- Protection Gear
- Women Special occasion Dresses
- Women Dresses
- Men Printed T-Shirts and Tees
- Women clutch bags
- Winter Wear
- Winter wear Jackets
- Bed & Bath – (Towels – Bathmat – Comforters-Shower Curtains – Duvet Covers)
- Home Decor (Tapestries – Curtains – Pillows)
- Licensed Merchandise
- Aswebman Designs
- Sports – Ali
- Teespring askwebman store
- Aswebman Designs
- Bed & Bath - (Towels - Bathmat - Comforters-Shower Curtains - Duvet Covers)
- Home Decor (Tapestries - Curtains - Pillows)
- Licensed Merchandise
- Men Printed T-Shirts and Tees
- Protection Gear
- Sports - Ali
- Teespring askwebman store
- Winter Wear
- Winter wear Jackets
- Women clutch bags
- Women Dresses
- Women Special occasion Dresses
A weekly podcast with the latest e-commerce news and events. Episode 224 is deep dive into the use-cases and best practices of customer cohort analysis with Dr. Daniel McCarthy, one of the leading experts in the field.
Daniel McCarthy (@d_mccar) is an Assistant Professor of Marketing at Emory University – Goizueta Business School, he’s one of the industries top thought leaders in the field of customer lifetime value (CLV). In this episode we discuss how CLV and customer cohort analysis can be be used operationally within e-commerce companies, as well as how customer data can be used to calculate a company’s true enterprise value, customer-based corporate valuation (CBCV).
Dan co-founded a predictive analytics company, Zodiac, which was later acquired by Nike. He’d made news several times by applying his CBCV to popular public companies using their public disclosures.
Listen to this episode just to hear Scot say “Goizueta.”
- Dan’s personal website
- Theta Equity Partners – Dan’s current firm, focused on CBCV
- McCarthy, Daniel; Fader, Peter (2018). “Customer-Based Corporate Valuation for Publicly Traded Non-Contractual Firms”. Journal of Marketing Research, 55(5), 617-635. Link (download)
- McCarthy, Daniel; Fader, Peter; Hardie, Bruce (2017). “Valuing Subscription-Based Businesses Using Publicly Disclosed Customer Data”. Journal of Marketing, 81(1), 17-35. Link (download).
- McCarthy, Daniel; Fader, Peter (2020). “How to Value a Company by Analyzing Its Customers”. Harvard Business Review, 98 (1), 51-55. Link
Don’t forget to like our facebook page, and if you enjoyed this episode please write us a review on itunes.
Episode 224 of the Jason & Scot show was recorded live on Thursday, June 25th, 2020.
[0:24] Welcome to the Jason and Scott show this is episode 224 being recorded on Thursday June 25th 2020 I’m your host Jason retailgeek Goldberg and as usual I’m here with your co-host Scott Wingo.
[0:39] Hey Jason and welcome back Jason Scott show listeners well folks we have a really awesome treat for you today it’s so good that I want you go ahead and pause the show here and leave us a five star review and then come back.
All right welcome back,
today on the show Jason I have to admit we are kind of fanboying here so we’re going to try not to giggle too much during this interview we are excited to welcome one of the brightest Minds not only in e-commerce and Retail marketing
but just marketing overall
so please welcome Us in bringing Daniel McCarthy to the Jason Scott show Dan is the assistant professor of marketing at Emery’s Gazeta business school Dan welcome to the show.
[1:24] Thank you for having me Jason and Scott.
[1:26] Did I say that right.
[1:29] Pretty much.
[1:30] Glue is that a little bit more of a quiz that kind of thing in there.
[1:34] It’s like sweater but boy sweater.
[1:37] We sweater okay I got it all right thank you.
[1:40] That that is actually part of the screening process to get into the school there’s you have to be.
[1:45] Yes this is why I’m not a professor of marketing at that school whose name I’m not great at pronouncing.
[1:51] Let’s check number one for us.
[1:55] I think in Dan’s case there might also be a math requirement that you may not like.
[1:59] Yeah I saw you had some stats at his background there.
[2:02] Exactly so Dan before we jump into what we do like to give the listeners a little taste of how you came to your your current professorship in your your case can you tell us a little bit about your background.
[2:17] Yes I’d spent about 60 years working at a value-based hedge fund before coming back actually for a PhD in statistics at the Wharton School,
and in the middle of the Ph.D program I made a pivot into marketing and so I actually I finish the PHD in statistics but half my committee when marketing people and half works this six feet below,
and I ended up becoming an assistant professor of marketing at Emory University along the way I also was bitten by the entrepreneurial bug so in the,
leave us in a third year of the PHD myself and my adviser had co-founded a company called zodiac which was a predictive analytic software as a service firm you basically,
predictable customers we do and use that to help marketers it can acquisitions.
[3:08] We grew that and then sold that in March of 2018 to Nike and then the following month we had also,
co-founded a company called Theta Equity Partners which
pretty much does nothing but what was the topic of my dissertation which we now in the early call customer base corporate valuation or CP CV for short so yes I kind of.
Straddle Both Worlds and say 100%,
you’re kind of a Quant marketing academic but definitely we appreciate.
You know things that work in practice and and even participating in that myself.
[3:50] Very cool and I did want to touch on a couple of things in your bio super quick hey I love the fact that PhD in statistics wasn’t challenging enough so you you pivoted to the the super complicated world of marketing.
[4:04] Yeah it was a it was a tricky transition I would say on the plus side,
you basically is doing the same predictive modeling that I was as of you know I’m just going to get a stat PhD and become a stack Professor sort of thing but now it’s just predicting what customers will do instead of predicting you know.
Anything pretty much in stock prices or.
Various things about sports teams or whatever else it was that we were doing pre-marketing pivot.
[4:38] And I for sure want to compliment you I feel like you’re in the small percentage of people that did a dissertation on something that you could totally commercialize so I think that’s super smart and savvy.
[4:50] Yeah it was weird how it kind of ended up that way but I really think it was yeah I kind of view customer base corporate valuation is really being at the intersection of,
marketing finance and statistics like you really can’t crack that topic without going pretty deep into all three I think,
and I think one of the things that Drew me to it was the fact that it allowed me to kind of do everything that,
I just find it be fun so you had the buy-side hedge fund experience I could bring that in the statistics I can bring that in and then,
obviously pretty King with customers will do bring in the marketing to.
