunities that do not close versus the sales that close.
  • Cien AI uses natural language processing to parse conversations and find if appropriate questions were asked at the right time. Then engagement ability can be measured. Andy wants to measure what really matters.

Episode Transcript

Andy Paul 0:00
Hey friends, this is Andy. Welcome to Episode 744 of Accelerate the sales podcast. My guest will be Robert Käll. Rob’s the founder and CEO of Cein. Today we’ll be talking about how to use artificial intelligence AI to quantify the intangible factors that can positively influence your sales results. Among those intangible factors that AI can quantify and we’ll be talking about today are the hidden revenue that sales reps leave on the table. Evaluating US sales reps engagement, ability, and communication skills mean their individual ability to engage with a prospect and effectively communicate. We’ll talk about how to measure the inferred work ethic of an individual seller versus their activity metrics. In other words, are they working smarter and harder, and quantifying if managers are unintentionally stacking the deck against the success of certain sales reps by for example, assessing if the leads are being distributed unevenly or evenly throughout an organization. So we’ll be getting into all that and much more. Okay, let’s jump into it. Rob. Welcome to Accelerate. Glad to have you here. You’re joining us from Barcelona.

Rob Käll 3:02
Yeah, today I’m in Barcelona. We have our R&D office here. We’re also in Dallas, Texas.

Andy Paul 3:06
So where’s where’s headquarters? I mean, last time, I think you and I spoke it was Barcelona.

Rob Käll 3:16
Our company structures as a whole gets very complicated. We are a US based Corporation. We’ve been headquartered actually in Miami because that’s where I’ve been doing business for the last 20 years. Activity level of businesses is in Dallas. Gotta pop to our R&D center in Barcelona. So I am always on a plane basically.

Andy Paul 3:40
I’ve got two offices in New York and San Diego and I’m always going back and forth. I thought I had it hard but gosh, you have to throw in a flight to Barcelona.

Rob Käll 4:20
Cien means 100 in Spanish, you know, it is a little bit of an homage to where we are here in Spain doing our R&D. And back to this whole thing that you want to get to 100% quota under percent on your test 100% on everything.

Andy Paul 4:35
I see some of your people have hashtags about that. So what was the impetus to start the company? I mean, what was the problem you’re trying to solve? And can you start by telling people about what you do first?

Rob Käll 4:49
So we help companies get to 100% quota. We do that by using AI primarily for SAS businesses, businesses. And the reason we started this business was for the same reason that most people start businesses. We were frustrated. I had been a SAS entrepreneur for the last 15, almost 20 years. Last company we grew from 2 to 100 people in sales in a very short period of time. And, coming from more of a math computer science background, I was like, I guess I can get 50 times as much sales. Guess what I did not. I was constantly trying to figure out what were the reasons and even if I work with awesome people that could never really get to the root causes. And the trades that were making that happen for x, y revenues didn’t grow in a linear fashion with the number of people you had. So my business partner and I had a successful exit with the last company. We worked with a new parent company for a couple of years, and then said, let’s do something different. And, that became Cien.

Andy Paul 6:08
And you’ve been around for how long?

Rob Käll 6:13
So the company was originally incorporated a little bit over two and a half years ago. And we started an active development about two years ago.

Andy Paul 6:24
So the product explains the product. So the product is a mobile app.

Rob Käll 6:30
It’s a web app. But what we’re doing is a little bit different from what most software companies are doing. We think that something like AI is very new and hard to get around your head for the average sales manager. They hear AI and maybe they say, Oh, we can do this or I can do that. What we want to do for our customers is to give them a chance to see what our product does without even engaging with the products. What we have is something called a hidden revenue assessment and that allows you to essentially get a PDF. That PDF is an assessment of your entire sales team. As the name implies, hidden revenue means that we think that every single team, we’re not everybody’s making quota. Sure, and let’s talk about this. Everybody’s not making sure that they’re considering hidden revenue. And we want to help you identify the root causes for that hidden revenue. So what we’re doing is to give you a chance to test our software without doing any onboarding. We just want a sample of your data, anonymized so no specific information, no company names, the contact information on that stuff. The analyzer using something like 200 AI models, and then to get back to you and say, Here are your best and worst reps and the reason why they’re the best in the worst rate reps. And here’s your revenue, and then you can start beginning using the application.

Andy Paul 8:17
Okay, so let’s talk about how the application works on a day to day basis. So, is it just purely pulling information from Salesforce and analyzing what’s provided, you know, on the dashboard reports, managers?

