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Maximizing Profit Through Revenue Management | Jared Wiesel from Revenue Analytics

When you think about boosting profit for any business – the first thing that comes to mind is probably selling the most items for the highest cost. However, pricing strategy is often much more nuanced than that.

In fact, nailing down the optimal price to stay competitive while also maximizing profit is an incredibly complex discipline known as revenue management. The history of the practice can be traced directly to a company called Revenue Analytics, whose chairman, Robert G. Cross, invented the revenue management discipline in the 1980’s — which was then referred to as “Yield Management.”

On this edition of UpTech Report, Revenue Analytics Senior Vice President Jared Wiesel takes us through the history of revenue management and how his SaaS company is helping enterprise manufacturing and distribution organizations maximize profit by addressing their most complex pricing challenges.

More information: https://www.revenueanalytics.com/


A pioneer of Revenue Management, Revenue Analytics is an enterprise SaaS company that partners with Hospitality, Media, Passenger Rail, Manufacturing and Distribution companies to solve their most complex pricing challenges.

By leveraging powerful analytics and deep strategic experience, Revenue Analytics’ next-generation software delivers intuitive answers to help companies perfect their pricing, reclaim missed revenue, and take back their time.

Jared Wiesel leads Revenue Analytics’ Manufacturing and Distribution vertical. He has 20 years of Pricing and Revenue Management experience helping Manufacturers and Distributors successfully sell the right product to the right customer at the right time for the right price.

With an intense focus on delivering data-driven recommendations that are business reasonable, strategically aligned, and adopted across the organization, Jared has partnered with many Fortune 1000 companies to drive profits and efficiency gains through better pricing. 

DISCLAIMER: Below is an AI generated transcript. There could be a few typos but it should be at least 90% accurate. Watch video or listen to the podcast for the full experience!

Jared Wiesel 0:00
But we help them do is walk that back to say, if you could have given a better price guidance from the beginning, not only will you make more money, you’ll close deals faster. But you remove a lot of that unnecessary process, right? versus sometimes folks have the misperception of well, we just need to speed up the review process like well, you can only speed it up when most deals are going through the review process, right.

Alexander Ferguson 0:26
Welcome to UpTech Report. This is our applied tech series UpTech Report is sponsored by TeraLeap. Learn how to leverage the power of video at Teraleap.io. Today, I’m very excited to be joined by my guest, Jared Wiesel, who’s based in Georgia, he’s the Senior Vice President at Revenue Analytics. Welcome, Jared, good to have you on.

Jared Wiesel 0:44
Thank you really appreciate the opportunity Alex.

Alexander Ferguson 0:46
Now Revenue Analytics is a revenue management and price optimization software company. And what’s fascinating is actually the history. In some ways your Chairman, Bob Kraft started this industry of revenue management in the 80s. Is that correct?

Jared Wiesel 1:01
Yeah, absolutely. I mean, it’s it’s definitely a fascinating legacy. Right. So the roots of our company day back to the 1980s in the airline industry during the time of deregulation, and Bob cross. Now, our chairman was actually a lawyer at Delta, and was tasked with finding opportunities to grow revenue in this kind of New World Order. And right as things became deregulated, and they set up a task force, essentially, that ultimately led to the invention of a lot of the core revenue management principles that still persists today. So I like to basically say he’s the reason why if we all went on line to our favorite kind of booking portal today and tried to buy an airline seat, we all pay a different price. Right? That’s, that’s really the science of revenue management based on willingness to pay available capacity, etc.

Alexander Ferguson 1:46
all started and he actually then wrote a whole book on and published in 1997, I think, on this this whole concept.

Jared Wiesel 1:51
Yes, he did write one New York Times bestseller, the guru of revenue management. So it’s a really richlegacy.

Alexander Ferguson 1:59
Now, his sons DAX and Zack, are the ones that have taken revenue analytics, what is today and have grown? Is it what is categorized as a family business starting as a family business? Is that a good way to call it?

