Our opt-in TikTok panel allows us to track paid mobile ads served to real TikTok mobile app users in the US.
What We Capture
- TikTok Mobile App
- We capture ads that appear in the For You tab. These may include In-Feed ads and TopView ads.
What We Do Not Capture
We do not capture ads outside the For You tab. These may include Branded Hashtag Challenge or Branded Effects ads. We do not capture organic influencer campaigns.
Due to technical limitations with the data we receive from our panelists, we are unable to capture creative images at this time.
Panel Based Data Collection
Our opt-in TikTok panel allows us to track paid ads served to real TikTok mobile app users in the US.
Mobile users organically discover and actively opt-in to share data about the ads served to them on their TikTok app via free third-party apps. We do not collect personally identifiable information (PII) from our panelists at any time.
Our TikTok panel brings a unique set of users to our growing global panel. In total, our global panel includes hundreds of thousands of active users across Desktop, Mobile, and CTV devices in North America, Europe, and Oceania who represent a diverse set of demographic and user characteristics.
Impression, Spend and CPM Estimation
Each quarter we project the total US TikTok spend, impressions and Cost Per Impression (CPM) based on third party data sources and industry reports.We apply our sampled data from the panels and estimated CPM rates to calculate impressions and spend per creative, brand and advertiser.
Brand and Category Hierarchy
In our advertiser and brand hierarchy, there is an advertiser at the top followed by up to four brand levels. Each TikTok social account is assigned to an advertiser or brand based on metadata, including creative text.
Each advertiser and brand is assigned a category. There are up to eight category levels in a category hierarchy, except via Connect (our data feed), which has up to ten.
Pathmatics receives the city and state of each panelist when each impression is served.
Historical Data Collection
US: started 01/01/2022