Brooks Hamilton is a principal at Hamilton AI Strategy Advisors, specializing in strategy consulting, product management, program management, cross-functional team leadership, and go-to-market strategy.
In this episode, Brooks discusses AI Pricing capabilities and upcoming opportunities that benefit pricing optimization, revenue and data management, and AI’s ability to enhance productivity in various areas of your business.
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Why you have to check out today’s podcast:
- Learn the basics of getting started with AI, especially if you are new to using it
- Find out how AI can help pricing people in price optimization, management revenue, and data management
- Learn about AI advancements in email response features, the challenges of using it, and the implications of not implementing it
“I would really look at the opportunity in front of them to delight their customers and delight their employees by simplifying the Excel file management problem that we all wrestle with.”
– Brooks Hamilton
Topics Covered:
01:30 – What you can expect from this conversation
02:15 – How is AI pricing helping businesses with no big data sets?
05:32 – The ease of consolidation of customers’ names with AI Pricing
07:46 – How much is there to learn with AI pricing?
09:31 – Getting started with AI and navigating it
12:13 – Addressing the issue of AI failing to generate your unique voice [ in the case of writing pricing blogs]
15:06 – Could AI potentially offer a precise solution for the problem presented? [in reference to Mark’s case]
16:53 – Going deeper into the analogy that Mark provided regarding the AI’s capability to provide a solution
18:55 – AI’s capability advancement in terms of pricing
20:43 – Email responses advancement where AI is concerned
22:17 – Two ways to find out your customers’ size in terms of revenue even with limited data
24:16 – Challenges and questions with regards to AI pricing
25:46 – What does Brooks’ company, Hamilton AI Strategy Advisors do?
27:07 – Some more challenges in addition to what Mark already mentioned and what could be the implications
27:37 – Brook’s advice on how organizations should look at and think about AI
38:33 – Brook’s best pricing advice
Key Takeaways:
“In the realm of pricing, certainly things like price optimization, and then more broadly revenue management, especially in a B2B realm, where do I go find these opportunities, have really been the domain of sophisticated analytical and optimization packages.” – Brooks Hamilton
“Right now I think that the main opportunities are going to be in data management, data cleanup, and then just trying to make your life as a corporate citizen or somebody who interacts with corporate citizens easier in terms of getting faster and more complete on your email responses. It can be that simple to try to just get more productive.” – Brooks Hamilton
“It’s one that I would advise them [companies] to not take off looking at it and saying, hey, this is just going to be crypto crap all over again. Because there are some real differences. And as McKinsey has pointed out, if you do not begin this journey, it is going to be very challenging later to catch up because unlike other tech revolutions, the pace of change of this one is rapid.” – Brooks Hamilton
Resources/People Mentioned:
- OpenAI: https://openai.com
- Outlook: https://www.microsoft.com/en/microsoft-365/outlook/email-and-calendar-software-microsoft-outlook
- McKinsey: https://www.mckinsey.com/
Connect with Brooks Hamilton:
- Email: [email protected]
- LinkedIn: https://www.linkedin.com/in/brooks-hamilton-austin/
Connect with Mark Stiving:
- LinkedIn: https://www.linkedin.com/in/stiving/
- Email: [email protected]
Full Interview Transcript
(Note: This transcript was created with an AI transcription service. Please forgive any transcription or grammatical errors. We probably sounded better in real life.)
Brooks Hamilton
I would really look at the opportunity in front of them to delight their customers and delight their employees by simplifying the Excel file management problem that we all wrestle with.
[Intro]
Mark Stiving
Welcome to Impact Pricing, the podcast where we discuss pricing, value, and the intelligent relationship between them. I’m Mark Stiving. Our guest today is Brooks Hamilton. Here are three things you want to know about Brooks before we start. He launched Hamilton AI Strategy Advisors about five months ago, but he was at Zilliant for 17 years, ending his career there as VP of Services and interested and focused on AI. In fact, his longtime passion has been reading about AI. Welcome, Brooks.
Brooks Hamilton
Yeah, thanks, Mark.