Jared Wiesel 2:11
I think it’s it’s definitely in their DNA. There’s no doubt about it. I think they’re their dinner conversations, as we as kids growing up are probably far different than mine. Right? I think it’s definitely in their blood. But you know, Bob cross when he had he had landed really on this concept. an airline’s had had left and started a consultancy that evolved into a software company, very focused in the airline space, and then grow into hotel etc. He ended up selling that kind of did the lecture to her book tour. And then a couple of decades ago, his sons came back now that they were in the workforce, right and said, Archer turn, you have to still still basically write the next chapter in the story, right? Where it’s not done right, there’s continually abilities to push the boundaries in what I consider the more traditional revenue management spaces like airlines, hotel crews, etc. And then selfishly, where I come in is also kind of how do we adapt and evolve those into industries that are much newer in the adoption cycle of you know, more data driven analytic consistent automated pricing and revenue growth decisions.

Alexander Ferguson 3:12
Now for you actually join the company seven years ago was the correct rep the right CSM seven and a half years ago. It started though, with building custom software solutions for the larger companies, like fortune 1000 to 5000 kind of companies. And, and helping them but now you’ve actually transitioned to to build a SaaS model so that even others can come on and help me understand like, what was that shift? And what was that? How did that look like?

Jared Wiesel 3:38
Yeah, and another interesting part of the growth story, right, so when the company was founded, you’re spot on, it was really a for hire custom pricing and revenue management consultancy, right. And what has remained corridor DNA DNA, even to this day is their companies basically split between business strategists, PhD mathematicians, and data engineers. And when you think about just the complexity of pricing every room and barrier, right, or pricing every transaction for a $20 billion industrial products company, our secret sauce is how do you create those cross functional inter workings across those teams? How do we understand the data? How do we statistically calculate what the right price would be? But then constantly, how do we calibrate and make sure it fits with the business use case in need? So that awareness allowed us out of the gate to build custom fit applications is great business, right? We have a ton of customers in that space and that still remain customers today. The problem is, it’s expensive, and it takes a long time and in those spaces where folks really appreciate that specific, nuanced, highly tuned, customized approach. It’s great, right but the opportunity to scale that becomes limiting. So that was really kind of what we call one Dotto with the company. The fascinating next step, as we started to progress towards this, Astro, there’s a lot of customers actually came back to us and said we absolutely love your capability. When we have customers that we’re presenting proudly. their annual reports to shareholders the type of uplift we were delivering, but they said, yeah, these these systems needs care and feeding, right things change, data change, its market changes. There’s acquisitions and divestitures. We want to make sure we’re continually tuning it like a fine tuned racecar, right? Are you all available to do that for us, because you have the expertise you built, that you’ve trained the software and running it, but we need to calibrate the models, we got new data come in, etc. So we moved into this world. And basically, we started to manage as an outsourced analytic shop, some of those custom built solutions. Now, it’s kind of our first foray into the recurring revenue type of world the value of being able to remain involved, right, and not just drive the system, but also adoption, right, one of the biggest challenges the most analytics initiatives that folks take on when they’re struggling, it’s not that the math is wrong, right? It’s an adoption challenge,

Alexander Ferguson 5:51
right? We’re actually using the numbers using the software using that

Jared Wiesel 5:54
data, using it right when once the kind of honeymoon phase wears off. So that was kind of the next four away, and you know, and then as we started to continue to grow, start to think about other industries that we can apply, you know, hey, we’re really onto something here. And these industries, while it’s not an exact lift and shift from a hotel, to a manufacturer of automotive parts, we should be able to leverage a lot of that, right. But the problem is you get into there is for places that are less further along in their sophistication, their adoption of analytics, even quite honestly, kind of prioritizing pricing as a discipline or muscle within the organization. Part of the adoption funnel becomes how do we do this cheaper, faster, better, more consistent out of the gate to really prove it. And that in combination with just the advent of technologies around the cloud, and computing and things that allow us to do things much quicker, iterate more rapidly, and a way more cost effective price point has pushed us now to be in a purely SAS Enterprise software offering to really just help folks make better pricing and revenue growth decisions.