Rob Käll 8:32
Yeah, the tool is primarily for sales leaders. We’ve built a tool that sales leaders have up until today, been flying by sales. It hasn’t been structured and it’s been very measured. And that’s what we want to help people understand. You want to be able to say something, but it’s very powerful. Johnny, you have a problem with attribute A, could be something like work ethic? Reasonably, you know what, you have a problem with that because we have compared it against your peers, controlling for all the factors like, for example, that the data may not been 100%, clean and so forth, right? And say, when it ends, then say using something called a value chain, if you changed your work habits a little bit, instead of going on these, you know, smoke rates every two hours and spending 20 minutes there, if you pushed in a few more calls, if you had a few more, you know, productive activities every single day, you could translate that into an additional $200,000 towards your quote every year right. And that is the unique aspect of what CMS do, they look at each one of these attributes and then translate them back to value. So you don’t have to worry as a manager or as an individual contributor, on the things that draw or do well on, you know, so much time today spent on meaningless training, for example, you need to try and train on the product. Well, half of the people in that group already know the product perfectly. And then there’s a few people that don’t know anything. So he needs to take the training two times probably right. That’s the type of stuff that we want to help people.

Andy Paul 10:30
You mentioned on your website that you measure the intangible so obviously, that would sound attractive to some people to be able to do that. But how do you do that for work ethic? And you give several examples. I want to go through some of them. Are you actually tracking them? That Johnny went and spent 20 minutes smoking? Or are you just tracking the fact you didn’t make as many calls as his peers?

Rob Käll 10:56
So we’re inferring this information. And we’re referring mostly from your CRM activities. And then every single sales leader will say, well, my sales data is not good enough, I don’t have all my activities, I don’t have all the things in CRM to be able to do those things. And that’s true, you don’t have all the data that you should have in CRM. But you probably have enough, especially if you’re a modern sales, SAS type of company that is using some of the more modern tools to to capture more information that we can infer all of these things. So for example, we can look at how much time you actually spend selling versus your peers.

Andy Paul 11:40
So how are you on the bottom?

Rob Käll 11:41
On the bottom of that when we call a bell curve, right? So if you’re on the bottom left there, we know that your level of intensity in that particular activity be it prospecting, be it selling, be it upselling, be it post sales support, whatever it is right? That piece is affecting your ability to take it home.

Andy Paul 12:07
Okay, so this raises all sorts of questions for me. So, you’re trying to measure work ethic? And you presumed part of that is in comparison to what peers are doing. But are you then extending it further and saying well, Hmm, this person may not be making as many calls than the other who is actually performing at a higher level. So are we digging in them on work ethic? Are we saying oh, well, maybe actually their work ethic is better because they’re being more effective than the other people who are just pounding out calls.

Rob Käll 12:47
So work ethic is the intensity of your offense. Again, how can you make sure the activity counts. There are so many sales leaders out there just sitting and saying how many calls were made this week how many calls were made last week? And they look at incentive skills behavior, right is managed to the numbers. So the second you start counting something like call numbers, guess what, call numbers go up, does that mean that the results go up? Not always right. Of course, it’s not just about work ethic, it’s also about effectiveness. So one effectiveness is his communication skills, and measuring communication skills, in a way that you’re thinking about it is extremely difficult, but we have found ways that we can get good information by using something called engagement ability and then we’re using the latest in natural language processing. That just basically means that we’re using artificial intelligence to analyze exactly what’s going on in each interaction. And then determine, for example, if Johnny sends a lot of emails that are completely ignored, and Betty is sending emails that are always soliciting responses and further conversations and turn into something else. So again, that’s another measurement. So you can have an okay work ethic, you don’t have to be perfect. And then be very good at engagement ability and get awesome results. Or you can be a little bit worse in engagement ability, but you’re very good at working hard, and then you can get similar results. So this goes to a core tenant that we have at CNN, no sales people are trying to clone everybody to be some kind of Michael Jordan.

Andy Paul 14:54
I agree. I think it’s one of the shortcomings. Some of the technology that’s been rolled out that people are trying to use are to create clones of Michael Jordan for example as opposed to trying to improve the battery, it’s of each individual.

