How Fanatics Thinks About LTV to CAC Across Multiple Product Lines

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I spoke to Glenn Schiffman, CFO of Fanatics. For those who haven’t tuned into a major televised sports game or bought a jersey lately, Fanatics is Michael Rubin’s sports merchandising, apparel, and collectibles company, valued at $31 billion in it’s last fundraise.

Glenn is a staunch negotiator and a guy who knows his business units down pat.

Fanatics operate across three distinct business lines:

I wanted to learn about the metrics a CFO with a sprawling sports platform tracks to stay on top of the business.

Glenn spent decades in investment banking before making the leap to CFO. And he’s no stranger to running seemingly disparate business lines, having also helmed the finance team at IAC, the holding company behind Angi.com, Vimeo, and Match.com.

The following is a peak into the leading and lagging metrics a CFO running a multi pronged business, with real inventory, manufacturing and shipping costs, uses to make decisions.

Here’s what we’ll cover:

When we talk about metrics externally, the majority of the airspace goes to output metrics, specifically revenue, EBITDA, and Free Cash Flow.

And look, those metrics matter. As Rasheed Wallace would say, ball free cash flow don’t lie.

But by the time they show up on your P&L, the boat has left the dock. The decisions you made that got you to these output metrics were made months (or even years) ago.

The way he spoke about the metrics underneath revenue and FCF carried a ton of passion. It was as if he was visualizing a jersey coming off the shelfs in a warehouse after it was ordered online through a third party partner like Dicks Sporting Goods, and monitoring it as it get loaded onto a Fedex truck and timing it until it arrived on the fan’s doorstep.

He spoke to leading metrics such as:

Many of these were obvious. But the metrics that really caught my ear were way more operational.

Each one is used as a directional marker, indicating where revenue (and later FCF) will be moving over time. So to restate the now obvious:

The other metric he flagged was discounting. Fanatics is actively working to pull it back, not by nuking promotions entirely, but by making them more personal and shifting the merchandise mix upmarket. The logic is you'd rather sell someone a hoodie they're extremely excited to wear to the office (you know, the heavy $120 one with the actual stitching) than train your whole customer base to wait for the next 20% off email. They do not want to be a bargain bin retailer. I’d never heard a CFO talk about discounting this way - making it more impactful to the individual - and it made me think differently about discounts I’d personally approved in the past to get tech deals done.

The ultimate output metric (which is as compound as compound metrics come) is LTV to CAC. There’s a lot of “stuff” in there. And you can’t pull just one lever to change the output.

I asked Glenn how they think about this ratio across Buy, Bet, and Collect, the three pillars of their business.

Similar to a software platform (think: DataDog or Crowdstrike and their beautiful multi product attach charts) a customer who engages across multiple business units is incredibly valuable. More specifically they are worth 4.7x more to Fanatics than a customer who engages with just one.

These customers come back more often, retain better, and demonstrate a higher level of participation in the Fanatics app. Glenn explained they are trying to create an ecosystem where they have arithmetic CAC (single and linear) and multiplying LTV (expanding and unbound).

But you can’t get to this without making an investment in data infrastructure.

Some Fanatics customers don't log in when they buy. Hell, they might not even come directly to Fanatics. They could come through one of 900 partner sites. Then there are people like me who walk into a stadium store, tap their card, and that's it.

So before you can do anything interesting, like personalization, cross-sell, and finding the next best offer for a fan, you have to figure out who that person actually is across three different businesses with three different transaction surfaces. That's a hard, messy problem.

Fanatics has spent a lot of money solving it. That includes deduping and cleaning data, and building towards a single view of the fan.

As Glenn explained, this investment only shows up on the P&L in the cost column. To the untrained eye, it just looks like expenses going up.

He framed this as “the precedent condition” to calculate that 4.7x LTV to CAC view. If you don’t have the view, you can’t make decisions that drive the ratio up over time.

And as you could have guessed, they’re investing in AI to further homogenize the data, with the aim of offering the next best product for their customers at the right time and in the right place.

Since they have over 100 million people in their database with billions of attributes, they can predict someone’s family size and favorite teams by their orders. So the question becomes what do you do with that?

Before we figure that out, let’s use an example outside of Fanatics - think of an Amazon user’s activity. Let’s say they’re moving homes.

To bring it back to Fanatics, they realize that with AI you can take this suggestion process to the next level and better understand WHY someone is buying, and then make probabilistic suggestions that have a higher chance of converting.

Maybe it can deduce you’ve bought tickets to the college national championship game next month and you should outfit your whole family, which they know is four people. And don’t forget the tail gate gear because you’re probably driving there based on where you got your merchandise delivered to last time and the location where the game is being held.

To tie it all together, I wanted to know how Fanatics thought about getting customers through the funnel. It makes a lot of sense that you want customers to buy from all business units, and to increase their purchase size and velocity over time. But how do you get them to make the first purchase? And then the second? Is there a preferred front door? And does sequencing matter?

It turns out you can enter from all angles, but by and large the commerce business is the biggest business to get you into trading cards and gaming.

Which brings us to what Glenn called their next engine of growth. A Fanatics credit card.

The credit card is the fourth product, and the interesting thing about it isn't the card itself (it could be anything), but rather what it does to the unit economics. You're now amortizing CAC across four products instead of three. As he alluded to earlier

The network effects in Fanatic’s business are a beautiful thing. And similar to how I wrote about Disney’s pricing and packaging, you can monetize an ecosystem better when you have clean, first party data on your customer.

Half the battle is picking the right metrics to track. The other half is having the courage to invest in the right tools and people to make that view possible.

Hoping your CAC is arithmetic,

CJ