Blog Software Development Product-Market Fit metrics - is your product something you can brag about?Product-Market Fit metrics - is your product something you can brag about?
Are you a digital product owner wondering if your product will ever achieve market success? If so, you are in the right place! In this article, we’ll go over our favorite metrics for assessing whether or not your product has reached its optimal level of customer satisfaction and engagement – AKA ‘product-market fit’ (PMF). Read on to learn about the product-market fit metrics that we use at Boldare, along with some of our favorite examples.
Table of contents
How to know if your product has reached product-market fit?
You’ve poured countless hours into crafting the perfect digital product, but now your finger is hovering over the launch button, you’re wondering, will people use it and love it? That’s the million-dollar question! The good news is that there are plenty of product-market fit metrics you can use to find out.
But first, a word of disclaimer: each product will have different metrics. Building a digital product is a complex endeavor, as each one of them is unique in its own right. The metrics presented here are just a list of what is available - and whether you use them or not depends on the nature of your product and its business model. So consider the metrics described here as examples backed by our own experience.
Before you measure your product’s performance in the PMF phase, it’s good to know if it has even reached it. That is why we’ll first look at product-market fit metrics used to determine if your product has reached this phase yet, namely: churn and retention.
Churn rate - the PMF metric that puts your lost clients in a perspective
Churn rate tells you the percentage of clients that stopped using your product in a given period of time. Understanding your customer churn rate helps your business calculate the number of customers departing from your product.
To put this in perspective, if you started with 250 customers and ended up losing 10 by the month’s end, then that would equal to a 4% churn rate, or turnover. It’s simple math: divide lost clients (10) by total start-of-time period customers (250). Then multiply the answer by 100% and you come to the same result.
Cohort retention score - was it love at first sight?
If you’re looking for product success, the cohort retention rate measures how many users are still using your product eight weeks after they first began. A score within a 6-20% range can be considered as one of the prime indicators that your product has indeed achieved product-market fit (source).
Net promoter score - is your product a new Netflix hit?
The net promoter score (NPS) is the product-market fit metric that measures the loyalty of your customers and their likelihood to recommend your product or service. NPS is easy to measure as it requires asking only one question: “How likely would you be to recommend our product or service?”
To answer, users give a score between 1 and 10 (with 10 being the most likely to make a recommendation). Now, depending on the score, users can be:
- detractors (6 or below),
- passives (score 7 or 8), or
- promoters (9 or 10)
Knowing this, you can calculate the actual NPS - it’s the difference between the percentage of promoters and percentage of detractors (compared to the whole group).
Net Promoter Score = Promoters (%) – Detractors (%)
This product-market fit metric is a predictor of business growth that will give you deeper insight into user satisfaction and willingness to refer your brand - key elements for sustaining success in the marketplace.
Customer lifetime value - was the juice worth the squeeze?
Customer lifetime value (CLV) is a metric that gives you an insight into the ratio between how much money your company makes per customer and what it costs to acquire them.
To calculate the CLV you need to know two amounts: lifetime value (LTV) and customer acquisition costs (CAC). Each of them can be calculated using basic accounting figures:
(LTV) = Gross Margin % X Avg. Monthly Payment / Churn Rate
and
(CAC) = Sales and Marketing Costs / New Customers Won
with that information, getting the customer lifetime value is a matter of a simple division:
CLV= LTV/CAC
In the context of product-market fit, this metric helps your business measure success more effectively by weighing incoming revenue against marketing investments.
Stickiness - a PMF metric that tells you who your biggest fan is
Stickiness is the key to creating a successful bond between customers and products. High stickiness indicates that users are deeply engaged with what you have to offer. Low stickiness is a sign that your users are merely curious.
Measuring stickiness is an effective way to determine whether or not your marketing and sales efforts are holding users’ interest. With tools like Mixpanel, Segment, and Google Analytics you can track your most active, expressive clients (AKA power users).
When a digital product becomes part of someone’s daily life, it can be seen as a sign that product-market fit has been achieved - transforming casual users into devoted followers who play an important role in your customer retention efforts. That is why this metric is valuable for product-market fit.
