There’s a saying we use often at Marketing Showrunners: Great marketing isn’t about who arrives. It’s about who stays. That’s because if people actually stick around, the good stuff we seek actually happens: trust and love and a relationship form; we get valuable feedback and insights from the engagement and conversation; and of course, our audience takes actions we value (because they value them too) like subscription, purchases, and referral.

Said another way: Great marketing isn’t about near-term acquisition. It’s actually about lifetime value (LTV). The problem is, rarely if ever do we actually try to measure the lifetime value of the audiences we develop. Yet that’s exactly the job.

As a marketer, theoretically, this should matter to you plenty, because it certainly matters to your C-suite. The LTV of a customer is essentially the amount of revenue or profit they will generate during the course of their time as a patron of your company. To calculate LTV, we need to know a few key bits of data, which we’ll explore in a moment. For now, we need to agree to shift how we usually approach marketing measurement.

Here’s one change we can make in how we measure:

Rather than obsess over totals, we should focus on value.

It’s not about how big the audience becomes, it’s about how productive, how much value they bring to the brand (which, of course, is directly related to how much value we bring to our audience). Then, once we know that an audience is productive (i.e. valuable to our brands), we can focus on making that valuable asset bigger. But we focus on the bigger without a defensible explanation as to how it’s a valuable thing to grow.

When you think about it, why do we value bigger audiences at all? Because of what we assume will happen as a result of all that reach. We just assume that, if we reach a lot of people, more people will also be productive and subscribe, buy, and/or refer business our way. We assume the productive part will just kinda … happen. It’s why we hear more marketers say the word “awareness” instead of “affinity.” We chase the former, but we need the latter. So it’s wasteful and kinda strange to obsess over a proxy (a broad audience) unless we first understand that we’re meeting our actual needs (a productive audience). Put the cart behind the horse: ensure something is valuable first, then invest in growing it.

So, this is our new mandate to measure a show — and really all of our marketing. Let’s measure value, not totals. Find what’s valuable, then make it bigger, ensuring the value doesn’t decline while you do so.

Next, we need a hypothesis for how our shows might contribute to this need to create more value, not just “more” of something. Starting our process with a hypothesis will help us test and measure strategically, in a focused way. When we lack a hypothesis, we lapse into an endless cycle of seeking ever-more stuff without real reason as to why. Do more things, measure it more ways, because we need more. Forever. This is exhausting, demoralizing, and ineffective.

But it’s also our reality. Marketers who “get” the value of shows often find themselves grappling with how to measure it and how to have productive conversations internally. In our conversations with our subscribers, marketers from brands as big as Amazon and as small as ten-person firms helped us identify two major issues with our current metrics when we try to measure our shows:

1. Some metrics are too squishy. These are the “awareness” metrics, or vanity metrics. Downloads and views are vanity metrics that are also tough to parse and require marketers to solely think about “bigger, faster.” Survey responses, while revealing, often feel too distant from direct leads or sales for some internal stakeholders to take them seriously.

2. Some metrics are too short-sighted. When we DO try to tie our shows to revenue, we often get pushed back on our heels. We want to think long-term, or at least think longer-term than, say, this quarter. Just the mention of “revenue,” and suddenly, our peers who don’t quite get the value of our shows demand to see results more similar to advertising campaigns than audience development and brand affinity-centric approaches.

Thus, our starting hypothesis needs to take this into consideration. That means the rest of this article will focus on trying to find a better way — an approach to measurement that is MORE concrete than the squishier stuff, and LESS ill-informed and short-term-obsessed than the typical “concrete” stuff marketers are asked to demonstrate with their content. In short, we need to be willing to wade into somewhat uncomfortable waters in search of truth. We can’t hide behind squishier things, nor run from the fight when someone talks dollars. We need to come ready, not only so we can have more productive internal discussions and secure additional resources, but so we can understand what’s actually happening with our shows, whether we’re having an impact, and how we might change and evolve in the right way.

Okay, I think we’re ready to decide on our starting hypothesis. Here is what I’m proposing that we say, then figure out how to test:

Subscribers to our show are more valuable to our brand than the average subscriber.

