A Media Operator is a media company for those building digital media companies.

As Traffic Gets Harder to Acquire, LTV Becomes Even More Important

We have entered an era where traffic is harder to get. Whether it’s Facebook, X, and Google sending fewer people, or more people using chat-based offerings and never needing to click over to begin with, the reality is, fewer people are hitting our websites.

And as one operator said at a business media dinner a couple of nights ago, “this can potentially be an extinction level event for many b2b publishers.” And while he was focused on b2b media, I believe the same would be true with consumer brands as well. With less traffic coming to our sites, we have fewer opportunities to monetize. The digital media business has historically been all about scale.

Although I am not quite so apocalyptic about the rise of generative AI and this new era, it’s going to get harder. Publishers that have figured out ways to differentiate their brands will continue to operate and thrive. Those that have simply been in the arbitrage business where they acquire traffic for free and then monetize will likely struggle a lot.

It isn’t surprising. For many publishers, there is a ton of revenue tied to “opportunistic traffic,” as this one operator said. It’s going to be really difficult for these publishers to continue running their business without this, in essence, free revenue.

We have reached a point where the industry needs to reframe the conversation. Traffic is going to shrink. We’ll see fewer people hitting our sites. That means we need to do a better job with the people that we do acquire. We need to be smarter about how we retain people and, ultimately, monetize them. The lifetime value of one of our readers needs to improve if our revenue is to remain constant, let alone grow.

I look at this through a couple of phases and it’s simplest to understand it by looking at the formula for lifetime value.

LTV = Average Revenue Per User (ARPU) * Customer Lifespan

To start with, we need to figure out how to ensure that people are going to stick around for a long time. It’s half the equation after all. For the rest of this section, the numbers are going to be very simple for demonstrative sake.

Consider how many publishers operate. Someone performs a Google search, visits the page, reads the article, and then leaves. The churn rate is effectively 100% and therefore, your LTV is entirely dictated by how much money you can extract from that single page. Let’s assume you can make $0.01 per user per page, which is a $10 RPM.

It may not seem like a lot, but if you’re getting 100 million people a year, you’ve now got a $1 million business.

And that’s how many publishers have thought because getting new people was so easy. But what happens if that 100 million gets cut in half? That same $0.01 LTV only generates $500,000. But if your costs are $400k, you went from a 20% profit margin to a quarter million dollar loss.

This means we need to figure out ways to reduce the likelihood of someone bouncing after visiting our site only once. And I would argue there are two ways of accomplishing this.

First, make the experience better. Don’t load it up with so many ads that the site becomes unresponsive. You might take a hit on revenue per page, but if the user doesn’t leave immediately, you ultimately increase the revenue per user. This is why a lot of publishers invest in content recommendations because it ensures that the user gets to another page where they can monetize again.

Second, figure out a way to convert that user to something. This is why brands are investing more in their newsletters. If the source of traffic is Google and you can only get them to stick around for a few pages before leaving, your lifespan is immensely short. But if they subscribe to a newsletter and engage with it, the lifespan expands. Perhaps they stick around for months or years.

If you can get a user to sign up for your newsletter and then they visit one page a day for a year at $0.01 of revenue per page. That means your ARPU is $0.01 per day multiplied by 365 days, giving you an LTV of $3.65.

This is a clear example of how lifespan can impact an otherwise really bad business model. If users stick around for a long time, the business will make money, but it won’t be very exciting.

And so, the question we have to ask is how can we improve the average revenue per user? In other words, how can we correct for a really bad business model?

Publishers have been doing this for years, moving from basic advertising to performance marketing—lead gen on the b2b side and affiliate on the consumer side. And this matters a lot because the potential revenue per user is greater. If a lead is worth $100 and 1% convert, that means your ARPU is $1. That’s a heck of a lot better than $0.01.

The problem here is that you’ve only monetized one of your users. The other 99 are not generating you any revenue. You could run ads on those pages as well, but that could impact the lead gen conversion rate or return to part 1 and negatively impact the retention. It ultimately becomes a balancing act of competing interests and publishers are desperately trying to find the right balance.

Ultimately, we need to become smarter about how we monetize people. And that’s a function of two things. First, the data we have on our audience (you didn’t think I’d publish a piece without mentioning 1st-party data, did you?). And second, a tool to promote different monetization schemes depending on that user data. Back in 2020, I wrote a piece about the concept of a revenue server.

The revenue server is effectively a CRM. But rather than simply tracking whether someone opened an email, clicked a link, consumed an article, or what have you, it’s tracking how the user is monetized. Here are examples of the types of data you’d be collecting:

• Ads: Did they see ads? How many ads did they see? Were they direct deals or programmatic? What’s the eCPM of those deals? For my B2B readers, did they download a sponsored white paper?
• Commerce: Have they engaged with a commerce ad? Did they ever visit your store? Did they add something to the cart? Did they buy something? How much did they buy?
• Subscriptions: Have they signed up? Have they churned? Have they ever even engaged with the subscription page? Have they churned and signed up again?

As we collect this data and start to better understand what type of user we have from a monetization perspective, we can start making informed decisions around the actions we take.

Let’s use the example about lead gen vs. ads. Which should run? If you have good data about your audience, your revenue server would be able to deliver the lead generation offer when the right user hits the page. For example, if the lead gen is all about taxes and the user who hits the page has nothing to do with tax, showing lead gen is a waste. Monetize them with ads.

You can also do it behaviorally. If the user has engaged with an ad in the recent past about tax, show them a lead gen offer about tax. Did they engage with a lead gen offering very recently? Don’t show it again.

With basic traffic control, you can dictate what someone sees based on who they are and what they’ve consumed. This allows for better monetization of those users because it ensures the right offer is going to the right person. Your monetization gets closer to 1:1 rather than canvassing everyone with the same message.

And this works with ads, commerce, subscriptions, and anything else you might be selling. Being able to show the right thing to the right person is a function of their data. Who are they and what do they engage with? What have they already spent money on? Are they already coming to that event?

The other great thing about this 1:1 approach is that you stop wasting inventory. You should promote that event, but if they’ve already bought a ticket, why keep telling them? Show them a lead gen offer or, if there’s nothing else, a basic ad.

As I said above, you have two levers to pull: how long a user sticks around and how much you can monetize them.

Improving how you monetize can impact retention because you’re not desperate to maximize revenue on the first page. If you can give them a clean user experience, promote a newsletter, collect data about who they are, and behaviorally track them, you can deliver the right monetization strategy to each user.

This isn’t easy, but as fewer people hit our websites, it’s going to become that much more important. And if we do a good job and successfully grow LTV, we then have more resources to invest in paying to acquire an audience. This is, ultimately, why more publishers will fight to get a reader revenue component. It changes the math about paid user acquisition considerably. But we’ll talk about that at a future point.