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Imagine that you’re driving a car. Usually, there's a dashboard that shows a car's speed, fuel level, and many other bulbs that light up in case of need. All this information is right in front of your eyes to help you track everything and react fast if something goes wrong.
Product management metrics have more or less the same function. They help to monitor how your product is doing: is it growing or falling, what affects positively, what negatively. It's a must to have such a dashboard with metrics when you start any business.
In this article, I'll zoom in on the metrics to measure product success for startups. We'll talk about why product metrics are important, look over 2 stages of startup development: pre-launch and post-launch, and set the metrics for each. There's a lot to cover, so let's dig deeper.
Why You Should Track Product Metrics at Startup
Besides that product metrics show how the product is running, they also have other purposes. So I suggest starting with the reasons to track product management metrics first, rather than cutting right to the metrics examples.
To Set Business Goals
Many entrepreneurs don't think much about numbers at the beginning, which is a huge mistake. Determining the right product performance metrics helps to make more intelligent decisions in business. These metrics are often called – product KPIs. In simple words, it's evidence that your product reaches or fails to reach the goals.
Product, marketing, and sales teams set the goals every quarter. For example, a product goal may sound like this: "We have to reach the retention level of 20% in the 2nd quarter." The percent wasn't plucked from the air. It doesn't work that way. The product manager has to check the analytics from the previous periods, study similar products, and make a wise prediction based on this information.
So one of the metrics' purposes is to help the company set realistic product management KPIs. Otherwise, product managers are forced to rely on pure assumptions.
To Figure Out the Product’s Weak Points
Let’s be realistic – no one builds a perfect product in one shot. It demands the cycle of iterations, users’ feedback, and constant improvements. And it’s fine; that’s exactly how the startups work. You build an MVP first, reveal the product's weak sides and improve them. Weak points could be anything that damages the user experience: a needless 'record' button, a map placed wrong, or a purple color text that frustrates users. Weak points could also be more crucial, like wrong product idea or inferior product that doesn’t beat its competitors.
Product management metrics give a better understanding of what these weak sides are. By looking at the analytics, you can track how users interact with your product, which buttons they click on, how they navigate in your app, etc. This data helps you unveil the parts of the product that require improvements, dig deeper and polish them up.
To Find Out When It’s Time to Pivot
The last and my favorite metrics' purpose is – they say when it’s time to stop. Let's say you launched a product, it gained users, reached some product KPIs, then it started to drop, and several months later, no traction. You have 3 ways out: cross your fingers and hope for the better, quit or open Google Analytics or any other tool you use, and look at the numbers.
If your target metrics are on the low level after lots of tests and experiments, it's time to think of pivoting. So, think of product success metrics as the speedometer and keep track of it.
Metrics to Forecast Startup Success
We approached the core of this article, product metrics examples. As I promised, we'll cover 2 stages of startup product development, and logically, the first one is – pre-launch. The goal here is to forecast your startup success. Sounds huge, so let's begin.
One word – unit economics. No matter what you start, a startup, a local shop with organic food, a real-estate business, you need to calculate unit economics. In simple words, unit economics tells you whether you get profit from this specific user/unit or not. To calculate it, you need to know:
- How much money you spend on acquiring a user;
- How much money you get from the user;
That's it. Now, let's figure out what product metrics we need here.
Customer Acquisition Cost
CAC – stands for how much money you spend on acquiring one user. So the result you get is the money spent on attracting one user. To calculate it, check out the formula below.
I noticed that defining sales and marketing costs often appears to be a problem. So I’ve gathered a list of the most common expenses:
- Money spent on salaries;
- Money spent on product development;
- Money spent on marketing, analytical, communication tools;
- Money spent on ads;
- Money spent on content creation;
The list can go on and on, but generally speaking, there are many tiny details included.
Customer Lifetime Value
You definitely faced up the Customer LTV product metric at business books, webinars, workshops, etc. It is very popular.
So why is it on everyone's lips? Because it tells the exact amount of money you get from one user. And who doesn't want to know that? There are different methods of calculating LTV, and I'll give you two of the most common ones.
The final step here is to compare CAC and LTV.
Revenue on Investment
Some of you may say, 'why do I need unit economics if I've calculated ROI?' And that'd be a perfect question, and my perfect answer to it would be 'you don't need to calculate both.' Yes, ROI is the same old product metric that replaced the whole unit economy, or it was the unit economy that replaced ROI. Whatever, it's a chicken and egg question.
