Using AI in Price Setting (Without Handing Over Your Judgment)

In this episode of The pricing Lady Podcast, we talk about using AI in setting prices. Doing so without handing over your judgment. Sit back, relax, and enjoy the episode. Hello and welcome to this episode of The pricing Lady Podcast. We're smart business owners, price with purpose and profit with clarity. I'm Janene your hostess. Now this is a topic that I have been bringing into what I do and how I work with clients for about a year and a half now, and I finally feel like I'm ready to have the conversation with you about how you can be using AI more effectively when it comes to setting prices. So why are we talking about this now and today? So first of all, AI is very accessible. Nearly everyone, not just big companies, has access to it and people are trying to figure out how to use it and when to use it, and what to do in the right way. And that has changed the starting point of a lot of pricing work, but oftentimes people go about doing it in a way that isn't going to help them in the long run. And that's why we're having this conversation today. I'd it should not replace who makes the decisions. And that's really important. We don't want to replace your judgment and you needing to make, it doesn't replace you needing to make that decision, but it does give you more information to work with, but we have to be careful about how we go about doing it. What this episode is about and not about. I think that's really important. I'm not gonna be talking about advanced optimization, dynamic pricing how to let AI to decide prices for you, any shortcuts or even prompts, in this episode, what we're going to be taking a look at is how AI can support your pricing thinking, can support that thought process. Where it can create false confidence and how to use it without outsourcing your own decision making. because ultimately, one of the most important things in pricing in your own business is being able to make pricing decisions. That's a skill that you want to build and develop, and so that when you get asked questions or when things come up in conversation. You have a good, solid foundation upon which to respond in that situation. If you outsource all that decision making, then it's harder for you to be able to have those conversations and to make those decisions going forward when AI isn't readily available to you or when it would be awkward to to consult ai, right? So we need to keep you in the driver's seat when it comes to decision making. Where does AI go wrong? We want to look at a couple of different areas here. because there's really two extremes. First is using AI as the decision maker. Treating the output as truthful. Which we all know, that there are issues with the truth that we get, kind of putting that in air quotes, you can't see me, you know the information that you get out, you have to be able to validate it. Skipping that validation, taking this truth, and then skipping the validation. And also confusing speed, the speed that it gives you with clarity and certainty. So using AI as a decision maker makes these things much more risky for you. Now refusing to use AI at all, in my opinion, is also another problem. It is a tool that you have at your disposal. It will do some things better with the caveat that you still have to validate it. It'll speed things up. It keeps you slow paced. It'll take you longer to do some things. It forces you to only rely on intuition. Where it's good to use intuition and some fact-based information or validated information to gather in your price setting. And you may miss early signals of things because you're not using the most readily available information that is out there. Refusing it to use AI at all in your price setting is just as risky as allowing it to be the sole decision maker when it comes to setting your prices. Both are judgment problems and not technology problems. It's about using it in the best way possible. You are probably asking yourself at this point, all right, Janene, I get it. I should use it, but where can it help me the most at this stage? That's a great question. My experience over the last year and where I've seen it help my clients the most is in that first round exploration. What I call the data gathering stage, where you're pulling in information from different resources. For example, and exploring different customer types or different aspects of your market. Earlier this year, I had a client who was selling a product, into food and gastronomy, into bars and restaurants and kiosks and things like that. And they didn't understand the margin levels that might be expected in those types of clients. Today, you can go into a i, you can ask that question quickly, and then you can go out and validate that information in the market. Right. Scanning market dynamics and competitors is another area. Pressure testing assumptions about value, net value or willingness to pay or even understanding value. You may have one understanding of value. AI can help you validate some of that, but also explore it further exploring different packaging options or commun ways to communicate your prices. And also spotting misalignment across an offer or across a portfolio of offers. These are areas where I have developed tools to help my client to use AI in their pricing in a more effective way. AI is very useful for exploration, not for making the final decisions. Certainly you can ask it its opinion, but you would want to know why it's coming up with that opinion, why it's saying that, and then validate it for yourself. The mindset that makes AI useful in pricing is really around these four core principles. First of all, AI output does not equal the truth. In any context, not just pricing, but we have to understand that AI is only going to give us what information it has, it's gonna extrapolate from what it has if it's not clear, which means that AI output is definitely not going to