Alexander Ferguson 6:55
So starting with those, those three parts of the business, the business strategist, PhD, mathematician, sales engineers, building custom software, and you deliver to them, and they’re like, wow, actually, we need to help to keep this updated and going. And so you’re providing that service. And then you realize, you know, what we could actually provide is ongoing as a software as a service to everyone. scaling the availability as well to more options. Now, your different verticals, you you guys help in media and ad buying, and travel and hospitality, and then manufacturing and distribution? Correct. Those are verticals, yeah, yeah. Now, obviously started in the travel hospitality. That was where where it began. But now you’re seeing opportunity in manufacturing distribution, which is it sounds like your your specific area that you leave, what is the let’s be frank, what’s the adoption? They’re like, Hey, we were like, Yes, I need this, that I want it? Or is there any pushback of Why? Why do I need that? Why do I want that?

Jared Wiesel 7:50
Yeah, it’s a it’s a great question. I mean, it I think it’s both what keeps me energized every morning when I get up. But ask me, it also has me completely exhausted by the end of the day, right? I think it’s, this is a incredibly immense and diverse space, right? manufacturing means a whole bunch of different things. There’s more than two dozen different sub sectors, right. And there’s a lot of common characteristics, but there’s also a lot of nuances. And so, you know, historically, these organizations have been incredibly adept from maximizing the operational efficiency of the business, right? These businesses are all about how do I squeeze every penny penny out of the manufacturing process out of the delivery of the logistics right out of the sourcing of the commodities that go into it? pricing has just always been an afterthought for them. Right. And I think because of that, they’re just I went in and said that adoptions? Well, we’ve experienced incredibly high growth in this space. It’s just that they are still very early in the adoption cycle as an industry right. So for the folks that recognize the either the pain or the game to be had from this, the doctrine Muay Thai, it’s just most folks are still very siloed in their thinking, right. And, you know, the classic story I always share is I’ve had a client where obsessing about removing a penny of cost from a pallet of their good, completely aspirational, it makes tons of sense when you’re selling hundreds of millions of pallets a year, right. But they then turned around and let the sales rep discount up to $50 off the pallet of goods with no justification or rhyme or reason. And so there’s this interesting disconnect from like, you talk to a CFO like that Penny must have been phenomenal, but you turned around and let the sales rep drop the price by $30. You need both right? You need golf. We’re not saying forget the cost side, but it’s time to also be thinking about the growth side. And so I think that’s where Kindle I probably spend as much of my time evangelizing as anything else, right, and just helping people understand because a lot of times they’ll feel they’ll feel the symptoms of bad pricing, but they don’t connect it to the root cause that it’s a pricing issue, right. And so that’s where we find a lot of folks and engage is actually Kimberly come to us with comments like, our customers are telling us it’s taking too long to turn around quotes. Or there’s a term in this space called Christ exceptions, which, essentially, you know, corporate will set some very loose guide rails kinda like the example I gave all their sales rep from discount up to $30 off this pallet of goods, what they need to go below that, that creates what we call the dreaded price exception, where now that deal has to pass approval of a various number of stakeholders that are typically highly compensated, tasked with driving the business are now basically rubber stamping deals that come across their desk. And that becomes a huge organizational drag with really no better outcome. Right. So those are the kind of symptoms that people have been increasingly coming to us with, what we help them do is walk that back to say, if you could have given a better price guidance from the beginning, not only will you make more money, you’ll close deals faster, but you remove a lot of that unnecessary process, right. Versus sometimes folks have the misperception of well, we just need to speed up the review process like well, you can only speed it up when most deals are going through the review process. Right.

Alexander Ferguson 11:05
So what does it look like in play? Like if someone starts to use this? How does it work? What’s that that interaction look like?