Mark Stiving
Okay. You were on earlier. We got the, how did you get into pricing? So let’s not do that. But let’s talk about AI since that’s really what we’re here for. And can I just say everybody and their brother is talking about AI? So, what are we going to say today that’s not going to bore everybody in the world?
Brooks Hamilton
Yeah. So we won’t talk about today’s regurgitating headlines. I think everybody’s been totally inundated with what a large language model is and how it works. Like not going to do that.
Mark Stiving
Excellent. Glad to hear that. Let’s see if we can make this applicable to pricing people. So let me start with this question. When I think about AI and pricing, the first thing that comes to my mind is companies that have huge data sets. So it’s typically B2C companies that are really large. They have tons of data. Wow, that makes a lot of sense. I can use AI to figure out what price I should charge for a Hertz rental car on Tuesday when it’s raining. Right? But what about the rest of us that don’t have these huge data sets? Does it have anything to do with our world?
Brooks Hamilton
Yeah. I think that there’s plenty that we can get out of it as pricing practitioners and as just general working individuals. So when I think about how I would go about using it as a price practitioner, there are a couple of things that really jump out. So, one, if I’m going to go about using these tools directly, I love the amount of analysis that people are doing on staff, but oftentimes my analysts are overloaded. Thankfully now with some of these tools, you can drop good information into them and then, just ask the model to go do the analysis. Hugely helpful. The other is, there’s some great tools coming out that are AI based, which will help I think both you and your teams, get out of the Excel hell that they are in and do so much of the grunt work that as we were pricing practitioners, I found these teams were engaging in.
Mark Stiving
Can you give us an easy example of one? So let me imagine what it might be, and then you say, oh, yeah, that works, or, no, here’s what it really is. let me throw in some historical data and you’re going to give me price elasticity and cross price elasticity of specific products without me having to do all the analytics.
Brooks Hamilton
Right. I think unfortunately right now, we don’t see models doing a lot of that. But I think one of the great examples or as we would talk to pricing teams, we would say, what are you spending your time on? And, how much of this time do you dedicate to strategy? And they would say, ah, like, two to 5%. And we’d say, all right, well, what are you doing the rest of the time? And they would say, well, we have a chunk of the team who is working on strategy, but then there’s a much larger number of people who are working on matching Excel files. We’re like, well, what do you mean? and a good example there would be, I get a national accounts bid in, and they would like me to bid in, a couple thousand parts.
And they’ve done a great job of including their part numbers and a somewhat correct version of the part description. Unfortunately, those don’t match mine at all, and I now need to go link in what the right part is, what my part number is, and then pull the pricing in for it. So it takes typically pretty experienced people to go do this. Because I’m kind of thinking about like, what do I know about this part? Okay, I got some information, I can link them together. There’s not any ETL or go find replacements that’s going to help you on this. The meanings are the same. So the semantics are the same, and this is something that AI can help with now. It’s like the meaning of one thing can get matched with another.
Mark Stiving
Okay. Maybe 15 years ago, we were doing a huge pricing project at a company I was working with. And before we could do the pricing project, we had to implement a master data management system, meaning we just had to get the customer names the same in different databases. And what you’re saying is that we could do that so much easier now with AI.
Brooks Hamilton
That’s right. So getting all of the names kind of consolidated and part numbers consolidated, part IDs consolidated. And also some great examples of, as you probably remember, like as you have new part introductions, you need to go find the right product category that it goes into. And you might have more than one hierarchy. So you might have one for marketing, one for pricing, one for sales, one for supply chain. You have to go try to update all of these. And inevitably what would happen is nothing gets a hundred percent updated. But luckily now as long as you have a a bit of a product description or even an image of a part, it’s much more likely that you can now have those things automatically tagged into the right hierarchies.
Mark Stiving
Okay. So you came out of the analyst world and you know a lot of analysts you work with, a lot of analysts. Would you say that this is solving the data cleanup problem that we always have to do before we even start analysis?
