Fantastic Metrics & Where to find them

I was working on developing a non-exhaustive PM glossary, and had originally included many key PM metrics there. But, as you can imagine, that glossary quickly became very long and unwieldy! (Plus, it’s just hard to break up glossary and metric lists with photos and fun formatting…sorry readers!)

So, I decided to split up my glossary and focus on some key metrics for PMs here instead. This is not an exhaustive list, but represents important metrics that have stood out to me as I delve deeper into PM-land. 

What are others you think I might have missed? Let me know!

Pirate metrics: The rest of this list is alphabetical, but I wanted to start with pirate metrics because I think they’re a helpful starting place, and many of the metrics below relate to different categories represented here. (Plus, I just love that pirate metrics as nomenclature exists – so fun.) Pirate metrics provide a way to categorize metrics that measure different parts of the business. The categories conveniently spell out the acronym AARRR – hence the name pirate metrics (I really love this so much)  –acquisition, activation, retention, revenue, and referral. I recommend this overview that digs in more.

ARPU: Average revenue per user. This is calculated as total revenue divided by the number of users or subscribers.

ARPPU: Average revenue per paying user. Note that this is distinct from ARPU! ARPPU helps you determine how much revenue you might generate from users over a set time period. To calculate ARPPU, you can use this formula: (total revenue during X time period) / (total number of paying users in X time period). 

CAC: Customer acquisition cost. This is closely related to CPA below, but differs in that it calculates the cost of acquiring a paying customer. There are simple formulas out there for calculating CAC, but they can give misleading results. Here and here are two breakdowns I’ve appreciated for accurately calculating CAC. 

Churn rate: This measures how many customers stop using the product, based on actual usage or if users don’t renew on a subscription-based product. Churn is calculated over a period of time, for example monthly or quarterly. To calculate churn, you can look at the percentage of total customers that stop using or paying for the product over a set period of time (divide the number of customers you lost during the designated time period by the amount of customers you had at the beginning of that time period).

CPA: Cost per acquisition. This measures the cost of acquiring a non-paying customer. To calculate CPA, divide the total advertising spend by the number of acquisitions. 

CSAT: Customer satisfaction. This metric measures users’ overall level of satisfaction about a product or feature–but is typically used at the product level. You can ask users for their feedback at different points in the customer journey to build an understanding of CSAT. The American Customer Satisfaction Index might also help serve as an industry benchmark.

DAU: Daily active users. Fairly self-explanatory: the number of users who have interacted in meaningful ways with the product, or performed valuable activities, on a given day. 

LTV: Lifetime value. This metric estimates net revenue each customer would bring in for a business or product over the length of the relationship with that customer. LTV can be calculated a few different ways, but one simple way is to divide ARPU by revenue or customer churn. Another way is to multiply 3 factors: 1) average $ of a purchase, 2) average length of customer relationship in years, and 3) number of customer purchases per year. Pro tip: for SaaS, your LTV should be greater than 3 times the CAC. 

Magic moments: If you’ve discovered your product’s aha! moment, you might choose to measure the number of users who have experienced that magic moment as a key metric. You could also measure how quickly a user moves from setting up their account to experiencing that magic moment. 

MAU: Monthly active users. Same ideas as DAU above, but measured over a month instead. 

MRR: Monthly recurring revenue. This is simply the amount of revenue generated each month. If your product is subscription-based, this is a really simple calculation: multiply the number of monthly subscribers by the ARPU. 

Must have status: This is a metric that can aid in understanding product market fit. You could survey even just a small sample of users, asking them how they would feel if they couldn’t use the product or a particular feature starting now. If you get even at least 40% of respondents saying they’d be disappointed, there is a good chance of product market fit. 

NPS: Net promoter score. This metric–although gameable, depending on the benchmark–can help understand user happiness and customer satisfaction. Typically, this is understood through a survey question asking users to indicate on a scale of 0 to 10 how likely they are to recommend a product or company to others. Scores between 0-6 are detractors; scores between 7-8 are neutral; and scores between 9-10 are promoters. To calculate NPS, subtract the percentage of detractors from the percentage of promoters (NPS = % promoters - % detractors).

Stickiness: Stickiness refers to how likely or prone customers are to return to your product and/or use it more frequently. To measure stickiness, you can look to the DAU/MAU ratio (divide the # of daily active users by the # of monthly active users).

Usage count: If you want to see how many active users you’ve had over the past 7 days, for example, you could use the following formula: # active users = # retained users + # new users - # churn users + # resurrected users