2.1.4 Customer Growth Models

In the previous section we covered common revenue growth models to understand how companies make money on different types of products. In those models, revenue was driven by essentially the same three factors:

• the number of customers making purchases,
• the number of purchases that those customers make, and
• the size of those purchases.

The number of customers that a company has depends on how well it acquires new customers and retains existing ones. On the other hand, how often those customers buy your products and how much they spend per transaction is based on how well the product and the entire customer experience is able to engage them. The models in this section focus specifically on increasing the customer base and how much customers buy.

Even though revenue depends both on how many customers a business has and how much they purchase, many business leaders focus on growing only the number of customers. Moreover, they tend to focus on growing the customer base by acquiring new customers without giving much thought to retaining existing ones. This trend is unfortunate because increasing how often customers buy and the size of those purchases can also be an extremely effective way to grow revenue.

Basic Customer Growth Model

The concept that your customer base will grow bigger if you improve how well you acquire new customers is a simple, universal belief. Perhaps this is why many businesses start with trying to improve acquisition in order to grow the customer base and revenue. However, the rate at which the customer base grows is not just a function of acquisition but also depends on how well the business is able to retain existing customers. Neglecting existing customers can really drag down your growth because you are essentially fighting an uphill battle. Every time you get more customers, you lose some number of them, and the resources that went into acquiring them are squandered. Consider the major cellular providers such as AT&T and Verizon. They know that retention is critical to the profitability of their business, so they bake it into their business model with long-term contracts. Moreover, they give great deals to existing customers when their contracts run up to make sure that existing customers stay loyal to them. Of course, no business can retain all of their customers, but the ones that do a better job hanging onto theirs have a leg up on the competition.

Let’s take a simple example to see how both acquisition and retention factor into the growth of your customer base. Imagine that you are able to acquire a hundred customer per day. At the same time, you lose one out of four of those customers the very same day. Perhaps they sign up for your product, but then realize that it does not really suit their needs and cancel their account right away. Therefore, the effective customer growth rate is seventy-five customers per day. In reality, the dynamic between acquisition and retention is a little more complicated.

First, the acquisition rate is rarely linear over time, so the business might be acquiring a hundred customers per day one month and three hundred customers per day the following month. Often times, seasonality plays a factor in acquisition rate. However, these nuances only matter when you are trying to develop more rigorous models for predicting growth. Just understanding the concept that acquisition and retention play a part in the net growth rate is enough for a high-level model of your business that will feed into your growth strategy.

Second, the retention rate is also not typically a simple function like described above. Instead, retention is almost always a function of time where the more time passes, the more customers abandon the business. For example, let’s say that your business acquired a hundred new customers today. It might be that ninety-eight of them will still be active customers tomorrow, but only half will be your customers in a year from now. Therefore, it is important to compare acquisition and retention rates over the same time periods to get an accurate sense of overall growth rate.

Third, the retention rate is often calculated in terms of the overall customer base rather than by cohort. This is a critically important distinction because how you calculate it will often give you vastly different results. Let’s consider the cohort example first. Imagine that you acquire 1,000 customers in a month, and the cohort retention rate is 75% for the second month. That means that of the thousand new customers that you acquired in the first month, you will have 750 in the second month.

Now let’s consider an absolute retention rate where your business loses 25% for your entire customer base every month, so you retain 75%. After a few years in business, you have 10,000 existing customers and your acquisition rate is a thousand new customers per month. That means that you business will be adding 1,000 new customers but losing 2,500 existing customers resulting in a net loss of 1,500. As you can see, the result is very different in this case than in the cohort analysis, and this is important to keep in mind when more rigorous calculations are needed.

As you can see, we are continually zooming in. We started with the big picture and revenue equations. Then we focused on how acquisition and retention work together to drive customer growth. In some cases, however, it’s important to focus solely on the acquisition part of the customer growth equation. The next three models provide insight into factors that drive acquisition rate.

User Generated Content Growth Model

Many websites and apps rely on user generated content to provide value to their customers. Products such as Twitter, Wikipedia, and YouTube all rely on some of their users creating new content for others. The most successful of these are able to build thriving businesses by creating a sustainable ecosystem of content creation and consumption.

The way user generated sites work is quite simple. The majority of users will just consume the content that is being created. However, a small portion of the overall user base will create content. As that new content is created, it will draw in even more new users, and some of those new users will also create new content repeating the cycle, which is modeled by the equation below.

For example, let’s say that we’re starting out with 1,000 users in the first period. Most of those users will just view content, but on average, one post will be created for every ten users. Those posts might get indexed by Google, and each of the new posts will then attract fifteen new users when they search for related topics. That means that in the second period, we should have 1,500 new users or a total of 2,500 users, and the cycle repeats agains. The important things to note from the above model is that the rate at which new users are acquired is driven by the rate at which new content is created as well as the rate at which that new content attracts new users.

