Impressions occur whenever a visitor is assigned a treatment (i.e. “variations”) for a split. Impressions are valuable for debugging the Split SDK as well as for customer analytics. Impressions are generated by SDKs each time
getTreatment is called. They are periodically sent back to Split's servers where they are stored and can be accessed for later use.
Impression event fields
Each impression contains these fields.
|Timestamp||Time the customer was served the treatment.|
|key||key which was evaluated.|
|Split name||Split which was evaluated.|
|Environment||Environment where the split was evaluated.|
|Treatment||Treatment that was returned.|
|Targeting rule label||Rule in the definition that matched resulting in the treatment being returned.|
|SDK and SDK version||Language and version of the SDK that was used in the evaluation.|
|Definition as of||Date and time of the last change to the targeting rule that the SDK used when it served the treatment. Valuable in understanding when a change made to a split got picked up by the SDKs and whether one of the SDK instances is not picking up changes.|
|Change number||Raw timestamp representation of the field Definition as of.|
Impressions are tracked by each SDK and sent to Split's backend services periodically. If you are not seeing any impressions in Split, first ensure that your SDK is installed and functioning as expected. Contact us at email@example.com if you have any issues.
By default Split retains impression data for 30 days. Custom data retention policies are available upon request. Contact the team at Split to learn more.
Targeting rule label
Targeting rules can be robust within Split. For instance, here is a split with two rules.
if user is in segment employees then split 100%:on,0%:off else if user.location is in list ["california"] then split 100%:on,0%:off else
If a user is served the on treatment for this split, the targeting rule label explains which of these rules the user matched. The targeting rule label is the summary of the rule that provides that explanation. The label is auto-generated and is valuable in understanding if your split is working as expected. Here are the targeting rule labels for the split shown above.
|Rule||* Targeting rule label*|
Usually, a treatment is served because the customer matched a particular rule. In this case, the targeting rule label simply indicates the rule that matched. However, in other cases, the SDK serves a treatment even though no rule was matched. This table shows the tarlabel generated in those cases.
|Special case||Treatment served||Targeting rule label|
|Split was killed||Default||
|No rule matched||Default||
|Split was not found, for example, it may not have been downloaded by the SDK yet||Control||
|There was an exception while evaluating treatment||Control||
If your impression tables are showing not available, consider upgrading your SDK and ensure that labels are enabled in the SDK configurations.
Labels do not capture identifiable information about your customers. However, if you do not want the Split SDK to capture or send the label back to Split servers, set
false in the SDK advanced configuration.
Use our integration with Segment and our outgoing Webhook to push Split data into platforms like Google Analytics, Mixpanel, or your data warehouse to quickly understand engagement and other key use metrics.
Additionally, if you don’t want to send a customer UUID to Split as the key you can hash that ID prior to calling getTreatment. If you decide to hash the ID you need to be sure to use a deterministic alogorithm that will result in the same hash value each time. In addition, if it’s important to identify the treatment received by specific users you will need to have your own method to be able to associate the hashed value with the actual user ID.