Rob Käll 15:17
Well, I like to ask this question. A few other things measuring product knowledge, to measure value received, which essentially means, Are you sitting on a good territory and your favorite in your labor distribution or not? Because this is such a constant chattering in your sales team, whether you’re getting a fair shake or not right. A few other things like the deal sizes and closing ability and so forth, stakeholder mapping, we have all of these different attributes and what we are finding is not that you have to make everybody the same. You’re making everybody Michael Jordan. Most of the time, you don’t have to be in the top percentile or anything like that, because, you know, quota is, in theory, something that is attainable for the average salesperson. But the reason why many of them are not making quota is because they’re failing in one or two of these core attributes. So what we’re seeing every single time we make these types of assessments that I was just talking about, they are sitting always, we weren’t called green badges. You can see those on our websites. They are like with, you know, some really outstanding abilities. The middle people are in the middle, and then the people that are failing, and they’re not yet getting up to speed and so they always have one or two red badges that there’s something wrong with what they’re doing. Sometimes it’s fixable, you know, product knowledge, you just need to send them to training. Sometimes there are more inherent problems that are close to the person that they just don’t want to work hard enough to be successful. And sometimes even the sales leaders fail, they’re given a territory, and it’s very hard or they’re giving a new industry segment that is very hard for their product to get into. We have every single sales leader identify those problems.

Andy Paul 17:25
I like that that idea of the value received because certainly we want the constant problems to see across companies is the uneven distribution of leads and it becomes a sort of, vicious cycle that perpetuates itself, as the sales managers cherry pick leads to give to certain people that think we’ll do a better job with them. So yeah, you have this uneven distribution. So, I mean, if that information is available publicly to the rep so they can see the whole team I think that really becomes valuable, right? Because it does put this on sales managers? Because one thing that I’ve seen hundreds of times in sales teams is people who really aren’t given the opportunity to succeed, right? They’re given, as you said, poor accounts, or they’re not as advantaged accounts as other people. And how can you ever expect them to succeed when they’re climbing much steeper hill and other people?

Rob Käll 18:25
And again, this is the demystifying of sales to some degree, which I know you are constantly writing about and breaking down and trying to turn into a more scientific way, this is our attempt to do just that. To say, hey, if sales is essentially a series of activities that are intended to increase the value in each step, from lead generation to prospecting to actual closes, well, if you can’t measure the various steps you have, you’re operating at a disadvantage and obviously just counting things is not sufficient because two lines are not the same. The referal you got from your best customer is much more valuable than some lead that your marketing department import from a database, right?

Andy Paul 19:14
Theoretically, yes it should be right. So you’d mentioned about time reps are actually spent selling. So how, how are you measuring that within the system?

Rob Käll 19:34
But I’m gonna try to conceptualize it here. Bear with me. But as I do that, our technology is a pyramid. The bottom layer is just our ability to capture different sorts of data sources. And for all intents and purposes, the most important one we’re always capture is a CRM data itself, including activities and so forth. The layer above that is to deal with the fact that no CRM data is ever good. Trying to analyze CRM data at face value is a fool’s errand, because there’s always a myriad of different ways that there are missing entries or inconsistent entries or methodology changes have happened, etc. I can go on and speak about that for the IRS. But I’m sure that’s not the best use of our time today. After that, now we’re trying to understand what’s going on with the data. So we call that a semantic understanding. That’s what I was talking about before, using natural language processing, and so forth. So now all of a sudden, the data actually makes sense. They’ve corrected it. The next layer after that is predictions. But we are starting to say if all of these things have happened in the past, and we can face this stuff with clean data, this is likely to happen in the future. And that obviously takes a lot of factors into hand. And then the layer on top of that is that value chain where we are applying dollar numbers to that. The final thing will be called mentor, which is a prediction or sort of prescription engine, or we’re saying this is what you should do about it. So going back to how I just wanted to give you that background, back to how do they figure out how much time you’re spending? Well, every single activity has a piece of information. So we’re looking at, for example, if there was an email, if it was a phone call, a lot of times we have transcripts of emails and phone calls in there. We also have statistical models that determine, you know, how long something like that day, we have that correction for the fact that we probably know that some reps may not log all of their activities. And then we see how much time is spent on everything else. And by inferring that and seeing the results of their activities by infernal, if we can determine, and obviously not down to the second, we can see where someone is spending 20 hours a week prospecting, or if they’re spending 10 hours a week prospecting, and that job makes a huge difference in how much pipeline they’re building, for example.

