Metrics vs KPIs
Alistair Croll and Benjamin Yoskovitz (1) define a "good metric" as "a number that drives the changes you are looking for." Good metrics are:
1. Comparative, not absolute, preferably a ratio or a rate.
2. Simple and easy to remember.
3. Tied to the desired behavior to achieve a goal. Actionable, not vanity.
Lagging metrics capture what happened, but leading metrics are most valuable because they predict what is going to happen. For example, metrics collected from employee exit interviews are lagging, while metrics from team health checks predictive future attrition. Another example is customer churn (lagging) vs. the rate of complaints (leading).
A pair of correlated metrics help predict the future, but causal metrics also help change it. Many growth hacks take advantage of human psychology. For example, people who sign up for a social media site are more likely to invite friends right at that moment. So an increase in the activation rate causes an increase in the referral rate.
The term "KPIs" should not be overused to remain "key." Each industry analyst on Wall Street can name a handful of KPIs for the industry s/he follows. For example, for hospitality, it is the trend in the number of nights booked. For gold mining, it is the all-in sustaining costs per ounce compared to the market price of gold. Croll and Yoskovitz use the term "KPIs" in this sense.
In most literature, metrics support KPIs. KPIs support strategic business objectives. Many metrics are meaningless by themselves ("vanity metrics") but are required to support KPI. For example, time on site may be a vanity metric. Still, it supports a KPI of percent of active users, which in turn helps a strategic business objective of increasing user engagement. Croll and Yoskovitz do not use the term "KPIs" in this sense; instead, they prefer "good metric."
Picking a single most important KPI for the current PDLC phase (or growth engine) creates focus. It is confusing that such KPI is called "one metric that matters" (OMTM).
traffic, open rate, app downloads
app launch rate, signups
churn rate, usage frequency
invites sent, churn, loss, referral type
Viral coefficient and cycle*
shopping cart size, ad clicks, subscriptions
CLV, CAC, Time to customer break even*
* Viral coefficient - the number of new users each user brings on
Viral cycle - the speed with which one user invites another
** CLV = customer lifetime value
CAC = customer acquisition cost
Dave McClure proposed five elements abbreviated as AARRR for building a successful business (2). He called them "pirate metrics." Ash Maurya created a "customer factory blueprint" with the pirate metrics (3). I will come back to the factory diagram in an article about systems thinking. Please note in the picture above that all five pirate metrics map to the Grow horizon (H2).
Eric Reis proposed three engines of growth (4). They also map to the Grow horizon (H2) and align with three of pirate metrics. The order of the three engines matters. It is essential to develop a sticky solution to retain your customers before making the solution viral through referrals. The paid engine focuses on monetization and breaking even before transitioning to the Profit horizon (H1) for optimization.
The value of pirate metrics and growth engines is that they propose fairly generic KPIs, at least for B2C software products. Moreover, I strongly recommend the same approach for the development of B2B software products. B2B users deserve lovable products, too!
Croll and Yoskovitz (1) go beyond pirate metrics and growth engines. They describe in detail "good metrics" and benchmarks for six business models (or application types): e-commerce, SaaS, free mobile app, media site, user-generated content, and two-sided marketplaces. Some of the metrics are unique, some overlap. I highly recommend this book.
Product KPIs provide a foundation for decision making in the lean operating model. They determine if a product team should pivot, kill the idea, or persevere. I will provide more details in portfolio funding and governance.