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In this episode of The pricing

Lady Podcast, we talk about

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using AI in setting prices.

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Doing so without handing

over your judgment.

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Sit back, relax, and enjoy the episode.

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Hello and welcome to this episode

of The pricing Lady Podcast.

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We're smart business owners, price

with purpose and profit with clarity.

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I'm Janene your hostess.

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Now this is a topic that I have been

bringing into what I do and how I work

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with clients for about a year and a half

now, and I finally feel like I'm ready

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to have the conversation with you about

how you can be using AI more effectively

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when it comes to setting prices.

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So why are we talking

about this now and today?

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So first of all, AI is very accessible.

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Nearly everyone, not just big companies,

has access to it and people are trying

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to figure out how to use it and when to

use it, and what to do in the right way.

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And that has changed the starting point

of a lot of pricing work, but oftentimes

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people go about doing it in a way that

isn't going to help them in the long run.

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And that's why we're having

this conversation today.

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I'd it should not replace

who makes the decisions.

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And that's really important.

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We don't want to replace your judgment

and you needing to make, it doesn't

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replace you needing to make that

decision, but it does give you more

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information to work with, but we have to

be careful about how we go about doing it.

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What this episode is about and not about.

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I think that's really important.

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I'm not gonna be talking about advanced

optimization, dynamic pricing how to let

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AI to decide prices for you, any shortcuts

or even prompts, in this episode, what

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we're going to be taking a look at is

how AI can support your pricing thinking,

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can support that thought process.

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Where it can create false

confidence and how to use it without

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outsourcing your own decision making.

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because ultimately, one of the

most important things in pricing

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in your own business is being

able to make pricing decisions.

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That's a skill that you want to

build and develop, and so that when

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you get asked questions or when

things come up in conversation.

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You have a good, solid foundation upon

which to respond in that situation.

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If you outsource all that decision making,

then it's harder for you to be able to

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have those conversations and to make

those decisions going forward when AI

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isn't readily available to you or when it

would be awkward to to consult ai, right?

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So we need to keep you in the driver's

seat when it comes to decision making.

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Where does AI go wrong?

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We want to look at a couple

of different areas here.

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because there's really two extremes.

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First is using AI as the decision maker.

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Treating the output as truthful.

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Which we all know, that there are issues

with the truth that we get, kind of

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putting that in air quotes, you can't see

me, you know the information that you get

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out, you have to be able to validate it.

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Skipping that validation, taking this

truth, and then skipping the validation.

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And also confusing speed, the speed that

it gives you with clarity and certainty.

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So using AI as a decision maker makes

these things much more risky for you.

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Now refusing to use AI at all, in

my opinion, is also another problem.

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It is a tool that you

have at your disposal.

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It will do some things better with the

caveat that you still have to validate it.

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It'll speed things up.

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It keeps you slow paced.

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It'll take you longer to do some things.

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It forces you to only rely on intuition.

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Where it's good to use intuition

and some fact-based information

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or validated information to

gather in your price setting.

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And you may miss early signals of things

because you're not using the most readily

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available information that is out there.

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Refusing it to use AI at all in your

price setting is just as risky as

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allowing it to be the sole decision maker

when it comes to setting your prices.

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Both are judgment problems

and not technology problems.

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It's about using it in

the best way possible.

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You are probably asking yourself at

this point, all right, Janene, I get it.

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I should use it, but where can it

help me the most at this stage?

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That's a great question.

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My experience over the last year and

where I've seen it help my clients the

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most is in that first round exploration.

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What I call the data gathering

stage, where you're pulling in

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information from different resources.

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For example, and exploring

different customer types or

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different aspects of your market.

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Earlier this year, I had a client who

was selling a product, into food and

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gastronomy, into bars and restaurants

and kiosks and things like that.

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And they didn't understand the

margin levels that might be

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expected in those types of clients.

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Today, you can go into a i, you

can ask that question quickly, and

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then you can go out and validate

that information in the market.

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Right.

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Scanning market dynamics and

competitors is another area.

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Pressure testing assumptions about

value, net value or willingness to

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pay or even understanding value.

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You may have one understanding of value.

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AI can help you validate some of that,

but also explore it further exploring

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different packaging options or commun

ways to communicate your prices.

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And also spotting misalignment across an

offer or across a portfolio of offers.

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These are areas where I have developed

tools to help my client to use AI in

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their pricing in a more effective way.

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AI is very useful for exploration,

not for making the final decisions.

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Certainly you can ask it its opinion, but

you would want to know why it's coming

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up with that opinion, why it's saying

that, and then validate it for yourself.

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The mindset that makes AI useful

in pricing is really around

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these four core principles.

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First of all, AI output

does not equal the truth.

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In any context, not just pricing, but we

have to understand that AI is only going

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to give us what information it has, it's

gonna extrapolate from what it has if it's

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not clear, which means that AI output is

definitely not going to equal the truth.