That’s what we believe. That’s the assumption, the best guess.

Theoretically, the lifetime value of a group of people who spend hours upon hours with us will be greater than those who spend minutes or seconds. (It’s also worth noting that what gets delivered inside those hours and hours matters. It’s not just “total time spent” that determines a show’s success. It’s what happens during that time that has impact. It’s just like measuring the show’s overall efficacy: it’s about the value, not the total.)

So now, we have our new mentality: We measure value, not totals.

We have our hypothesis, too: People who subscribe to our show are more valuable to our brand than the average subscriber.

Next, we can systematically deconstruct this complex idea of show measurement and audience LTV into smaller pieces, each of which can help us arrive at the validity of our hypothesis. Is our show’s audience really more valuable? To what degree?

And look, I know this already seems much more complicated than tracking, say, the traffic to your blog. But this will never been as easy as Google Analytics generating some nice, neat chart you can slap onto a slide. So if you’re actually committed to this showrunning stuff (and I know you are), and you actually believe in building brands in nuanced, lasting ways (and I know you are) then let’s just embrace that this is chess, not checkers. We get it: It’s more complicated than some other things in this world. “It’s hard.” Yes. It is. Meaningful work is. Change is. Anything worth doing in this short life we have indeed is.

This is chess. Not checkers. So let’s stop griping about it and figure out how to master this game.

Why You Can’t Talk Shows without Talking LTV

The reason a show’s audience should theoretically have higher LTV than other cohorts or sources of subscribers is simple: A show is one of the few things marketers do that is expressly built to create the “L” part of “LTV.” Shows are meant to take people on a journey over time, not hastily rush to transact the audience as soon as they arrive. There’s actually a “lifetime” to look at, since audiences invest meaningful time into the experience. That should create a longer-term, deeper relationship compared to the majority of what we measure as marketers: clicks, traffic, followers, downloads, views, form-fills, and even sales. Again, these are transactions, and when you center your measurement on transactions, it’s a slippery slope towards caring solely about an infinite “more.”

The thing is, it doesn’t matter if we saw more, if that growth was hollow. Who cares if 1,000 more people downloaded our show this episode compared to last episode if none of them come back? Who cares if 100 people joined our email list if they unsubscribe a few days later? The job of a marketer isn’t to create “more.” It’s to create better.

So, again, we’re measuring value, not totals. To do that, we need to look at the longer arc of time, which is where the relationship between us and those we aim to serve actually forms. Picture a long list of marketing activities, all kinds of interactions that consumers can have with your brand. Adding a show into that mix allows all that stuff to work harder and better, since anyone who invests serious time into your show will inevitably see other content from you in a different light than people with little or no affinity built up over time. Who’s more likely to say Yes to your request? Your best friend, or a stranger?

Remember: Great marketing isn’t about who arrives. It’s about who stays. (The horse is dead, and I’m beating it. I get it. I’ll stop. Maybe. Probably not. Sorry not sorry.)

Thus, it’s worth asking: What is a show for? It’s for holding attention, not just grabbing it, going deeper instead of broader. It’s about resonance, not reach. (Horse. Beaten. I hear you. I’m done. Except maybe not.)

So if we accept that this is what a show is FOR … let’s measure that!

Now, I’m not the smartest person in the world. I know how to shave and shower and iron my shirt (but only the parts you can see; turns out if you wear a jacket, you can keep alllll the hidden parts messy — wheeeeee!) I’m not the smartest (or sanest) person in the world, but I’m pretty confident in saying this: 

Telling you to change is a lot easier than you … yanno … actually changing.

How to Start Measuring the Value of Your Show’s Audience

For us to change our approach to show measurement, and for us to truly understand the value of those shows, we can calculate one signal of that value, prioritizing it over other data that might talk about totals. 

Our value metric: revenue per subscriber.