[5:27] Oh dear so why did you make that marketing pivot to was there you were in stats and you kind of like started to do something connected to marketing or what what was the connective tissue there.
[5:38] I blame Pete fader yeah he is that a name that comes up a lot with the sort of things that I do but someone who actually had worked out of the stats Department,
he said you know I think that you really get along with this to be fair guy and he’s a marketer but let’s not hold it against me.
So yeah I basically went up to the seventh floor which is where the marketing department is and Warden and yeah we really just kicked it off I just really enjoyed the problems that he was working on and yeah I like them enough that I just said I want to do this,
you know I want to do this all the time.
very cool well you kind of raised us let’s jump into this so I’ve enjoyed your your analysis your analyses that you do on Twitter and your papers but let’s talk about CBC TV,
let’s talk about the origin of it and how you are applying it to think about valuations.
[6:38] Yes really yeah a lot of the early work that I had done was to use these marketing models to predict what customers will do in the future and use that to compute customer lifetime value and other related measures.
typically in marketing that’s where the exercise ends you say alright you know we predicted well they are completely I’m done and,
basically because of my work in valuation I was like we could take this a step further and use this to actually inform
view as to how companies doing his whole and obviously I won’t say that I’m the first one thing about this you Pete had done some work in this area and,
yes even some work going back to 2004 but it was mostly kind of proof of concept not super well validated models.
And it was really.
Yes saying let’s kind of peel back the onion a bit further with this and I think that’s really kind of one thing led to another and you know I now have,
three academic Publications and other two along the way on the topic and basically there’s just so many different facets of the problem that I designed to be completely fascinating.
[7:50] Well in my world of startups we think about valuations at a pretty simple kind of you know kind of multiples right so you have a revenue kind of calculation you have an ibadah kind of a calculation then it’s
I’ve gotten into Wall Street analyst you know they’ll do a variety of discounted cash flow projections and these kinds of things how is this different
like what what do you what is this take into consideration that those those kind of mechanisms don’t.
[8:16] Yeah that’s the beauty of it it can really be all of the above it can be used to do an enlightened version of to come up with an enlightened Revenue multiple ebitda multiple,
you know kind of straight up discounted cash flow valuation because ultimately if I were to kind of just summarized with cdcd is is it’s a way to,
make a more accurate Revenue projection by really exploiting the fact that all the revenue has to come from customers who have to be acquired,
retained make purchases and have spend associated with those practices and so a typical Wall Street analyst will,
look at historical revenues the bring in macro variables and use that to help inform of view as to what revenues will be in the future and ultimately that revenue forecast will drive the DCF model or the ebitda forecast.
And over saying is.
If the company has a lot or even even a little customer data that they’ve disclosed let’s bring that into and in marketing,
we spent so much time and energy building these predictive models for customers will do and it’s just basically saying it’s use those predictive models that are super well validated from within marketing.
You do that Revenue projection just a bit better and do it from the bottoms up instead of doing it purely from the top down.
[9:40] So you’re essentially bringing customers into the valuation discussion crazy,
it’s amazing sometimes don’t you wonder like why no one’s done this before no offense but like so he sings seems so obvious in hindsight but no one you know it just like not a common thing.
[9:55] Yeah that and this is video clip that will sometimes show of Jim Cramer talking about this work yet,
he brought up and spent a bunch of time on our way Fair analysis and he’s like what’s so special about this you know academic research where these academics doing well they they try to put a value on the customer,
and they compare how much you spend to acquire the customer to how much he get after the customers require you like.
Duh seems kind of sensible to me but but it hadn’t been done before and I think I think that was the real opportunity.
[10:30] Yeah I think the first time it hit my radar is you wrote a really good article about Blue Apron so they were one of the you know they have this huge valuation they had filed their S1 and then you put out you know I’ll use the word scathing but I think it was like,
that that may imply something that’s not there a surprising analysis around their unit economics is that kind of the first time that that that really hit the the radar.
[10:56] That’s the first time it really got mainstream attention.
[11:00] Yeah so for listeners that didn’t see that maybe give a brief summary of what you discovered when you kind of peeled onion on the customer metrics that were in this one.
[11:09] Yeah basically the company was growing really quickly and it’s something like a hundred percent Revenue growth you know year-on-year and,
they didn’t disclose a whole lot about customer churn and I was like huh that’s interesting for a subscription business you think they would put something about that in the filing and so,
the interesting what thing was that even though they didn’t put anything about customer churn they didn’t disclose a number of other scraps and so,
basically what I did was use the methodology that I just published and use that to kind of triangulate my way back into what the company’s retention curve Wise from all those different scraps that they put into their,
cipo prospectus and and you’re right near the conclusion was kind of damning that something like seventy percent of the customers churn after six months.
And you know obviously the implication being that they were acquiring a lot of customers I think on promotion and.
[12:08] And they just weren’t staying and and the other kind of,
even more damaging data point was that even though they were growing really quickly their marketing spend was growing even more quickly.
Then that and so essentially what I had inferred from the model was that their acquisition cost used to be something on the order of 60 dollars,
and it’s something like doubled you know in the run-up to the IPO.
So yeah they were buying Revenue growth so they showed strong top-line growth but the underlying fundamentals of the business that gotten significantly worse that they were actually,
reasonably profitable at you call it a $60 CAC but if you double that you know it just makes things a lot worse on a per customer profitability basis.
losing money to acquire the customer and then making it up and scale is never you know I think we always call that the pets.com business model but somehow chewy got out of that we’ll talk about that later
so I think the finish the story I think I think
everyone said that you were crazy your analysis was dumb this is again me as a third party watching this from afar you know they had a huge IPO and then suddenly I don’t know how many quarters it took but suddenly
the Dynamics you had anticipated came true and that must have been kind of self must have been interesting to be proven right by that.
[13:35] Yeah it was kind of a surreal experience the most surreal was we were going on a vacation and I just remember looking at my phone you know we just were having lunch outside of a grocery store.
And that post had just gone viral it ended up getting like.
I don’t know we broadcasted whatever the term is unlike a hundred different websites and and,
of all of the bases all sorts of like LinkedIn comments and all sorts of other engagement measures they were all kind of hitting at the same time and I had never experienced anything like that before.
[14:16] Yeah so.
