Event-Based Automation
Event-based automation runs actions in response to discrete events, such as a signup, purchase, or quiz completion, treating each event as a signal to act on.
Key takeaways
- An event carries a name, a timestamp, an actor and typed properties.
- One event can feed many consumers without the producer knowing about them.
- Duplicate and out-of-order delivery is normal, so consumers must be idempotent.
- Consistent event naming is what lets new automations reuse existing streams.
- Events record history and are a poor substitute for current-state fields.
In depth
An event is a named record of something that happened, stamped with a time, an actor identifier, and a set of properties. A producer emits it, a bus or a webhook carries it, and one or more consumers subscribe to the name and act on the payload. Because the payload travels with the event, the consumer needs no lookup to decide what to do: a quiz_completed event carrying the tier, the category scores and the answer identifiers already contains everything the follow-up needs to branch on.
The quality of event automation rests almost entirely on the schema. A small vocabulary of well-named events with consistent property names lets you add consumers without touching the producer, which is the whole point. Loose naming does the opposite: quiz_done, quizCompleted and completed_quiz become three separate integrations doing one job. The trade-off is speed against discipline. Defining a taxonomy slows the first build, but skipping it means every later automation carries a translation layer that nobody maintains.
Teams usually keep one producer per surface and let many consumers subscribe. The same quiz_completed event updates the CRM record, enrolls the contact in a sequence, posts to a sales channel and lands in the warehouse for analysis, with no consumer aware of the others. Properties do the segmentation work: branching on the weakest category rather than on the total score gives follow-up that names the prospect's actual gap. Adding a new consumer then costs a subscription rather than a rebuild.
Events describe what happened, not what is true now. Replaying a month of events to reconstruct a contact's current state is expensive and often wrong, because events arrive out of order and duplicates are normal whenever a producer retries. Consumers therefore need to be idempotent, keyed on an event identifier. Events also age badly: a property removed from the producer breaks consumers silently, and historical events keep the old shape, so analysis spanning a schema change needs manual reconciliation.
Example in practice
How to measure it
Track delivery health first: events emitted, events delivered, and failures per consumer. A consumer with a rising error count is silently dropping automations, and the symptom reaches marketing as leads that never got a follow-up. Watch queue lag as well, meaning the delay between the event timestamp and the consumer processing it, since lag is what quietly turns a real-time design into a batch one.
Then check schema conformance: the share of events arriving with every required property populated. A slow decline usually means a producer changed and nobody told the consumers. Pair that with outcome by event type, comparing conversion for contacts whose automations were driven by a quiz completion against those driven by a page view, so you learn which events deserve a consumer at all.
Common mistakes
The usual failure is letting each team name its own events. Within a year the same user action arrives under three names with three property shapes, and every new automation begins with a mapping table. Agree on a naming convention early: object plus past-tense verb, lowercase, with a shared set of identity properties on every event. Publish the list somewhere the marketing team can read it, not only in code.
The second failure is a consumer that assumes exactly-once delivery. A webhook retry sends the same quiz completion twice, the contact receives two welcome emails, and the score is added twice. Store the event identifier and ignore repeats, or make the action naturally repeatable by setting a field to a value rather than incrementing it. Test this deliberately by replaying an event instead of hoping it never happens.
Frequently asked questions
What is an event payload?
A payload is the data attached to an event, such as the score, tier, and answers from a quiz. Automations read the payload to personalize the next action rather than treating every event the same.
Why standardize event names?
Consistent event names and properties keep automations reliable and analytics accurate across tools. Without a naming convention, flows break and reporting becomes hard to trust.
What is the difference between an event and a trigger?
A trigger is a condition a platform watches for; an event is a message a system publishes when something happens. A trigger usually lives inside one tool and reads its own database, while an event travels between tools and carries a payload. Many stacks use both: the event arrives by webhook, and the receiving tool treats its arrival as a trigger.
How should I name events?
Use an object followed by a past-tense verb, lowercase with underscores: quiz_completed, deal_created, trial_started. Keep the vocabulary small, and put identity properties such as email, account identifier and timestamp on every event. Avoid encoding variable data in the name, because quiz_completed_security forces a new consumer for every variant instead of a simple property filter.
What properties should a quiz completion event include?
At minimum the contact identifier, the scorecard identifier, the total score, the assigned tier, and the per-category breakdown. Adding the individual answer identifiers lets later automations branch on a specific response without a lookup. Include a version number for the scorecard, so an analysis spanning a question change can tell which version produced a given score.
Do I need an event bus, or are webhooks enough?
Webhooks are enough while one producer talks to a handful of consumers. A bus earns its keep once several tools need the same event, because it gives you one place to retry failures, replay history and add a subscriber without changing the producer. Many teams start with webhooks and move to a bus when retry logic starts being copied around.
What happens if a consumer is down when an event fires?
That depends on the transport. A plain webhook with no retry loses the event, and the automation simply never runs. Systems with a queue hold the event and redeliver it, which is exactly why consumers must tolerate duplicates. Ask how long your platform retries and whether failures are visible anywhere, because silent loss looks identical to weak conversion.
Can I use the same events for analytics and automation?
Yes, and it is usually the point: one well-defined stream feeds both a warehouse and the marketing tools. Be aware that the two have different tolerances. Analytics can wait minutes and clean duplicates later, while automation needs the event promptly and needs it once. Route both from the same producer, but never make the automation wait for the warehouse.