Jared Wiesel 11:13
Yeah, absolutely. So, you know, kind of think about this in a couple of different dimensions. So first and foremost, you know, being a pricing analytic shop, we got to get the math, right, we got to get the price. Right, right. And really, in the simplest terms, this is about helping folks D average their pricing, right. So the common starting point for most of these folks is they set some loose guardrails, they set some loose profit threshold or desired pricing, but it’s one size fits all. And I’m sure you can appreciate in this type of space, well, a customer that’s bringing $10 million worth of orders to you should not get the same price as a transactional buyer that’s going to cherry pick you at once a year for a part. And of course, there’s all kinds of shades of grey in between, right? Then you start to layer in things like Well, there’s different products, there’s different markets, there’s different competitors, there’s different strategies. So first, we say how do we statistically basically D average that guidance? How do we find the attributes of every one of those deals that will signal a different willingness to pay? And then how do we give better guidance? And really, it’s all about how do we calibrate the guidance around where they’ve had success in the market? So this is not aspirational corporate pricing algorithms we’ve built over the last five plus years, it’s all about how do we calibrate where you’ve had success in the market? And then how do we continually recalibrate that logic? So you keep striking the right balance of winning but winning profitably and winning in the places you want to be winning? And so that’s kind of the analytics at the highest level?

Alexander Ferguson 12:38
It’s so it’s anything someone probably say could do this, they probably are doing this, they’re sitting there and themselves having to look oh, here’s the deal. As you said, it gets it takes forever to come back. Because someone has to sit there and look, well, $10 million, well, I guess that would be good. So someone can make these decisions, but it slows everything down. What you’re saying is, throughout the algorithms that you guys have researched and built, along with the historical data that the company should already have, that should be able to be automated,

Jared Wiesel 13:11
that it should be able to automate the price guidance, right. And I stress guidance, right. So there’s a reason I stress that is, in today’s environment, in this space, most transactions are still done human to human, right, I think there’s this seismic sea change coming where this space is eventually going to go digital like many others, which creates a whole nother leg up of opportunity for these analytics. But even today, it’s just about informing a better starting point, or giving the rep some confidence, removing the time that would have spent researching with the right prices, and then removing the time everyone’s gonna debate it right. And so, you know, the classic example like a customer for a $500 deal, it used to have to go through eight rounds of approval. And these folks have day jobs, these aren’t approvals of like people that are dedicated to this, like this is going to a p&l owner of the category, it’s going to an SVP of sales, it took two weeks to two weeks to get back to a customer to tell them whether we could give an extra 5% discount. Now the answer isn’t to just automate all those as a Yes, right. We’re not in the business of rubber stamping things. But we typically find that we can remove up to three quarters of all those exceptions by getting the right price guidance out of the gate. Because again, every customer is got a different willingness to pay. And if we can hone in on that spot out of the gate, that removes it right then you just you manage by exception.

Alexander Ferguson 14:28
So it’s almost like there’s two parts that come to my mind. You’re not saying that suddenly, in industries like manufacturing distribution that’s going to be like the airline’s which is all automated. They don’t touch anything. No one actually thinks about it. Maybe one day, but we’re not there yet. But at the same time, it’s those type of decisions when it comes to their desk, I can imagine they’re feeling like Gosh, don’t don’t they already know that. Like, what, what something like this should be it should be yes or no. Because of these data. are they feeling that or are they wanting to still have that control? Or like they want to say just figure this out, you should already know what’s in my head.

Jared Wiesel 15:01
It’s a very astute question. I think it’s a little bit of both, right. So I think the good and bad is everyone has their perception of what the price should be. The bad part about that is, is it’s all anchored on a completely different rhyme or reason some of them valid, some of them are not right. And we go through this class, we call it a scattershot diagram, where we will actually take like a top selling skew, and we will plot out in just a two by two chart, what’s the price paid relative to the revenue of the customer. So give us your top selling skew, it will look completely dispersed with no rhyme or reason, we typically see price will vary three, four or 500%, for that skew, with no justification whatsoever. And again, some of that is the blessing because this is not yet in a digital world. It’s a very opaque market. So they’ve been able to get away with it. But that’s going to start to change. At the very least people can appreciate that, if I don’t set the price, right, one of two things can happen. If I’m going too low, I’m unnecessarily giving a profit. If I go too high, I actually may risk losing the deal. And I probably would have been okay, gone a little bit lower. But how do I know that the permutations right, like the typical customer, we have selling 10s of 1000s of different products to hundreds of 1000s of customers across many different channels. And so, you know, you might have a sense of kind of an average price. But when you start to break it down by all those different intricate dimensions, it’s really harder to do anything other than reference your past deal, right? Well, I wanted at this rate to this person, and you forget that that was a million dollar deal. And this one’s a $10,000 deal. Or when you become the the product line manager who’s got their day job. And every day, they wake up to 300 approvals that they need to make, they’re just going to do something simple, like is it above my gross margin threshold, right? And not really think about it. And so none of those are inherently bad. But that’s where the science comes in is, it’s a game of inches, right? And we just believe that we can be much more fine tuned without slowing down the process at all, to do two things, right, speed it up, but make more money and you make more money by being more consistent, right? Just be more rational. So you’re not debating it, customers are getting what they expect. It’s more predictable financially.