Andy Paul 22:17
So, yeah, just finishing up on the time thing. Unless the customer has SIN data from, you know, from their dialer or their phone system or so on, they have to have access to all the data sources. So you can get that right.

Rob Käll 22:39
So we are always trying to get as much data as possible. And this is obviously one of the challenges with being in this field of being data dependent. The good news and one of the reasons why we are exclusively focused on SAS companies this fast growing, you know, companies that are coming out with minimum of 10 reps going up to 200 reps or something like that. That’s our sweet spot. And almost every single one of those companies are using tools like sales, loft, outreach, io, etc. that we basically get very clean data comparatively speaking on a couple of occasions taking more quote, unquote, traditional sales companies, and we’d have a much harder time for every single assessment that we’re doing. Our sales team does what we call a confidence score, with these SaaS companies that have the confidence scores for things tend to be in the 80 to 95% range. Once in a while, you have to say there is not enough data to give up all of the recommendations that we have can still give you recommendations on a few items. But if you have very few activity records and so forth log their overall accuracy, which is essentially our estimate of one isn’t so if you have 50% accuracy then 50% of the staff say it should be there. Right? What we’re finding for the SAS businesses is that their accuracy tends to be 80 to 90%. And that also gives us a high level of confidence. So this is all math driven, if you will, right? We have ways to verify this stuff because we have ground truth. In some instances, we know exactly what’s going on.

Andy Paul 24:22
Yeah, I’m thinking in terms of the phone calls, right? So if you’re to say look, I want to capture every minute that Rep A has spent on account B from the initial point of contact all the way through to the deal closing right. Now, can you do that?

Rob Käll 24:44
Yeah, we do that but we don’t display it like that because we don’t want to mislead people to say that there’s an exact thing because if unless of course, the dialer stamps in exactly what time most spent on the phone, we would essentially make an estimate of how much that phone call took based on the transcript based on things like when the next phone call started, etc. So there are a lot of different signals. The AI Institute can take all of this disparate signals are each one just like you as a human, you can say, well, this conversation we’re going to have today, it’s not going to take four hours because none of us and we’re not going to be able to cover it in in five minutes, because we’re not going to profoundly. So we know it’s going to probably be something like 45 minutes to 15 minutes. And that’s essentially what the AI does. And then we can aggregate it up and it becomes very useful and meaningful when you look at it from a rep standpoint and how they spent their time during a month, for example, becomes a little bit less meaningful if you just want to look at an account, especially during prospecting, where you might only spend, you know, make a few calls and so forth. But what we want to make sure that we’re doing is to help you understand the level of intensity, that a rep applies to a specific type of activity. And of course, also to the overall goal of their sales code, etc. And the beautiful thing is that once you have that this is kind of like a puzzle. And you know that you’re right, because at the end of the day, everything adds up and the puzzle comes together or not. So you talked about the work ethic when we see that you have one rep that spent 30 hours in meaningful sales activities in a 40 hour week, and you have a rep that has spent 19 hours in meaningful sales activity, and you see that pattern in just one week or two weeks. You see that across, let’s say, you know the last few months for example, then it’s very easy for us to compare him or her to the rest peers and then grade them on the work ethic scale, right. And again, most of the time people are in the middle, that’s the beautiful thing about human behavior that tends to go into bell curve and you tend to be in the middle. So on most things, people are in the middle. And that typically gives you that average result. The thing is that the people that are struggling, they are typically on the left, like on the bottom quarter, on one or two things, and then that prevents them from succeeding. And when you can identify that, all of a sudden you have a problem that seems intangible and hard and it becomes very fixable. Except in some cases, whether everybody agrees with me or not, and we should not do it. Right. And then at the same time, one of the things that sales leaders come to us and ask all the time is, you know, my 20 person team, it’s doing pretty good, but also revenue is coming from these three guys, right? Like those three people are selling everything. And of course that’s not true. But that’s the perception. And when we go in and look at it, it is almost always based on two factors. One, those reps are good, you know, they don’t suck, but they’re not good so that they are just extreme. But what happens is that they tend to be sitting on the best accounts, you don’t do a lot more out upselling then the rest of them, you see them doing much bigger deals, then the rest of the people and you see them being just in very favorable territory compared to that to the rest of them. So then that becomes from a sales leader standpoint. Oh, I mean, I kind of knew it, but now I have it on paper. And then it’s a question about, well, what would happen if one of them were to leave for example, could I then quote/unquote, we talked about you and clone people before but in that particular case, perhaps you’re in control to replace that person and get similar results.

