16/36 : 📈 Discover the Power of Product Metrics
One accurate measurement is worth a thousand expert opinions.
What Is Product Analytics?
Product metrics are indicators that show how users interact with a product. They are derived from measurements and often have a numeric component of time, ratio, rate, etc.
Product metrics are quantifiable data that provide businesses with insights into the overall success of their products. Companies analyze product metrics to get the information they need to set or modify their product strategy to increase revenue and customer satisfaction.
Product metrics are used to drive product decisions about:
Pricing
Pay model
Feature mix
Onboarding flows
User interface
Ideal customers
Messaging
For example, you could A/B test different pricing and pay models and measure the success of each experiment with activation rates. Track feature usage to see what features your average user finds most useful compared to your power users and decide what features to prioritize or remove in your next update. Find out if your onboarding flows are performing as well as you’d like by measuring the time it takes to activate your users.
Why is it important to track different metrics on your product?
Product metrics matter because without them, teams would have few reliable ways to understand how the elements of their digital product are performing. Business metrics can capture the overall success of a company, and customer interviews can provide qualitative information, but only product metrics give you objective and immediate data on how users interact with your product.
Different product metrics tend to be useful in different contexts, with some offering a high-level view of product performance and others more focused on individual features.
Leading vs. lagging indicators
Every product metric tells a story about where your business is headed or where it’s already been. These are called leading indicators and lagging indicators, and a business needs both to understand how it is performing.
The metrics you use as your leading and lagging indicators depend on your product goals. For example, if your goal is to increase the number of new subscribers to your product, you might use the number of new signups as your leading indicator. If you increase the number of signups, you are hypothesizing that the number of new subscribers will increase in the future.
Leading indicators should drive your daily tactics. They should be something you can measure frequently and easily because you’ll need to hypothesize, test, measure, and frequently readjust as you work to improve them.
Lagging indicators, then, are about measuring whether your actions were successful. You might use annual recurring revenue as a lagging indicator for your goal of gaining new subscribers.
Lagging indicators are based on a long-term strategy. It’s important to know that changes you make today may not show up as improvements in your lagging indicator until much later.
Product metrics categories
Product metrics show you how users are interacting with your product. Your team can use these metrics to better understand what users find helpful, what keeps users coming back, and the best way to take users on a successful journey to becoming loyal customers. Tracking these metrics helps you monitor your business so you can make informed adjustments and continue to grow your business.
These metrics can be split into five categories: acquisition, activation, engagement, retention, and monetization. The acquisition through retention categories represents the general user lifecycle through the product, whereas monetization can overlap with several stages in the customer lifecycle.
Acquisition metrics, like the number of new signups and qualified leads, measure when someone first starts using your product or service. They’re great for understanding what marketing channels are working best for your company.
Activation metrics, like activation rate and time to activate, show you how well you are moving users from acquisition through that critical “aha” moment where they discover why your product is valuable to them and, in turn, provide value to your business.
Engagement metrics, like monthly active users and feature usage, measure how (and how often) users interact with your product. Those interactions might include sharing a song or editing their profile. Users who engage with your product are considered active users. Increasing the number of daily, weekly, and monthly active users is important for company growth—but only if you measure them right.
Retention metrics, like retention rate, free-to-paid conversions, and churn rate, gauge how many of your users return to your product over a certain period of time. These are critical metrics for your company’s growth. It doesn’t matter how fast you fill the top of your funnel if users are leaking out the bottom just as fast.
Monetization metrics, like net revenue retention, monthly recurring revenue, and average revenue per user, capture how well your business is turning engagement into revenue.
Each category of product metrics tells a different story, but they all tell an important one. Here’s a cheat sheet of metrics you should be tracking to monitor the health of your products.
The anatomy of a structured KPI includes:
Key Performance Indicators (KPIs) are the elements of your plan that express what you want to achieve by when. They are the quantifiable, outcome-based statements you’ll use to measure if you’re on track to meet your goals or objectives. Good plans use 5-7 KPIs to manage and track the progress of their plan.
A Measure – Every KPI must have a measure. The best KPIs have more expressive measures.
A Target – Every KPI needs to have a target that matches your measure and the time period of your goal. These are generally numeric values you’re seeking to achieve.
A Data Source – Every KPI needs to have a clearly defined data source so there is no gray area in how each is being measured and tracked.
Reporting Frequency – Different KPIs may have different reporting needs, but a good rule to follow is to report on them at least monthly
Defining the right metric
What is the one metric that matters most to the success of your company and that you can rally your team around? For Facebook, it is active users; for WhatsApp, it is the number of sends; for eBay, it is gross merchandise; for PayPal, it is total payment volume. Once you identify this “top-line” metric, you can set success criteria around it, monitor it, understand what drives changes in it, obsessively push it in the right direction—and properly evaluate and manage the health of your product.