Alexander Ferguson 17:14
It’s standardizing the decision set of why do we Why would we price it this way, you’re across the board, you made the point that each person will have a different perspective of Oh, because of what I know, but they have no clarity of whatever else that has been doing or thinking. And so it’s just really standardizing everything across the board in the organization.

Jared Wiesel 17:32
Exactly, exactly. So easier said than done, right. But that’s where we’ve just invested in an incredible amount. And again, you know, kudos to the, to the company’s legacy we had, we’re already standing on the shoulders of giants, but we had to adopt them while the science as well to just fit the nuances of this space. One of it being it’s a negotiation, so we’re not trying to optimize to 10 decimal level point precision, because at the end of the day, we still need to give the rep. There’s an adoption element here, that’s critical, right? Because we’re working a lot of times with sales reps that have been selling in the space for so long to your point that they come in with a perception. And so if we, the bar we have to hit is basically every deal, we have to re earn our stripes as adding value to the deal, right? Because the one time we don’t they say See, I knew that the price should have been $8 per widget instead of nine. Right? So it’s continue to hone the science at the right level, it’s being transparent. You know, we talked a lot about the math, but we spend a lot of time early on with our customers, walking them through the paces, we’ve built analytics. Now mathematically, then once we have the data in a good spot, we actually just timed this for one of our large industrial products companies, we can we can price more than 2000 products for them across a couple 100 companies in less than 10 minutes. Which is billions of dollars of of you know, revenue flow through which is amazing from a computing power and scale. And that is done at the individual, every deal. Every line item, every customer has any price. But there’s no organization that’s living in the world of an Excel update and Christ once a year that can make that transformational leap in 10 minutes, right. And so we also go through a very methodical process upfront going back to evangelizing in this space. This isn’t a muscle these organizations already have. So we also have a very purposeful delivery process where we’re very transparent we get there by and we bring them along the journey so that by the time the guidance is out there, everybody understands where it’s coming from what’s influencing it and what’s in it for them is the biggest thing right so now it’s about Hey mister missus sales rep. If you can price within this guidance, which you said you’ve already confirmed, calibrated to your market and you understand how it’s been collected. Your deal is now instantaneously approved. There is no more eight steps in following up and waiting for emails and oh, Bob’s out of the office this week. Right now my deal is going to be delayed another another month and as on a call with the customer in Asia and they’re waiting for the sales approval. From a guy in the US, and it’s like, I’m just trying to close a 70 $500 deal, and I have to wait for the timezone to catch up to get approval. You know, it’s just like, again, maybe that should happen for a really big deal, right? We’re not in that spirit of automating everything in this space. But you there’s just a world of efficiency gain to be had

Alexander Ferguson 20:21
this speed of being able to price everything so fast. That’s the power of technology, but the adoption across the board right now we have the pricing, but now let everyone start using it and believe in it and trust it and want to use it. That’s that’s a whole nother piece. That’s why I think the power of or the existence of SaaS Software as a Service, not just here’s a piece of software, and then nobody uses it. I think that you were mentioned that earlier. It’s like, that’s one other piece. I feel like that’s where you guys have started to really hone in on. All right, here’s not just the software and in solution, the technology, but we’ll help you get it in use with the team. Is that correct?