equal the truth. So it's up to us to use that information in the right way and not accept it as the truth. Exploration does not equal decision. That's the second core principle. Using it for exploration does not mean letting go of the decision making. It doesn't mean that you should. Yeah. Or that you are now, speed does not necessarily equal confidence. Just because you have a lot of information now, you have a lot more information more quickly than you did in the past, that's for sure. Right? Doesn't necessarily mean, you're going to feel more confident about it unless you know how to use that information the right way. So for some people who choose not to use it, it might feel like information overload is one of the reasons not to use it. So yes, you'll get a lot more information, but you can then narrow that information down to what's useful and then go out and validate that. But having that information faster is not necessarily going to build your confidence about how you use that information. And the last core principle is a validation is non-negotiable. And this, I'm a big stickler for this. I am always telling my clients, use ai, use it wisely and validate the information you're getting. Before when you wanted to understand your customers, you really needed to go out and talk to them in the first step. Now you can do a little exploration upfront using something like ai. And then AI can help you understand, okay, what do I need to validate in the market and how can I best go about doing that in these interviews, let's say. And it can help you with that step as well. So validation is so important in this whole process of you using ai. You can't just take it at what it's, you know, at what it's telling you. You have to go out and then make sure that that information aligns with what you're actually doing in the market and what you're actually hearing and seeing from people. All of this is very strongly tied to the pricing and value anchors in your business. AI can help surface possibilities or opportunities for you that you've never seen. I've also experienced that as I've been playing around with it, if you will, in my own business. But the anchors come from the decisions that you ultimately stand behind. Yes, it can give you ideas, it can show you opportunities, but ultimately when you make a decision about something based on a foundation of information that you believe represents the market and represents the situation and what you need in your business and what your clients need, that is where you come up with decisions and prices that you feel, "yeah, I can stand behind this. I know why this is the price and it's the right price." Fairness also still needs to be assessed by human. Yeah, by a human being. So is it fair? Sure, you can ask ai, but ultimately it's that personal relationship with an individual that's going to determine the fairness in. The price that you set or the decisions that you make. All of this again, ties back into some solid anchors. I don't know if you remember the last episode we were talking about value anchors. Again, that's all tied in here and you want to make sure that you have the right value anchors, the right pricing anchors for your business, and ultimately you are the one who determines what those are. Pricing anchors don't come from tools they come from your judgment ultimately. Here are a few guard rails to help you use AI more wisely. Yeah. First of all, treat outputs as directional, not as definitive. We've touched on this a lightly here, but this is information gathering. It's not the final story. It's not the final answer. You have to bring all that information together to see the big picture. Sanity check against real customers. And context. So again, that's hints towards this validation. So you need to go out there, you still need to talk to customers, in my opinion. Not just my opinion, but this is my experience that, even using AI in your business still, the most important thing any business owner will ever do, is talking with customers and understanding what their needs are, what they value, how they make buying decisions, all of these things. It's good to gather information on that from ai, but then you want to test it soundly, check it against real customers and content. Don't outsource those pricing decisions. Make sure that you are using that information to support you in making decision as opposed to making it for you. And use AI to ask better questions, not necessarily just to answer the questions for you. So you, like I said before, you can use the outputs from a AI where you're exploring your customers to then have it help you figure out what questions to ask customers in a robust way throughout that whole process, not just getting that first information. I'd like to close this up by reinforcing a few key messages. The first is AI lowers the cost of starting your pricing work. Before in order to get market information and customer information is a very laborious process. Sometimes a very expensive one as well. And nowadays you can quickly go onto AI and start doing some research, getting some first information. It lowers the cost and it lowers the time aspect of this. It does not, however, reduce the responsibility for deciding, even deciding well making good business decisions. That is still ultimately your responsibility. And pricing still needs anchors you believe in. You still need to anchor it in things that are relevant to you and your customers so that you can make decisions and have prices that have a solid foundation and that you ultimately believe in. I'd like to leave you with one last question today, and that is the following. Are you using AI to think more clearly when it comes to your price setting or are you using it to avoid making decisions? I leave you with that final thought to reflect on. I hope you enjoyed this episode. I've enjoyed preparing it for you. I wish you a great day and as always, enjoy pricing.