Music Think Tank

Most aspiring artists intuitively understand that there’s value in building an audience for the long-term rather that focusing solely on short-term revenue. Bands offer free downloads, play free shows, and spend countless hours on- and offline interacting with listeners in hopes of developing a fan base that will support them over their careers.

But how much is a fan actually worth? How much should an artist be willing to sacrifice (or spend) today to acquire fans? And how many fans are needed to be able to make a living as a musician?

These aren’t easy questions to answer, but I want to try anyway. Or at least start. That’s why I’ve created a spreadsheet model to help artists estimate the lifetime value of the average fan.

What is Lifetime Value?

In marketing, lifetime value is a framework that companies use to figure out how much a customer is worth. A customer’s lifetime value is essentially the total expected income that he or she will generate for the company over time. By calculating the present value of these future payments, the company can in theory determine exactly how much they can spend to acquire a customer and still be profitable in the long run.

For musicians, the lifetime value of a fan depends on several factors:

The products and services (recorded music, merch, etc.) that they plan to offer over time, and the expected income from each

The probability that a fan will purchase each product offered (“conversion rate”)

The probability that a fan will remain a fan over time (“churn rate”)

Who is a “fan”?

How exactly we define “fan” is important. In order for an analysis like this to be useful, the artist has to have some sort of direct communication channel with the fans we consider. This could include email subscribers, Facebook fans, Twitter followers, or any other relationship that is observable. It’s important to keep in mind that each of these segments is likely to have different conversion and churn rates.

To keep things simple, I’m restricting my analysis to an artist’s email list subscribers. In general, email lists tend to be more valuable than other online marketing channels, so this seems like good segment to focus on as a starting point.

How the model works

To use the model you need to:

Download it (it’s an Excel document)

Enter your product information - what you plan to sell, how often you plan to release new products, the expected income from each, and a few other inputs.

Enter your discount rate. You can also change the default churn rate and sales conversion rates if you are so inclined.

The model then calculates the lifetime value for:

1. A hypothetical fan who purchases all direct-to-fan products that you offer over your career. This represents the maximum potential lifetime value of a super fan.

2. The average email list subscriber. This scenario considers the likelihood that someone would buy each of the artist’s products over time and calculates the average expected lifetime value per email signup.

Limitations

The model DOES NOT consider potential income from concerts, licensing, and other sources where it’s difficult to allocate or estimate income on a per-email-subscriber basis. (If you can think of an elegant way to include something like live shows in this analysis, let me know!) It only considers things like albums, merch, fan club subscriptions, and other items that can be sold direct-to-fan.

The model also makes a simplifying assumption that income per product will be flat over time. Depending on the situation, this could be a conservative assumption (underestimates top/bottom-line growth) or an aggressive one (overestimates ability to sustain margin).

Please share your feedback

This is definitely a work in progress. Like any model, I know this one isn’t perfect. But I’m hoping to make it as useful and simple as possible for artists and their teams to use.

Download it here, experiment with it, and let me know what you think. In particular, if any of you marketing experts out there have any suggestions/comments about the churn rate and sales conversion rate defaults, I’d love to hear from you.

I look forward to refining this model with your help…