Jared Wiesel 21:03
Yeah, absolutely. So you know, there’s a, there’s a couple of key points, that’s upfront, right? When we’re implementing the capability, we spent an incredible amount of time you know, walking in their shoes, we want to understand what they’re going through, we want to understand that we get that to some degree, everybody’s a special snowflake, right? Or they at least want to appreciate the fact that they are. So we want to understand those nuances. Because, again, we got our rear and our stripes on every deal, right? So we want to understand what would make you decide to price differently, to understand their systems where their starting point is. And so that’s a big piece of that empathy and training.

Alexander Ferguson 21:36
How long does it typically take, by the way that that that onboarding process,

Jared Wiesel 21:40
so we’re generally a couple of months. It varies by customer. And again, that’s a purely adoption thing, right? And it’s a it’s an investment on both our sides. So just make sure that the impact sticks, right? Because again, once we have the data, we could give you the answer in 10 minutes, but that just doesn’t do you a lot of good. When we now push that through a CRM to 1000s of sales reps and say today, we now have a better mousetrap for you, right? We promise you’ll we’ll win more deals and you’ll make more commission, right. So it’s a very purposeful process to get involved. And even though we’re very confident in math, we want them to be believers in it. You know, we were going through a training the other day with a customer, we’re rolling this out to, you know, their sales force in North America. And this is not aspirational pricing. This is not the CFO told us we have to make at least 50 points of margin, get out there come out and go team, right. We walk them through very purposely the math that we’ve developed, good is specifically designed to calibrate on the sweet spot where them in their peers have had the most success, winning business, right, and we start there. And so this should help them right, which isn’t probably the the term that they usually believe, right? Because I’m sure you get a lot of that and you’re from corporate, I’m here to help type of thing. But we want the stress test, we welcome that we want sales reps to be pushing back, because it’s only going to make it that much better than when we get it out there. We’re very focused on you know, these are the metrics that should give you confidence in this but it’s not a one time said forget it. Right, which is the other power of the SAS is that even if the math is right, and even if the sales rep is doing anything they can make a lot of our customers right now are going through incredible inflation challenges, right? lumber, pay paper call, you know, metal, you name it, right? They’re going through really interesting dichotomies in their business where there’s certain product lines that are sold out and have lead times of months. And the other half of their business is just sitting there waiting for offices to open up, right? And so you kind of got everything in between. and you need to make sure that the math is calibrating for all of that. And that’s something

Alexander Ferguson 23:37
that you guys do. Is that something that you guys do based on knowing the the current trends you’re able to adjust the the album’s that’s not to say, Alright, this is the algorithm that you should be accurate all the time, but to today’s market?

Jared Wiesel 23:50
Yeah. So there’s a couple of different dimensions to that. So then, so the core logic behind the algorithm, which we’ve invested a incredible amount of incredibly talented team, a team of PhDs as well as business strategies and data engineers around that that have been working with the customers are at the forefront of this is how do we leverage the the best of machine learning and artificial intelligence to auto calibrate this guidance, right. And so the notion is we put the guidance here, if we start winning more deals here, we should tighten the guidance and raise it. It’s almost like a continued series of tests and learn because again, it’s an opaque market. It’s not like a hotel where I can go out and understand on the web, all my other competitors price there isn’t that available, which gives you some leeway. But we also that means there is really no idea of where that sweet spot is to drive the right KPIs and stuff. The model you can calibrate and set the guardrails. So you feel comfortable around profit threshold when rates volume realization, we can tune those KPIs and then let the math auto calibrate over time. The power of that is we often find for most of the products, he actually could get away with a little bit of higher price because naturally it’s not picking on but naturally Salesforce. sales reps are going to choose the path of least resistance right and default a little bit lower. Because the flipside is, you might Up to a quarter of your products actually, were going to end up a year later with lower prices. But the difference is it’s only where mathematically that’s making it up, right? You’re putting more dollars in the bank and you’re putting more wins on the board versus just the hypothetical. Geez, if I could lower my price on this, I would win more. Right. So it’s a really neat functionality that what we found is it continues to folks get a pop out of the gate with a lot of SAS investment, and then it kind of tapers off right with that auto calibration allows us to do is be continue to drive sustainable outcomes. But that’s just the math right? The second piece, then is the other big differentiator for us because we get it in this space. This is not a plug the widget and and be done. We offer different tiers of service where that same cross functional group can do everything from just make sure the math is continued calibrate to your business, all the way up to what we call team boosts, which is an added service where we can actually be an extension of your team. So I have some clients where you know, they’re paying for full or part time staff members to constantly be working with the business, to test strategies to evolve for more forward looking things that they maybe don’t have data for today. But that we want to get out ahead of right. And that can be everything from we get calls all the time of you know, lead times are looking tough next month, let’s go ahead and adjust pricing now. Because they’re starting to build that muscle of like, well, that’s a better way to calibrate demand than just tell people we don’t have, let’s start only selling the precious few, we have two people that are willing to pay more, right as an example, or men inflation next month is going to be really tough. And we need to adjust things up or down. So there’s there’s still some strategy to it that we help them think through and then execute as well.