 

Nuance Is Neat caveat #1: Revenue per subscriber is not a God metric, the one single thing to measure to solve all problems. Like the tactics we choose to execute, measurement is a portfolio approach. I’m not saying ditch everything and focus solely on revenue per subscriber. Heck, I’m not even saying that measuring totals is entirely bad. However, I am indeed saying that we need to START measuring revenue per subscriber, or if we already are, actually USE IT to change our behavior. I’m asking you to put this concept at the center of your approach. (Isn’t nuance neat?)

Why Revenue Per Subscriber?

As our value metric, revenue per subscriber (RPS) allows us test our hypothesis. Remember our hypothesis?

People who subscribe to our show are more valuable to our brand than the average subscriber.

The vast majority of marketing is measured in a vacuum. We look at one project, campaign, or channel, and we judge its totals. It’s as if everything we do must act like direct marketing, or it’s not worth doing it.

Here’s an analogy: If you’re building a basketball team, the marketing mentality would lead to a team entirely comprised of shooters, people who try to score every time they touch the ball. Because we value that. If a player doesn’t score 20 points a night, well, they’re benched. They must not be worth playing. They didn’t score. But on a genuinely good basketball team, you need some players willing to assist the player who scores, setting them up for success. Still other players set up the player, who sets up the player, who sets up the player, who then scores. It’s the interconnected, complementary roles of all players working together that helps the team score and win.

Unfortunately, as a result of our score-now, score-or-else mentality in marketing, we tend to look at totals: total downloads, total views, total subscribers, and total leads and sales. If it doesn’t clearly score right now, it gets benched.

In the case of a show, if we can’t escape this mentality, we’re better off just not making one. Shows are not built for the things we usually measure, and so the stereotypical marketing mentality handicaps our ability to build a successful series. Again, shows are about value, not totals.

It’s only logical, then, that it’s more likely for a CMO to fund a blog indefinitely than, say, a podcast. The traffic to our articles looks nice and high compared to the downloads of our episodes. But which is more valuable? Do we stop to consider it? (Side note: Another reason blogs and podcasts shouldn’t be measured against each other is technical: actual articles from actual blogs rank on search and get shared on social media easily and often; actual episodes of audio from actual podcasts don’t benefit from either search or social. Only the content we create around the podcast ranks or gets shared.)

A show is built for depth, resonance, trust, time spent, and ultimately the roll-up of all those things: creating the most valuable audience possible, not the biggest.

Remember the hypothesis: Show subscribers will be more valuable than average subscribers. When we measure revenue per subscriber, now we create an apples to apples comparison between shows and other things, like blogs. We eliminate the need to measure totals and look at the value created by all our marketing — ultimately tracking down to revenue.

If we built a car and an airplane, we wouldn’t ask, “How much did that car fly?” Cars aren’t for flying. Airplanes are. Of course the airplane will fly further, faster, better. Instead, let’s find a question we can ask that makes it a more even comparison. What’s a car for and a plane for? What do they share?

How about: How effective are these vehicles at getting us from A to Z?

For the “vehicles” we create with our content, Z is revenue. Always. We might lose sight of the fact that we can’t leap from A to Z immediately, but the fact remains that everything we do is supposed to contribute in some way to revenue. All other measurements are proxies or pieces of measuring revenue — the letters A through Y en route to Z.

How effective is your show at getting you from A to Z compared to some other vehicle? How effective is your show at getting people to revenue, compared to another type of content?

 

Nuance Is Neat caveat #2: A measure and a goal are different. I was careful not to say that our goal is revenue. We often claim that our goal is revenue, or our goal is to grow by X%, but in reality, these are measures of our goals. Real goals are plain language things like “Become the most trusted resource on podcasting for marketers,” or, “Show the world how fun and relevant we are,” or, “Help change the way we view climate issues,” or, “Build the most beloved product in our niche.” Those are goals. We can measure them any number of ways, and perhaps revenue is one of those ways. People buying from us is a measure of something else we’ve done, a signal that we’re achieving our goals, or even a byproduct. Have we become the most trusted source? Have we shown the world we’re fun and relevant? Have we changed the way people view climate issues, or built a beloved product, really? We were one way, now we are another way. We were one thing, now a different thing. The process of moving between the two was what we aimed to measure. Thus, if you think about it, BEING something is a goal. YIELDING something, the PROGRESS towards being something — that is the measure of the goal.