[14:18] You’re like maybe yeah awesome so so I’ll kick it over to Jason I’m sure you have some follow-ups on this.
[14:29] Yeah I’m always saying this tongue-in-cheek but like it turns out that the one flaw in your whole model is you didn’t factor covid into the blue apron.
[14:40] Yeah I know I always say if we were in January there’s nothing that we would have not predicted covid so it’s no Magic Bullet.
[14:53] But I do feel like they are one of those companies that has at least had a tertiary benefit from from the current climate.
[15:03] Yeah I think that one other fish related point is there’s a distinction between the predictions and the framework,
and I think at the end of the day no one can argue the framework has to be true.
And even the covid Boost that they’re getting I think the framework can be super helpful in thinking about that is it coming from repeaters who are just repeating more or is it coming from a whole bunch of new people that are going to stay.
So so the framework always has to be true it just provides this additional Dimension but our predictions that’s a function of the model of the data that’s available and obviously of,
things like covid happening.
[15:45] The thing that must be surreal is I got the like you I have a weird Hobby and that I love to read us once so I think I think the three of us kind of are probably only,
people that have that hobby but so I was reading to stitch fix that’s why I was like you know
I wonder what kind of churn they’re going to give and then they had all this cohort analysis detailed turn now since I was like wow the Blue Apron dude like totally has changed the disclosures around this stuff you know I don’t know if you viewed it positively or negative but it was like really fascinating where you can tell that people are like
all right people are going to look at these,
there’s no way for us to hide what’s going on in here so we might as well reveal at least what we think are the good aspects of these underlying metrics I thought it was pretty interesting that it felt like you had some role in kind of making that happen so I was pretty cool.
[16:33] Yeah they put a lot more in instead of definitely hats off to them I would have wished and so after they had filed their ass when I have acid was Point through that thing very carefully to
I wish that they had something like cohorted revenues over time if they put something in like that then,
for sure you would have seen an analysis from for me / just the reason we didn’t do one was because they there,
they’re non-subscription enough that I wouldn’t feel comfortable modeling them as a subscription business and and it wasn’t quite enough data,
to fully immuno account for all the facets of there being a non-subscription business.
[17:15] It’s probably funny so on the other side that’s probably what they’re going for they’re like how do we how do we do this so that Dan doesn’t write a paper on,
not not that would be negative or positive but you know there’s the the Blue Apron case study was not a on the other side of the table you probably wouldn’t want you know that happens.
[17:33] I flip it around and paper number three so you know
it is paper number one was all right let’s lay out the framework for subscription businesses so this nails down to telcos the Jim’s the blue aprons of the world the second one was all right let’s lay out the framework for non-subscription so these are all the e-commerce retailers,
and then the third one was let’s lay out a model for.
Businesses where we’re not only incorporating SEC disclosures like whatever we find in S1 but also,
credit card panel data which the hedge funds are all buying consuming voraciously and now that that their credit card panel data is wonderful for Stitch fix in particular its.
The panel seems to be quite representative of their customer base and in so,
I think that that’s kind of one of the emerging Frontiers for this whole area is it can we be able to incorporate other data sources to,
to be able to kind of do this exercise for more companies or you just have more confidence in the results because we have more data at our disposal.
[18:36] Yet the thing I found so I did an IPO of Channel advisor in the thing I found really weird is you go public and you know you’re going to be doing all this transparency but all your advisers are telling you
to be really careful with what you disclose because you know if you just there’s this feeling that all the stuff you disclosed and that’s one you’re going to have to disclose forever and there may be some reason where you want to wind down a business line or
pandemic hits and some of these metrics kind of Swing different ways so so in the operation side everyone’s giving you this advice to minimize what you disclose which I found as a you know,
as a private company it was oddly kind of the opposite of what I thought being public would be like so it’s interesting to be on the other side of the table from of that stuff.
[19:26] Yeah we’re starting here bit more of that too and certainly we’ve heard the same thing like anything can and will be used against you and so so there’s kind of this risk-reward asymmetry that incentivizes companies to try and discuss as little as possible,
so and certainly I think that there’s kind of a fine balance to be drawn where
you know I’ll be the first to say this is a certain line past which it is competitively sensitive and you don’t want to necessarily open up the kimono so all your competitors know
exactly what you’re doing but I think there is kind of a middle ground where there are measures that companies can put in that.
They’re very not competitively sensitive but super informative they tell investors a whole heck of a lot of information about you know how the companies doing.
And and there’s small in number so we’re not asking for you know a dozen different things you were just asking for like three things,
I think that hopefully is how we can help kind of move the conversation forward that that.
We put something out there but we make sure that it’s reasonable and it’s not overly costly to to the disclosure.
[20:38] And I do want to double click on that just a little bit like it does seem like so there’s a,
a fundamental part of your framework the customer cohort chart this III and it do I have this right like it does seem like some companies are starting to include C 3s in their disclosures.
[20:56] It shows up a lot more than I thought that it either it’s that it shows up a lot more than I thought that it did or that,
yeah maybe if you know we’ve had some small influence that more companies are disclosing because we’re yelling so loud maybe some combination of the two.
Actually Scott I think it goes back to one of the other points you raised I would love to see more companies disclosing that data and non S1 filings I feel like,
there is now at least a couple dozen companies that have put that in the S1,
as soon as they go public and they start filing the case in the queues OR investor presentations I stop seeing it it’s like two companies I know of it still disclose it.
[21:40] Yes so the advisors that give you all these case studies of where it has been companies in the but so classic ones Twitter right so so Facebook got out first and they started talking about it may use monthly active users so then Twitter launched and they just kind of went with that kpi
and then that kpi slow down on them very quickly whereas Facebook’s accelerated and everyone always uses that as you know if they hadn’t disclosed that
and then what happens is the other thing that I see that super surprise me first time going public was all the short hedge funds and some of the nasty tricks they do so they’ll take any of these metrics you put out there
that could be cast in a bad light and they’ll use them against you to create a short trap kind of a thing so so there’s all these case studies of that and then you know we’ve fallen into,
over the years you’re just shocked by the behavior that goes on with
with some of these these crazy firms I guess I was super naive that I thought it was more like VCS but at this whole super high level where everyone’s going to be like you know I’m Fidelity and I’m really on board with your company for the next 10 years there is that but it
you know right now it seems like it’s the minority versus the majority is a lot of these kind of long-short hedge funds that do all kinds of wacky stuff.
