Managing to develop an effective product roadmap goes beyond a product manager’s vision or intuition, even if these aspects matter as well. In an increasingly data-driven business world, the product management field isn’t exempt from this need. Analytics will help you sharpen your product sense and give more weight and credibility to the decisions you make and submit to stakeholders.
As a product manager, collecting information about your product performance, its features, the market adoption, etc., is essential. The right product metrics will give you invaluable insights on its health, strength and weaknesses, potential issues or bottlenecks, and let you improve it greatly. In this article, we will go deeper in the definition of product KPIs: what they are, who needs them and why; then, we will go over the steps to find the right metrics for your product; and finally, we will provide some product metrics examples.
What Are Product Metrics?
Like any metric, they are quantitative measurements that help business workers to gain insights into the efficacy of their methods and the evolution of their project. In that specific case, they help in assessing your product performance by checking if it meets the original business goals and if the product strategy is working. Without product KPIs, evaluating the performance of your product might very well end up in a guessing game where reality is skewed.
Product KPIs can be related to user requirement, size, quality, product growth, or user comfort. They can evaluate architectural measures, quality measures, software complexity, or functional size. However, depending on who you are or who you address your report to, product metrics might vary: at the end of the day, stakeholders care about cash but the PM wants to understand how customers are interacting with the product.
And that’s where the big challenge lies. Picking up the right metrics is not as easy as it seems, and even seasoned product managers might not always measure the right things. First of all, not all products are the same and thus, not all data will be collected with the same importance – some are more valuable than others. Another trap executives often fall into is the monitoring of an ever-growing number of indicators (for the fear of missing something), which might very well cloud their vision.
Let’s go over the steps to help you choose the best product metrics for your business.
Finding The Right Product Metrics
Define your business goals
Setting up a data-driven product management starts with having a clear vision of the business goals your product serves. This is essential in the construction of your product strategy, so you need to define them clearly: do you want to grow your existing business? Retain the already-existing one? Target new customers? Goals can be defined as a specific target to reach (percentage, dollar amount, etc.), and should be aligned with your overall objective.
This first step is also very useful to put everyone on the same level: indeed, different members of your team might have different ideas about the goals of your product. This first step provides an opportunity to set up a consensus on where you are heading to.
Find the right metrics by asking the right questions
We all heard somewhere “what isn’t measured cannot be improved” – and this is what this second step aims at: making your goals measurable. You want to know what you measure and why – and to do so, you need to start asking the right questions.
In the matter, the HEART framework from Google can be of a good help: happiness, engagement, adoption, retention, and task success are five categories for which you can ask questions that will define the metrics you want to track. Foster collaboration with different people across the product team (managers, researchers, designers, engineers) to broaden the scope of questioning and develop impactful success metrics.
Do not reduce your questions to purely quantitative measurements that will give you a plain and direct result. Even though these metrics are easier to handle, collecting qualitative feedback will help in understanding why something has happened (why users are unsatisfied for instance). The combination of both will give you a balanced outlook on your product, and reduces the risk of losing sight of the most important success factor: the individuals behind the figures, the people who buy and use your product.
Avoid common pitfalls
In a perfect world, once you’ve asked the right questions, your metrics should normally be well-defined and ready to go. However, this is reality and there are some traps we easily fall into – especially with data.
First mistake is to measure all that you can for the sake of measuring. By doing so, you’ll drown in data and have a hard time discerning the meaningful from the superficial, wasting valuable time and effort analyzing data that creates little to no insights.
Another mistake is to track metrics that look good on the paper and for the ego, but that truly bring nothing to the improvement of your product: the infamous “vanity metrics”. Depending on your product, these metrics can vary, but they always come down to the same thing: they feel good but are not actionable. That can be for instance, the number of downloads of your app: a fair amount of people might download the product, it still doesn’t tell you anything about its performance or how successful it is. Instead, measuring the daily active usage or the referral rate might be more relevant.
To quote the advertising tycoon David Ogilvy: “Most people use analytics the way a drunk uses a lamppost, for support rather than illumination”. Don’t be like most people.
Work on your data and visualize it
Once you have selected the right indicators for your product, you need to collect the relevant and analyze it regularly. Even better, finding a way visualize all of your data on one single dashboard will help in understanding it all together, identify trends or correlations that would remain unseen otherwise.
