Hello. And thank you again, for tuning
in to another episode of the professional pricing Society
podcast. My name is Terrence and Hey,
listen. We have a great episode in store
for you all today. Now, as the founder of two very
successful pricing companies over the past 15 years.
Karen gagne, one of our PPS 022 Global pricing conference
speakers has implemented pricing strategies at some of the
largest organizations from the United States, Mexico, Europe
and also Asia and he will be spared.
In the conversation today, centered around designing
analytics, based pricing Frameworks.
Now, we'll go ahead and jump right into the conversation.
Keyring, if you wouldn't mind, go ahead and explain to us and
break down. What exactly is an analytics
based pricing framework. Yes.
So pricing as a function in any organization, right?
It has evolved. From history.
Right? So so typically, this is how it
was being done. And now, everybody's learned
from how it was done previously and mostly depending on the
stage of the organization but still mostly, it is done based
on intuition based on best practices based on what feels
right. Right now in today's world where
we have more data sources, more ability to analyze this
information and to actually use this information may be As a
decision support system or maybe to make decisions and then
measure what happened, or maybe to even automate these
decisions, right? These are all possibilities of
how data and Technology can be used for pricing today, right?
So the goal of this workshop and then what we're trying to convey
here is, how do you design this framework to leverage this
information? That's available to you, again,
this information is different for different businesses.
Has so for Abby to see is very different from B to B say for
example, but there's always data is always information available.
So how do you structure this data in a format?
It can be readily analyzed for your decision.
Making around pricing is is the focus of this conversation
tariffs. Now let me ask you.
Can you use any of these best practices for quick wins?
If you will? Yes.
So you don't have to build. You know, the most complex
pricing process or function overnight.
One of the first thing we could do is we could analyze
historical data to see how each organization has performed,
right? Say, for example, we could
collect historical competitive prices or even our own sales
data to see how it performs. Say, for example, some
categories might perform better in summer versus winter or or
some categories reacted Very drastically when a competitor
change its price in others, we did not write quick.
One win, would be to take a look at your own data, to see how you
performed in the past. And if we can get any learnings
out of it, and it doesn't have to be in a most complex
software, use Excel or, or you know, look at these numbers and
then I try to come up with some kind of insights.
That's the start of analytical Journey for somebody.
Okay, that's good. Now, you mentioned looking in
the past, how would you say pricing is different today than
it was from the past? You know, considering things
like inflation. Yes.
So one of the key things, you know, I work a lot with retail
and some of the Retailer's I work with are and Latin America
and because of the high inflation of its suppliers, it
could be from the US. It could be Europe.
The cost are changing continuously, right?
Well they traditionally have systems where they don't change
prices continuously, they might only change price once in six
months once in three months. So they had to make
accommodations. Now to make like new processes
to react to these costs changes much more quickly.
Otherwise they're going to bleed money right?
If they have the higher cost comes through and you still
selling at an old price, that means you're selling at a loss
now. So one is build processes to
understand and react quickly. Second is, there are some
categories where customers don't like these constant change in
prices, whereas in other cop agrees, they are, they're okay
with it, right? So, how do you pass these
changes in cost to your consumer is a decision retailers or other
businesses have to make. Sometimes it is done in a more
tiered fashion or sometimes they take it all at once.
But we definitely need to do is build new processors for this
new environment. Otherwise, we're going to be
inefficient in the market. Okay, and you also mentioned the
different categories. As you know, some people may be
in favor of certain categories and certain other people may be
against it for clarity. You are referring to Consumers,
correct? Yeah, yeah, or whatever it is.
Buying from you, right? So, the consumer doesn't have to
be like a customer walking into a store for a B2B business.
To Consumer is very different, right?
It could be like, say, for example, BMW buying car parts.
Sure, fire in the US. Oh sure, sure, absolutely.
Now let me ask you this. Is there a difference between
pricing infrastructure regarding B2B and b2c?
Oh yes. In in case of B to C, we see
much more sources of data typically I've done a lot of
b2c, right? So I know there is a lot of good
sources of data, we can process say, for example, for each
store, location. I know exactly what is the
demographic. Affix, what is the income right
now? What was the weather on a
certain time of the day of purchase?
Right. Also, I have point-of-sale data
and I have competitive data. All of this is much more readily
available in a b2c environment to process in a be environment.
The data is a lot more qualitative than quantitative,
right? It could be like a relationship,
somebody has built over time, you know, let's say your
grandfather was friends with another person in a company
which is why they're still giving you a good price.
Thing. So there is still is a need for
a process. There is still a need for an
infrastructure to process all of it but the way the qualitative
information is handled is very different from quantitative
information, okay? Now, what aspects of pricing
should be handled in-house compared to being out sourced.
What would you say? Yes.
So so depends on the focus, that goes the size of the
organization, right? So to go back to the example of
what we're doing in Latin America.
So this is a very large food company with more than 1,500
locations of their own where they sell through their own
stores, but still, they don't have an experienced.
Data scientist, 20 years of experience to build their
mathematical models, right? They can build it but it's too
much of work too much of a hassle for them because they
don't need these data scientist to be there full-time, right?
So that's when they hire our organization, I've had these
algorithms built by these data scientists in the past, which is
sufficient for them, for their need of pricing, to make a
decision on what they need to do as a strategy, right?