 

In the end, our work must yield revenue. Maybe not immediately. Maybe not in a way that some kind of tracking pixel dropped neatly onto a webpage can reveal to us. But eventually, revenue is the way to measure our goals.

By understanding RPS, we can begin to measure the value of our shows, regardless of how big they are. This can help us secure more resources to grow an asset that proves valuable, invest resources to fix a struggling series, or end the show entirely.

How to Measure Revenue Per Subscriber (RPS)

Remember, we’re hypothesizing that the average show subscriber is more valuable than the average subscriber across our content. If shows supposedly make more valuable audiences than elsewhere, we have to measure that. To begin testing our hypothesis, we need to answer two big questions: What’s the value of the average subscriber, and what’s the value of a show subscriber?

Big Question for Calcuating RPS #1: What’s the value of an average subscriber?

Here, we are defining “subscriber” as “an individual who opts in via email to receive more of your content.” Let’s count anyone who subscribes to assets like your blog, newsletter, webinars, videos, podcast, and other forms of content via email. We should not count anyone who is on your email list but did not volunteer to be there (because shame on you). Don’t buy lists, add people you’ve emailed to your list, or people whose email you can find elsewhere, like LinkedIn. The lone way your email list should be growing is because the owners of those emails have knowingly added themselves to your list. Period, end of discussion. If you believe otherwise, kindly leave this site.

Ahem. Where was I before telling some marketers to get off my lawn? Ah yes: Subscribers! Healthy, happy, and knowingly subscribed subscribers.

Let’s do a crude pass at calculating RPS, then get more detailed once we grasp the basics. Ready?

The crudest approach to revenue per subscriber data is to answer the following questions about your business:

1. How much revenue did we generate last year (or whatever consistent timeframe you want to use)? (e.g. $5 million)

2. How many paying customers did we have? (e.g. 50,000)

3. Divide them, and that’s our revenue per customer, not subscriber. (e.g. $100)

4. Next, what percent of subscribers are customers (because we will need a larger number of subscribers to yield our actual paying customers)? (e.g. 10% of subscribers are/become customers)

5. The average revenue per subscriber is $100 times 10%, or $10.

In this scenario, which is again rather crudely formulated, we know we need 10 subscribers in order to get 1 paying customer. Thus, we can divvy up the revenue generated by 1 customer ($100) across 10 subscribers, and we land on the value of each subscriber: $10. Our hypothesis is that our show will yield subscribers who are worth more than $10 to our company (exact numbers will vary, this is theoretical placeholder stuff). We’ll talk about how to measure the show-specific subscribers in the next section, but for now, let’s remain focused on the average subscriber.

 

With me so far? If not, go back and take another pass at this section, and also scold me on the internet, because we need to get on the same page, and you’re reading an English major trying to do math for the first time in decades. But math I will! Math. I. Will.

After all, if we don’t know how the pieces move on the board, we can’t learn chess.

If you’re with me so far, let’s now try a more detailed approach to figuring out the average revenue per subscriber — again, staying focused on the average subscriber, not the show-specific subscriber just yet.

1. What’s the average purchase total by our customers? i.e. the average cart in retail, the monthly subscription in SaaS or membership-based businesses, the monthly retainer in client services, etc. (e.g. $200)

2. How often do customers buy from/pay us? (e.g. 12 times a year, or once per month)

3. What’s the average revenue per year? ($200 times 12 = $2,400/year)

4. How long does the average customer stay with us? (e.g. 3 years)

5. So what’s the average revenue per customer (not subscriber yet) across their lifetime with us? ($2400 in revenue per year times 3 total years = $7,200. This is a rough look at LTV, since we’re not factoring in a whole slew of variables that we might opt to consider later, like acquisition costs and profit margins. It’s the average revenue per customer across their lifetime with us.)

6. Thus, $7,200 is our rough (or maybe “gross”) LTV per customer. But, again, we need revenue per subscriber. So once again, we ask: What percent of subscribers are customers? (e.g. 10% of subscribers to our content become customers).

