Video Lecture: Revenue Models: Translating Users into Dollars

Video Contents

• [0:11] Common Revenue Models
• [1:17] Three core components of all revenue models

Revenue Models: Translating Users to Dollars

Let’s go to making money. We have this idea of revenue models. It’s one element of our business model. Here’s the definition of it a list of common models.

[0:11] Common Revenue Models

You probably know already, without having a name for it, what the revenue model that you are planning to use for your organization is.

If you don’t know, it’s probably retail sales. Business to business is also retail sales. If you’re selling units of your own product or service to other people, through a network of people which might be retailers, which is why it’s called retail sales. Then that’s retail sales. It’s by far the most common business model.

But there’s some other ones. And we see a lot of them in digital markets. We see a lot of use of subscriptions, pay per use…

And then we have the broker markets, the two-sided markets, brokering transactions. We saw that with the Wildfang case. They were contemplating switching between a retail sales revenue model and a brokering revenue model, or having a piece of both.

Media models are all about brokering attention. I’m capturing somebody’s attention so I can sell them advertising. That is a brokering model. Media models are fundamentally two-sided brokering models.

I encourage you to have a claim about what your revenue model is. People want to know, if you’re trying to build consensus, how are you going to make money?

[1:17] Three core components of all revenue models

There are three core components to all revenue models. We’re going to chain them together, just like we chained our estimates for TAM, to translate the number of customers to number of units or dollars.

So if we have a number of customers in our market, we then add three more estimates, the annual transactions per customer, units per transaction, and what’s the average price. Chain, these three things ,together add it to your estimate of number of people, and you have an estimate in units and dollars of the market size.

Annual transactions per customer is fundamentally built around your hypothesis about the customer decision-making process, That’s bottom up assumptions. We validate those assumptions by the customer insight that we built and it’s going to be different based on different segments.

Units per transaction is our choice. If we sell things in big boxes or we sell things in little boxes, that affects how many units people buy at one time. If we package things up and give you a monthly subscription, instead of requiring you to pay per use, you’re going to have different units and different prices.

And then price is a choice that we make.

So annual transactions is something you can go find through your customer insight. Price per transaction is something you set or something you could observe others in the market setting, and units per transaction is a connection between those two pieces.

So you’re going to have to pull together information from your customer insight, with information about your competitive and own product strategy to come up with an estimate. It does require about definition and estimation. Here’s some examples I came up with. What is the relevant transaction from the customer perspective? I eat a meal, right? I’m trying to serve somebody who is looking for a meal, I might define a meal as burgers, fries, and a drink. If I’m working for McDonald’s, that’s how I define my average meal. That might not be the average meal for everybody, but that’s how we think about quantifying this qualitative definition of a meal. Our first estimate of that.

Music download one song for music download. That’s the dominant product structure right now of music, if you download it at all. We don’t really download music much anymore. We’ve shifted to a different model, which is we buy it per month, on a streaming model or we do a brokering model where we listened to it and exchange for ads. So music downloads is a whole whole revenue model that shifted.

Movie night- two tickets, vacation- seven nights. The exercise here is we have to define what it is from the customer perspective, translate that into what that means for us in terms of products, and then use the combination of the two to estimate a unit of production that we care about.

If we’re a hotel, we build the size of a hotel based on serving X number of people every night. So we want to know on average, how long do people go on vacation? These are kind of numbers that we use to build our models.

And again, just chain them together. Annual units per segment. Customers per segment, which we got from our TAM and SAM analysis, adding on transactions per customer, multiplying transactions per customer and units per transaction. It gives us units

Add on price per unit and we get annual revenues per segment.

As you do this, you will often find yourself saying, it depends. If you find yourself saying it depends, the next question is on what? The answer to your, “on what” question is a factor that is likely defining a segment in your market. Because by definition, on average, these values should be similar for all customers in a segment. And to the extent that they’re not, that means that our segment definition is perhaps too broad to be efficient.

The smaller the segment, the more likely it is to be true. So if we’re trying to make some initial estimates again, that’s why we go small,.