Why is user retention rate a matter of life and death?

Some companies see a huge growth in users in a short period of time, but the company goes bankrupt not long after. Why do these companies go bankrupt when the situation is so good? Why do people say that user retention rate determines life and death?

In late 2013, Paul Graham posted a graph showing a very good growth index on an unnamed startup , revealing it was the fastest growing startup YC had ever funded. The mystery company he referenced was later revealed to be Homejoy.

Shortly after the tweet, Homejoy raised $38 million.

Too much joy brings sorrow...the company closed down after 18 months. This story is not unique, it happens time and time again.

In 2011, Fab.com saw a crazy growth of 500,000 users in 10 weeks, which helped them raise $150 million at a valuation of $1 billion. Eighteen months later, after raising $336 million, they sold the company for $15 million.

Need a third example?

OK…

BranchOut, another example of a high-profile death of a startup, went from 1 million active users to 5.5 million active users in 2 months in the spring of 2012. They raised $50 million in funding, $25 million of which came in April 2012 during a period of crazy user growth . However, 18 months later, the company was sold for a bargain, this time for $5.4 million.

These three companies have attracted attention because of their rapid growth, large financing amounts and short life cycles. But this is just a small sample of the countless startups that you never hear of until they die.

So what is the root cause?

Each company was founded and developed by a talented team and funded by deep-pocketed investors , and they all grew rapidly.

So why did they close down?

The reason is the user retention rate. A high retention rate will make the company's growth healthy, and a low retention rate has become the main reason for companies to fall into the abyss of death.

In this post, I’ll walk you through three key ways companies go wrong during the retention phase:

1. The priority of retention was completely eliminated;
2. Misdefined retention metrics;
3. They didn’t measure engagement.

1. How to prioritize retention rate

Short-term retention data can lead you to make bad decisions because it takes time, usually years, to see an impact on your company’s growth. To really understand how it drives the health of your product, you need to look at at least a year of data, preferably 2.

Most companies and teams have short-term goals (quarterly, monthly, or even weekly), and organizations and teams should prioritize retention initiatives, even though retention is somewhere in the middle of the growth funnel.

In-depth research requires the establishment of a forward-looking quantitative growth model, where we assume Company A and Company B for comparison.

What you need to know:

1. Company A adds 1 million new users per month.
2. Company B adds 2 million new users per month.

Hearing these numbers, it’s easy to assume Company B is more valuable than Company A but what about retention?

What else you need to know:

• Company A’s monthly retention rate is 85%.
• Company B has a monthly retention rate of 65%.

A 20% difference doesn’t seem to mean much, and since Company B has twice as many new users per month as Company A, at first glance it seems like Company B might still win.

Let's see what happens over time, after 6 months Company A has about 4.2M MAUs. Company B has approximately 5.3 million MAUs, which is more than 1 million MAUs more than Company A.

The data tells you that Company B will win.

Let’s extrapolate that data out 3 years, and Company A has about 6.6M MAUs, while Company B has about 5.7M MAUs — Company A now has nearly 1M more MAUs than Company B, despite having half the number of new users per month!

As time goes by, Company A's market share will gradually gain the upper hand.

From this example, you can see the impact that high retention can have on long-term growth.

Effect of improving retention rate:

1. Increase new user acquisition;
2. Improve profitability;
3. Step up customer acquisition efforts so you can drive competitors out of your channels and explore new ones;
4. Accelerate the return on investment so that funds can be recovered more quickly for reinvestment.

Even without the additional advantages mentioned above, the company with the higher retention rate wins.

The actual result, including these advantages, is likely that Company A will crush Company B, even though Company B has a very high customer acquisition cost and a lower retention rate.

2. The Risks of Misdefining Retention Metrics

Besides neglecting to plan for retention metrics, another common mistake companies make is to incorrectly define their retention metrics. If the definition is wrong and the data is not recorded accurately, it may render the entire strategy invalid.

1. Choosing the wrong units of measurement

A critical part of measuring retention accurately is choosing the right units of measurement to best understand your product’s retention. When choosing retention metrics there are usage, revenue, transactions, and other aspects, and it is very important to choose the right metric.

The easiest place to get it wrong is in the SaaS market. When you ask someone in a SaaS business or other subscription model business about their retention, the answer you get is one that involves monthly or annual revenue retention.

We should be more interested in how retention is reflected in the breadth and depth of product usage.

Revenue is the output of participating users, and user usage is the input. There are two major problems with using sales revenue as a retention reference:

1. Revenue can hide issues with actual product usage and protect you from long-term product health concerns. You can get a month or year’s worth of revenue from a paying subscriber , but if that person doesn’t use the product, then when the month or year is up, they’re simply going to churn away and you won’t know what went wrong.
2. If you try to improve retention but only track revenue retention, the game is over before you have a chance to play the game . Once you lose paying customers to a competitor, it’s nearly impossible to win them back. If you want to improve retention, you need to first look at usage retention.

2. Choosing the wrong frequency

The second part of accurately measuring retention is choosing the right frequency.

When considering the right frequency for your product’s retention metric, ask yourself, “Do my users need to use my product daily, weekly, or monthly to be considered active (or perhaps longer for some products)?”

The wrong reference time will make you mistakenly believe that your product retention rate is high.