7. The average revenue per subscriber = $7200 * 10%, or $720.

In this scenario, we’ve gotten more detailed. We’ve looked at a few more factors about customers paying us, how much, and how often. We’re still making some reasonable assumptions here. It’s not exact. It’s reasonable. This is enough to get unstuck from the two extremes of measuring nothing (shrugging and claiming “brand awareness”) or waiting around for the exact right numbers, gifted to us from some magical blend of third party tech companies who don’t care and analytics tools that don’t exist.

Either way, we should be willing to make more reasonable assumptions as marketers. We freeze when we don’t have everything we think we need, but with a little digging, we can still arrive at some approximate RPS data, whether by a crude approach or a bit more detailed process.

 

Nuance is Neat caveat #3: I do want to point out a third layer of detail we can add. We tried a really crude calculation first: “All revenue divided by all subscribers.” We then went a level deeper, including the dollars and time customers spend with us. Ultimately, however, this second stab is still lumping 100% of subscribers together, before we compare them to show-specific subscribers (in the next section). However, what a great marketer really ought to do is look at specific sources and how they effect our calculations. The simplest way to think about this: Look at #6 above (the % of subscribers who turn into customers). That number is probably different depending on where the subscriber originated: blog, newsletter, webinars, video courses, events, and more.

Thus, we can get more detailed in finding RPS for specific cohorts based on subscription source, examining their likelihood to turn into paying customers. If just 5% of blog subscribers convert to customers, they’re below our average of 10%. Maybe we pull budget from the blog and divert it to the podcast, if we later determine the podcast subscribers convert at a rate that is higher than average, like 12%.

We can continue to add on complexity as we get more familiar with the data, e.g. “Just 5% of blog subscribers convert into paying customers, but 20% of people who get both our blog content AND sign up for our webinars convert to customers.” Or, “Just 5% of blog subscribers convert into paying customers, but they spend 2x more per purchase.”

When we know more details, we can add them. Maybe to start, try the list as written above, then break #6 into little branches — one per subscriber source. We can thus arrive at the RPS for each type of subscriber before comparing show-specific subscribers to other types of content. The more you incorporate, the more detailed and true to reality your look will be, but just like trying to write a great blog requires you to write a lot of initial drafts and medicore posts, it’s about taking a stab, reflecting, and updating what you do. Start measuring, learn, and update your approach. Strive for truth and quality, but ensure you take action today.

NOTE: For the sake of simplicity, for the rest of this post, I am only going to write about comparing show-specific subscribers to the average of all subscribers — not break apart average subscribers into blog, et al. But please remember this is still somewhat crude and meant to get you started only.

 

To recap: we have our average revenue per subscriber, i.e. the value of a single subscriber across their lifetime with our business. That was Big Question #1. Now, we can move from looking at the average group of all subscribers to the specific group of show subscribers.

Big Question for Calculating RPS #2: What’s the value of a show subscriber?

Here, we have to rip the bandage clean off, leaving behind a painful streak of bright red truth: We have to stop relying on third party apps or platforms to give us data. It ain’t happenin’ y’all. Sorry.

I repeat: Apple Podcasts, Spotify, and Google Podcasts won’t be our saviors in helping us measure our podcasts. YouTube, Vimeo, and Facebook/Instagram won’t prove heroes when we want to show the value of our video shows. We have to take matters into our own hands.

To measure a show, don’t rely on third party platforms. Instead, rely on email.

 

There are two ways to use email to measure the RPS of your show: get people who watch or listen elsewhere to join an email list you own, or identify which of the emails you already have are from people who already like your show — or do both.

First, inside the content of our shows, the single-most important thing we can offer our audiences — and thus, the singular focus of our calls-to-action — should be an exclusive email list. This email list should be available to fans of the show only, not promoted more broadly by your marketing team. Talk about the email list on the show, put a link or a form on the show’s landing page, and generally let your show’s audience know this is a special thing just for them.

The email list should also offer exclusive value, like bonus content, behind-the-scenes stuff, early access to episodes or other projects, or invitations to chat directly with the show hosts or guests.