[22:50] Yeah yeah it’s nice.
[22:52] Yeah yeah.
[22:54] But so Dan you know what would be helpful for some of our listeners that may not be as familiar with clv analysis and some of your work can you like,
this is hard on a podcast can you paint us a word picture of what a cohort analysis is and what that C3 looks like.
[23:13] Yes of course the first Steve this may be the easier one is the C3 that’s simply saying you know if you if you open up a 10K,
it’s going to show annual sales year by year you know so 2015 16 17 18 19.
[23:30] This would be the same except it’s in a chart format where the height of the bar is the amount of total revenue.
But it’s tax that so you kind of brace it down by acquisition cohort so you know for a company that,
imagine it company was the first went public in 2016 and now we’re here in 2020,
they’re at here’s our sales in 2020,
here’s how much came from customers that were acquired in 2016 here’s how much came from customers and required 2017 2018 2019 and so on.
So it’s basically chopping up that Revenue bar into acquisition cohorts and showing that over time and what it allows investors to see is.
When a company acquires a group of users.
How much revenue is that company getting from those users in future years as it going up is it going down and if it’s a b2c business you kind of expect it to move move down.
And hope that is that doesn’t move down very much in other sectors like software as a service businesses typically if you’re seeing a C3 chart,
you probably seeing expansion over time they acquire a bunch of customers and then in future years to getting more revenue from those same customers than they did in the previous year.
So yes it is a whole lot of information you can get from a C3 in conjunction with everything else that does companies tend to provide.
[24:59] And it goes back to that I think to the first question of what is a proper cohort analysis and it really is just that it’s saying let’s look at let’s not just look at everything that happened in 2020.
Let’s look at things by acquisition cohort you know let’s eundel together all the people who are first acquired in 2016 and say,
how good were they and then let’s compare it to all the people that were required in 2017 you have good with a and if you repeat that exercise across all these years.
This whole new level of understanding of how healthy a businesses.
[25:37] So for like an e-commerce business where you’re not going to have a huge let’s take subscription e-commerce businesses out of it like let’s say a Macy’s or someone like that that has you know
just kind of a more transactional model what are you expecting that for your to look like like what’s a really good looking at wind what’s a terrible one.
[25:56] Yeah General generally in transactional business like Macy’s or any other you know B to C typically customers were melting Ice Cube and.
And so you’d be pretty happy if you know four years out you’re still getting,
twenty percent of the revenue that you had gotten when you first acquired those users.
But they’ll drop off pretty quick so you know so certainly.
My general Pryor is is that Revenue retention tends to be on the very low side unless you’re truly one of the exceptional retailers.
[26:38] Have you ever done it for Amazon.
[26:42] We have not because they have really Rain back there disclosures unfortunately.
The other yeah the other issue with them yeah so they disclose like active users but they disclosed nothing about the number of customers they’ve acquired in different years.
Obviously if we even if we did have the information probably right now it’s like zero because everyone’s been acquired but the other wrinkle with them is I think you many people would argue they’re making most of their cash flow from there,
from the cloud computing business and so.
Retail business is certainly it’s an important piece I think you know a lot of people short change it because they don’t take into account the you know- working Financial working capital position that they have.
But still there’s so much else to their business that it is a little bit tricky.
[27:39] And I like I do like obviously we’ve been focused on company valuations which is a super interesting use case and obviously quite important but.
Company valuation is far from the only reason you’d want to be doing a cohort analysis if your acquisition cohort analysis if you’re a company right like isn’t it,
even if you’re getting if you’re a private company and you’re not going to disclose anything it seems like there’s huge benefits to understanding the value you’re getting out of those Acquisitions and.
Helps you plan future Investments no.
[28:15] Oh tremendously so yeah and actually said for example the the marketing use cases I think are at least is compelling to marketers as
yes it is from a valuation perspective to the CFO yes I kind of I think of
this way of looking at the world is kind of like the the translator that allows marketers to speak with the finance people and have a common language between,
and I think it can allow marketers to communicate the value that they’re creating,
in a way that Finance people would would respect and understand.
And in Reverse yes I think you finance people can then you communicate that on to their investors which increasingly they’re having to so so suddenly I think,
as these ideas take hold a bit more it’s as if the CMO becomes a lot more powerful because they’re kind of the trusted advisor they can actually really explain.
What the heck is going on with the customer base in a way that the CFO is just not going to be able to but at the same time they’re going to be a lot more accountable because suddenly,
everyone is really obsessing over things like the retention curve which are probably a little high level for your typical CMO and they typically are thinking about.
More tactical measures.
[29:42] Yeah and I if you don’t mind I would like to double click on that a little bit just a side note for listeners it’s funny we often call those the visual cohort analysis we caught a wedding cake.
Um which I think is like a good mental image right like because you you see all these new new colored layers of.
Different acquisition cohort stacked on top of each other and if things are going well the layers get like thicker in the in the middle over time.
Is that is that an industry term or did I make that up.
[30:18] You know I had never heard of the term before.
[30:21] All right well I we use it with multiple clients so I don’t know yeah so you.
[30:26] I like it though.
[30:27] Dan you can have it for free but in exchange you can settle an age-old question for me customer lifetime value clv lifetime value LTV,
I hear people use those acronyms interchangeably like are they different and is there one that you officially prefer.
[30:47] I yeah I think that there is a lot of questions about you know what should be defined as what I’ve traditionally defined those is being equivalent to each other.
But distinction that I draw actually is one that I’ve I haven’t really heard other people draw which is COV or LTV versus the post acquisition value of a customer so.
To me I think the to two key components of a customer’s value or how much you spent to bring them in the door and that’s the CAC.
And then all the value that you get after the required and to me I call that the post acquisition value of the customer,
and so if you take the P AV and you subtract off the CAC.
That gets me the customer lifetime value but there’s just so many people who actually would say that clv is p AV and and they’ll have no definition for clv.
So so I think you have one of the first things that I’m really hoping that we can do it’s almost the simplest thing it’s just,
let’s agree on some common common definitions for these terms you know I think that everyone would benefit and to be a lot less confusion when we’re all talking about,
these terms and and potentially having different ideas in our heads as to what they actually mean.
