Do you provide reporting on impressions and click-throughs?
Yes. The LiveIntent platform supports various types of campaign reporting on impressions and click-throughs. This reporting can be retrieved via the LiveIntent UI, custom push reports, and the reporting API. The supported metrics include impressions, unique impressions, reopens, clicks, conversions, post view conversions, revenue, CPM, CTR, and more.
For a full list of supported metrics, take a look at our Reporting Metrics Guide.
Can I see reporting by email property or title?
Yes. The LiveIntent platform supports various types of campaign reporting on impressions and click-throughs split by publisher, newsletter, and ad slot. This can be achieved from any of the reporting methods mentioned above.
Can I run a forecast on my inventory?
Yes. You can access LiveIntent’s forecasting capabilities by going to the Reporting tab and utilizing the Forecasting Tool. The Forecasting Tool allows a user to forecast the number of available impressions across their inventory in conjunction with what is already reserved in the system for their direct sold campaigns.
Can I see campaign reporting on viewability rates?
Yes. The LiveIntent platform accepts all 3rd party viewability tags (we must run either the no-script section of the wrapped tag, or preferably a 1x1 with accompanying image pixel).
We do accept the standard (non-script) Integral IAS tags (as well as other 3rd party viewability trackers like MOAT and others).
Are third-party trackers for impressions, clicks and viewability rates supported?
Yes. The LiveIntent platform supports the use of third-party tracking of impressions and clicks. Up to two impressions trackers may be used and applied on the line item or creative level. Any impression tracking applied on the creative level will override those set on the line item object. A single click tracker may be used, being applied on the creative level only.
Why do I see “unknowns” in my campaign reporting?
Some fields in your campaign reports are based on our third-party data partners’ data. For these data points, like age and gender, some users may not be found in these partners’ databases, which ends up resulting in the “unknown” label.
(The users certainly have an age and gender, but it is just not known to the system!)
Ok — got it. Now how can I get the system to “know” these people?
Think about the audience you're trying to target and try an “exclude” vs. “include” approach.
If you want to reach ALL women, select 'exclude males', instead of 'include females.' This will let you reach all the women who are in the 'unknown' segment, and give our algorithm a larger audience -- with the ultimate goal of learning which placements produce the most efficient conversions.