Nov. 11, 2020

The stats - how to evaluate companies. By Daniel McCarthy

The stats - how to evaluate companies. By Daniel McCarthy

Daniel McCarthy, Director and Co-Founder of Theta Equity Partners and Co-Founder and Chief Statistician of Zodiac acquired by Nike, talks about building and selling companies, how some funds invest based on stats only and how he personally approaches fundraising and investing.

Daniel's LinkedIn: https://www.linkedin.com/in/danielmcc/

Pipe - get access to your annual cashflow today (funds based on stats only): https://www.pipe.com/

Wareclouds: https://www.wareclouds.com/

 


Transcript

And today is a guest speaker, we have Daniel McCarthy Co, founder at sodium. That was acquired by night in 2018.

and currently, he's a director and Co founder at fade equity partners and also an assistant professor of marketing at emery University.

And today we'll talk about both of his current rules, and that previous acquisition by night, how it happened, how he got there. And, of course, we'll talk about fundraising. So, Daniel, let's kick it off by you're giving us some background on yourself and on.

Zodiac yes, it's great to be with you. Yes, as you mentioned, I'm kind of wearing 2 hats now the 1st is as a ivory tower academics. I'm a assistant professor of marketing at emery University.

I teach a class on customer lifetime valuation to undergraduates and MBA students here.

And in addition to that, I also have, I've been bitten by the entrepreneurial bug. So I've started 2 companies 1 of which I'd sold the Nike in March of 2018.

the subsequent month I had started another company called fade equity partners.

Uh, both companies are again, their focus is basically leveraging customer level predictions.

To better understand the health of a company.

Uh, the former company Zodiac, it primarily used customer level predictions to help marketing departments, make tactical marketing decisions so who to send the Mailer to.

And then say to equity partners, it's using similar predictive models, but instead of using it to understand who to send a Mailer to.

It's using it to understand whether say, like, a private equity firm or a venture capital firm should move forward with a an investment in a particular company.

And so the way that we'll go about an analysis like that is basically by better understanding the economic health of the firm. So, what is customer lifetime value? What is CAC how they've been evolving.

Across cohorts and over time and then how is it different across different kind of customer segments or slices say different acquisition channels or what not? So, yes, it's all kind of both my research.

My teaching and the entrepreneurial activities they all revolve around customer level predictions. So, it's really an area that I'm virtually spending all my all my waking hours studying. Nice. That's that's really cool.

So, 1st question is going to be about tomorrow itself. So I personally.

Not not the biggest fan, but I kind of a like, that model of prediction. So let's go a little bit in depth into this. So, how exactly does it work? Do you look at some, you know.

Let's say 10 or 15 or 20 metrics of a firm and you're locate that from us. Can I keep doing well in the upcoming 2 or 3 years? Or is it some somehow different.

Now, the main thing that we, mine is the transaction log, so I'm not a big fan of watch what they say.

I'm a big fan of watch what they do, and basically you can think of customer based corporate valuation as exploiting an accounting identity that all revenue has to come from customers and those customers have to place orders.

And the customers either had to have been acquired in the current period, or they had to been retained from a prior period.

And so basically, we'll take kind of historical data on the flow of customer acquisitions over time. A customer retention, customer, purchasing while customers are with the firm.

And then the amount that spent on purchases and essentially train a series of predictive models off the historical data to predict future acquisition, retention, ordering and spend and so.

It might my pH D was formally in statistics at the Wharton School,
and I found that to be a really helpful background for this sort of work because 1 of the 1st,

things that we'll always do is you don't want to just have to trust the model and so we'll always subjected to very.

In very tough and predictive validation checks when we say, let's leave off the last 6 months, 1, year or 2 years of data. And let's imagine that we didn't get to see it. Let's predict.

What we would have thought would happen over that period of time and then compare our predictions to what we actually observe.

And it's only after we do really well along those predictive validation checks that we would have the confidence that were adequately capturing the.

The behaviors that are worth capturing, got it. Yeah. So if you, if you stick with the model all the time, you will end up like that, that for long term capital management.

That big start by the way everyone who has not heard that story. Definitely read a book. And it is just super fun. So, let's go a little bit even more in depth. How do you extract that information?

Do you just source some particular base, like crunch base or Facebook or where do you get that information on the company?

Or is it, like, when the company applies for funding from the equity partners, they have to submit all the data or how does that data collection basically.

It's a great question. There's kind of 2 main sources and it really depends on the company that we're performing diligence on. The 1st, is we'll often get the data.

Directly or indirectly supplied by the company itself and so you typically, we won't invest ourselves. We're primarily just a research outfit.

