Product and engagement
How customers use the product and reach the value it delivers.
12 terms
Aha moment
The Aha moment is the instant a user first perceives the real value of a product, the click that turns a curious visitor into an engaged user. Identifying which concrete action represents that moment and getting users to it as fast as possible is the foundation of activation and retention. Classic examples are sending the first message, inviting the first teammate or importing the first data.
Onboarding
Onboarding is the process that takes a new customer from welcome to first value, the aha moment, and from there to the habit of using the product. Good onboarding shortens time to value and lifts activation and retention, while poor onboarding is one of the top causes of early churn. It can be self-serve, guided by the product, or assisted by people.
Time to value (TTV)
Time to value (TTV) is the time between signup and the moment the customer gets the first real value from the product, the so-called aha moment. The shorter that interval, the higher the odds of activating, converting the trial and retaining. Shortening TTV is one of the central goals of onboarding, because every extra step before value drags conversion down.
DAU / MAU
DAU and MAU are the daily active users (Daily Active Users) and monthly active users (Monthly Active Users) of a product. The DAU/MAU ratio, obtained by dividing average DAU by MAU, is the stickiness metric: it shows what fraction of monthly users comes back on a typical day. Near 50% indicates a product of daily use; a low ratio indicates occasional use. The number only means something if "active" is defined honestly.
Engagement rate
Engagement rate measures how intensely the base uses the product: the share of users who perform the key value action in a period. There is no single formula, each product defines that action. High engagement precedes retention and expansion; low engagement precedes churn.
Power users
Power users are the small fraction of a product most engaged and frequent users, who get the most out of it and tend to generate a disproportionate share of activity and value, a Pareto effect. They are the main source of expansion, referrals and feedback, and understanding what makes them power users guides the roadmap and the onboarding of everyone else.
North Star Metric
The North Star Metric is the single guiding metric that best captures the value a product delivers to its customers and predicts sustainable growth. It sits above the input metrics that feed it and aligns every team around real value, not vanity numbers. Chosen well, it rises when the customer wins, not when the company extracts.
Product-led growth (PLG)
Product-led growth (PLG) is the growth strategy in which the product itself drives acquisition, activation, conversion and expansion, with little or no sales touch. The user enters through a free trial or a freemium plan, feels the value on their own and becomes a paying customer. The buying signal is no longer a filled-in form but usage: the PQL, the lead qualified by the product.
NPS
NPS (Net Promoter Score) is a loyalty index based on the question "on a scale of 0 to 10, how likely are you to recommend us?". It is calculated by subtracting the percentage of detractors (scores 0 to 6) from the percentage of promoters (scores 9 and 10); passives (7 and 8) do not count. The result ranges from -100 to +100 and measures loyalty and word of mouth, not point-in-time satisfaction.
CSAT
CSAT (Customer Satisfaction Score) is the metric that measures customer satisfaction with a specific interaction, product or moment, calculated as satisfied responses divided by the total, as a percentage. It is point-in-time and transactional, capturing the feeling in the heat of the moment, unlike NPS, which measures long-term loyalty, and CES, which measures effort. Each touchpoint can have its own CSAT.
CES
CES (Customer Effort Score) is the customer effort score: it measures how much work a person had to put in to complete a task with your company, resolve a ticket, turn on a feature or finish a purchase. The typical question is "how easy was it?". Low effort predicts loyalty better than trying to delight, which is why CES complements NPS and CSAT.
A/B testing
A/B testing is an experiment that randomly splits users between two versions, A (control) and B (variant), to measure which produces a better outcome on a chosen metric, such as conversion, activation or engagement. It exists to decide with data instead of opinion, but it is only reliable with enough sample and statistical significance, so you do not mistake luck for effect. It is the engine of continuous optimization in self-serve products.