Brooks Hamilton
I think it’s kind of giving us the superpowers that we always wanted. We got ETL tools, the data transform tools, but unless things are exact matches there, it’s really hard to use them. so it usually took somebody who has had a lot of industry expertise to go through those matching exercises, and now there are models that have that expertise built in.
Mark Stiving
Wow. Okay. I’m going to change topics to what I actually said we were going to talk about now, if that’s okay. But I found those examples fascinating. And that actually is the problem I have with AI is that there are so many things you could possibly do with it, but I don’t know what they are. I don’t know if I should care if I should use them, when to use them. And so before we hit the record button, I actually said to you, I don’t like AI. And it’s not that I don’t think it’s good or useful, it’s that I don’t want to have to learn something else. And do I have to? So, pontificate on this, do I have to learn AI?
Brooks Hamilton
Not much. What we’re seeing now is a lot like when software was being introduced originally in the business landscape. So you have people who are really technically aware of it. You have business individuals who will say like, hey, can you write me a CRM program next week? And it’s just vastly different expectations of what’s going on and all of the user interfaces, like if we think about Windows three, one, it’s kind of terrible. it is better than DOS, but right now we’re kind of going through that DOS to Windows slash visual interface within the tool sets of AI. Luckily it’s moving quickly, but, we know that our first one that we typically became accustomed to using is ChatGPT, which is all text-based, to now we’re seeing purpose-built tools where they are plugins to excel or plugins to word where there’s not really a lot of interface that I need to go learn. It’s really just, how do I think about using this in my process?
Mark Stiving
Okay. So by the way, that was a great answer because it got me thinking about AI differently than I have in the past, right? And so I think of AI as this big, essentially computer that I have to interface with. And you’ve made it, not you personally, but ChatGPT has made the interface easier, but there are still a million different functions it can do. It’s kind of like saying, here’s Excel, go use it, it’s going to change your business. What am I supposed to do with it? And so I’m lost there. How do I know what I’m supposed to do with AI?
Brooks Hamilton
That’s a great question. When I speak with businesses about this, what I recommend is when you’re starting, look for two things, one is, almost a hundred percent there’s somebody in your organization who’s already using it. And the chances are those people are your entire marketing organization, whether you know it or not. and then the other is probably your software development group is leaning on it pretty heavily as well to make their roles easier. So I would first go look for the things where people are actually just already using it, and then try to get that to be consistent. So if you have, let’s say you have a marketing team of five, two people are using ChatGPT, the other three aren’t, well maybe talk about like, hey, how do we use this? For what assets are we going to use it? And what are the times where we really should not use it? And then if we are using it, how do we make sure we make good use of it? So, in terms of let’s have sophisticated prompts which reflect the voice of our business or even my voice as an individual. And then let’s make sure to use those things on a consistent basis.
One quick thing I’ll say, Mark, is it’d be great to go find things that are just a total pain right now, generally when you talk about, like, our prior example of going and matching supplier part numbers with your part numbers, I don’t know that anybody really goes home and like, man, I love matching those things. No, people don’t. It’s a pain. And so it’s like, go find the things that make your employees unhappy or make you unhappy and go see if there’s a tool for it.
Mark Stiving
Okay. So one of the things I struggle with, this is just my business for a second, right? One of the things I struggle with is writing blogs. Yeah. and oftentimes it’s coming up with ideas. Oftentimes it’s actually doing the writing. And I have in the past taken a blog that I’ve written and asked ChatGPT to rewrite it or make it better. And I never like what it gives me, right? It isn’t personal, it isn’t my voice. And so I’m not sure that it’s the right answer. And then I tried to get it to title a new book or title something, and you go through hundreds of examples that they come up with, different suggested titles, and it’s like, no, no, no, no. And eventually you get to something that works. So it feels like it’s great at generating ideas, but it didn’t give me the answer.