But we'll perform this work on behalf of, say, a private equity or venture capital firm and so they'll express interest. They may have moved to the letter of intent phase.

And often at that phase, these companies will provide a whole bunch of data in the data room. And and many of them, surprisingly large number of them.

Will put pretty much the full transactional history and Sierra data in there. So, assuming that they do a, we can run a series of models.
Right out and you basically send me automatically and we, we probably run.

Models I trained on transactional data.
For call it 20300 different companies. So that model is.

You know, pretty much ready to go right out of the starting gate. The other type of data structure that we'll often encounter is.

When we're doing work on public companies, and for them.

The sort of data that we get to observe are public disclosures that come from filings and investor presentations. And so they'll give summary measures such as.

Our net dollar retention rate was X, or the number of active customers that we have is why? The total number of orders that we place was Z and.

Well, basically have to play this game of, of triangulating our way into, you know, what were the acquisition retention ordering and spend patterns that are most consistent with this aggregated data.

So, yeah, those are basically 2 kind of polar extremes and there's then a number of other circumstances where.

It's kind of in the middle and so it could be you say we're doing work on behalf of a private equity firm. They didn't put the full transactional data into the data room, but maybe they put in something that's.

You kind of a lot richer than we would normally see in filings. So, yeah, there are shades of gray, but you typically, it's going to be some combination of granular and in aggregate data.

Right. That's really interesting. So, last question on the equity partners, and then we'll move on to zodiac. Uh, would you invest in what stage do generally invest in and.

That's those are the only 2. yeah, so we don't we won't make investments ourselves. It's really more a function of the, you know, that the client need. So, you know, we've done work on companies as large as.

You know, Slack Dropbox.

The major telecom firms again, those are all public company examples, but we've even done some diligence is.

On behalf of public companies, extremely large ones where we were under strict NDA. So so we've done work on companies as big as the biggest that are out there.

We've also done work on companies that are are very small and.

Yeah, it could be a private equity firm that's looking at a company that's been in commercial operations. For your call it 4 or 5 years they may have.

Not a whole lot of data on customers that are really tenured. That's kind of scraping at the. Kind of the maximum that we're able to stretch our models to handle.
So, yeah, I'd say the typical company's going to be somewhere in between call it.

A company that's been around for 510 years, got a whole bunch of customers. Yeah. So we feel comfortable with.

The volume and quantity of of data, but not not super small and not super large.

That's that's great. So now let's go back to the audio and.

Well, I started with the fund raising for so 1st question is you raising money for that company?

Yeah, so we had a seed round that was led by 1st Round Capital you may heard of as well as the felices Ventures and a VC firm that had been known as Metamorphic. They had rebranded.

Now, they're known as the compound VC.

So, um, you said, 1st round, it was Josh compliment who kind of runs the show there who lead a lead on their side. And, um, and if Lisa, it was a, who he's kind of the top dog over there.

Really a kind of Premier VC backing very, very fast growing.

We had a term sheet for the, a round on our desk when we basically had gotten a better offer from from Nike.

So, basically it was an offer that we couldn't turn down because of our obligation. Our fiduciary obligations to our, our stakeholders, but.

Yeah, so we didn't go beyond that that stage but but certainly we were very much, you know, kind of your.

Kind of traditional venture, backed high growth startup company.

Night so, let's start this fundraising discussion with the question. When did the fundraising for zodiac start so, when was the moment when you're like, okay, now we're going to go out and raise money from actual investors.

It was relatively early on because we knew that we knew we needed. We needed to invest in our growth and.

And we would not be able to bootstrap that growth. So, yeah, there was some investments in primarily in hiring headcount.

That,
you know,
if we didn't have that money,
it would have been very hard to have been able to to get where,
where we needed to be able to kind of hit that critical mass for the business, where we could then kind of move to the next stage of our evolution,
so.
Yes, it was it was quite early on that that we had kind of made that decision.

So, early on how early on was it? Pre revenue? Do you have some sort of product? So basically, what was your major selling point when you were talking to investor you were saying, like, you know, we have X Y, Z that's why you should invest.

So, what was that X Y, Z that investors really liked? Thankfully, at that point, we had the luxury of having been revenue generating and we had a few nice client in place and ships that we could kind of.

Be able to brag about, so, yeah, it was a little bit easier to sell in that way. Right great. That's that's always like that. So, question about customers. Now, how do you manage to acquire the customers so early on?

So, do you really have some previous relationship with them prior just starting Sonia or do you actually reach out to them or what was that? Actually, how did you make it?

Yeah, it was basically kind of out of relationships that we had at the time.

Yeah, so Pete fader he's, uh, he was my Co, founder of zodiac and he's my Co founder again at data. We.

