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Hello, and welcome to the 
Professional Pricing Society 

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podcast. 
I'm Kevin Mitchell from PBSN. 

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I'm thrilled to have you with us
today. 

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Our podcast explores the latest 
pricing strategies, industry 

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insights, and expert 
perspectives to help businesses 

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optimize their pricing for 
profitability and growth. 

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Today we have a fantastic guest 
joining us. 

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Mr. Fred Quesch is the founder 
of Kenolytics, a boutique 

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consultancy specializing in 
pricing analytics and strategy 

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for food service and e-commerce 
companies. 

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Fred has over 15 years of 
experience in pricing and he has

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worked across a very wide range 
of industries. 

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He has been APPS member for well
over a decade and has LED 

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several CPP workshops at our 
conferences. 

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He holds a PhD and a Master's in
Economics and he's also going to

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lead a workshop at our upcoming 
event, PPS Profitable Dallas in 

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May from May 6th to May 9th. 
Our conversation today is all 

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about pricing analytics and 
strategies along the customer 

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journey. 
We're going to talk about how 

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businesses can use data-driven 
pricing strategies to enhance 

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profitability at every stage of 
the customer experience. 

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Brad, let's start by setting the
stage from a brand's 

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perspective. 
What are the key touchpoints on 

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the customer journey and what 
role does price play? 

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At each of. 
These key touchpoints. 

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Yeah. 
Thank you, Kevin. 

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So typically what I what I see 
is if you want to simplify it, 

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there are mostly three main 
touchpoints along the the 

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customer journey and three 
prices, I would say attached to 

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those to those touch points. 
The main price, the number one 

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is obviously the everyday price.
That price is visible to anyone 

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and everyone, including non 
customers. 

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You know, if you think of an 
e-commerce platform or an 

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ordering app for a restaurant, 
even if you decide not to order,

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you will see the the everyday 
price and that everyday price 

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usually then and that ends up 
being used in about 50 to 75% of

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orders. 
So it's, it's the main one. 

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I would say the second one you 
will have a number of promoted 

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or let's call them discounted 
prices, limited time offers, 

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coupons, you name it. 
And these prices, they should be

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primarily used for new customer 
acquisition. 

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And by that we mean the first 
time a customer ever orders with

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the brand and also to get the 
2nd order, getting the 2nd order

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and we'll get to that maybe a 
bit later, getting the 2nd order

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is, is crucial, especially 
getting the 2nd order as quickly

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as possible after the first one.
It's the best way to build the 

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loyalty. 
The 3rd and and last type of or 

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set of prices that you can use 
as as another touch point is 

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precisely everything that 
pertains to your loyalty program

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and more targeted offers. 
And that's usually what is what 

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is used primarily after that 
second order. 

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So once a customer you know is 
placing a 3rd, 4th, 5th, 10th 

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order, they're more familiar 
with your brand and it's 

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obviously a different type of 
relationship as when it's a 

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brand new customer. 
Fred, that's a great breakdown. 

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With these different touch 
points in mind, where should a 

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company start? 
Which pricing element is the 

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most critical? 
Yeah. 

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So, you know, I'll be preaching 
to our own church here with 

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Pricers listening to us. 
The the everyday price, sort of 

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the traditional everyday price 
is it remains the most important

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one and for a couple of reasons.
The the first one is that it 

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ensures that the company remains
profitable. 

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And you know, everybody who's 
listening to us here at, at PPS 

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knows that, you know, that's 
what price is for first and 

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foremost is to maintain and grow
your, your business's 

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profitability. 
And what it does here is that 

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you, you can think of that 
everyday price as the reference 

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price for all your transactions.
So all the discounted prices, 

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loyalty prices, targeted offers 
that I just talked about, in a 

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sense they will be set off of 
that, that everyday price, which

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is sort of the the baseline, OK.
And that baseline should be set 

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in a way that that your business
is profitable. 

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The, the second reason why it's,
you know, the everyday price 

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remains the the most important 
one and the one where any brand 

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really the one that any brand 
should tackle first is that even

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with at most aggressive brands, 
you know, the brands that are 

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going to do a lot of 
discounting, a lot of promotions

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with a heavy loyalty program, 
usually that everyday price 

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remains used in about half of 
the transactions, sometimes in 

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about 75% of them. 
So obviously that's that's the 

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one that you you don't want to, 
you don't want to set wrong, 

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wrong. 
Thank you very much, Fred. 

