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The TikTok Ads data connector enables the ingestion of both delivery and metadata from TikTok’s advertising API. It is composed of two job streams—one for delivery metrics and one for metadata refresh. This integration facilitates campaign performance analysis with a comprehensive set of metrics and joins to enrich reporting capabilities.

For more information on this connector and its use cases please follow <a href="https://brightanalytics.com/connectors/tiktok-ads-reporting-api/" rel="nofollow noopener noreferrer" target="_blank">this link</a>

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The TikTok Ads integration provides a complete view of campaign performance, combining delivery metrics and metadata for detailed breakdowns by campaign, ad group, and ad. With robust metrics around engagement, video views, and costs, it supports performance monitoring and optimization use cases across brands leveraging TikTok for paid media.

TikTok API Connector

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Field	Value
Feed	`tiktok`
Status	`1` (active)
Job Label	TikTok Ads - Delivery Import
Lookback Qty	5
Lookback Unit	day
First Run Hour	5
Poll Frequency	24
Update Mode	append
Create Target	true
Date Column	`stat_time_day`

Type	Table	Description	Priority	Update Mode	Create Target
data	`tiktok_data_ad`	TikTok Ads - Delivery Data	1	append	true

Field	Value
Feed	`tiktok`
Status	`1` (active)
Job Label	TikTok Ads - Meta Refresh
Lookback Qty	1
Lookback Unit	day
First Run Hour	7
Poll Frequency	24
Update Mode	refresh
Create Target	true

Type	Table	Description	Priority
lookup	`tiktok_meta_campaign`	Campaign Meta	1
lookup	`tiktok_meta_adgroup`	AdGroup Meta	2
lookup	`tiktok_meta_ad`	Ad Meta	3

Key	Description	Type	Required	Notes
`tiktok_advertiser_id`	TikTok Advertiser IDs	text	true	Comma-delimited list of advertiser IDs
`tiktok_app_id`	TikTok App ID	hidden	true	Used internally
`tiktok_app_secret`	TikTok App Secret	hidden	true	Used internally

TikTok API Connector

Job Configuration

Job 1: TikTok Ads – Delivery Import

Job 2: TikTok Ads – Meta Refresh

Connection Configuration

Dimensions

Base Metrics

Composite Metrics

Datasource Joins

Summary

Dimension Name	Field Source
Campaign [TikTok]	`tiktok_meta_campaign.campaign_name`
AdGroup [TikTok]	`tiktok_meta_adgroup.adgroup_name`
Ad [TikTok]	`tiktok_meta_ad.ad_name`

Metric Name	Formula	Rounding	Prefix
Spend [TikTok]	`SUM(tiktok_data_ad.spend)`	2	£
Clicks [TikTok]	`SUM(tiktok_data_ad.clicks)`	0
Impressions [TikTok]	`SUM(tiktok_data_ad.impressions)`	0
Comments [TikTok]	`SUM(tiktok_data_ad.comments)`	0
Profile Visits [TikTok]	`SUM(tiktok_data_ad.profile_visits)`	0
Shares [TikTok]	`SUM(tiktok_data_ad.shares)`	0
Button Click [TikTok]	`SUM(tiktok_data_ad.button_click)`	0
Video Watched 2s [TikTok]	`SUM(tiktok_data_ad.video_watched_2s)`	0
Video Watched 6s [TikTok]	`SUM(tiktok_data_ad.video_watched_6s)`	0
Video Views Quartile - 25%	`SUM(tiktok_data_ad.video_views_p25)`	0
Video Views Quartile - 50%	`SUM(tiktok_data_ad.video_views_p50)`	0
Video Views Quartile - 75%	`SUM(tiktok_data_ad.video_views_p75)`	0
Video Views - 100% [TikTok]	`SUM(tiktok_data_ad.video_views_p100)`	0
Video Views [TikTok]	`SUM(tiktok_data_ad.video_play_actions)`	0

Metric Name	Formula	Round	Prefix	Suffix
CTR [TikTok]	`{Clicks [TikTok]} / {Impressions [TikTok]} * 100`	2		%
CPC [TikTok]	`{Spend [TikTok]} / {Clicks [TikTok]}`	2	£
CPM [TikTok]	`({Spend [TikTok]} / {Impressions [TikTok]}) * 1000`	2	£
CPV [TikTok]	`{Spend [TikTok]} / {Video Views [TikTok]}`	2	£
VTR [TikTok]	`{Video Views - 100% [TikTok]} / {Impressions [TikTok]} * 100`	2		%
VCR [TikTok]	`{Video Views - 100% [TikTok]} / {Video Views [TikTok]} * 100`	2		%

Source Table	Joins
`tiktok_data_ad`	`ad_id → tiktok_meta_ad.ad_id` `adgroup_id → tiktok_meta_adgroup.adgroup_id` `campaign_id → tiktok_meta_campaign.campaign_id`