He has an amazing he's basically built up.

A lot of relationships over his 30 year tenure at at the Wharton School. So, is there a lot of people who really, really, really respect all the work that he's done? You know, the path breaking work and customer lifetime value research?

So, yes, it'd be able to kind of get it from the source and I think a lot of people found that to be something that they wanted to try. So so that was really helpful. I would say, kind of, in general, we found that.

Thought leadership has been very.

It's worked very well for us as a source of kind of getting prospects through the acquisition funnel.

So, whether it's hosting webinars or putting out blog content yeah.

Put out a lot of content on social media as well really nice way of being able to kind of establish credibility and keep people kind of in your orbit.

And then, kind of when, when that right time happens, where they have a deal, or they got the green light from from their boss to.

To move forward with some sort of a project that you might be relevant for that you'll kind of be top of mind and be part of the considerations that. Right, right. So.

I'm wondering if we should talk a little more about customer acquisition or and move on to the exit. Was, let's take 1 more question about customer acquisition, so.

Once you got that 1st, funding, how, what was your major strategy of getting new customers? Because that's basically 1 of the major struggles of every single start, you know, how to get more customers in how do I scale that process.

So, how did that work out for you when you couldn't really leave off your previous connections and you had to acquire actually new connections completely off from scratch.

Yeah, that's kind of the crossing other Rubicon, the inbound.

That we get just by virtue of having those relationships, you know, that That'll run out. And so you really have to move too.

A sustainable kind of outbound strategy for people who who don't know us, and they're not aware of. Our reputation and the work that we've done.

I'd say we kind of had a few ways of going about it and it worked reasonably well so we still had a bunch that was coming in through the relationships,

but it was really kind of this multi prong approach of really beefing up our of our content marketing. Yes, we had a lot of really nice materials that we had created to.

To be able to give people a good sense of what we do and to very quickly establish. We are not just another martec vendor.

We know that if you're speaking with a CMO at any reasonably sized company, they're probably getting hit with like, 30 random spammy martech. Inbound emails a day, so oh, yeah.

And that's probably an understatement kind of.

Establish that we are not them. Yeah, that's an important 1st step and so being able to kind of.

Look to the, you know, the academic credibility that we built up.

Yeah, I think that that's important. Differentiator. So yeah, for us, I'd say content content content was a big piece of it. We were more aggressive on webinars.

We had really nice blog content. We had hired somebody who did a really nice job of putting together articles for us because obviously 1 of the other things is.

Yeah, I was the chief statistician in the firm and Pete, we both have a lot of other obligations supposed to the business and as professors. So we can't just spend all day.

Writing blog content and so other people yeah, it's just stuff if you could kind of more quickly scale, the content creation, where it still has the. Yep. That's Pete.

But but it's being a lot of the legwork is being done by somebody else. That's invaluable. From a scaling perspective. So, yes, the content was a big piece of it.

And that that really did help kind of generate generate leads. The other 1 was and this was kind of to help get people from.

Kind of being leads to to working all the way down through to the acquisition was hiring a couple people to help.

To help without down sales.

So, yeah, I won't say that we had had a kind of fully nailed down by the time that we had sold to Nike.

But but we had been doing a reasonably good job of being able to go to people that we didn't know.

And and to be able to get them to respond to our emails and take that 1st call and if we had that 1st call lined up and you had someone like Pete or myself,

or 1 of the other Co founders on the team on it, that.

That that would be enough to at least be able to show that person. There's something here that's special. And I think that, that that was, I think, what we needed to be able to actually get.

Sales from these people who we otherwise didn't know nice. That's really cool. So, 1st question is going to be 1st, follow up question here is going to be.

About current integration, then we're going to move on and all that talk about sales, but.

Concentration, that's another big huge trends recently. It's been paying off great for multiple firms, but multiple 3rd founders are trying to focus on that, and it doesn't really give them anything any return for the amount of time that they spend there.

So, what's your advice? Too? Early stage startup founders what kind of content would you recommend them? Create? How good are the webinars.

Or blog posts or podcasts or what do you think is basically the best content type for early stage startup founders.

I wish I had a strong answer a strong opinion. I'd say we've been spoiled.

Um, I'd say the issue that a lot of founders have, and I'm not trying to to be mean here, but they have no credibility. Now, they've, they may have done something in the past but.

They're not a domain, they're not necessarily a domain expert, so being able to kind of go to people who.

We'll spend 5 seconds looking at you and to get them to say this person is credible. That's kind of the 1st major hurdle and.

And being, you know, say, like a 30 year. We're in marketing faculty, just.