So they didn't Have to do this in-house, but Albert, Einstein,
this is another company. We were trying to sell our
businesses, sell our services into in, in Amsterdam, and they
quite decided that they have the capability to hire their own
team. Get a team of data scientists to
do, the real-time fresh produce pricing for them.
It was the right decision because they already had a big
enough pricing team, which could accommodate this new high-end
mathematical models through there.
Team, right? So again depends if your focus
is to enter the new market, or if your, if your core focus is
to produce the best product, keep keep your core focus and
let the pricing be done by somebody else.
But perhaps you're in an already commoditized market and you want
to bring more of these functions, in-house to reduce
your overall cost. Then you could take this, you
know, hiring firing of the right resources, probably one step at
a time to do this yourself. For probably two more customized
request in in, in the future, right?
Okay, so you're saying is basically what it?
What is your focus? That's what's going to help to
determine if? It's something should be
in-house or Outsource, that makes a lot of sense is that the
same case for personnel or automated when it comes to
aspects of pricing, depending on what the focus is.
So I'll give you another example of what I did, right?
So I was a pricing consultant Aaron.
So I did In Consulting for about, I don't know, 17, 18
years then but this was very boring for me after a while
because I will do the exact same thing.
We would do, the data analysis, we would do the strategy, we
would do the pricing, we would do the measurements its exact
same step. I would do it again and again
and again, that's what we decided.
Hey, why don't we automate? What is standard?
Hmm, let's focus. Let's use our brain power to do
more Innovative stuff. Let's try to And how many days
of life is left on a banana instead of trying to pressure,
you sell it against the competition that can be
automated, right? So like anything in life, I
believe once it becomes routine, once it becomes standardized,
there is a prime opportunity to automate it or to delegate it
and then focus on Focus. Your brain power on doing
something which is path-breaking an Innovative instead.
Maybe it's just me. A suggestion, is if it's too
boring, if it's Standardized. Think about a way of automating
it. Mmm, you know, that's such a
simple thought that I feel many people are companies May
Overlook. And so, that can really become a
game changer choosing to create something in an automated
version that is already in routine or standard.
You know, versus just like you said trying to find out how much
time is left in a banana, you know, exactly that's good.
Now, how does Has someone determine what their next step
in their pricing journey, is or what, how do they determine what
it should be? It's always good to do have this
conversation with an expert, right?
Like, in an industry whose done this in the past, to see where
exactly, they might stand in in evolution of pricing inside
their own organization. Because somebody might feel like
we're already doing a good job, but but an expert in the
industry might be able to point out and tell them by the way.
This is good, or this could be what you do next.
By the way, the pursuit of perfection is a never-ending
goal, shortening, it should. It's new, can never say, have
reached their. So, so, take a look at like,
say, for example, if you haven't done analysis in an Excel, don't
think about a big data solution yet.
There is a lot of low-hanging fruit.
You could pick from Quick analysis of data, right?
And then go to Big Data, like add more sources of Of data to
it, right then, think about okay.
How can you do this using artificial intelligence?
How can I add more real-time sources of data?
And then probably think about completely automating it.
Eventually, if you take a example of the airline industry,
Trends complex commercial jet right requires only two people
to fly it. Why?
Because everything, that can be standardized and automated, it
is already automated. Add that airplane and the pilots
only use their time to react to real-time changes in the flying
conditions. It could be, whether it could be
like a traffic controlled saying, do something else or
passenger going. Crazy.
So think about what where do you want to spend your time and
attention and then and that will tell you where you are in the
cycle of adoption and what should come next amazing advice.
Let me ask you this one. Last question.
What are you? You may have kind of touched on
it. I mentioned a little bit or
alluded to a little bit before in our previous discussion
earlier within this discussion, but what do you foresee the
future? Climate of companies utilizing
analytics, based Frameworks. See if you if you take an
example of a more mature pricing industry, right?
Like say for example pricing for Airlines earlier what happen is
every Airline was doing their own pricing.
And this then they started paying Consulting companies to
do it for them. Specialized Consulting companies
may be Bane was doing it. Mackenzie was doing it, I don't
know. And then it became so
commoditized. Now anybody can Loop in an API
and get these pricing done automatically for an airline,
right? So that's going to happen for
each and every industry when you think about how it's going to
evolve. First, it's going to be have to
be custom-built. Then you will see Consulting,
companies do it. And then you'll see automated
Solutions. Providing it to you as a service
as a commodity, which will become very cheap.
Hmm. Well one good idea is to check
if your industry is already there.
Maybe you're not aware of it. Is there an automated solution
to do pricing for you already? Then?
Yes, let's do it. It won't be too expensive if
it's already commoditized. Thanks so much for answering all
my questions. Do you have any resources that
listeners can can retrieve maybe from your website or any social
platforms? Well, in a few months and
release In my first book. Hmm, welcome, you to come by.
It it is toward an expert guide to pricing for.
Now, connect with me on LinkedIn, please and attend this
Workshop. I'm going to conduct at PPS in
Barcelona, and December 7th. So these are places to start and
I am not an expert in all walks of pricing, but I do have a good
enough Network in many places. If I can, I will help you guys
connect with the right people to take it Forward, also as well.
L. Okay.
Sounds like a plan with thank you so much mr.
Kiran and we look forward to seeing you in Barcelona and just
a couple of weeks that was good. Thank you so much Darren's.
My name is Kiran, gong ji Gan GE you will easily find me on
LinkedIn. I hope to see you at the
Barcelona conference at the listeners and you also Terrance
absolutely.