Andy Paul 29:07
Well, that gets back to what you’re talking about earlier is, you know, subconsciously or not, every time I’ve seen a situation like you described, again, I’ve seen hundreds, is the sales leader knows exactly why that’s the case, right? It’s not a mystery to them for the reasons to talk about for they may not want to admit it to themselves, but they’ve been unevenly distributing the leads, I’ve been playing favorites. And yeah, it’s interesting, you know, when they get data from you, what they decide to do about it, are they self aware enough to say, Oh, well, maybe I should split a territory, maybe I should. If these guys really were that good, these top three people, and I’ve done this with clients before as you take top people and put them in new territories, right? If they’re so good, great new territory. The accounts that we’re getting from those sales leaders are interesting sales leaders actually self aware enough to take action or whether they, as they oftentimes do is they just protect what they’ve got, because they’re afraid to make any changes.

Rob Käll 30:16
Right? Exactly. Like you don’t want to rock the boat. But if you understand what’s going on, then you can take things because another opportunity is always the middle pack. The middle pack are the people that have, you know, decent attributes on everything. They’re not so poor on any one of these things, that prevent them from being successful at all. Basically selling nothing close to nothing, but they’re also not exceeding and perhaps, you know, doing significantly more than quota. And then again, what can you do with them? And is it one or two things that could make a big difference compared to their peers? Is that about, you know, for them, perhaps increasing the territory pie or the lead distribution? Or is it the, you know, going back and saying, if we changed our Salesforce structure and gave them SDRs, for example, they would spend less time prospecting themselves. And therefore they could apply decent skills to do more deals and hopefully actually improve on their closing skills and all of that stuff as well. So there are always multiple ways to skin this cat when it comes to looking at a situation. When we’re looking at a company. Let’s say for example, that they did $20 million in bookings last year, we almost always find between four and $6 million. So what we call hidden revenue. And this is the stuff that they’re leaving on the table because of various problems with various reps. And the question then becomes, what problems are the most urgent while we sort by the dollar opportunity, basically. And then we say, next 60 days, we’re going to work on one or two of those problems. So for example, if it is engagement ability, which is the ability for us to kind of start a conversation or re-engage the conversation that is stalled out, right. Well, at that point, you start looking at who has the problem, you start digging in and how they’re communicating. Are they writing the standard sales, and I think I’ve seen this thing too, you know, “Just checking in. Have you looked at my thing from last week?” Why would I know. I mean, obviously, I may or may not have seen the prospecting email you sent me before, but clearly did not, you didn’t provide any form of value for me to act. So perhaps using a different tactic, I mean, you’ve seen the myriads of tactics or people are using out their videos, this and that. Well now what you can do is to see what are your best reps doing? How are they communicating differently, and oftentimes, it’s not the video, it’s not the clever little joke or something like that. It is talking about the problems that those people have. And making sure that’s crystal clear that you have a solution for those problems, right, those are back to the just very basic. So can you as a prospector as an SDR so as an AE that’s trying to kind of restart a conversation, pinpoint back to the buyer’s core issue that he or she is experiencing right now. And make it crystal clear that talking to you on the call or in the meeting or demo, whatever it is, is worth your time. Then what’s giving you great engagement ability, and it wants to see that you have completely different results. Right?

Andy Paul 34:08
So how would you measure it about value received, I guess? How would you measure value given to the to the customer

Rob Käll 34:18
I’m sure you have seen tools out there for lead scoring.

Andy Paul 34:27
I see less but that’s pretty engaged. I’m talking about gun II, moving somebody past most likely through the sales process.