Alexander Ferguson 26:35
What can you share on your your roadmap, what’s coming up what you’re excited about what you’re either have launched, or we’ll be launching soon?

Jared Wiesel 26:42
Absolutely. So you know that there’s a couple of dimensions to this. So in the capabilities we’ve already launched, and a lot of where we’re focusing today is we’re preparing for that next wave, which is this space will eventually be more digital. It’s a long way until it’s going to be you know, what we all experienced as consumers on Amazon, etc. But folks are starting to dip their toe in the water, whether it’s their own portal for just reorders for existing customers, or some more aggregator sites. And so a lot of what we’re working on now to adapt our existing capability science to how do we operate that in a world where there is no human interaction, right, and there’s a couple of different dimensions to that one, you got to get the price even more, right, because all else equal, there usually isn’t going to be that opportunity to negotiate, right, at least on smaller transactional deals. And so we’re working through a lot of early use cases with that with our customers. The second fascinating thing is, you know, we’re pricing but we’re also a random growth company, right. And one of the other pieces we just organically started to develop with some of our leading customers in the spaces. You think about the transformation from on the sales route selling to you, I’ve developed a personal relationship, I understand your business, if I’m doing my job, I’m not just taking your order, I’m proactively recommending products, right? what we typically find in this space is for our average customer, you know, for our customers, their customer probably needs four or five or six or seven other products, but they only sell them one, right. And so another big breakthrough piece for us that we recently launched, and we’re starting to see some really strong adoption is around product recommendation, which is very different in this space, because it’s like Amazon for your b2b business. But it’s more nuanced than that, right? Because there’s application fits, right. It’s not just Hey, you can offer up anything, right? Just because I bought a red t shirt now I should suddenly buy a pencil, right? Like that won’t make sense in a b2b world away, and maybe it doesn’t a consumer. And so that to me, is really going to be the ying and yang with like, now, it’s not just about getting the right price and trusting that the sales rep is offered the right product, the next frontier, we got to offer the right product at the right price, right. And so it’s that intersect, that’s had our team incredibly jazzed. And we’ve had some great early wins on it. But candidly, that’s also where we just need the technology. And we want to be ready right at the forefront. But we need the technology and the folks that catch up enough to to be willing to transact more in that type of world.

Alexander Ferguson 28:59
And that one, that one two punch that makes it possible. So what I’m fascinated by is this future that you paint in the b2b world that it could become more like the consumer world that so a lot more transactions are going to happen digitally. And I’m wondering if that actually could concern anyone like, like, the really like, especially manufacturing distribution? Like what everything would go digital? I wouldn’t we wouldn’t have sales people doing these interactions, like, how is that going to change everything? Or not?