It immediately establishes credibility. Yeah. If a lot of the pioneering work on customer lifetime value has been done by that person. That's a really great starting point. So we would kind of leverage that as best we could.

And that's why, I don't know if other companies would necessarily have.

The sort of the sort of lead generation that we did. So in general, my, my view for everybody is, you really want to play to your strengths.

And not try to make weaknesses strengths. It's just a lot easier to let your winners run. And for us, you know, 1 of the things that we just had, the good fortune of being able to rely upon was people would resonate.

And our content would resonate with people so, and we just kind of kept it doing it.

That's a good way to go. So now about sales you mentioned that if he managed to get on a call with the potential with the leads, basically, the deal was close. So.

Where do you get to learn but what do you think? What do you think'll taught you the best you know, how to make those calls how to make those sales?

Because that's another struggle for many, many founders because, like, half of them are technical, another half, our finance focused and.

Point 1 of them are really good sales. So the other 99.99% are heavily struggling with sales. What? What would you recommend there? Is there some particular book you would recommend them to read or webinars to attend, or anything to practice their sales? Basically.

Yeah, I keep going I know I'm going to sound like a broken record again, but play to your strengths and not to your weaknesses, you know, for me, it was.

Um, get the right people on the call with you. I know that I'm, I'm a technical geek and and that's what I excel at. And so I'll be helpful on a call for establishing credibility.

And if we have another data scientist on the line that they can tell, I'm not making this stuff up. And and that's kind of my role on the call.

Certainly, hopefully they can do more than that, but I'll be the 1st to say, I'm not a sales person. And so so I would rather make sure that I've got a really good salesperson on my team and have that person on that call.

So that.

When we get to that part of the conversation that they take over because otherwise I'm just not going to do as good a job as they would.

And it's kind of doubly bad that even if I was just as good as that person, you know, I've got a number of other hats that I'm wearing, including.

Literally specifying entirely new models that we need to develop for for clients and so I need to be off those calls or at least I need to be not kind of the main point of contact for sales. So yeah, so.

So, I think we did a reasonably good job of being able to find people who could actually fill that that sales role. The other thing I would say is.

Our businesses is really technical, we basically have algorithms that we make available to to corporate clients. And so.

So, being able to communicate something like customer lifetime value and that that's tricky. Um,

and that's why it really wasn't it wasn't simple to find to find that just right person because salespeople they won't necessarily or they almost certainly won't have the sort of technical background that they need to really speak very,

very intelligently about about the quantitative aspects and so.

It's really finding that person who, you know, even though they don't quite have that background that they still understand in general what's going on enough that.

That they can communicate the value proposition effectively.

Right that they can sound smart and intelligent, as you said. So now let's talk about the acquisition, the exit of these zodiac. So how did that happen? How did you get that proposal from 19.

Well, that yeah, we start venturing into territory where I don't want to trip over any non disclosure constraints. No specifications. Basically, I'll actually narrow down this question a little bit. So do you already have, did you like, for the exit?

Did you prepare? Did you try to reach out to those big firms that were potential acquirers or did you just randomly stumble upon 1?

Now, basically, what had happened was, you know, we knew that we were, we needed that next round of funding and so yes, the round was.

Was moving forward and that's really I think that's what we had been planning for. We didn't expect to to be acquired by a strategic customer of ours. So that really just kind of happened without our really having.

Proactively pushed for it and as you can imagine, you know, we, and this kind of goes back to our value proposition, you know, we, we take in transactional data and we use it to make customer level predictions.

And so the sort of business that that would.

Resonate the most with, and we would have thought.

It'd be like a Google or a sales force or Shopify or.

May be some really large, purely.

You know, direct to consumer business, cause they have full.

Transactional granularity they view it all the activity of their customers.

If someone had said, you know, it's going to be Nike, I would have said you're crazy because they, they had.

Basically cut their teeth as a company that sells through distribution partners.

Um, and so they didn't have customer level visibility so they, they wouldn't have even been able to have run our models.

Call it 25 years ago, where they would have run it on an exceedingly small proportion of their business.

Now, they've been making this big pivot towards direct to consumer, but it's still kind of a growing part of their business. So, in retrospect, it makes a lot of sense.

And that they would want to beef up their capabilities in this area. But.

It was definitely not something that we were planning for nice love, hearing those stories for random kind of acquisition. So let's go back to more of a current situation.

So, as an exit founder, do you do any mentorship or angel investments in earlier stage startups? Yeah, I do. Yeah, I'd say I've primarily been pursuing.

The angel investing on the advisory front. Yeah, I want them to make sure to be fully respectful of my obligations to Nike as part of the acquisition. So mm.

