# How to calculate unit economics for mobile apps. What metrics are required?

Unit economics describes how much a business earns or loses on a single unit. A unit is a basic income-generating entity, and each business has its own unit. For example, if you produce and sell goods, your unit is an item. If you have an app with a subscription model, your unit is a user. For consulting services a unit is a contract, etc. As a rule, the unit economics calculation is necessary to understand how sustainable the business is and whether it can be scaled (that’s why a unit for each business is something that can be scaled).

Unit economics answers a simple question – do we make money on a particular user (unit) or not. To answer this, we need to do the math:

• How much money did we spend to attract a user?
• How much money did we earn from a single user?

There are many ways to calculate the unit economics and different approaches for doing so with various metrics. In this article, we share one way to easily calculate the unit economics of a mobile app with a minimum number of metrics.

## How to calculate the unit economics

Basically, we need to calculate the profit that our app generates:

Profit = Net revenue - Costs

To do this, we’ll need 2 types of metrics: product metrics and marketing metrics. Let's dive into the nitty-gritty of these metrics and see how they affect the product.

Let's assume that we are calculating the unit economics of a calorie counting app with two types of subscriptions – Basic (\$7) and Premium (\$10), it also has limited free functionality (freemium app).

## Product metrics formula of unit economics

Product metrics show how a product makes money. Net revenue is based on product metrics:

Net revenue = Users x ARPU x (1 - Commission),

Where ARPU:

ARPU = Average price x Conversion x Lifetime

Next, we'll take a closer look at what ARPU and other product metrics are.

So, what are the product metrics that we will need to calculate: ‌

• Average Price
• Conversion
• ARPU

This is a metric that shows how long a person remains an active user of a product (the cycle from the first to the last launch of an app). Lifetime can vary for different verticals, from a few weeks in games to several years in social networks. Lifetime is related to Churn Rate. Сhurn Rate is the percentage of users who stopped using the app or deleted it. The higher the Churn Rate, the lower the Lifetime of the product.

Note: Lifetime is not the same as Lifetime Value (LTV). LTV is the revenue that a user brings for the entire time he/she is with you. LTV is an important metric that should be regularly calculated for all products, but in our version we use Lifetime.

Let’s say that Lifetime of our calorie counter is 7 months.

### Conversion formula

Shows how many percent of users took specific action in the product (e.g. Buying a subscription, completing a level in a game).

The August cohort of the app had 20,000 users, and 1,700 bought a subscription.
Conversion = 1,700 / 20,000 = 8.5%

However, conversion figures alone cannot tell if a product is successful or not. You need to consider the big picture and see how it relates to other metrics.

### Average Price formula

This metric is needed to calculate ARPU. Remember that you need to keep a balance in pricing – the price should cover operating costs and still be adequate for the user. We recommend using The pricing thermometer proposed by Kavin Hale, Y Combinator partner, as one of the pricing methods.

Let's go back to our example. Out of 1,700 users, 1,200 users bought a basic subscription for \$7, and the remaining 500 bought a premium subscription for \$10. The average price of paying users in the cohort equals:
Average Price = (1,200 x \$7 + 500 x \$10) / 1,700 = \$7.9

### ARPU formula

ARPU (Average Revenue Per User) shows how much revenue one user brings on average within a cohort. To find out the revenue generated by paying users you need ARPPU (Average Revenue Per Paying User) metric.

So, reminding you of the formula for calculating ARPU:

ARPU = Average Price x Conversion x Lifetime

In our example, the calculation would look as follows:
ARPU = 7.9 x 8.5% x 7 = \$4.7

### Commission

These are all commissions that we deduct from revenue. For example, the App Store charges a 30% commission (The small business program assumes a 15% commission if the app earns less than \$1M). Then:

Net Revenue = Users x ARPU x (1-Commission) = Users x ARPU x 70%

Assume that there are 13,000 users in the app, let's calculate with a commission of 30%:
Net Revenue = 13,000 x \$4.7 x (100%-30%) = \$42,770

## Marketing metrics

Next, let's calculate marketing metrics, it’s our advertising and promotion costs. Marketing metrics reflect how the team is able to attract users to the product. There are many free and paid ways of user acquisition. In our article, we talk about how to calculate the economics of an app from paid channels (like Facebook).

Costs per cohort, which are marketing costs, are calculated as follows:

Costs = Users x CPU

We’ll need these metrics:

• CPM
• CTI
• CTR
• CPU

### CPM

CPM stands for cost per mille, meaning the cost per thousand impressions. This metric can be found in the Facebook Ads Manager. To calculate the unit economics, we need to divide the CPM by 1000, so we know how much one impression costs.

Suppose the CPM in August was \$8. Thus, one impression costs \$0.008.

### CTI formula

Click-to-Install, or CTI, measures how many people downloaded the app after clicking on the ad. Knowing CTI gives you an idea of how many people are really interested in your product. It is calculated as follows:

CTI = Number of installs / Number of ad clicks

For convenience, we equate the number of users (13,000) to installations. 230,000 clicked on the ad, so CTI = 5.6%.

### CTR formula

CTR stands for Click-through Rate. It shows what percentage of people who saw the ad clicked on it. This metric reflects how catchy your ad is. It also can be found in the Facebook Ads Manager and is calculated as follows:

CTR = Clicks / Impressions

In August, our app's ads were seen by 8,250,000 people and 230,000 users clicked on the ads. CTR = 2.8%

### CPU formula

CPU stands for Cost per User – an average cost per cohort user. The terms CPI (Cost per Install) or CPA (Cost per Acquisition) may be used instead of CPU. How to calculate a CPU:

CPU = (CPM/1000) / CTR / CTI

CPU calculations for our example:
CPU = \$0.008 / 2.8% / 5.6% = \$5.1

Since we are counting marketing costs, we must take into account here the users on whose attraction the money was spent. That is, only non-organic traffic. However, not all users we attract will pay. You can calculate how much we spend only on paying users, and in this case, you will need the CAC (Customer Acquisition Cost) metric instead of the CPU. In general, CAC is calculated as follows:

CAC = Acquisition Expenses / Clients

The difference between CAC and CPU is that CAC is the cost of attracting a customer, and CPU is the cost of attracting a user. There can be both users and customers in the same product. The difference here is that users, unlike customers, do not pay for the product. For different products and business models, the components in the CAC formula will be different. For example, a product may have different pricing plans, then CAC should be calculated separately for each pricing plan. In products with an advertising monetization model, a user becomes a customer when he interacts with an ad. A user is activated when he sees an ad or clicks on an ad. It follows that New activated users will be used instead of Clients to calculate the CAC of a product with an advertising monetization model.

So, once we have all the metrics we need, we can calculate Net revenue and Costs and understand the profitability of the product.
Costs = 13,000 x \$5.1 = \$66,300
Profit = \$42,770 - \$66,300 = - \$23,520
It turns out that in August our app will have losses, it is necessary to optimize the unit economics of the product. Based on this data, we can formulate hypotheses to improve the product.

### What’s next?

Keeping track of the unit economics of your product is essential so that you are always in control. Scattered data doesn't tell you whether your product is generating revenue. Build a visual chart with product metrics to see which one you need to keep track of. For your app's unit economics, you might need more data than we had in our example.

All of these metrics can then be optimized so that you can find the best traffic sources for the product, metrics to aim for to make it profitable, and mobile advertising strategy. Even a small increase in conversion rate can make a tangible difference to your profitability.

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