3. Choosing the Wrong Core Action

Choosing a retention metric involves defining the core actions that users take in your product. In other words, what is the core of your product that attracts users to become active users? What is this metric?

To summarize, there are two main problems that arise when retention metrics are defined incorrectly:

1. You’ll end up masking big problems in your product and disguising yourself, and by the time the problems show up in the metrics you’re tracking, it might be too late to fix them.
2. Motivating your team to solve the wrong problems because they are focused on optimizing the wrong metrics will waste a lot of manpower and resources in the wrong direction and end up with nothing.

3. You may have breadth, but not depth (measuring engagement)

Maybe you have your retention metrics fully defined, you have a long-term retention monitoring plan in place, and you’ve invested time and resources into improving your product’s retention. Still, if the product has widespread engagement, you may run into problems.

The breadth of retained users is the percentage of users who remain active within a given time period. But it doesn’t answer the key question – how active were they during this time?

This is a measure of product engagement that answers this question.

The problem with retention as an overall metric is that it’s binary — your users are either retained or they’re not. However, the depth of user engagement is the strongest indicator of the long-term value of both the user and the company because deep users don’t just stay, they stay forever.

LTV is highly driven by CPA, but it is actually driven more by life expectancy. Marginal increases in life expectancy have a huge impact because registered users are fixed and retained users are permanent.

Retention and engagement are the yin and yang, retention without engagement only tells half the story, if you have breadth, if you don’t have depth, that’s okay, and I’ll tell you why below.

1. Engagement drives your revenue model

The success of a product’s revenue model is related to the depth of engagement of its users. Your product’s users may have a good retention rate (breadth), but without deep engagement, conversion and monetization are impossible.

Let’s dive into some basic examples with different revenue models to understand this more fully.

(1) Advertising-based model

Let’s assume Company A has 1 million DAU and Company B has 2 million DAU, and both have similar retention rates. Now let’s look at the engagement of each company’s product, assuming that Company A’s 1 million DAUs visit 4 times a day, while Company B’s 2 million DAUs only visit once a day.

In this case, Company A has 4 million visits per day, while Company B has 2 million visits. If they both make money through advertising, it's obvious that Company A will make more money since it makes 2x more advertising revenue than Company B.

(2) Trading model

In this example, we will compare the impact of engagement for two restaurant delivery companies. Assume that an active user is someone who places one or more orders per week, both companies have 100K Weekly Active Users (WAU), and company A receives an average of 2 orders per week per active user, while company B receives 1 order per week per active user.

Then Company A will receive 200,000 orders per week, while Company B will only receive 100,000 orders per week. If the average order quantity for both is the same, then it is obvious that Company A will make 2 times more revenue than Company B.

(3) SaaS Model

Most SaaS companies build deep engagement into their pricing structure. For example, email service providers typically charge by the number of contacts. Likewise, companies that offer premium integrations charge by the number of actions, such as Zapier Zaps or Google Maps API calls. In all of these cases, depth of engagement is built into the revenue model and is a key driver of revenue.

2. Participate in building defensibility

Deep engagement not only drives product monetization, but also helps the product defend its position in the market. Again, let’s look at some examples with different business models to understand how engagement builds defensibility.

(1) Trading model

Consider the same example above of two restaurant delivery companies with the same number of WAUs, again, Company A receives 2 orders per week and Company B receives 1 order per week.

In this case, Company A's weekly orders double, which leads to two positive outcomes:

1. Restaurants that are part of Company A’s network are more likely to be around for the long term;
2. Company A will better leverage the cash flow from its platform.

Both of these factors are key to driving network effects, which helps Company A build a stronger defensible moat.

(2) SaaS Model

Defensibility in SaaS is generally driven by three dynamics that increase switching costs as engagement deepens.

Product Mastery: When end users become deeply engaged with a SaaS product, over time they begin to master it. They learned esoteric functions and keyboard shortcuts, and this profound knowledge enabled them to work much more efficiently using the software. When this mastery is combined with easy access to their data, it becomes more expensive for users to switch products.

Organizational embedding: This occurs when a company embeds a SaaS product into its products or internal workflows. By being embedded, the product becomes an integral part of how these companies operate and produce results, making it costly to “rip away.”

HubSpot provides a great example of a SaaS product using this strategy. As it brought more marketing automation customers into its sales automation tool , it deepened customer engagement and increased the pain points for customers switching to the new tool.

Network effects: These occur when adding more users improves the product experience and, again, makes switching to a competing product more painful. Slack is a great example of a SaaS product where network effects create switching costs. If the entire team is actively using Slack, admins are less likely to switch to another chat product.

One thing to keep in mind here is that, generally speaking, SaaS products have weaker network effects than B2C products like WeChat , and it’s much harder for WeChat users to change platforms than it is for administrators to choose a competing SaaS product.

4. Why retention determines your life or death

1. To properly understand the impact of retention and prioritize initiatives that require long-term action, which often conflict with the short-term goals of most teams.
2. Retention metrics are easy to misdefine, and if not defined correctly, can lead your team in the wrong direction.
3. Healthy businesses are a function of breadth (retention) and depth (engagement), but too often teams give up on one, or worse, they give up on both.

Hopefully, the examples above reveal the importance of prioritizing user retention and engagement in your growth plans, and inspire you to invest time and resources into analyzing and improving your product.

Source: Langyu