[32:08] Yeah no I think that would be super helpful because that it is,
I you know in the virtue of my job I go into a lot of different clients in the vernacular is totally different and this you met your eyes may roll in the back of your head but I would even say like a monk my client base.
[32:29] Yeah one also clv I’ve so frequently see people Computing it just off of sales they’ll not even factor in causing.
[32:37] Yeah it’s Revenue it’s like customer lifetime Revenue not customer lifetime value right there.
[32:42] Yeah you know finite Horizon forecast and you know just the list goes on and still all the different ways you can kind of screw it up in my view.
[32:52] So I have this kind of simple mental picture of how this whole discipline involved and I’d love for you to confirm that I have it right or correct me if I’m wrong,
um but I sort of imagined that in the early days of thinking about COV that it was primarily a marketing kpi,
and then it feels to me like it evolved into being in really good mature companies it evolved into being a corporate kpi,
and then you know largely because of your your paper and and blue not Blue Apron going viral.
Now it’s become a corporate valuation tool like is that is that the matriculation then it sort of food through our time I’m making that up.
[33:34] I think it’s definitely the case that COV has been born and raised a marketing marketing kpi.
Yeah and I think now we are seeing a gradual progression that it’s showing up more in investor decks which has been super heartening to see.
[33:52] In terms of the link to cut the corporate valuation so our work will very frequently talk about customer lifetime value.
But usually it’s kind of a summarization of like the unit economic health of the firm it’s obviously a really important one.
But but actually we kind of focus on on this other thing that,
I think some people will call it customer Equity you know I’ll call it customer base corporate valuation was really drawn this distinction between,
you kind of a per customer measure of profitability and the overall value that’s being created and.
In Canada the example that I often give is if you wanted to maximize the clv of your business.
You should go after this super tiny Market where this is like a few super good customers in it and and they’ll all be great you know but there’s so few of them that you leaving money on the table you know so,
it’s kind of what we want to maximize this kind of like P times Q you know like the quality times the quantity and.
And so I’ll actually kind of have this notion of the five Horsemen of CBC TV.
And that’s actually you know what would companies should be striving to optimize.
[35:15] I love that and I I’m a big fan of those sort of false of using a metric as a kpi because per your point like you can just manipulate one of the variables and make it awesome.
I frequently help clients in Pre increase their conversion by just dramatically reducing their traffic to their best customers for example.
The so I and I do have a bone to pick with you and I’ve been really good about trying not to bring it up until now but I just can’t resist.
I primarily work with marketers and in my world like even LTV is a metric is.
A vastly superior metric to what a lot of my clients tend to live in like sadly like I have a lot of clients that.
You have tpi’s around things like Awards and return on ad spend which.
Find abhorrent right and so often we’re trying to move people towards more financial base,
measure right rui measurable quantifiable metrics and you mentioned in the intro that you you started this previous company zodiac,
which actually provided both tools and services that help companies,
make that progression and you don’t know this but I actually prescribed zodiac to a bunch of clients and then you went ahead and sold the company to Nike and they promptly fired all of my clients.
[36:39] Yeah that that was the most difficult part of the sale was honestly we.
We’re academics you know so we we almost feel like this semi-religious you no desire to get people to use customer lifetime value to be using these models and benefiting from them,
instead of kind of get these companies to buy in and then kind of you know have to we didn’t fire them we were forced to.
[37:08] Sure sure no I’m mostly nobody blames you for doing,
in your own best economic intro I’m teasing you but it was like it,
useful tool and I am curious and it’s fine if you want to pass on the question but there are some other companies that have emerged.
I wouldn’t say have the exact same offering that zodiac had but.
Some sort of overlapping value prop and so I think if companies like ambition data or dynamic action and I’m just curious if you’ve ever looked at them or or even better review you’ve come across any other companies that you think are doing a good job and that’s.
[37:45] Yeah thankfully a lot of them are friends of ours so so ambition data Allison heart cells the good friend
they do some good work there certainly I think they’re more tactically oriented and zodiac was but I think their philosophies are
you’re very consistent so both Peter fader and myself we’ve been on under podcast as well,
retina that AI is another one that I like with the what they do they basically have a version of a probabilistic model for how customers behave and,
and they’ll use that to help you know oftentimes marketing analytics departments you make acquisition retention decisions but I wouldn’t also leave out Theta so you clearly I’m not here to,
that’s a pitch the company but I’d say about half of our revenue is actually coming from corporates directly and in while we’re not helping the marketing department make those tactical acquisition retention decisions,
we do provide kind of the,
a lot of the Machinery that we use to make the predictions is very similar or even better than Zodiacs we use it to obviously summarize how the business is doing in terms of.
[39:02] Clv in CAC over time,
but then also slice that by you know things like acquisition Channel and so to the extent that you want those very highly validated predictions to,
to see where you’re getting the highest return on investment you say by acquisition Channel this would would give you that so.
[39:23] Very cool okay,
so and Scott’s chomping at the bit to get back into the conversation but I did want to I feel like I haven’t this limited window to learn some stuff.
Eight sometimes a knock on the like so one of the things about the customer base valuation is it,
it’s a very bottom of the funnel monetizing the customer and therefore this is how valuable that acquisition channel was or how they both companies or whatever else and,
the old-school CMOS I work with like when we start talking about those kinds of processes,
they quickly go to yeah Jason but that doesn’t really capture my long-term brand Equity like I’m building this value that doesn’t show up in that number,
and I’m imagining you you have to heard that before and debunk.
[40:15] Yeah I love that question because in general and this is where I will get a little bit controversial again all the revenue has to come from customers making purchases and so if you believe in that,
accounting identity which hopefully that’s completely uncontroversial then,
then you have to kind of buy into the notion that it all comes down to acquisition retention ordering and spend and then variable profits and so so sick to kind of flip it back on on the old-school CFO yeah I’d say.
If they’re spending on things that aren’t generating any measurable effect on those five Horsemen if CV CV,
then it’s worthless completely worthless but to then give you know a little hat tip to the old school or I think what what they may be trying to say is that.
I can make an investment today and I may not necessarily see the long term effect of that until three four years from now and that you know.
That the long-term retention of those customers will be better because of the investment that I’m making.
I think that’s a very important distinction because it’s saying that you can look at and just focus a hundred percent of your attention on the CB CB framework.