Brooks Hamilton
Yeah. I would probably compare a lot of how we interact with AI models to how we interact with another person. It’s not an oracle. It’s absolutely not. It has what’s equivalent to a high IQ, but if I were bouncing book titles all around with my publisher, and they came to me with 20, maybe I like two, and of the two, I’m probably going to change 50% of it. And I think that’s kind of a way in which to set the expectation level for working with these tools. So that’s one. Another idea is, what I really liked about what you told me was that you used it to generate some ideas. You used it to draft some things, or I think is, that’s a really good way to use it, because it takes refinement that we have as individuals, and we need to kind of combine those things in order to get to the best outcome.
So as part of, like my workflow, if I’m going to go work on a blog, what I’ll do is I’ll find five other people’s blogs that I think are great and just have the titles and a quick snippet. I’ll load that in and say, hey, I’m doing, I’d like to do something in this area. What might my audience, and I describe my audience, find helpful? Can you give me 10 ideas? It’ll give me 10. And then I’ll say, all right, great, take these four and then write something up. And then I’ll say, hey, I want you to now adopt being a professional writer who is deeply familiar with the realm of pricing or AI, and I would like for you to go back and critique that and show me how I could make this a little bit better. And then it’s usually from that spot where I’ve guided it along the way and also have a specific process where I actually come out with a better output of where I’m going to start my work.
Mark Stiving
Okay. So what’s going through my mind now is I often coach companies and we talk about the difference between a solution and a platform. So companies that have platforms are really hard to price, right? Because you just don’t know who’s going to use it and how much money it’s going to make them, or how it’s going to help them. Whereas companies that have solutions, it’s so much easier to say, okay, so what’s the value of someone solving this problem? And so pricing wise, that makes a lot of sense. When we’re talking about what you just described to me, I would say, okay, here’s this wide-open platform. You can go do anything you want. And what I really need is someone to say, Mark, here’s your solution. Here’s the problem you have. Go solve it this way. And so do we see people coming out doing that in the near future?
Brooks Hamilton
I think that’s what we see a lot of SIS starting with to say, well, let’s try to discover where the low hanging fruit is for these AI applications. And, but that’s all, because it’s extraordinarily new. We’re what, like 10 months into this journey? And if we can think about a common, big platform integration and an enterprise, if you’re 10 months into, name it, SAP, Salesforce, CRM, project 10 months, you’re still kind of in the early innings of transforming your organization to utilize that platform. And I think we’re kind of in that, in that same spot. But I would agree, like try to be very focused on what problem am I trying to solve with this, not the other way around of what problems can I go solve with this general purpose technology at this point? I would leave that either into the realm of the CTOs or into the realm of the technologists themselves.
Mark Stiving
Okay. I think that was a fabulous answer, and I am, this is me personally. I’m going to go start, do a little bit of research to figure out who has the best process for using AI to help write blogs or to help write content. Yeah. I’ll bet you that there’s a dozen people, if not a hundred people out there that have suggestions on how to go do this. And so that makes a lot of sense to just say, okay, here’s a problem. How would I go do this? And I guess in a lot of ways that’s like learning how to use a function in Excel you’ve never used before.
Brooks Hamilton
Yeah. That’s a great analogy. Yes, it is much like going to a menu ribbon on the ribbon you haven’t messed with a lot before. Like, oh, I’m going to look at the data ribbon now, and oh, I can actually do a transform suite. I think there’ll kind of be another ribbon on there, our menu up there, which is going to say something like, AI stuff, you know, make me a great chart or analyze this thing for me. And right now we’re also in that middle spot of, we see some fantastic capabilities coming out of OpenAI, which is much as we all know a very public organization, in terms of where the data is getting used. And we are seeing some of those capabilities starting to migrate over to the cloud providers like Azure, AWS, Google Cloud that respect our privacy and security concerns that larger organizations have in particular with sensitive customer data. But I think it will be really the beginning of next year, like, call it Q1, when we see some of those really neat capabilities. Like, we have in, I think what’s called like code interpreter or analyst now in OpenAI where I can drop an Excel file in there of 10,000 rows and say, hey, who are my most profitable customers? And this is how you should, and then just describe via text, like, this is how you should calculate margin. Go for it.