ROI shows how much money you get back from investing in a particular distribution channel.
To cut the final line here, the pre-launch stage is all about researching, making assumptions and predictions as realistic as possible. Get ready to spend lots of time comparing your business with the competitors' ones, studying the approximate marketing, sales, and development costs, and making a financial plan for your business idea.
It seems like a work with too many unknowns, and that's what it really is. But by making these calculations, you lower down the level of uncertainty. And it’s not a one-time activity, you should make these calculations periodically after the launch.
Metrics to Measure Product Success After Launch
So, we calculated the possible startup success, and the numbers told us, 'yeah, you should launch.' After passing all the stages of the product development process and preparing a go-to-market strategy, your product entered the market finally.
How to measure the success of a just-released product? First, there's no one-off answer here because everything depends on the product type. Second, to measure product success in the first days after launch, you need to define your target metrics. This is where the most interesting part begins. To define your target success metrics for a product, you need to follow the next steps:
- Study how users interact with the product;
- Learn what value they find in the product;
- Define which actions they need to complete to get the value;
- Start to track the analytics for these actions;
Though product success metrics may vary, there are some key metrics that almost everyone uses to stay on board. Let’s check them out.
Retention rate is one of the crucial product metrics. Why? Because it determines the growth potential of your business. The more people repeatedly use your product, the more likely you bring the value, the more likely using your product will become a habit.
There are several ways to calculate retention rate, depending on how you define "active users" and how you set the period of time. You need to determine both according to what makes the most sense for your business.
A small tip, a retention chart looks like a smile in the best scenario. So, strive to make your retention smile:) Generally, the retention rate formula looks this way:
So, retention is all about creating a habit. As Ben Horowitz, an American businessman, investor once said:
"The primary thing that any technology startup must do is build a product that's at least 10 times better at doing something than the current prevailing way of doing that thing. Two or three times better will not be good enough to get people to switch to the new thing fast enough or in large enough volume to matter".
In one article, the author claimed that Spotify's freemium conversion rate is above 40%, while "for most companies that leverage this business model, freemium conversion rates hover somewhere between 2 - 5%." Why so? It turned out that the calculation was made wrong. They considered the conversion rate as the ratio of paid users to active users, which is completely different from the conversion rate of new users into paying users.
So what is the conversion rate exactly? It is the number of users who made a target action (purchase, registration, click, download, etc.) divided by the number of new product users.
Note that the number of new users who made a payment is not the number of users who keep paying. And the total number of new users isn't the active ones.
Though I described the conversion into paying users only, conversion rate can be very different. For example, the number of users who clicked the ‘contact us’ button at the end of this article compared to all people who opened the article would also be a conversion.
Last but not least, product measurement metric – churn rate. The churn rate, also known as attrition rate, basically shows the percentage of customers that stop using/paying for your product.
It's important to measure churn rate in 2 ways:
- in customers – it will always be positive;
- in money – it's nice to aspire to negative attrition;
‘Why should I keep an eye on both,’ you may ask. The thing here is that these two product management performance metrics can be quite different, and it's useful to keep track of them to understand the ongoing processes.
To make it less confusing, let's put it into practice and take the Spotify example again. Imagine that Spotify has 70 clients with a subscription cost of $10 a month and 30 with a subscription cost of $5.
In total, they have 100 clients, and their monthly revenue is $850. Now imagine that they lose 10 customers next month. 9 of them paid $5 each, and 1 paid $10. So the customer churn rate will be 10%, and the revenue churn is only 6.4%. So keep track of both.
What about growth metrics as DAU, MAU, the total number of registrations, etc? They are useful for a general product analysis but making product decisions based on them is a waste of time. When you’re launching a startup, product metrics should be your target.
Product success metrics are the speedometer for any product. They help to measure a product's success and alarm you when things need to be changed.
The starting point is the startup pre-launch. It's a time of making realistic predictions of your business idea, calculating the basics of unit economics, and based on this making a decision: to start the development or to pivot. The next stage is sustaining your startup, and it could last long. Very long. You start with a small data set and define the target metrics. Then adapt according to the outcomes you need to measure. The key metrics examples at this stage are Retention, Conversion, and Churn rate. They are vital for keeping your startup on board.
The power of product success metrics is vast. Though I tried to cover the great part of the product metrics topic in this article, there could be questions left. Feel free to drop us a line if you need any additional information or consultation. We'll be happy to help you!