Rob Käll 34:35
I like to go through everything. So I’m going to start with lead scoring and then go to the upper disc to score because they’re not the same but they’re related. And on the lead side, we look a lot at the standard attributes that make a lead good or not. How did it get to you like, was this a referral? Was it an ASIO type of thing that people are actively searching for, for their product. Obviously, where the person is located, the type of individuals, we do a lot of stuff to understand titles and break them out down in different dimensions, their seniority and the job functions and so forth, etc, We look at all of these things and in many cases customers come to us and say, all of those things are fine and dandy, but we also want to make sure that you’re measuring this particular attribute that we keep track of, and it could be a particular system that people are using in their database or website, technology, whatever it can be anything. So once you have all of this stuff, you run your your algorithm and all of a sudden you get a statistical probability that this type of lead is going to convert into an opportunity and so forth. What we’re doing is taking that one step further and saying, given all we know about what happens during the sales process, let us all supply a value to that lead. And we’re doing that for patent pending process. It’s called a CM value chain. So all of a sudden, you understand that this lead here, athlete is only worth 10 bucks. You know, it’s not terrible, but it’s certainly not something that is just going to close itself. And here’s a narrow lead that is worth $1,000. Once we have now opened up an opportunity with that lead, you have the ability to do a similar thing on the on the opportunity. And there we look at one thing that I think most people that have looked at implementing an SDR team and have been frustrated with is that if they are not sure about the quality, what’s coming through the pipeline from the SDR right? It looks good on paper. But then, of course, he says, no, this was not real, you know, write SQL if that’s what you’re used to in the terminology. Obviously people use different terms for this, but this was not something that I could act on. The guy was not ready to have a demo, they were in the wrong industry, etc. So we’re taking all of those factors that you have during lead scoring plus looking at what type of engagement you’ve had so far? What is the expressed interest level that the customers find down? And then who was it that did this stuff, this SDR normally generate good opportunities, right? We take all of that stuff, and then we say, this opportunity is probably worth x. And an opportunity is obviously not worth then the pipeline value of it, you know, if the value of the opportunity that came through, say $10,000, well, you know, you can send through a bunch of $10,000 and that doesn’t mean that every single one of those units are gonna close needs to get, you know, probability adjusted down, right? So these are the types of things you’re doing and then go. This was a long explanation, and I’m getting very technical here. But I know at least you appreciate that. I don’t know if the audience likes it or not. But going back then to them, you know what that is? Well, you just simply add up all those numbers and what you receive is what you value received, right?

Andy Paul 38:27
Yeah, I think I was asking a slightly different question, though, which was from the buyer’s perspective because at the end of a call, how do you measure value?

Rob Käll 38:45
Yeah, it was delivered in that particular interaction. That’s a little bit tricky to take in. We have been experimenting a little bit with surveying and stuff like that. So knowing whether a specific interaction was valuable or not is very difficult. However, knowing if an aggregate number of interactions delivered value or not, it’s not so difficult because that your results from it are very dependent and correlated to that. So ultimately if you are having a bunch of interactions, and you get that engagement we talked about before, but you’re not closing. Well, there was something that was missing there. And if all the beautiful thing with AI is that you can do what you would call regression analysis, keeping all other things equal. So if you compare similar deals to each other, and then you know, everything is the same, so to speak, except that when they interact with one rep, they don’t close and when we interact with our reps, they do close, then you can infer that Rep that is not closing. He or she is lacking what we could call for example, closing ability, right?

Andy Paul 40:09
Yeah. Not a term I like because I’m not a believer that there actually is closing I think closings and outcome right is it’s everything you do before that it’s your discovery, your needs analysis, your qualification. So it’s our last question is how do you measure effectiveness or can you through SIN? You could say, Okay, well, this person’s done a very good job of qualification, but you gotta look at discovery first, because the qualification effect is directly tied to how well they do discovery.

Rob Käll 40:50
We don’t have a measurement as of today that is called the ability to do discovery whether or not it can essentially be inferred from a few other things. Again, we are using NLP natural language processing to understand a little bit about what’s going on in conversations. And we look there for things like problems and definitions and so forth. So if those are present, you can infer that some discovery happened, whether the questions were exactly right or not. That is hard to infer. And we don’t make claims that we can figure out exactly right, which is not the mind of the buyer. We can’t read the mind of the seller. And that’s when we were talking about individual activities on things is always an approximation. The beautiful thing is that in sales these things are not happening one time or two times, but they happen hundreds of times. And then the patterns emerge very clearly. And that’s why we can say, this is a person that has problems with things like engagement ability, product knowledge, and closing ability, which all three would be affected to some degree if you are not doing effective discovery, which in my definition is essentially just figuring out what the customers problem is, and communicating effectively about how your product or service solves those problems.

Andy Paul 42:41
Yeah, roughly, I might have a different definition. But we have to come back and talk about it because we’re running long but yeah, it’s very interesting. And I think this is overall just a direction that we have to go and sales is to do a better job of measuring what really matters. But I think you’re you’re taking some first steps toward that. Okay, friends, that was Accelerate for this week. First of all, as always, I want to thank you for joining and I want to thank my guest Rob who will join me again. Next week my guest will be Richard Smith.