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Now let's talk about the 
analytical tools that are 

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available to us as pricing 
professionals. 

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What are the main types of 
analytics that businesses should

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use when setting prices? 
Sure. 

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So there's there's a lot you can
do and especially with the the 

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type of businesses that we're 
talking about here with a heavy 

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component of digital sales, 
whether it's e-commerce or 

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restaurant brands now selling 
more and more online. 

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There's a lot of data available 
and a lot of, a lot of things 

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that you can do to help you set 
those different prices the, the 

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right way. 
Let's start with the everyday 

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price, which again is the most 
important of the, the Trinity 

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that we're talking about here. 
Here number one thing you you 

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ought to do is, you know, use 
price elasticity and quantify 

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price elasticity. 
A lot of businesses now, 

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especially online, do they run a
lot of experiments. 

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So they try different prices and
different, different price 

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points for for their product. 
So they actually have a lot of 

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data, experimental data, but 
real life data, you know, with 

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actual orders from their 
customers to use to build 

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predictive models of demands 
that can then help you quantify 

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the price elasticity of your 
product. 

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Price elasticity. 
Just a quick reminder, what it's

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going to tell you is whether 
your product is very sensitive 

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to a change in price or not. 
Obviously if you are, if your 

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goal is to take to run a price 
increase, you're going to focus 

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on the items that are not price 
sensitive. 

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So with a low price elasticity, 
the ones with a very high price 

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elasticity, you will stay away 
from for your price increases, 

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but they will be good candidates
for promotions though, right. 

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And so Speaking of which sort of
second type of prices, we, we 

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talked about promotional prices 
and, and discounted prices here.

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Typically you're going to focus 
on promotional effectiveness. 

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What I've noticed is that 
there's actually a lot of 

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companies out there that are not
very good at measuring the true 

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impact of, of their promotions. 
It's a lot of just very simple 

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top line before and after 
analysis where all look volume 

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went up. 
Our promotion is successful. 

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It's not that simple. 
You need to go a lot deeper than

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that to really understand 
whether a promotion worked or 

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not. 
One way to do this is to build 

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what statisticians and 
economists called a 

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counterfactual. 
So a counterfactual will tell 

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you what would have happened 
without the promotion. 

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There are fairly simple ways to 
do it. 

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There are also more advanced 
ways to do it where you can 

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build again, a a predictive 
model that will tell you, all 

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right, had the promotion not 
happened, this is what we would 

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have observed at a very high 
level of detail. 

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And by comparing that kind of 
actual with your actual 

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performance, this is where you 
can really get a good read on 

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the effectiveness of of your 
promotions. 

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Last but not least, for 
everything related to loyalty 

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programs, targeted offers a good
long in depth analysis of your 

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order patterns and customer 
behaviour on the customer sides.

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Typically I start by analysing 
cohorts and that's something 

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very common in e-commerce, 
right? 

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Cohort analysis, so you look at 
all the customers acquired in 

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the same month or the same 
quarter and you track them over 

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time and see how they behave and
then eventually you're going to 

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build more advanced customer 
segmentation. 

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You know, Kevin, the customer 
segmentation is key to pricing, 

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whether it's B2B consumer, you 
know that that never goes away 

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again. 
Now with the the B to C digital 

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businesses that we're talking 
about here, you can do a lot of 

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that customer segmentation 
because now every time a 

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customer places an order online 
or through your app, you 

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actually have the customer ID 
attached to the transaction, 

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which opens up a lot of 
possibilities obviously for for 

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analytics and, and, and customer
segmentation and, and customer 

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analysis. 
Thank you. 

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Fred, you mentioned how 
important it is for companies to

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clearly define the purpose of 
each pricing touchpoint. 

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What are some of the common 
mistakes you see businesses 

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making in this area? 
The the main mistake is not to 

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take advantage of it actually 
and to try to have either A1, 

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let's call it A1 price fits all,
you know. 