A dashboard software is of great help to do so. You can connect all your data sources in one single point of truth and work on all of it conjointly – which is rather time-saving since you do not need to perform complicated cross-database queries: the software does it for you. It is also very helpful to share and communicate your insights with the data visualization a dashboard offers: whether you present them to your team members or your stakeholders, picturing all the metrics that matter on one control panel will make everyone work more efficiently.
Product Metrics Examples You Can Use
You have now defined your goals, asked the right questions to your product strategy and are ready to turn each desired user action into a measurable value. In this section we will provide you with product metrics examples that you can use to monitor your product performance, according to what you decide to prioritize on your strategy roadmap.
- Customer retention: it measures the number of customers that repeatedly do business with you. It is important to keep it high because it is far less expensive to retain customers than to acquire new ones.
- Net promoter score: one of the customer satisfaction metrics that will let you know how likely a user would recommend your product. It tells you whether they are happy about your product and gives insights on both customer promotion and loyalty.
- Churn rate: the churn rate is the opposite of retention, as it measures the opposite (i.e.. the customers that stop doing business with you by unsubscribing for instance). It is important to compare it to previous data, as a sudden high churn rate might mean that your customers are not happy with a change in features, pricing or structure.
- Conversions: the number of free-trial users who converts into customers.
Engagement and Features metrics
User engagement metrics are very useful when you want to understand how they interact with your products and identify where there is room for improvement.
- Product usage: a good starting point is to track how often users log in their accounts. In other words, it is the number of sessions per user, and is a good starting point for engagement and behavior analysis. Taking medians over averages is preferable, as they give stronger statistics that are less sensitive to outliers.
- Number of key user actions per session: after selecting specific user actions that matter to you (e.g. clicks on a share button), trace them over time for various cohort of users. You can compare the difference between retained and churned customers.
- Feature usage: how often is a featured used, and how long are users spending on it? What are the profiles of people using this or that feature? Are there seasonal trends in their usage? These are key questions you can answer to build a specific feature profile.
These metrics are rather high-level and will help you shape or re-shape your strategy. These metrics result from the actions of your customers and how they affect your bottom line. They include:
- Customer Acquisition Costs (CAC): all the costs incurred in turning someone into a customer. They encompass the marketing, sales, advertisement, etc.
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- Monthly Recurring Revenue (MRR): evaluates the total amount of revenue a company expects in a given month. The MRR goes hand in hand with the revenue churn, which measures the percentage of revenue your company loses each month because of downgrades (or churns). It is more important to pay attention to this churn than to the general, ‚logo‘ churn rate: serving fewer customers but getting paid more is in the end more important than serving a multitude and getting peanuts.
- Customer Lifetime Value (CLTV): measures how profitable your customers are in the long run, by forecasting the average amount of money you can make out of a customer. The higher it is, the more sustainable is your business. It also helps in identifying marketing campaigns where you spend more for a customer than he is worth it in the end.
The list can go lengthy, especially when you want to test different hypothesis and correlations and need to gather a lot of varied data. However, as we stated above, it is more important to track metrics related to your top goals and avoid dispersion because you can easily lose focus on what matters the most.
The whole point is to learn from this data to improve your product by making better decisions. As product consultant Vince Law states, "a metric will tell you that something is happening, [but] an analysis will tell you why something is happening". Your products metrics are not standalone objects that measure, they need a context to be understood that will give them a narrative, and leverage for improvement. If the only thing you know is that your investment was successful without knowing why, you won’t know what your next investment should be.
To guide your product to success, the recipe is simple: use the scientific mindset that describe the hypothesis, defines a test, and measures it.
As a product manager, you will define the product’s strategic goals, ask the right questions and set up indicators to measure your progression to achieve those goals. These KPIs can be business-oriented, customer-oriented or measure the user engagement, as we have shown in our product metrics examples. Limit your metrics to a handful that will provide you with the most strategic insights, without consuming all your time and resources. Track these metrics on a professional business dashboard to get the overview you need for the general strategy, that you can share with team members, top-management, investors and stakeholders, demonstrating them that you brought evidence backed up with information, on top of your product manager intuition.
Implementing a KPI dashboard software will help you greatly in communicating the insights you gained thanks to your product metrics analysis. If you want to benefit from business intelligence and data visualization, you should test our 14-day free trial.