It’s just an empirical question of how we can be able to measure its effects rather than saying you know actually we need to focus on brand Equity to.
[41:44] Yeah and ironically like that cohort analysis is,
is validating like when you know when it’s done well it’s validating the Investments made in that long-term brand Equity right because they they show up in like subsequent years value for those cohorts.
[42:02] Exactly yep.
[42:03] The Indian one more totally wonky one so so again old school seeing those like me and where should we put our marketing dollars and in particularly like that we all have this debate.
What’s what should we be putting above the line IE what should we be spending to build brand Equity versus what you know should we be spending to drive actual activation.
Things got and I talked about all the time like e-commerce and those sort of things and like historically like I mean from the 1970s,
marketers use this media mix modeling which is pretty archaic and lately like as I work with all these ad agencies,
the the academics that come up constantly are these guys and I’ve never met them less Bennett and Peter feel they’ve are you even Vaguely Familiar with him.
[42:56] No you’re not.
[42:58] Well then we’ll skip it but suffice it to say they did a quantitative analysis of a bunch of companies in found that in general the best like,
mix of investment was 60% brand 40% activation and therefore there are a ton of like quite large.
Marketing Enterprises with very large budgets that Loosely follow that parameter and it just seems,
too simple to be true to me so I was just curious but I’ll let you take a pass on that and I’ll let Scott jump back in.
[43:35] Yeah this is so just kind of
apply this to an interesting argument so two of my favorite followers on Twitter are web he’s been on the show and then this guy digitally native I forget his name he’s in Austin,
they’re constantly going back and forth over well first of all they really focus on the realm of digitally native vertical Brands so I don’t know if you’ve dug into that there and fortunately haven’t been a lot of,
IPOs in there so there may be a lack of data on it but the kind of go in the circular argument I’ll try to do my best of kind of
figuring it out so digitally native dude will say the one metric you should focus on as a digitally native or co-brand is gross margin
and then now then web comes in and says Nope
it’s got to be so first of all he doesn’t like it when companies raise Capital so it’s like it’s got to be bootstrapped and the only way to bootstrap it is cackle TV and then they then the kind of wheel spins around and goes back and forth back and forth do you have a point of view on that.
[44:39] Yeah I kind of go back to to me the ultimate goal is customer base corporate valuation now I would say that does kind of lean more towards cackle TV,
but I’m not sure that the distinction needs to be that you know that big because ultimately you know a higher gross margin is going to drive.
Higher lifetime value all else being equal so certainly.
But even their gross margin is not the only,
component of variable margin yeah I think that if you really binds the notion that lifetime value is important well the profit margin that you use in that calculation should be the effect of The fully-loaded effective variable,
profit margin and so you should be factoring in,
this is going to be probably very common knowledge to you both but you things like fulfillment expenses and merchant processing fees which often times they’re not included in cost of goods sold they’re included in.
In an operating expenses,
so we want to put those in as well but I’d also include effectively variable indirect expenses to so even things like.
This is going to sound totally brutal and conservative but even things like accounting expense.
[46:01] New companies as they grow they need to hire more accountants and even companies like Microsoft spend ten percent of their sales.
On expenses like that and so so what I want is I want that lifetime value figure to represent.
If it’s positive that means there’s a path to profitability and if it’s negative there is not a pilot at the profitability and you won’t get that if you’re using gross margin as your margin.
[46:29] So then so tactically how do I allocate that like I just divide by the number of customers acquired over that period and all my costs and that period.
[46:38] Yeah there’s a few different ways you could do it yeah let’s say the kludgy is simplest way would be take all of the expenses that are not direct expenses.
And in regress them against sales,
and with that can help you get a sense for is the relationship between those expenses and how they grow as you Revenue grows obviously if you’re inside the company though oftentimes companies especially if they’re young,
they’ll kind of pre build and so you may see operating expenses grow quickly then but it’s not because those expenses are variable they’re just kind of building for the future so that’s really where I think if,
if you’re an inside operator you have a much better view of that,
as an outsider I think conservatively most any company can simply at least at the very start just knock off five percent of sales and just say,
you know probably at least that much is going to be effectively variable indirect expense and.
And then just you know kind of continue to run the analysis is you may otherwise have done.
[47:47] Got it so sokak is easy to get your head around and then LTV you’re essentially saying LTV should almost be like cash flow.
[47:54] High LTV should be the net present value of all the future variable profits after a customer’s acquired yeah so yeah as having to kind of peel that one back but I know.
[48:08] I don’t think anyone’s calculating it that way that’s why it’s funny.
[48:11] This this is why I like Theta is b or zodiac is because they do it for you they provide the mathematical.
[48:19] And will you know we’re totally an open book you know will show you the academic papers so hopefully I’ve been kind of by into exactly how we’re going about the you know the calculations that were going about but,
yeah I mean at some point I think the math it’s a very hard prediction problem yes a to be able to have someone.
We’ve now done probably 250 different you know paid engagements on behalf of 250 different firms.
So you kind of develop that dirt under the fingernails that could be hard if you’re just a really smart operator who’s building a business and don’t don’t even have the budget necessarily for you know much or any data science team.
[49:02] Yeah I’m a big study of Amazon if you haven’t figured that out yet and it’s always funny because,
people always ask Jeff Bezos these things he always comes back to cash flow and I almost wonder if he kind of like intuitively got to a similar place where you have where you know one of his answers will be
customers you know I can’t take a gross margin to the bank you know I can’t take fifty percent to the bank
when in the early days when people accused him of being a super low margin business
and or like with Amazon Prime they thought he was crazy and I think he was thinking I think he was way ahead of the thinking here,
what do you think about do you agree with that.
[49:46] Yeah I think a lot of people they’ll look at these highly free cash flow negative digital companies often times,
and I’ll say well you know yeah but but Amazon and if you look back carefully at Amazon,
typically those comparisons are very bad you know that I think it was in the Amazon second year you know maybe it’s there that it was operating cash flow positive and,
it’s the even the even though it took them a while longer to become Gap profitable.
Who cares about Gap if you’re bringing in the cash flow you know that that’s ultimately what what drives the value of the firm and keeps the lights on so,
so I think they did a lot of things right that are still under appreciated and have still led to a lot of confusion with this emerging crop of,
fast-growing money-losing companies.