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So for every transaction, 
regardless of who your customer 

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is, where they are in their, 
their journey with your brand 

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using the same price or 
sometimes using the wrong price 

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for the wrong purpose. 
And what I mean by that is 

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typically, so again, if you go 
back to the, the three types of 

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prices I, I, I described here, 
so your everyday price, your 

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promotions, Lt. 
OS discounts and then your, your

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loyalty programme and targeted 
offer. 

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Well, again, your everyday prize
is here for profitability. 

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And that's what that's what 
pricing is for. 

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I don't think anybody who 
listens to us here will disagree

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with with that statement 
promotions and that's where I 

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see a lot of mistakes being 
made. 

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Sometimes people use promotions 
to try and drive volume from 

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existing customers and to drive 
loyalty etcetera. 

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That's a losing gain. 
Usually promotions are most 

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effective when they are used for
customer acquisition and by that

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I mean customers or consumers 
who have not purchased from your

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brand yet or who are very early 
in their customer journey with 

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you. 
So some sometime around the 

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first or second order with your 
brand and if you tailor your 

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your promotions and your 
discounts to really attract 

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these new customers to your 
brand, this is where your 

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promotions become effective and 
your marketing dollars become 

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more more productive. 
Loyalty programme and 

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personalisation. 
These are great tools and great 

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sort of prices or pricing 
programmes to use for retention.

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Again, you know you're not going
to get someone who is totally 

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new to your brand. 
They're just placing their first

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order. 
They've never tried your 

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product. 
You're not going to going them 

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to sign up for a loyalty program
right away. 

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Whereas once a customer has 
placed 123 orders, they've tried

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several of your products, that's
where they, they will start 

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liking your brand, liking the 
value that they're getting from 

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your product and they will, they
will sign up for the, for the 

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loyalty program. 
And one, one comment here, 

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loyalty doesn't mean deep 
discount necessarily, right? 

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And that's where we we're sort 
of at the intersection between 

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pricing and other marketing 
initiatives as well. 

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Sometimes, you know, loyal 
customers, they enjoy having 

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access to new products before 
everybody else, for example, 

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right, or special bundles or you
know, things like that. 

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They of course do welcome a 
discount, we all do. 

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But it's not necessarily about 
pricing as low as possible. 

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It's more about recognising the 
value that you're giving to, to 

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your customers. 
My last comment on this, Kevin, 

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is, you know, it may sound 
familiar to you because actually

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we're getting closer and closer 
to what B2B companies have been 

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doing or trying to do for, for 
yours and, and decades, right, 

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Especially with trying to create
loyalty with their customers and

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customer segmentation, etcetera.
So this I think a lot of 

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convergence happening here 
between the the the two spaces 

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B2B and PSC. 
Thank you, Fred. 

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That makes a lot of sense. 
So if a company wants to 

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implement this pricing 
framework, what kind of data do 

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they need to get started? 
Yeah. 

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So that's, that's the beauty of 
it. 

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You, you actually don't need 
that much fundamentally. 

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You, you need a single table of 
data, which is your order 

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history at the order line level.
And that's something I feel very

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strongly about, you know, and us
as a consultants, we are 

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sometimes guilty of pushing 
companies towards, you know, 

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you, you need a data warehouse, 
you need a data leak, you need a

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tech stack and, and whatnot. 
But actually there's a lot that 

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you can do with just that one 
table of data with your order 

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history at a very granular 
level. 

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So really at the product line, 
the product line level, so that 

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one table that will have your 
order ID, customer ID, product 

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ID and then quantity and either 
price or revenue. 

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There's already a lot that you 
can do with that. 

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Now the more the better. 
Obviously a lot of companies 

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actually they have a lot more 
data than than that. 

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If you are an e-commerce 
company, you're using Shopify or

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you are an Amazon seller and you
can pull your data from Amazon 

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Seller Central, the tables that 
you get actually have a lot more

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columns than that. 
It gives you all the details 

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about the discounts that that 
you gave at the order level and 

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at the item level. 
So there's a lot of things that 

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you can do. 
You also obviously have more 

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data available in terms of 
additional tables. 

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You a lot of companies have 
ACRM, right, even in B to C, So 

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they have a list of all their 
customers and they collect a lot

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of information on those 
customers that they that they 

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can use for segmentation. 
You have a lot of data about 

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your products that that you can 
use as well. 