Jared Wiesel 29:30
I think it’ll change everything and not change much at all right? He’s kind of the classic answer, right? I think the demand is already there, right? I mean, all of us are consumers. We’ve just come to even pre pandemic, we’ve come to appreciate the convenience of picking up my phone and reordering something right. And, yeah, there’s an opportunity to talk to an expert if I need it. But for my day to day needs, I don’t need to talk to an expert as I’m ordering my kids cereal right to be delivered or what have you. And so I think in that world, that’s more transactions. More commoditized it really shouldn’t change much, right? It’s a convenience play. And I think the first step was to work with a lot of our customers, you don’t have to force everybody there. But you got to start making that channel available, because customers are more and more going to want to self select into that, but you can give them out. And that’s what I mean by it’s not going to change a lot overnight. Like this isn’t like every sales person’s gonna go away tomorrow kind of thing, right? I think on the big accounts, right, there is still absolutely a role for the sales rep as far into the future as I can see, but the pressure is going to be more on the consultation piece of that, right? I’m not just here to take your order, I’m here to help you solve your problem, right? So I’m selling you automotive parts into a brake repair shop, or I’m selling you electrical components into a building, you know, construction project, or I’m selling your paper products into your office. Like, it’s not just Hey, Jim, I’m here to I’m here to take your order. But let me talk through what your needs are, how can we best package it together? But I think it’s going there, right, whether folks want to want to kind of come along for the ride, but I think the winners are gonna have to get there faster. And you know, I think there will be savings from a resource perspective, but it’s not just the Hey, let’s swap out sales reps for a URL. Right?

Alexander Ferguson 31:12
Right. for you guys. Because going back to the product for a moment is your your product price Plus, I think is what it’s called. And then also the product one is that product product class. Yep. Very simple. Dave’s I like it, keep it simple price plus product Plus, the the, the best customer for you that that makes sense to be able to what what do they look like? Can you describe them? So those are listeners on? They might be like, Oh, this sounds really good. But they actually aren’t a good fit for you or and there’s others be like, just help me understand who those are?

Jared Wiesel 31:46
Yeah, I think it’s a great question. I appreciate you asking this, there’s a couple of buckets right from from a company characteristic perspective, the three things we’re typically looking for is a complex catalog of products or services that you’re selling, right? selling it through multiple channels, right, which really, basically, today means you’re almost competing with yourself, which has become really fascinating more than anybody else, right, I can go buy your product in a retail shelf, or through a distributor or through your sales rep. And then you know, release a significant piece of that product being tied to underlying commodity costs, right? It’s really the intersection of those three, because where the math again, this is kind of a game of engine, we’re just looking to stack the deck. Right? That’s really what we’re looking to do for you. So we need a large number of observations. And we need a business where the complexity is just pushed beyond that Excel within a couple of people could handle on to pacement. Right. So that’s kind of the characteristics that we look to, as a result, there’s a handful of sub sectors that are really focused on from a pain point perspective. I mentioned a few earlier on, folks that are you starting to hear things like it’s taken us a really long time to try to reach our customers are saying we’re too slow, right is one, you know, huge alarm bell kind of going off. That’s a pricing problem, it’s probably not you need even more CRM software. Right. You know, the other one we hear a lot is, geez, you know, our either win rate is too high, or it’s too low, right? We’re just not winning as much as we used to, we can figure it out working versus that we’re winning a lot from my margins kind of kind of eroding. Right. Another one is this whole price exceptions thing, right is probably the one that’s the most emotionally attached. When I get on a call with somebody, I’m just fed up on what we do. And I mention the price exceptions, you know, you can quickly tell you’re like, no, it’s not for us, or they get really close to the screen. like can I tell you how many I wake up to every morning, right? It’s it’s like, finally, it’s like this cathartic experience, right? We have 25,000 of these that are the year that we have to process. Right. And so if you have price exceptions, that is not a workflow automation problems, it’s a pricing problem. I think you’re really the, the main pieces.

Alexander Ferguson 33:50
Well, thank you so much for walking us through both the history of of the company and the product and, and also a little bit of the future of what we could expect for those that want to learn more, head over to revenueanalytics.com. And you’ll be able to kind of dig in, you can even take a look at the book that the book that they wrote on this, and book a demo to explore more. Thank you so much, Jeff, for joining us. It’s good to have you on.

Jared Wiesel 34:12
My pleasure, Alex really appreciate the opportunity.

Alexander Ferguson 34:14
So I will see you all on the next episode of UpTech Report. Have you seen a company using AI machine learning or other technology to transform the way we live work and do business? Go to UpTech report.com and let us know

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