Adding the data source
This data source is in beta mode
Requirements
- Follw the instructions below with an user with at least Ad Account Analyst permission
Instructions
- Log into Kondado > Create > Data Source > Tiktok Ads
- Click on the “Signin with TikTok button”
- On the next pages, accept all permissions that are asked without modifying any of them
- Now save the data source
Pipelines
To make the best out of your pipelines, learn more about Breakdowns, Metrics, Periods and Update Window
Summary
The report breakdowns are able to segment the data into smaller groups. By using a breakdown different than the entity ID alone, the number of available metrics decreases
- campaign_id: Group by Campaign ID
- adgroup_id: Group by Ad Group ID
- ad_id: Group by Ad ID
- advertiser_id: Group by Advertiser ID
- stat_time_day: Group by day
- gender: Group by gender
- age: Group by age
- country_code: Group by location code.
- province_id: Group by location ID.
- dma_id: Group by Designated Market Area (DMA). Only U.S. has DMAs.
- ac: Group by audience network
- language: Group by audience language
- platform: Grouped by operating system
- interest_category: Group by first_level interest category
- interest_category_tier2: Group by second_level interest category
- interest_category_tier3: Group by third_level interest category
- interest_category_tier4: Group by fourth_level interest category
- behavior_id: Group by behavior
- placement: Group by placement
- device_brand_id: Group by device brand.
Every report offers automatically available metrics. To use most of the metrics, you should use only the entity id as the breakdown (eg: advertiser_id, campaign_id, adgroup_id, ad_id)
Attribute metrics
- campaign_id: Group by Campaign ID
- adgroup_id: Group by Ad Group ID
- ad_id: Group by Ad ID
- advertiser_id: Group by Aadvertiser ID
- stat_time_day: Group by day
- stat_time_hour: Group by hour
- gender: Group by gender
- age: Group by age
- country_code: Group by location code.
- province_id: Group by location ID.
- dma_id: Group by Designated Market Area (DMA). Only U.S. has DMAs.
- ac: Group by audience network
- language: Group by audience language
- platform: Grouped by operating system
- interest_category: Group by first_level interest category
- interest_category_tier2: Group by second_level interest category
- interest_category_tier3: Group by third_level interest category
- interest_category_tier4: Group by fourth_level interest category
- behavior_id: Group by behavior
- placement: Group by placement.
- device_brand_id: Group by device brand. When this dimension is used, lifetime cannot be true .
Basic metrics
- spend: Total Cost
- cash_spend: Cost Charged by Cash
- cpc: CPC (Destination)
- cpm: CPM
- impressions: Impressions
- gross_impressions: Gross Impressions (Includes Invalid Impressions)
- clicks: Clicks (Destination)
- ctr: CTR (Destination)
- reach: Reach
- cost_per_1000_reached: Cost per 1,000 people reached
- conversion: Conversions
- cost_per_conversion: CPA
- conversion_rate_v2: CVR (Impressions)
- real_time_conversion: Real-time Conversions
- real_time_cost_per_conversion: Real-time CPA
- real_time_conversion_rate: Real-time CVR (Clicks)
- real_time_conversion_rate_v2: Real-time CVR (Impressions)
- result: Result
- cost_per_result: Cost Per Result
- result_rate: Result Rate (%)
- real_time_result: Real-time Result
- real_time_cost_per_result: Real-time Cost Per Result
- real_time_result_rate: Real-time Result Rate (%)
- secondary_goal_result: Secondary Goal Result
- cost_per_secondary_goal_result: Cost per Secondary Goal Result
- secondary_goal_result_rate: Secondary Goal Result Rate (%)
- frequency: Frequency
- currency: currency
Video play metrics
- video_play_actions: Video Views
- video_watched_2s: 2-Second Video Views
- video_watched_6s: 6-Second Video Views
- average_video_play: Video Average Watch Time Per Video View
- average_video_play_per_user: Video Average Watch Time Per Person
- video_views_p25: Video Views at 25%
- video_views_p50: Video Views at 50%
- video_views_p75: Video Views at 75%
- video_views_p100: Video Views at 100%
Engagement metrics
- engagements: Clicks (All)
- profile_visits: Paid Profile Visit
- likes: Paid Likes
- comments: Paid Comments
- shares: Paid Shares
- follows: Paid Followers
- clicks_on_music_disc: Music Clicks
- ix_page_duration_avg: Instant Experience Average View Time
- ix_page_viewrate_avg: Instant Experience Average View Percentage
The period sets the time granularity of the metric_date field. It is useful to more accurately report metrics that perform a “count distinct” operation and that can yield different results on a monthly sum with a monthly granularity vs adding up all the days on a given month (with a daily granularity). For example, a metric such as “unique_clicks” that reports how many distinct users clicked on an ad on a give period will yield very different results on the two cases: this user should count just as 1 user on a monthly window but will become 30 if we add up all days on a month (daily granularity.
The available periods are
- hourly: segregates the data by hour. The metric_date field is presented as single day and a new metric_datehour field is created. The number of metric fields available is restricted
- daily: segregates the data by day. The metric_date field is presented as a single day. The available metrics vary with the breakdown
- weekly: segregates the data weekly. The metric_date field is presented as the Monday of the week and each data row ranges from Monday to Sunday. The available metrics vary with the breakdown
- monthly: segreates the data by month. The metric_date field is presented as the first day of the month and each data row ranges from the first to the last day of this month. The available metrics vary with the breakdown
- lifetime: all data is available without any date limitation. There's no metric_date field. The number of metric fields available is restricted
This parameter controls how many days prior to the savepoint the same data will keep being refreshed. This means that a pipeline with an update_window of 7 days will, during each execution, read the 7 last days of data (in case the period parameter is weekly or monthly, the whole week or month that a given day falls into will be fetched). This parameter aims at refreshing fields that can change after have already been written to the destination (attribution)