[50:42] That one random observation is you so I think you said in your bio you were at like a hedge fund doing analysis of things but Jeff Bezos was to write wasn’t that where you kind of started is there is there something that you think
cut came out of that where you both kind of saw this this kind of light bulb moment that you know this is the ultimate metric for for these kind of businesses.
[51:05] You know that I think it was a de Shaw and I forget what role he he was at the firm butt,
I would say there is something that actually this goes back to zodiac Theta,
Finance people we’ve often done in the questions that you find the comparison yet selling to a marketing person versus selling to a finance person and I’ll often say selling to the finance person is easier actually,
even though you’re presenting them with this Mark ostensibly marketing way of looking at the world ultimately its Net Present Value,
and they just live and breathe that you know they’ve been doing that for probably since they were an undergrad you know whereas marketing people sometimes have sometimes happen.
And it’s to a finance person I think they will get a lot of this and they’ll immediately see the analogy to project finance that project financing the you spend money on a project you’ve got this,
you know you think about payback periods you think about the net present value of the project you think about the internal rate of return,
that’s just how they think about their project and so if you just replace project with customer Suddenly It’s like a light bulb goes off and they say oh you know that that totally makes sense the customer is my project.
Yes I think that to them this is all quite natural,
to marketing people there could be more of an education that that’s required to kind of get them where they need to be.
[52:31] I will totally buy that I do have to point out early in the show I complimented you on monetizing your academic background but now that Scott’s comparing you to Jeff Bezos you probably have a little ground to make up.
[52:43] Definitely a loser there to him.
[52:47] Jason builds you up I tear you down it’s part of its are good cop bad company.
[52:52] Pivoting a little bit I’m curious like if you so a bunch of the company is in our space we talk about all the time,
and you know where there is some debate about how sound the unit economics are we talk a lot about companies like Shopify and,
Peloton and chewy why do you like look any of those companies do any of them provide enough data that you kind of formed an opinion.
[53:21] Yeah actually all three I haven’t done a formal customer base corporate valuation of Shopify but I’d love to and,
and they’re actually one of the firm’s where I’ve seen a customer cohort chart outside of the s-1 filing and as you can imagine.
As you were alluding to Scott when companies disclose these things it’s probably because it looks good and and I definitely was the case with Shopify that there there C3 looks amazing,
and in there an interesting case because you know they’re kind of a business in a box whatever the,
terminology is now they’ll have a lot of companies that,
yeah they go kaput they go out of business but they get so much incremental business from those who survived that they see very strong Revenue retention over time.
So you know I haven’t I’ll be the first to say I haven’t been out the math is to say what their marketing Roi is but but it must be quite good.
[54:31] You know I don’t know how like how close you father but like their CAC is actually quite low so that helps too.
[54:38] I don’t think they do any marketing that’s another thing that they’ve always said that they let the product do the marketing and yeah.
[54:44] Yeah so even better you know it’s really it’s it so I think you then it does become a question of valuation but even the valuation question you become some really hard I was actually just tweeting about this a couple days ago that.
If you have very strong Revenue retention presumably you’re earning a very high return on your marketing investment and,
and is a very strong analogy between marketing Roi and the return on invest the marginal return on invested Capital to business.
So for business like Shopify I be astounded if their marginal return on investment wasn’t,
at least an order of magnitude higher than their weighted average cost of capital like the required rate of return that investors demand of them to supply them with the capital that they have.
And in theory if you are if your return on invested capital,
is permanently above your whack there’s no you would deserve an infinite valuation.
[55:51] I think they’re getting there.
[55:52] Yeah it’s so so I’ll be the first to say that but I would say for Shopify there is a valuation question that we all know mean reversion is is a reality and so when,
you know when those economic start to kind of go back to levels that are more in line with competition.
You know that is that on that out and so I think that’s kind of the open question there so yeah valuation it’s.
It’s not purely a function of current period clv you know I wish it was that easy but but it’s not.
[56:33] It was super easy everyone would be doing it so where would the fun in that be.
Have you up to Peloton at all maybe free covid or assume post covid there now like the next trillion dollar.
[56:47] Yes I again yeah I’m kind of an s-1 geek like you both so when they drop the S one I looked at that one really carefully and especially because there was a lot of controversy I know if you are following this the time,
that that their churn rate was just about to spike and,
and they were timing the IPO it just at the point where a whole bunch of these,
prepaid you know customers are locked in for two three years boom you know now they IPL all those things are going to move to month-to-month contracts and a whole bunch of people are going to turn in there you know.
Average turn rates going to quadruple or even more and.
[57:32] Yes I felt obligated to kind of jump in to see what the heck was going on and it’s I posted this analysis on LinkedIn hints and fully transparent not even provided the spreadsheet showing all of the calculations just so that people could,
see or point out if I’m wrong and,
in the main conclusion that I came to was now you know they’re their turn seems pretty low and there’s no Smoking Gun it should probably stay low and.
And I would say even pre covid thankfully that seem to Bear out as being true.
So we didn’t go all the way to I didn’t go all the way to valuation but it certainly you have I’d run like hardcore statistical models on them.
[58:18] Gotcha and then I’m assuming about 400 billion dollars in value transferred from Jim’s to them as a result of the shelter in place orders.
[58:26] Yeah they definitely benefited so.
[58:28] It’s just a bike with an iPad strapped to it who would have thought.
[58:32] Yeah there’s still it’s amazing in this thing again it goes back to Blue Apron there they’re always the haters.
And and for Peloton there was still a whole bunch of people who argued that you know because of the economic contraction unemployment 15%.
Is this super expensive bike are people that are pay two thousand three hundred bucks for a bike you know.
And in that has I was on the opposite side of that trade yeah I was openly in webinar saying.
Don’t be surprised at how many how many wealthy people are retaining their jobs and buying peloton’s now and and yeah it seems like that that’s that’s played out as well.
[59:18] Oh yeah and and now they all those wealthy people have the capex invested in that bike and they’re presumably less likely to renew their gym membership when they’re able.
[59:29] Yeah yep and I think that’s one of the arguments for why why their turn should remain generally quite low you know is that people are paying $2,300 for a bike,
you know are they willing to Pony up the 30 bucks or whatever it is a month for the you know for the subscription.
Definitely you know they’ve huge sunk cost fallacy but you know still people fall for that that’s the oldest trick in the book.
