Terminology
- User: your end-user/customer. Each user should have a unique identifier (User ID) to differentiate them. When the user is anonymous, some form of UUID can be used.
- Event: a data structure generated when a user takes a certain action (eg view a page, click a button, log in, sing a song etc) or when something happens to a user (eg send a push notification, subscription renewal, app made an API call). Events are the most critical data for behavioral and product analytics.
- Property: every event can have multiple properties associated with it to capture the context information when the event happens. For example: Timestamp, User ID, Country, Device, Gender, Age, App Version and Marketing Campaign etc. These properties can be used to filter events, breakdown metrics or aggregate into measures in analytics.
- Filter: a condition applied to some properties to filter events or users. For example: Age > 18, Country = US, Date between 2/1/2020 and 2/29/2020.
- Function: a computation method on events or its properties. For example: Count Events(Login), Unique Users(), Sum(Subscription Event’s Amount Property).
- Measure: a computed value from events and properties using functions and filters. A Compound Measure is composed of other measures in a math formula (eg X+Y, X/Y).
- Dimension: a special property usually is used for breakdown or lookup purposes. For example: Country dimension is a property called Country on all Events; Campaign dimension is a separate table which contains detailed information about every campaign while on Events there is only a campaign_id property which you can lookup (join) in the Campaign dimension table.
- Breakdown: a way to slice a measure into groups based on dimension(s). Sometimes it is called Slice-and-Dice, or Group By. For example: breakdown by Age, Country.
- Cohort: a group of users who match certain criteria. For example, “New Users” means those installed in the last 7 days; "Frequent Singers” means users who sang more than five songs every day.
- Formula: a generic term for any analytics question. It includes Query, Funnel, Path, Retention, Predication and Effect.
- Query: a question to get some measure, optionally with filters, breakdowns or cohorts.
- Funnel: a special analysis to visualize the remaining users at every step in order to measure conversion rates.
- Path: a special analysis which uses a Sankey diagram to visualize users’ journey during all the steps between a starting event and ending event.
- Retention: a special analysis which measures how users come back with a returning event over time since the occurrence of the starting event.
- Prediction: a special analysis to find different events’ predictive value relates to how users move from a source cohort to target cohort.
- Effect: a special analysis showing the impact of a trigger event on an affected event by measuring the changes in event count, frequency or percentage of active users.
- Analysis: a detailed examination of some formula (an instance after executing a formula). Usually it is associated with a visualization view (chart).
- Metric: an analytics view of some measure.