Thus, when we say “exclusive” email list, ensure yours has two forms of exclusivity: (1) exclusive to the show’s audience, and (2) exclusive value inside. That’s the first way to rely on email subscription to measure a show’s value to your brand: Move some audience from third party platforms where they consume your show over to an email list. But what about all those emails already in your database? Those must be segmented.

The easiest way to do this is to survey the audience to ask who consumes the show and who does not, which then allows you to separate out the fans from everybody else.

How to Measure Revenue Per Show Subscriber

With all that groundwork laid, we can now run our show subscribers through the same formula that we ran all subscribers through earlier. (Underlined words below are newly added compared to what I wrote before.)

1. What’s the average purchase total by our customers who also subscribe to our show? (e.g. $300)

2. How often do customers who also subscribe to our show buy from/pay us? (e.g. 12 times a year, or once per month)

3. What’s the average revenue per year from customers who subscribe to our show? ($300 times 12 = $3,600 per year)

4. How long is the average customer relationship when they also subscribe our show? (e.g. 4 years)

5. So what’s the resulting average revenue per customer (who subscribes to our show) across their lifetime with us? ($3600 times 4 years = $14,400)

6. That’s our average revenue per customer who subscribers to our show over their lifetime with us. To find the average revenue per show subscriber, we ask: What percent of show subscribers are customers? (e.g. 20% of show subscribers become customers)

7. The average revenue per show subscriber = $14,400 times 20%, or $2,880.

If a show does its job, then the RPS of a show subscriber should be greater than the RPS of a generic subscriber. (As we get more detailed in our measurement, we can also compare the RPS of show subscribers to the RPS of other sources, like blog subscribers, webinar signups, newsletter subscribers, educational course subscribers, and any type of content we publish that offers the CTA to “subscribe”).

Additionally, note how any of the variables in the formula above might affect the resulting RPS. Just go down that list and imagine what we might learn: What if, by virtue of consuming our show, that specific audience’s one-time purchase totals increase? Then their subsequent value, i.e. their RPS, would go up. Keep going down the list: Maybe we’re more likely to experience repeat purchases via our show’s audience than other sources, or maybe their average customer relationship with us is longer. Maybe a greater percentage of show subscribers turn into paying customers (i.e. the conversion rate is higher). In the examples I’ve used today, the RPS of a show subscriber was $2,880. The RPS of all subscribers is $780. What changed? In the above, fake example, we found that show subscribers spend more per purchase ($300 vs. $200), and although they pay us 12 times per year just like the average subscriber, fans of the show stay with us 1 year longer (4 years instead of 3). Subscribers on our show-specific email list also prove to convert at higher rate than the average subscriber to otherr content (20% vs. 10%).

In this example, they spend a bit more, stay a bit longer, and convert at a bit higher rate. All of that led to a massive difference in their value to our company, and all of that value was unlocked by the show.

If a show does its job — in other words, if we as showrunners do ours — then we should be able to see just how much more valuable our show’s subscribers are compared to others. If that’s not the case, we should be able to see where we’re falling short and address those issues proactively.

To do this, we need to look across the lifetime of a customer, not just the short term. We need to measure value, not totals. We need to be willing to take matters into our own hands, not wait around for third parties to provide us with more data.

We need to look at revenue per subscriber, not vanity metrics, and certainly not no metrics … but also not direct marketing metrics.

 

Nuance is Neat caveat #4: None of this works if we’re not willing to (A) use email instead of third party apps, but just as crucially (B) measure for the longer term. If we don’t do the latter, we might as well not make a show. That’s beacuse, without glancing at the big picture, we risk overinvesting in something that looks great right now thanks to some kind of vanity metric (“totals’), but it doesn’t yield any value. The flipside is also true: We might underinvest in something that is actually working, but since we’re focused on the short-term, we don’t see it. Consider the following example and what happens when we underinvest:

Example Inc sells video courses. The average course costs $700; the average student takes 3 courses with the company, ever, and they stick with the company around 1 year (i.e. their last paid course is about 1 year after their first). So, the average student is worth $2100 in revenue to Example Inc.