A vision statement should be aspirational, inspiring, and future-focused. For example, eBay’s vision for commerce is “enabled by people, powered by technology, and open to everyone.” eBay’s mission is “to be the world’s favorite destination for discovering great value and unique selection.” Taken together, these two statements point toward eBay’s dream of a world where everyone can find whatever they want, however obscure, at a good price.
What top-line metric would best encapsulate this goal? It is not the number of active users shopping on the site; that metric doesn’t measure whether buyers are actually finding what they want and at the right price. How about the number of active buyers? While and similar buyer-side metrics can tell us whether users are finding what they want at the right price, they cannot address the “unique selection” criteria of eBay’s mission statement.
Some additional guidance on choosing a top-line metric for your company:
Do not pick more than one metric. A single “metric that matters” is unifying and will enable you to set priorities across your entire organization. While it may be tempting to track everything and choose multiple metrics, this isn’t wise. Many metrics correlate with one another; they may help move the top-line metric but can become unimportant and distracting when measured on their own. The more metric goals you have, the more complicated it is to weigh them all and make trade-offs against them. Keep it simple.
Avoid vanity and non-actionable metrics. For example, the number of likes your company gets on social media generally isn’t correlated with business results or customer success.
When choosing between multiple metrics, pick the simplest measurable metric you can move. For example, if your number of advertisers is correlated with your revenue, and the number of advertisers is easier to measure and move, choose the number of advertisers. You can always establish an exchange rate to determine the impact from one metric to another. Likewise, if you are ultimately interested in a metric that has a low sample size or takes a long time to measure, consider instead choosing a correlated metric to measure.
Pick the metric that most closely represents the usage of your product. For a company like Facebook and Instagram, for example, the single most important metric is active users. To measure growth at such a company, we could pick one of several active user metrics, such as daily, weekly, or monthly active users (DAU, WAU, or MAU), all of which are typically correlated. Choose based on the expected usage of the product. For example, if you expect the product to be used once per day or more, select DAU as your top-level metric. If instead, you think the product will be used only on a weekly basis (e.g., when searching for specific restaurants, businesses, etc.), then choose WAU. One of these three—DAU, WAU or MAU—is a top-line metric for most consumer companies.
Do not be afraid to change the metric if you need to. This can lead to thrashing, but it is better to change to a metric that accurately reflects your mission than to move the wrong metric. Ideally, you will put in the time and effort upfront to make sure you begin with the right metric. But if you must change it, do so sooner rather than later.
Choose a simple metric that connects to your drivers. Let’s say you are looking to increase new user acquisitions. You send emails to potential customers, and a fraction of them visit your landing page. A smaller group of users then sign up, and an even smaller group becomes active users. From these numbers, we can create a simple framework to think about the problem of user activation (as seen below). You can increase the total number of users who activate by increasing any of the four terms above. For example, if you see the largest drop-off among people who visit the site but do not sign up, it may make sense to set the percentage of site visitors who then sign up as your metric to move.
Avoid ratios. If click-through rate is what you really care about, see if you can instead measure the number of clicks. However, this isn’t a hard-and-fast rule; there are many examples of companies that successfully used a ratio as the “metric that matters.”
Consider counter-metrics if needed. In the eBay example above, useful counter-metrics include the number of unique items sold and unique inventory listed. If such counter-metrics remain flat or decrease, that may indicate you are drifting from your mission. To address this, you could set an explicit goal that these counter-metrics not decrease. In eBay’s case, the primary GMV metric would remain in place, but the counter-metric would allow the company to maintain checks and balances in a complex environment.
Change the metric as your business evolves. Your top-line metric may need to change over time. For example, before the mobile age, users checked products such as Facebook less frequently because of lack of access and connectivity. As mobile use increased, these companies revised their primary metric from MAU to DAU. This evolution is also common when companies launch new products. For example, Amazon Video has likely increased overall visits to Amazon, which could warrant a change in the company’s top-line metric.
Setting Goals
Teams often think about metrics and goals simultaneously, as they cannot easily be separated. Once you have identified the right metric and goal, you will be prepared to define a strategy and roadmap against which your product team can execute. Goals should highlight what you hope to accomplish and are often stepping stones to accelerating business growth. They can unify your company around a common objective and hold your team accountable for its promises.
As an example, let’s assume you want to grow your number of active users. A goal statement could be “grow MAU to 10M by Q4 2018.” This goal connects the metric (MAU) to a target (10M) and a time frame (Q4 2018), clearly describing what the product team wants to achieve and providing a purpose for the organization. Goals should be simple, actionable, achievable and most important, easy to measure and track.
You can choose goals based on:
Product or business aspirations: Most long-term goals are based on the company’s mission. For example, if your company is in the video space, you might aspire to have the fastest-growing share of time spent on video. If you want to achieve that goal in x years, you can then break it into chunks to determine the growth you’ll need over the next y months in order to stay on track.
