Sampling

Sampling is used to reduce the amount of tracked data being transported to different destinations.

This can help save ingestion and bandwidth costs.

Filtering vs sampling#

Filtering is the concept of allowing only certain events to be tracked and transported to different destinations if they match certain conditions.

Sampling, on the other hand, chooses a percentage of the tracked events to be transported. Meaning, not all users/devices will transport the tracked events, but only a subset of them.

Consistency#

It is recommended to use a consistent value to sample the events by (like userId attribute), because this will allow maintaining a consistent sampling strategy across different devices and sessions (think web, iOS, and Android apps) for the same user.

Defining sampling#

You can define sampling rules either at events or destinations level.

To keep things simple, we will start with destinations level below:

Simple sampling#

# ...
sample:
  by: attributes.userId
  percentage: 10 # 10% of unique users

This assumes you already have set a userId attribute in your application using Eventvisor SDKs.

Sample by custom range#

Instead of a percentage value, you can also be more specific by defining a custom range:

# ...
sample:
  by: attributes.userId
  range: [0, 50] # first 50% of users

Multiple properties#

Some applications are complex, and you may want to sample based on multiple properties together:

# ...
sample:
  by:
    - attributes.organizationId
    - attributes.userId
  percentage: 10

First available property#

You may also choose to sample based on user's ID if available, otherwise falling back gracefully to device ID.

In that case, you can use the first available value:

# ...
sample:
  by:
    or:
      - attributes.userId
      - attributes.deviceId
  percentage: 10

Conditional sampling#

You can also define multiple sampling rules based on different conditions. The first rule to match will be applied:

# ...
sample:
  - conditions:
      - attribute: platform
        operator: equals
        value: web
    by: attributes.deviceId
    percentage: 10
  # ...more rules here

Different sources#

We used attributes for the sampling strategies above, but you are not limited to them alone. You can use other sources as well:

# ...
sample:
  by:
    # one of the properties below (not ALL together!)
    attribute: userId
    # or a lookup
    lookup: localstorage.userId
  percentage: 10

Event level sampling#

Instead of destinations alone, you can also define sampling rules on a per-event basis:

# ...
sample:
  by: attributes.userId
  percentage: 10

Overriding destinations#

If for a certain event, you wish to define sampling rules targeting a specific destination only:

# ...
destinations:
  browser:
    sample:
      by: attributes.userId
      percentage: 10

If there's any event-level sampling defined, it will take priority over the destination-level sampling rules.

It is highly recommended that sampling is done at destination level, and event-level can be used for more complex use cases.