Putting it all together: pirate metrics
Dave McClure developed the AARRR metrics to help businesses maximize customer potential. This metric outlines key stages in a customer’s journey, such as acquisition and activation, right through to retention, referrals, and revenue. Here’s what each of these product-market fit metrics can tell you about your product and its development:
Acquisition
Acquisition, as the name suggests, is about users finding out about your product and downloading it (if it’s an app).
For acquisition to be successful, it is essential that your product or service stands out from the rest of the market. This can be achieved by exploring all nineteen channel options presented within McClure’s Bullseye Framework:
question yourself about which channels are driving maximum traffic (#), value (%) or have lowest cost ($) per conversion!
Activation
Activation is about getting that “Aha!” moment during users’ first experience with a product/service. Once they download and start using it for the first time will they like it? Will they see a value in it?
For example, one of our client’s products deals with supporting HR services between work agencies and job seekers. We used pirate metrics in tandem with a tool called Metabase.
We measured the acquisition of users (number of users authenticated per week/month) and activation of users (number of users involved in contracts per week/month).
We then measured if (and how) users found out about the client’s new product features and then used that data when preparing for a major redesign of the client’s landing page.
Retention
Retention tries to answer two questions: Do people come back to your product? Do they keep using it? Retention rate is defined as the percentage of users who continue using your product or service over a given time period. The period may vary depending on the product.
For example, Airbnb’s customers should be considered retained after they make their second reservation within 18 months after their first reservation. Netflix’s users are retained when they renew their subscription each month.
Referral
Referral is about finding out if people recommend your app. If you start seeing referrals to your product, it’s a sign that people are falling in love with it - and are willing to recommend it to others.
Revenue
Revenue is a simple matter of finances: Is your product bringing money in? Has it reached a break-even point?
Product-market fit metrics are not the only ones that matter
Coming back to the previously mentioned HR services product: to better understand metrics and the cause of the issues with the product (e.g. poor performance), the team often relies on user testing and interviews.
To perform them, the product team uses Metabase, but also Hotjar and Google Analytics. Here’s how each of these product design tools and metrics are beneficial to product-market fit.
Metabase Metrics
In their biweekly user experience (UX) reports, the product team reviews and compares metrics from Metabase to evaluate how effective their product (HR service) is. This data tells them what features are being used the most as well as the numbers of new contracts signed, vacancies created by users, and CVs posted - all of which provide major insights into user engagement.
A real-life example was when this was used by the team to implement some changes in the client’s marketplace, adding additional fields that needed to be filled by users in their vacancy posts.
Google Analytics
With Google Analytics (GA) the product team compares users’ countries of origin, their browser languages, devices etc. GA can also be used to track new and returning users. However, be warned, this data can’t be completely trusted: the product team has come across discrepancies on more than one occasion.
Hotjar Heatmaps
Although not a product-market fit metric in itself, a heatmap allows for deeper study of the product to see where users are clicking, what functionalities they are using, and how they are engaging with the product.
This allows the product team to find out where, and potentially why, users don’t perform certain actions; e.g. not completing a transaction or posting a listing. This helps the product team effectively improve elements of the product that have a direct impact on product-market fit metrics.
Other product-market fit metrics that deserve a mention
Another one of our clients deals in the food and beverage industry in Europe. Their product is currently in the product-market fit stage, and for the most part, uses a combination of the metrics that we have listed in this article. However, the product team also tracks:
- Team velocity (amount of work that can be completed by a development team in a single sprint)
- Predictability (ability to plan and deliver)
- Number of current open sessions (for a web-based product that can be viewed in a browser)
- General availability percentage (how close the product is to becoming generally available)
- DTU usage (the usage of database throughput units such as CPU, memory, etc.)
One last product-market fit metric worth looking into is feature adoption rate. It’s the number of users who have used a functionality, divided by the number of users who visited the page that the functionality was located on (in percentage terms).
What product-market fit metrics should you choose?
The PMF metrics presented here can be categorized into two groups: first, the typical metrics used in the product-market fit phase. The second is metrics specific to each product.
Both types of metrics come with a risk of being used for the sake of showing only the good side of your business; i.e. becoming vanity metrics. The alternative is to focus on metrics that can bring a tangible benefit to your digital product; i.e. actionable metrics.
Picking the right metrics requires experience, which is not something that every product owner can take advantage of. If you find yourself in a situation where you want to make sure that your product is measuring the right things, be sure to contact us.
Share this article:
