Behind nearly every successful technical product lies a knowledgeable, analytical, intuitive product manager. Effective product managers wear a multitude of hats, juggling responsibilities including conducting customer interviews, user testing, feature prioritization, roadmap planning, resource allocation, and defining, tracking, and comparing key metrics.
This last function is key to guiding and adapting product development and rollout. While certainly part science, using metrics effectively is also an art. Interpreting, weighing, and giving life to cold numbers is vital for data measures to have real, usable meaning. As explained by author and UX designer Molly Norris Walker, “The numbers should speak for themselves, but they don’t.”
There’s an ever-growing number of ways for SaaS PMs to measure product and process performance. Here's an introduction to seven key product management metrics and KPIs to add to your analytical toolbox.
7 metrics to add to your analytical toolbox
1. Net Promoter Score (NPS)
Quantifying customers’ happiness with your product is a multifaceted undertaking. One of the simplest ways to do this is by measuring your Net Promoter Score (NPS), which is based on a single question:
How likely are you to recommend this service/product to a friend/colleague?
Customers answer on a scale of one to 10, where one through six are deemed “detractors,” six through eight are categorized as “passives,” and nine and 10 are considered “promoters.” Then, your NPS is determined by subtracting the percentage of detractors from the percentage of promoters. Generally, a healthy NPS score is considered to be anything above zero.
So, once you know your NPS score, what should you do with it? First and foremost, once you’ve figured out your score, continue to measure NPS and watch how it changes over time. Set up a dashboard and consistently compare different periods of time to understand how inflection points in your roadmap led to increases or decreases in your score.
Second, your promoters are an invaluable asset. Not only are they likely to promote your product via word-of-mouth, their positive feelings can also be leveraged through marketing efforts like case studies and interviews.
Additionally, PMs can (and should) use your NPS data to track down the source of your detractors’ frustrations, and turn dissatisfied customers into happier ones.
2. Feature Adoption
When you launch a new feature in your product, the obvious goal is for your customers to start leveraging it as soon as possible. There are several angles from which product managers can measure feature adoption, including:
Time to adopt, or how long it takes customer to begin using a feature after learning about it, which can show how well the feature addresses a pain point
Breadth of adoption, or what percentage of your users adopt the feature, which can tell you how appealing it is
Depth of adoption, or how often key user types engage with the feature and if they’re using it as intended, which can demonstrate how relevant the feature is and how easy or difficult it is to use
Duration of adoption, or how long a customer continues to use the feature after learning about it, which can tell you whether the feature is actually valuable to your users
For SaaS companies, a baseline measure feature adoption is relative to monthly logins: Monthly Feature Adoption Rate (%) = [feature MAU / monthly logins] * 100.
In order for your users to adopt new features, they need to be aware of them. There are several ways to communicate with your users about releases and updates, like through email newsletters, feature spotlight blog posts, social media announcements, and in-app notifications and/or walkthroughs. If a new feature is more complex or requires training to get the full value, consider hosting live or on-demand training webinars that users can tune in to.
Of course, feature adoption isn’t only a concern for new features. There are many strategies product managers can employ to boost adoption for existing features that might be under-used or have recently been updated, including running experiments, retooling your onboarding experience, and gathering user feedback.
Moreover, monitor the lifecycle of features by comparing adoption at release to different points as time goes on This can show you what types of trends and patterns, such as seasonality, might affect the uptake of new or existing features.
Give your team the insights they need to compare the patterns that lead to a perfect digital customer experience.
Request a FullStory demo to get started.
3. Retention rate
Retention rate is an especially vital metric for SaaS and subscription-based businesses. It’s the percentage of active users versus total users over time. For more in-depth retention breakdown, HubSpot offers a free downloadable customer service metrics calculator.
Much like its converse churn rate, retention rate goes beyond just marketing. Customers have bought the pitch. Keeping their monthly/yearly loyalty is a matter of meeting expectations, delivering continuous value and giving them reasons to stay. Improving retention is a deep, large, and wide challenge involving every customer touchpoint, from product to performance to customer service. For ideas and inspiration, check out 2020’s top brands by customer loyalty.
One specific strategy for boosting retention is through a loyalty program. Many companies extend perks and incentives to reward and engage current customers to recommend products and membership to others.
4. Customers lost/churn rate
Reducing churn, as with increasing retention, is a multifaceted objective. It’s of little surprise that attrition rates are highest among new customers and especially trial customers.
Like retention rate, churn rate is relatively easy to grasp and often complex to improve. It’s the percentage of customers that leave over a given time period. Simple enough. However, defining the time period to measure, even defining what constitutes a customer, varies almost as much as the companies using the metric. More importantly, when you can compare customers lost across different time periods, you can achieve a better understanding of the patterns and trends influencing churn. In any event, the guiding principle, as with any calculation, is to keep it simple.
5. Customer satisfaction (CSAT)
Customer satisfaction, or CSAT, might seem a bit vague in concept, but nonetheless is vital to quantify for players in highly competitive spaces. Whatever the particular calculation, the prime driver of CSAT is meeting customer expectations. And they have many. From ordering/signup to delivery/access to performance to support, keeping customers happy means firing on all cylinders, every time.
The complexity of determining customer satisfaction begins with determining what “satisfied” means for your business. The term is commonly defined by lack of frustration–as in, customers won’t leave if they don’t have a reason to. However, more insightful qualitative data can reveal deeper understanding of users’ desires and how well they’re being met.
There used to be only one way to find out how customers really feel—to ask them. Now, with tools like Session Replay, not only can you uncover customers’ feelings without conducting lengthy interviews, you can also quantify their sentiments with data and analytics.
Ready to unearth the issues causing lost conversions (and figure out how to fix them)?
Talk to a FullStory expert about digital experience intelligence.
6. Conversion Rate
Conversion rate is a basic metric that can have any number of different meanings, even within a single company. Simply put, a conversion rate is the percentage of users who take a desired action or set of actions.
For SaaS companies, conversions often refer to the rates at which people move through your sales/marketing funnel. This might look something like: number of people who are targeted by a demand generation campaign → % of those people who visit your site → % of visitors who start a free trial → % of free trialers who upgrade to a paid plan.
For product managers, conversion rates signal how successfully your product strategy is performing. Monitoring conversion rates and comparing them over time can also reveal how well your different marketing and demand generation campaigns align with that product strategy over the long term. Low conversion rates might be tellers that you’re missing the mark somewhere within these strategies.
No other metric is as performance-driven at stickiness. Are people actually using your product, and how regularly? For SaaS and tech providers, whose products are designed for daily and weekly use, stickiness gives a clear view of adoption. This metric is calculated as daily active users (DAU), weekly active users (WAU) and/or monthly active users (MAU) versus total number of subscribers/downloaders.
Stickiness trends are prime indicators of both churn and retention rates, and any spikes are certainly cause to track down the source.
Just as no single food guarantees physical health, no single metric, nor collection of metrics, guarantees product success. The importance of all indicators, including the ones listed above, depends upon organization and circumstance. But identifying and relying on the most relevant metrics provides the best-informed guide to achieving it.
Equip your team with the insights they need to improve the digital customer experience.
Request a FullStory demo to get started.