Next, let’s assume it costs $10,000 for Example Inc to make a podcast THIS quarter. Now here’s the question: How many paying students would Example Inc’s podcast need to yield to cover its costs? $10,000 divided by the average revenue per customer ($2100) equals 4.76. They’d need about 5 show subscribers to become paying students. Is the show a good investment? I’d say so! Getting five students to become paying customers through the podcast sounds pretty easy. They should invest with confidence. Except … Example Inc measures for the short-term.

They know the show will cost $10,000 this quarter, so they only look at revenue generated THIS quarter. That paints a different picture. Why? Well, one of our data points we gathered earlier was that it takes 1 year for students to buy their 3 courses on average, for an average of $2100 per student. If their marketing team only measure this quarter’s expenses against this quarter’s revenue, they’re not seeing the full picture. They’d see a $10k expense and maybe just one course taken per student (for an average of $700 per). It would look like a failure, so they’d kill the show.

But! The students who began listening to the show that quarter, and even perhaps paid for 1 course that quarter, are worth a lot more to the company than the money they paid to Example Inc THAT quarter. On average, those students will go on to take 2 more courses — but it’ll take 9 more months, i.e. 1 full year, to fully reap the full revenue reward for Example Inc. Thus, the company should have continued running the show, but they didn’t. Making it even more foolish to kill the show is the likely benefit of the podcast audience becoming even more valuable than the average audience, which makes the numbers look better … to say nothing of a passionate listenership referring new business to Example Inc FOR FREE. All of this adds up to make Example Inc look rather silly.

They should have kept running the podcast, but they’d have no way of knowing that unless they choose to measure their results using lifetime value, not short-term totals.

Don’t make decisions based on near-term totals. Make decisions based on value — particularly, across the customer’s lifetime with you.

 

How Revenue Per Subscriber Affects Strategy and Investment Choices

Imagine a future where you know with greater certainty that people who watch or listen to your video series or podcast are more valuable to your brand. Maybe you can eventually say, “People who listen to our podcast are twice as likely to purchase than those who do not.” Maybe you say, “People who watch our video show purchase 50% more from us than the average customer.” THAT is the Holy Grail we’re on a quest to find. But here’s the thing: This isn’t some fictional relic. This is very real, very attainable, and yet, so many of us won’t reach out and grap this opportunity. And why? Because just like searching for the Holy Grail, it requires a bit of a journey to get there. This doesn’t feel the same as glancing at Google Analytics or Apple’s podcast dashboard or YouTube’s subscriber count.

But for a few willing adventurers — maybe you? — they’ll start making brilliant decisions. On the one hand, if show subscribers prove less valuable than the average subscriber, they’ll know they need to fix the show (or kill it). Maybe they make what seems like a radical choice and rebrand the program and revisit its premise, name, tagline, and messaging entirely. Why?! It had some listeners! They were growing! True, but their RPS was lower than other subscribers. It was attracting audience — but the wrong audience. Even if that audience was large, it was low value. Time to make a change.

On the other hand, if show subscribers prove more valuable than others, now it’s time to get proactive. Invest more to grow the show. It’s working. Subscribers are valuable to the brand. Great! Grow the thing. Find net new audience. Additionally, since it’s so valuable, we can ensure existing audiences find the show: visitors to the home page, the log-in screen (Mailchimp does this for new show launches), offline events (we’re doing this for Boston friends on Feb. 26, 2020), and during the sales process. Find out where existing audiences who already interact with you are paying attention, and alert them to the show. Because show subscribers prove more valuable than others.

Regardless of the specific approach, we can use RPS data to make informed, strategic decisions and to have more productive conversations internally. The key is to focus on value, not totals, and look across the lifetime of a subscriber, not grab at short-term numbers.

Our hypothesis: Shows yield more valuable audiences for our brands, because shows deepen relationships in ways few other things can. This isn’t a marketing thing. This is a human thing. That’s our hypothesis.

Our challenge: Match what you measure with what you create. Why does a show exist? Why do we do marketing more generally? It’s not about who arrives. It’s about who stays.

Maybe it’s time we measured accordingly.