[59:58] Yeah yeah I think that’s going to be our next podcast is all about those cognitive biases so that’ll be a perfect transition there and then chewy have you acted chewy at all.
[1:00:08] I have not looked at you we personally so I have it’s been nice to see they’re now more and more people are kind of doing their own cbcb analyses and so there was one super smart person who had.
Done some interesting analysis on them it ended up his conclusion was bearish that.
Things did not look good and I also I do agree that the way that they Define the proportion of people who are unlike auto-ship or whatever they call that program is is is very aggressive but.
But I actually I haven’t done a CBC analysis.
[1:00:48] Okay mildly interesting like they had their their first earnings call Post.
Covid and you know of course reminder like,
their revenue growth has been wildly awesome and they’re one of the few direct to Consumer companies that you know his vastly exceeded a billion dollars in sales they’re really struggling to be profitable,
the covid quarter was their first quarter where they had a profitable ibadah but earnings was still negative but which is why I was curious if you see,
like you know are they just on this Wayfarer style treadmill where they can never make money or or you know is there a model where they scale out of that but one of the things that was interesting they mentioned is,
me and 1.6 million new pet owners adopted a pet in covid and we think the covid cohort for us is worth 90 million dollars this quarter like I just that was it like it wasn’t so much I mean it was,
they were they didn’t provide data but they had a narrative around an acquisition based cohort in there there.
[1:01:54] Wow yeah I was about to say that they’re going to argue with all the pets parts of the world shut down that all that business is now increasingly going to the chewy but.
[1:02:05] Yeah well I think there’s some there is some data there right like pre covid 22% of,
of pet spending was e-commerce and you know in covid it’s like 35% so like all those new pet owners who I clearly you know were born digital,
you know suppliers for their pet food and all that stuff.
[1:02:25] Yeah that’s like a free gift that covid has given to these companies.
[1:02:28] Oh my gosh yeah there’s a lot of free gifts and a lot of free I don’t know what the right.
[1:02:34] Fold in the air colder in the star.
[1:02:36] Yeah exactly that have been like disproportionately handed out its kind of kind of brutal with the winners and losers.
[1:02:44] Not just disproportionate but in some sense random,
is that a lot of otherwise great companies and you know just so happens well you were a mobile gaming company so you will be a winner you were you were an underwear Stellar you will be a loser but you.
[1:03:01] Except if your underwear seller that also sells lettuce in which case you’re you’re a winner.
Like that those are the weird distinctions right like.
[1:03:10] Yeah the milk is to go back to Blue Apron.
[1:03:14] Yeah I feel like I saw you on one of the new shows talking about Wayfarer and covid did you like you want to recap your your thought process there.
[1:03:25] Yeah yes it’s obviously I’ve been falling Wayfarer for a while now and,
you know I’ve been probably as much press on them as with blue apron and.
And they had first finally it was as if the writing was finally on the wall they said they.
The CEO had even said we were growing too quickly and we’re going to now lay off a bunch of people and move to more you know sustainable growth.
[1:03:54] And then covid and basically you know I was speaking with someone from CNBC it’s ended up being featured in her article but it’s something like 86 percent of all home good sales,
had been brick and mortar and so suddenly covid you shut all that down and you know this little slice you know the other 14%.
Sunny they’re the only game in town and not only that.
Wayfarers biggest competitor with in HomeGoods had been Amazon and Amazon now is prioritizing essential Goods so there are not focusing a lot on HomeGoods.
So they’re not only kind of the only game in town when you compare them to the brick-and-mortar players but they’re also one of the only games in town even on online so so they’ve seen their growth go from something like.
20% or 25% to 90% And presumably that’s all,
I would imagine it’s quite profitable growth that there’s just a lot of people now who are organically coming to Wayfair and making the purchases are because they they want that new chair to put in their work from home office,
so yes they really they benefited on all sides from from covid which you know hats off to them I’m happy that it’s been.
It’s been good for them.
[1:05:20] Yeah it’s going to be in a mean I obviously we all wish all these companies the best it’s going to be interesting like,
hey they’ve got to be able to be get profitable on that on that revenue or like certainly it’s going to be scary and hopefully they can they can leverage all those new customers into a long-term viable.
[1:05:38] I think the long game is the big question that I have and still to me now it’s just an open question I feel like you thankfully.
Yeah I feel like our thesis was validated the stock actually fell to within our valuation range before you know things went crazy with covid so I feel like I don’t have a whole lot of skin in the game right now,
but I do still wonder those stores will eventually come back online some of them are closed permanently like Pier One is not a company called Tuesday they are liquidating you know so so that Supply is not coming back on the market but,
you know we will still see a lot of you know home goods stores reopening and then Amazon is going to reprioritize furniture and so,
I think there is a question of how much of the growth that we’re seeing Wayfarer how much if it’s going to stick.
And how much of it will go back to what we had seen before.
Yeah I kind of think it’s a question of how severe covid it’s going to be yeah they did a certain variables that I just don’t have a good sense for right now but I think that that will be a big part of the valuation story.
[1:06:46] No I think you’re right like I you know it’s going to be interesting because I feel like a lot more competition than we realize right now is going to go away like of the traditional competition because.
There’s a bunch of Independence that you know have become insolvent and we just don’t hear about them but I mean aggregate their 25% of the furniture market there’s a lot of regional chains that.
You know just haven’t bothered to file bankruptcy yet because they can’t run a liquidation sale right now it’s kind of hard to declare bankruptcy at the moment so that’s going to happen but then for your point,
Amazon and you know the most healthy well resource of the surviving retailers as you know are all going to want to grab that share nobody’s going to want to just advocated.
The Wayfarer so it’s going to be a,
interesting battle to watch play out but Dan that’s going to have to be a good place to leave it because we have slightly exceeded our allotted time but we were enjoying our conversation so much that.
You thought it was well worth it so we really appreciate you taking the time and really enjoy the.
[1:07:47] Yeah thanks thanks again so much for thinking of me and having me on the show this is this is a stuff I stay up to talk about this to anyone who’ll listen so so so thank you it’s been a lot of fun for me too.
[1:07:59] Thanks and we really appreciate it and I think you know my goal is to learn a couple things everyday I think I’ve filled up at least the rest of the month and maybe July so really appreciate it.
[1:08:11] Being too kind but thank you.
[1:08:12] And until next time happy commercing.
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