Mark Stiving
Okay. I personally have gotten value out of this conversation so far. Now let’s see if we can give value to all of the other pricing people who are paying attention. Is there something in the world of pricing that makes sense for pricing folks to be thinking about and looking at, besides the data, by the way, the data cleanup I thought was wonderful too. But, besides that piece, is there something else that pricing people should be looking at or thinking about?
Brooks Hamilton
So in the realm of pricing, certainly things like price optimization, and then more broadly revenue management, especially in a B2B realm, where do I go find these opportunities have really been the domain of sophisticated analytical and optimization packages. What I expect is we will see the democratization of those types of capabilities. So if you can talk to a model, kind of think of it like this and say, hey, what I’m looking for are areas where my pricing is not aligned, or can you help me find where I have inconsistencies with the size of the customer and the margin that I’m getting from them? Can you please surface those? So I think those will be some things that we will see coming out. but right now I think that, and by right now, I mean really until the end of this year, I think the main opportunities are going to be in data management, data cleanup, and then just trying to make your life as a corporate citizen or somebody who interacts with corporate citizens easier in terms of like get faster and more complete on your email responses. It can be that simple to try to just get more productive.
Mark Stiving
Okay. So the other day, I’ve done this a million times, I’ve sent emails that talked about an attachment that I never attached, and finally the other day my email said, you sure there’s no attachment. It’s like, dang, why hasn’t it been doing that forever?
Brooks Hamilton
Yeah.
Mark Stiving
I’m not sure AI gets credit for that, but boy, it was valuable and useful.
Brooks Hamilton
There’s a feature coming out in the next, major version of Outlook, which is, it will scan back through your email and determine the voice and the regular things that the voice that you use when you write and the types of comments that you make. And then it will suggest either full or part emails. So you just kind of outline, here’s my response, please put it in my typical text. I’ll write a three paragraph response with those, just quick, few liners.
Mark Stiving
Very nice.
Brooks Hamilton
Looked at that and I thought, well, man, it’s about darn time!
Mark Stiving
Better than the ones at the bottom of LinkedIn that said yes. Well, my pleasure.
Brooks Hamilton
Yeah. Whoah! That’s some time savings there.
Mark Stiving
I know. Okay, so you brought something up and I wanted to ask because this seems exciting to me as well. Yeah. So I could say, I want to know what’s the price I charge correlated with the size of the customer, not necessarily the deal size, but how much revenue that company makes, or what’s the size of the customer? And I haven’t, in my own databases, built a database that says, here’s the size of each customer, but because I’ve got AI and AI understands most of what’s going on outside in the world, I could ask that question without having to go build that data. Is that accurate?
Brooks Hamilton
Yeah. I mean, there are two really neat ways of using it. One is to say, instead of me having to rank my customers by size, go add it up, I can just provide the transaction file or point it to where the transaction file is and say, go look at this and determine who are my largest customers. I want you to sort them by the total amount of business they’ve done with me over the past 12 months. Now, the really neat part that would be a big pain for an analyst is you can also add on, as long as that model has internet access, is to say, hey, also, can you please go look at the revenue or the total employee counts for all of those companies and tell me where there’s some discrepancies in between the amount of business that they are doing with me and the amount that I would think that they could do with me. Because we know, like in those 12 month look backs, it could be that there’s a customer that looks like a small customer, but it’s just because I haven’t won much of their business. But the opportunity is giant. And as we all know, every salesperson will tell you the opportunity is giant on all opportunities, but this is a great way of getting some of that independent verification of their outlook.
Mark Stiving
Okay. So now we’re back to why I hate AI. There are just so many different things. It’s like, well, what should I be doing? And as a pricing person or as a solo practitioner, however you want to look at it, I’ve only got so many hours to spend in the day. How do I say, look, I want to spend time on AI, or I mean, I guess you gave me the answer earlier, what’s your big problem and can you get AI to help you solve that problem? But it just feels like there’s so many things out there that I’m going to be missing if I’m not watching this.