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So it's up to us to use that

information in the right way

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and not accept it as the truth.

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Exploration does not equal decision.

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That's the second core principle.

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Using it for exploration does not mean

letting go of the decision making.

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It doesn't mean that you should.

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Yeah.

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Or that you are now, speed does

not necessarily equal confidence.

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Just because you have a lot of

information now, you have a lot more

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information more quickly than you

did in the past, that's for sure.

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Right?

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Doesn't necessarily mean, you're

going to feel more confident about

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it unless you know how to use

that information the right way.

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So for some people who choose

not to use it, it might feel

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like information overload is one

of the reasons not to use it.

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So yes, you'll get a lot more

information, but you can then narrow

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that information down to what's useful

and then go out and validate that.

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But having that information faster is not

necessarily going to build your confidence

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about how you use that information.

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And the last core principle is

a validation is non-negotiable.

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And this, I'm a big stickler for this.

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I am always telling my clients,

use ai, use it wisely and validate

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the information you're getting.

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Before when you wanted to understand

your customers, you really needed to go

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out and talk to them in the first step.

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Now you can do a little exploration

upfront using something like ai.

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And then AI can help you understand,

okay, what do I need to validate in the

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market and how can I best go about doing

that in these interviews, let's say.

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And it can help you

with that step as well.

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So validation is so important in

this whole process of you using ai.

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You can't just take it at what it's,

you know, at what it's telling you.

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You have to go out and then make

sure that that information aligns

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with what you're actually doing in

the market and what you're actually

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hearing and seeing from people.

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All of this is very strongly

tied to the pricing and value

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anchors in your business.

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AI can help surface possibilities

or opportunities for you

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that you've never seen.

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I've also experienced that as

I've been playing around with it,

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if you will, in my own business.

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But the anchors come from the decisions

that you ultimately stand behind.

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Yes, it can give you ideas, it can show

you opportunities, but ultimately when

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you make a decision about something

based on a foundation of information

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that you believe represents the market

and represents the situation and what

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you need in your business and what your

clients need, that is where you come

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up with decisions and prices that you

feel, "yeah, I can stand behind this.

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I know why this is the price

and it's the right price."

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Fairness also still needs

to be assessed by human.

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Yeah, by a human being.

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So is it fair?

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Sure, you can ask ai, but ultimately

it's that personal relationship

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with an individual that's going

to determine the fairness in.

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The price that you set or

the decisions that you make.

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All of this again, ties back

into some solid anchors.

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I don't know if you remember

the last episode we were

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talking about value anchors.

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Again, that's all tied in here and you

want to make sure that you have the right

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value anchors, the right pricing anchors

for your business, and ultimately you are

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the one who determines what those are.

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Pricing anchors don't come from tools

they come from your judgment ultimately.

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Here are a few guard rails to

help you use AI more wisely.

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Yeah.

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First of all, treat outputs as

directional, not as definitive.

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We've touched on this a lightly here,

but this is information gathering.

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It's not the final story.

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It's not the final answer.

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You have to bring all that information

together to see the big picture.

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Sanity check against real customers.

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And context.

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So again, that's hints

towards this validation.

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So you need to go out there, you still

need to talk to customers, in my opinion.

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Not just my opinion, but this is my

experience that, even using AI in your

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business still, the most important

thing any business owner will ever

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do, is talking with customers and

understanding what their needs are,

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what they value, how they make buying

decisions, all of these things.

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It's good to gather information

on that from ai, but then you

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want to test it soundly, check it

against real customers and content.

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Don't outsource those pricing decisions.

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Make sure that you are using that

information to support you in making

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decision as opposed to making it for you.

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And use AI to ask better

questions, not necessarily just

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to answer the questions for you.

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So you, like I said before, you can

use the outputs from a AI where you're

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exploring your customers to then have

it help you figure out what questions

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to ask customers in a robust way

throughout that whole process, not

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just getting that first information.

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I'd like to close this up by

reinforcing a few key messages.

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The first is AI lowers the cost

of starting your pricing work.

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Before in order to get market

information and customer information

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is a very laborious process.

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Sometimes a very expensive one as well.

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And nowadays you can quickly go onto

AI and start doing some research,

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getting some first information.

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It lowers the cost and it

lowers the time aspect of this.

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It does not, however, reduce the

responsibility for deciding, even deciding

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well making good business decisions.

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That is still ultimately

your responsibility.

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And pricing still needs

anchors you believe in.

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You still need to anchor it in things that

are relevant to you and your customers

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so that you can make decisions and have

prices that have a solid foundation

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and that you ultimately believe in.

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I'd like to leave you with one last

question today, and that is the following.

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Are you using AI to think more clearly

when it comes to your price setting or are

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you using it to avoid making decisions?

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I leave you with that final

thought to reflect on.

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I hope you enjoyed this episode.

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I've enjoyed preparing it for you.

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I wish you a great day and

as always, enjoy pricing.