Viral Growth Model

Some products such as social networks rely heavily on existing customers inviting others to grow their customer base. This acquisition model is often called the “viral model” although to be truly viral, each user has to successfully get more than one new user to sign up, on average. All the same, viral growth can be modelled similarly to user generated growth, where the number of new users is a product of the existing users, the average number of invitations per user, and how many of the invitations are accepted.

For example, if we have a thousand users in the first period, and each of those users invite an average of two people in that period, they will send out 2,000 invitations. Let’s now suppose that only one in four of their invitations get accepted by their acquaintances. That results in 500 new users in period 2. Therefore, you will have a total of 1,500 users in the second period, and the cycle repeats.

One thing to note is that the invitation and acceptance rates need to be over the appropriate periods of time. For example, we could figure out the average number of invitations that existing customers send over a day, week, month or a year. We would need the same period length for comparing the acceptance rate. In other words, if we are calculating the invitation rate over a week, we need to use the acceptance rate over a week as well.

Another point to note is that the acceptances have to happen after the invitations, so in order to be truly accurate we have to remember to take into account a time period lag. For example, if current users send the invitations in period 1, the acceptances will happen in period 2. The above model captures this in a simple way, but you might have to be more explicit in your equation to be more rigorous.

Paid Acquisition Growth Model

There are a number of products that cannot greatly rely on growing their customer base through viral features or user generated content spurring search engine traffic. These products are often in the software as a service (SaaS) space or other commercial product space. In these cases, those companies have to rely on paid acquisition such as paying a partner company money for getting their customers to try your product. This strategy works great when existing customers pay for the acquisition of new customers through the revenue they generate for the company, which the company reinvests in paid acquisitions.

The cycle transpires as the following. First, existing customers generate revenue for the company, which translates to profit after we subtract the expenses of serving them. The company then decides how much of that profit to reinvest into paid acquisition — the investment rate. Together, this determines the total amount that the company is going to spend on acquiring new customers in a given time period. However, that’s not the end of the story since a dollar does not necessarily buy you one customer. Each new customer will cost you a certain amount of paid acquisition spend, which we call the acquisition rate per spend. Now, putting all these parts together will give you how many new customers you can get in the second period if you start with a given number of customers in the first period.

Let’s imagine that we have 1,000 customers in period 1, and each one generates an average of $10 of profit for the company for a total profit of $10,000. The company decides to reinvest one out of every five dollars for paid acquisitions, costing $10 for every new customer. In period 2, the company can expect 200 new customers or a total of 1,200 customers.

The great thing is that the above model can apply to any paid marketing activity that is subsidised by profit earned from existing customers. Simply generalize paid acquisition to paid marketing, and the model still holds true. The acquisition rate will take into account the probability of acquiring a new customer if the conversion rate is not one hundred percent.

Lifetime Value (LTV) Model

The last model that we’ll cover in this section is not really a customer growth model nor is it a model for the total revenue. Instead, the customer lifetime value model shows us how the average revenue that a company earns from an individual throughout the time that he is an active customer is the product of the average revenue that a customer brings in a given time period and the average lifetime of the customer. The customer lifetime value model helps us see that we can grow revenue by either increasing how much customers spend in a given period or how long they stay active customers. For example, imagine that the average amount that your customers spend per week is $15, and they tend to remain customers for ten weeks. (In other words, your company loses one customer every ten weeks — the churn rate.) That means that the average lifetime value (LTV) is $150 per customer.

It’s worth noting that the above model is a simplified version of a more rigorous model that takes into account interest rate for a discount rate and a gross margin. Nonetheless, this simplified model provides great insight into how retention rate affects revenue.

Combining Customer Growth and Revenue Models

As we saw with the revenue models in the previous section, the number of customers that you have greatly determines how much money your business can make. While the revenue models provide a broader picture of the different ways to influence revenue growth, a key driver is often simply how many customers your business has. The customer growth models in this section can be plugged into the revenue models in the previous section to give you a deep understanding of factors that contribute to increasing the number of customers, which in turn influences your company’s revenue.

For example, we discussed how the total revenue that the company makes from the marketplace is a product of the number of items available for sale from sellers, the probability of a sale, and the average transaction fee. If you wanted to see how a feature allowing users to invite their friends might play into that model, you can simply plug in the viral growth model into the marketplace revenue model to see how virality can affect the number of sellers, which drives the number of products for sale and ultimately revenue. While this is one combination, you can combine any of the customer growth models with the revenue models to gain deeper insights into factors that you might optimize as part of your comprehensive growth strategy.

Be sure to check back tomorrow to learn about strategizing and prioritizing experiments. New sections of Growthzilla are published every weekday.