So, basically, that that's that hasn't really been an opportunity that I pursued, but certainly in terms of angel investing, there's been a number of wonderful opportunities that thankfully, I've been able to to be a part of.

So I'm happy to talk through some of those stories.

Sure, we will not really go through the stories as I don't want to run over 30 minutes, but quickly. Let's go over. Would you like to invest and what stage?

That's just for my listeners in case, if someone who's listening to this is a good fit for you, Daniel and.

Yeah, so 1st, those 2 questions yeah. For for good or for bad I'm gonna find out in like 5 years. It's been all seed investing. So yes the companies that are typically definitely post revenue.

Um, where I've had the opportunity to.

See, very clear evidence of product market fit and of unit economics.

Um, I have not I've done angel investing in both B to B and B to C companies. So.

B, to B versus C. that's not really a distinction that.

Yeah, I've cared about as much beauty and again, this goes back to customer base, corporate evaluation.

I like to see strong evidence that the incremental rate of return on newly acquired customers is is very, very good right now or if it's not very, very good right now.

There's a very clear rationale as to why it's going to transformed. If we get better. You say in the near term so that really I practice what I preach in terms of.

You know, making customer lifetime value, front and center, and in my own investment decisions. So that's kind of how I've been approaching some of the investments that are made.

Got it so, yeah now, quick question about.

Some positive, I would just want to add some positivity to this particular episode and ask you a question of. Is there anything in your portfolio that's performing?

Just super well, after deep endemic hit or something you're really proud of or some really interesting investment that you would like to share with the listeners.

Yeah, there's 1, I think that would be that's really there's 2 that I feel I have to mention is a company called pipe and a company called wear clouds pipe.

They, they basically help SAS, firms, monetize customer contracts.

And again, this goes back to customer lifetime value again, but essentially imagine that you're a firm like Slack and you've got a new contract with a company like Lyft.

A lot of companies like, Slack will offer these juicy discounts to encourage people onto annual contracts.

But if you were to just look at the revenue stream, the value of it is very, very large. And so when it makes sense to be able to effectively extend capital against that contract.

And so that's what pipe does is they, they'll extend funding against customer contracts.

So, it's not a factoring arrangement. It's actually lending against revenue. That may not be booked. So, that concept. I think it's just amazing that that's the future of the customer lifetime value work.

So,

they've,

they've been growing extremely quickly and I think they're moving into more of a,

a middleman sort of position in the value chain where they're just kind of helping link potential investors in those SAS contracts with the SAS firms.

So, growing like gang busters, I think, I think the world of them and the team.

Where clouds is the other 1 they basically are a distributed logistics company.

And, uh, and so what they do is they help E, commerce firms a.

Get the product that they need shipped out through kind of non traditional distribution through non traditional distribution channels.

So, instead of having to ship out your goods through a company, like GPS, instead they have a series of people that you could think of them. It's kind of like Uber or Lyft where they'll establish relationships with these people.

The product is stored in these people's houses or facilities.

And there'll be shift from there and so the product, the distribution centers are effectively, like, right next to where the, the customers might be.

It's much lower ship times, much cheaper and so they've been they've also been growing really, really quickly. So they're very young but.

I think that they have a really, really bright future ahead of them. That's a really nice concept. Personally I love it. And I'll make sure to leave links to both of those companies that you mentioned and probably to.

Uh.

To the equity partners of course, I'll leave a link to that as well. And now we're moving on to the last question of today's episode, which is a call to action. So, Daniel, what's the 1 thing you want to do? As soon as the episode is over?

I will certainly if if you're a company, I would definitely love to speak with you about. And how we could potentially work together. So, um, so certainly very early stage. Yeah,
I think the,

the price point of update equity partners may be a little high,

but you were in the process of putting together software that will make access to these sort of models very.

Quickly and easily available to you and I think the, the self service nature of that product.

It could make it very much worthwhile. I think most companies, especially if you're very young, you have, you're wearing so many hats and you're trying to do so many things that you may know that

customer lifetime value and you economics are important, but you just don't have the.

The time and the staff to be able to really understand it and so I think both from a potential fundraising standpoint, and from just a day to day management standpoint, you really owe it to yourself to understand where you are.

And we'd love to be able to help you with that. Absolutely. That's just awesome. And once once that is ready, definitely keep me up. And I'll make sure to announce that on fundraising renew.

So people keep listening to the episodes that's going to be. My call to action. Sequel is easier for 1 reason radio. Of course. And once.

At the end of 1 episode, you will hear the announcements of.

Data equity partners, finishing their product that's going to be really helpful for you. So, do that check the description of this episode and have a good date.