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And then obviously you have 
external data, web scraping, 

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we're at the point where it's 
almost table states now, 

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unbelievable to say that 10 
years ago it was sort of the, 

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the frontier in competitive 
pricing and competitive analysis

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was very hard to do. 
And the data you would get was 

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so, so nowadays it looks like 
everybody's creeping everybody 

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else and everybody has access to
their competitors prices and you

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know, it's, it's all out there. 
And so that, but that's another 

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data point that you can use 
when, when making decision. 

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I've also had several clients 
using third party consumer data,

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so complementing their, their 
order and their customer data 

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with, you know, credit history 
or credit data from companies 

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like Experian. 
And that adds a lot of 

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dimensions to your customer 
segmentation because as you 

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know, those those credit 
companies or credit card 

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companies collect a lot of data 
on consumers as well. 

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Thank you, Fred. 
For brands that are new to this 

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approach, where do they start? 
What's your best advice for 

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getting started with pricing 
analytics? 

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Sure. 
So again, step #1 pull your 

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order data. 
You already have the data, it's 

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available. 
It's usually pretty clean, 

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already in, you know when you 
pull it out of your system 

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again, if you are an e-commerce 
company, you're using Shopify or

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you are an Amazon seller, you 
can pull the data from Amazon 

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Seller Central. 
It's very easy to do. 

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If you're a restaurant brand, 
you know, you have your POS 

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system, you have your app system
that allows you to pull these 

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these orders very easily. 
So I feel that getting access to

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the data now is, is not the 
challenge anymore. 

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The data is there. 
It's fairly easy to pull, you 

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know, for someone who knows what
they're doing now, once you have

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the data, usually what I advise 
clients is to start with the 

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basics. 
And in this case, the basics 

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would be cohort analysis. 
It's not even pricing at first. 

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Just break down your business by
quarterly cohorts of customer 

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acquisition and start looking at
your main KP is average order 

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value, average discount. 
You can look at average price by

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by product and by cohort. 
Just by doing that, you'll be 

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surprised by what you see. 
You you will learn something by 

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just. 
Doing a simple average price by 

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product, by cohort over time, 
right, If you do it on a 

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quarterly basis, you'll, you'll 
see that there's, there's a lot 

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of insights that you can gather 
there. 

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Then as I mentioned earlier, the
I would say the first step 

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beyond the basics would be to 
make sure that you set your, 

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your everyday price optimally 
from a margin standpoint. 

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And now we get back to the price
elasticity modelling the 

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predictive models of of demand 
that I talked about earlier. 

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Again, at the end of the day, 
we, we are pricers here and that

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everyday price is, is the most 
important one in your business. 

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All the other prices we we 
talked about today, your 

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promotions, your Lt. 
OS, your coupons, your loyalty 

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programs and your personalized 
offers will sort of revolve 

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around your, your everyday 
price. 

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So get that one right. 
That would be my my advice. 

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Thank you, Fred. 
This has been such an insightful

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00:21:23,840 --> 00:21:26,880
conversation. 
Before we wrap up, I want to 

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remind our listeners that you'll
be leading a full day CPP 

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workshop coming up at PPS 
Profitable in Dallas. 

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Fred's workshop is pricing 
analytics and strategy for 

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optimal growth in B to C, So 
make sure to take advantage of 

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that. 
But Fred, can you give us a 

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00:21:44,720 --> 00:21:48,680
quick preview of what your 
attendees can expect from your 

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00:21:48,680 --> 00:21:52,240
full day CPP? 
Workshop, sure, yeah, Thank you,

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00:21:52,240 --> 00:21:57,000
Kevin. 
I'm really, really excited to to

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00:21:57,000 --> 00:21:59,000
get there and looking forward to
it. 

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So the workshop will actually 
I'll, I'll be talking about a 

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lot of the things that I talked 
about today. 

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We obviously will have the full 
day. 

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So we will go in a lot more 
depth than than what we covered 

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today. 
And so I will talk about the 

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customer journey. 
I will talk about the different 

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touch points and the different 
prices available. 

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But more than that, you know, as
you mentioned, my, my bread and 

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butter is pricing and I did it. 
So I will share with the 

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attendees how you can use, you 
know, the, the transactional 

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data I just talked about, you 
know, so once you've pooled that

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order data, how you can use the 
data to set your everyday price 

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to analyse your promotions and 
promotional effectiveness. 