Product metrics: If your product has been around for a while, you can do a “bottom-up” forecasting exercise to determine your goal for your top-line metric over a given period of time. For example, a forecast of MAUs could consider historical data on seasonality, platform, country, penetration and product changes. (Future blog posts will offer in-depth guidance on forecasting.)
New products: If your product is completely new, it will be useful to look at external benchmarks and set “top-down” goals. For example, if the product is a Messenger-style communication app, you may choose to study growth at similar companies and let that inform your goals. You may also consider postponing goal-setting for a completely new product for a couple of months, until you see how it performs.
Common Product Metrics
Here are the primary product metrics, organized by type.
Business metrics
Monthly recurring revenue (MRR) is the total amount of revenue your product brings in each month. It’s useful for predicting cash flow and financial health, as well as surfacing gain trends.
How it’s calculated: Multiply the number of customers by the amount each one pays per month.
MRR = Number of customers x amount each customer pays per month
Customer Lifetime Value (also known as CLTV, CLV, or LTV) is the amount the average customer spends on your product during their relationship with the company. It’s useful for understanding how much you should spend to acquire customers, and for identifying the customers you should be pursuing (hint: it’s usually the customers with the highest LTV).
How it’s calculated: Multiply the Average Order Value (AOV) by the average frequency of purchase and the average customer lifespan.
CLTV = Average Order Value x purchase frequency x customer lifespan
. If the average customer makes two $40 purchases each year, and does this for five years, your CLV is $40 x 2 x 5 = $400.
Customer Acquisition Cost (CAC) is the average amount your company spends to acquire a new customer. CAC is useful for measuring the efficiency of marketing and sales activities, and for knowing if the amount your company spends to acquire new customers is worth the revenue they bring in.
How it’s calculated: Divide the total cost of marketing and sales activities by the number of users who become new customers
CAC = Total cost (marketing + sales)/Number of new customers
Churn rate is the percentage of users who stop using your product over a specified period of time. It tracks your company’s ability to retain customers, and is often used as a proxy for customer satisfaction.
How it’s calculated: Take the number of users you have at the beginning of a period and subtract the number of users left at the end of that period. Divide the result by the number of users you had at the beginning of the period.
Churn rate = (Number of users beginning – Number of users end)/Number of users beginning
The adoption rate is the percentage of users who move past exploring your product or feature and start to use it in earnest.
How it’s calculated: First, determine what event(s) count as “adoption.” In general this should be an action that signifies a customer’s getting value from the product, or using for the purposes it was designed. This may require a customer to have used a product or feature multiple times.
Once you’ve determined what counts as adoption, divide the number of users who have performed the adoption event(s) by the total number of users, then multiply by 100.
Adoption rate = (Number of new users / Total number of users) x 100
Daily Active User/Monthly Active User (DAU/MAU) measures the frequency with which users engage with your product, and is meant to capture value gained from your product, with the assumption that users who engage with your product more often are getting more value from it. For SaaS companies in particular, DAU/MAU is often a key measurement of retention and growth.
How it’s calculated: First, determine who is an “active user.” While Google Analytics encourages teams to call anyone who visits your site “active,” a better strategy is to count as “active” only those users who perform an important action on your site or app—clicking “like,” making a purchase, or saving a report, for example.
Once you’ve determined what counts as active, track active users by day and month, divide the former by the latter and multiply by 100.
Ratio = (DAU/MAU) x 100
Conversion rate measures how many people complete a specified action in your product, called the conversion event. Conversion rates measure how effectively your product guides users to take the action you want them to take—making a purchase, downloading an ebook, filling out a form, or any other action that matters to you.
How it’s calculated: First figure out what the relevant conversion event is. Then divide the number of conversions over a given time period by the total number of visitors.
Conversion rate = number of conversions / the total number of visitors
Sessions per user measure the number of times an average user has been active on your site or product. Expectations for a number of sessions may vary across the industry.
How it’s calculated: First, define what counts as a “session.” Note that simple logins or visits are usually not good benchmarks for measuring sessions, since what usually matters is not whether a user has your site open on their browser, but whether they’re engaged with it.
Divide the number of sessions over a given time period by the total number of users.
Number of sessions per user = Sessions / Total users
Net Promoter Score (NPS) measures overall perception of and/or satisfaction with a brand, product, or feature.
How it’s calculated: First, customers rank their perception of the product, brand, or feature on a scale from 0 to 10. They’re then ranked as promoters, passives or detractors:
Promoters (score 9-10): love your product or feature
Passives (score 7-8) are satisfied but not enthusiastic
Detractors (score 0-6) are actively unhappy with your product or feature
NPS is then calculated by subtracting the percentage of detractors from the percentage of promoters.
NPS = Percentage of promoters – Percentage of detractors
Tracking product metrics can feel overwhelming at first, especially when trying to pinpoint what really moves the needle. You might want to check out Loyally AI for keeping tabs on customer engagement and retention—it helped me simplify things and focus on what actually matters. That way, you can make smarter decisions without drowning in data.