Brooks Hamilton
Yes. The real challenge I think that every function is grappling with right now is the question, what tools are available? Do those tools do what they say they do? And is it kosher to use those tools given my company’s security requirements and privacy requirements. Every single function in every single organization on the planet is wrestling with this at the moment. Hmm. So what I would recommend here is, I think there was something like 300, you can just kind of benchmark, there are about 10 new AI companies a day and that creates a very crowded space. So this is one where I would lean on industry, either publications or experts like yourself to identify where there are relevant tools, and then also look out for the standard write-ups by the big analysts of IDC Gartner and so on about what they see as relevant for these various functions.
Mark Stiving
Got it. So, I didn’t ask this in the pre-call and I’m really curious now that we’ve had this long conversation, what does your company do? What have you been doing the last five months?
Brooks Hamilton
Yeah, great question. One is I’ve been having a lot of fun. This has been a long time passion of mine for the last decade for both professional and personal reasons, in terms of just an interest in AI. And what I help with is to educate companies, especially their executive team, on what AI is and why is it different today? And the next portion of that is how do we go about starting, where do we start? Where are those typical low hanging fruit? And how do I begin this in the low risk manner rather than trying to make a big investment or build a big team when many portions of this ecosystem are, it’s not even a matter of settling out, it’s still just being initially structured. So we help them, we guide them through that process.
Mark Stiving
And so if I thought I had problems thinking about how AI works for pricing, imagine an executive who has to worry about pricing and owe every other function inside their company, how does AI help them there? And they’re going through the same thoughts I’m going through, and that is, look, how do we know when to focus, how much to focus, what to focus on? I mean, it is just so confusing.
Brooks Hamilton
Yeah. And there’s an additional challenge they have, which is how are their competitors likely to use it?
Mark Stiving
Yes. And so will they gain a competitive advantage or lose a competitive advantage because somebody’s moved first and done it well, or or they might gain a competitive advantage by saying, look, this is, and I’m going to steal your phrase from our pre-call, this is just blockchain all over again.
Brooks Hamilton
Right.
Mark Stiving
Everybody hypes about it and it doesn’t really mean anything.
Brooks Hamilton
Yeah. I think that’s one of the decisions these organizations are going to have to make, it’s one that I would advise them to not take of looking at it and saying, hey, this is just going to be crypto crap all over again. Because there are some, I think, real differences. And as McKenzie’s pointed out, if you do not begin this journey, it is going to be very challenging later to catch up because unlike other tech revolutions, the pace of change of this one is rapid.
Mark Stiving
Nice. So Brooks, we’re going to have to wrap this up. I’m going to ask the final question, and if you want to repeat something that we’ve already discussed, that’s okay with me. But, what is the one piece of advice you would give our listeners do you think could have a big impact on their pricing?
Brooks Hamilton
Yeah, I would really look at the opportunity in front of them to delight their customers and delight their employees by simplifying the Excel file management problem that we all wrestle with. And to delight your customer is, you get it, the files back to them, they’re complete and they’re correct, and they come back faster than they were necessarily expecting. And if we think about how do sometimes you increase your win rate, just be first.
Mark Stiving
Yep.
Brooks Hamilton
Then the second part is in terms of employees, wouldn’t you rather have your employees who you’ve invested all of this training and certification and years of getting to know your business, working on customer problems rather than working on technical problems, especially around things like matching. so there’s just a huge opportunity there to delight and be a total hero.
Mark Stiving
Yeah. Nice. Brooks, thanks so much for your time. This has been way better than I thought it would be. No offense.
Brooks Hamilton
If you’d like, we can really try.
Mark Stiving
Okay, good. Let’s do that. If anybody wants to contact you, how can they do that?
Brooks Hamilton
Yeah. Feel free to reach out to me at Hamilton AI Strategy Advisors, email, [email protected].
Mark Stiving
And I’m sure we will have that in the show notes as well so people can find it pretty easily. And to our listeners, thank you so much for your time. If you enjoyed this, would you please leave us a rating and a review? These are the currency upon which podcasts get rated, so please, please, please. We would love that. And finally, if you have any questions or comments about this podcast, as long as it’s not about AI or pricing in general, feel free to email me, [email protected]. Now, go make an impact!