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So you can set your, your 
discounts and promotions 

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properly and how to use the data
also to help you develop a 

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00:23:00,080 --> 00:23:03,720
loyalty program and personalized
offers. 

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00:23:04,800 --> 00:23:08,200
We will go into a fair amount of
details because we will have the

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time to do so. 
We'll, we'll have the entire day

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together. 
So I will be able to share even 

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00:23:17,200 --> 00:23:21,040
for each one of those type of 
analytics that I just described 

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00:23:22,200 --> 00:23:25,120
the, the different levels that 
are available, right? 

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00:23:25,280 --> 00:23:30,520
Not everybody can be, you know, 
PhD level or Nobel Prize level 

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00:23:32,240 --> 00:23:34,600
modeller of, of price 
elasticity. 

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00:23:35,000 --> 00:23:40,400
And I know there's typically a 
lot of beginners who attend 

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these workshops and they may be 
a little bit overwhelmed at 

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00:23:44,240 --> 00:23:45,800
first. 
By all my goodness, I, I've 

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00:23:45,800 --> 00:23:48,880
never run a regression model. 
How do I do price elasticity? 

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00:23:49,480 --> 00:23:53,560
So what I do is that I usually 
share different levels of 

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00:23:53,560 --> 00:23:58,960
techniques or technicality as to
how to run these analytics from,

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00:23:59,080 --> 00:24:01,920
you know, the beginner, you've 
never done it where here is 

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00:24:01,920 --> 00:24:05,680
where you can start. 
Keep it simple, just get it done

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00:24:06,160 --> 00:24:08,480
all the way to. 
Well, yeah, if you are a little 

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00:24:08,480 --> 00:24:11,840
bit more advanced, these are 
sort of the state-of-the-art 

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00:24:11,840 --> 00:24:13,720
techniques that are available to
you. 

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00:24:13,720 --> 00:24:18,600
And so I'll, I'll share a lot of
examples from project work that 

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I've done as well. 
So a lot of, a lot of data to be

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expected and very, as you know, 
Kevin and I'm very keen on 

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00:24:27,760 --> 00:24:34,080
keeping things practical, right?
And making sure that at the end 

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00:24:34,080 --> 00:24:38,480
of the workshop, the attendees 
can go back to their their desks

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00:24:38,480 --> 00:24:43,200
or their their offices and 
actually use what I've taught 

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00:24:43,200 --> 00:24:45,960
them in the workshop. 
Thanks so much, Fred. 

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00:24:46,280 --> 00:24:49,480
That sounds like a must attend 
session for anyone looking to 

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00:24:49,480 --> 00:24:52,920
refine their pricing strategies.
And of course, if you want to 

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00:24:52,920 --> 00:24:56,720
learn more from Fred and other 
top pricing professionals, make 

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00:24:56,720 --> 00:24:59,000
sure to join us at PPS 
Profitable. 

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00:24:59,320 --> 00:25:02,560
We'll be in Dallas from May 6th 
to May 9th. 

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00:25:02,640 --> 00:25:07,000
Lots of strategies and tactics 
and best practices for you and 

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00:25:07,000 --> 00:25:08,840
your team. 
You can find 

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00:25:08,840 --> 00:25:13,600
allthedetailsandregister@pricingsociety.com
or you can always reach out to 

363
00:25:13,600 --> 00:25:17,120
me if you have any questions. 
Fred, thank you so much for 

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00:25:17,120 --> 00:25:20,600
sharing your expertise with us 
today and also thank you to all 

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00:25:20,600 --> 00:25:23,920
of our listeners. 
Fred, of course, thanks very 

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00:25:23,920 --> 00:25:26,440
much to you. 
Thank you for being a part of 

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00:25:26,440 --> 00:25:29,680
the PPS podcast. 
And everyone, if you found this 

368
00:25:29,680 --> 00:25:34,760
episode valuable, make sure to 
subscribe to us on Apple Podcast

369
00:25:34,760 --> 00:25:39,080
or Spotify to stay updated on 
the latest in pricing. 

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00:25:39,520 --> 00:25:41,560
Until next time, take care.