StackAdapt
SourceUse Dataddo's StackAdapt connector to explore any data available via the official API of StackAdapt. Access hundreds of metrics and attributes, from basic to advanced. Build and blend custom datasets directly in Dataddo, then send them anywhere.
Explore Data You Can Extract from StackAdapt
Data Category
- All Attributes (63)
- Campaign Insights (51)
- Campaign Metadata (12)
Need fields you don't see?
Let us know and we'll add them to the connector. Just send a request here..
Available Attributes (63)
| Attribute |
|---|
campaign_id Campaign ID |
campaign_name Campaign Name |
campaign_group_id Campaign Group ID |
campaign_group_name Campaign Group Name |
advertiser_id Advertiser ID |
advertiser_name Advertiser Name |
supply_source_id Supply Source ID |
supply_source_name Supply Source Name |
audio_starts Audio Starts |
audio_completions Audio Completions |
audio_completion_rate Audio Completion Rate |
atos Average Time on Site (ATOS) |
clicks Clicks |
click_conversions Click Conversions |
click_secondary_conversions Click Secondary Conversions |
conversions Conversions |
conversion_revenue Conversion Revenue |
conversion_revenue_percentage Conversion Revenue Percentage |
cookie_conversions Cookie Conversions |
cost Cost |
cost_percentage Cost Percentage |
ctr Click-Through Rate (CTR) |
cvr Conversion Rate (CVR) |
ecpa Effective CPA (eCPA) |
ecpc Effective CPC (eCPC) |
ecpcl Effective Cost Per Click-Link (eCPCL) |
ecpcv Effective Cost Per Completed View (eCPCV) |
ecpe Effective Cost Per Engagement (eCPE) |
ecpm Effective CPM (eCPM) |
engagements Engagements |
engagement_rate Engagement Rate |
impressions Impressions |
impressions_percentage Impressions Percentage |
impression_conversions Impression Conversions |
impression_secondary_conversions Impression Secondary Conversions |
page_starts Page Starts |
profit Profit |
profit_percentage Profit Percentage |
rcpa Revenue CPA (rCPA) |
revenue Revenue |
revenue_percentage Revenue Percentage |
roas Return on Ad Spend (ROAS) |
secondary_conversions Secondary Conversions |
total_time Total Time |
unique_impressions Unique Impressions |
video_starts Video Starts |
video_completions Video Completions |
video_completion_rate Video Completion Rate |
views Views |
view_rate View Rate |
date Date |
id ID |
name Name |
goalType Goal Type |
isArchived Is Archived |
isDraft Is Draft |
tacticType Tactic Type |
freqCapExpiry Freq Cap Expiry |
freqCapLimit Freq Cap Limit |
freqMinExpiry Freq Min Expiry |
freqMinThreshold Freq Min Threshold |
timezone Timezone |
updatedAt Updated At |
Pricing
See all Dataddo plans
Compare Dataddo's flow-based pricing tiers side by side and start your 14-day free trial.
View pricingWhy Dataddo?
One Ingestion Layer for SaaS, Databases, and Files
Most teams use multiple tools and “spaghetti code” for ingestion, depending on the type of sources and loading patterns. Dataddo brings this under one control plane and one predictable pricing structure. 400+ connectors included.
Built for Cloud and On-Premise Environments
Run Dataddo in both cloud and hybrid on-prem configurations. The control plane stays in the cloud; your data never leaves your perimeter. Supports segmented and private networks, and legacy systems including DB2, Informix, and Sybase.
Full API Control - No UI Required
Dataddo is built API-first. Use the UI when you want it; bypass it entirely when you don’t and orchestrate your pipelines programmatically.
Managed Ingestion Operations. We Own the Reliability.
Dataddo takes operational responsibility for your ingestion layer. We manage connector maintenance, handle API changes from source systems, monitor pipelines proactively, and execute backfills and recovery. Your engineering team doesn’t have to.
Full Visibility Into Every Data Flow
Dataddo gives you complete observability across your ingestion layer: pipeline logs, run histories, data lineage, and audit trails. Know what moved, when it moved, what changed, and why. Built for environments where explainability and accountability are not optional.
The Data Foundation Your AI Needs
Enterprise AI depends on a governed, secure data layer. Dataddo consolidates SaaS, database, and file data into a unified managed pipeline, delivering to vector databases, feature stores, and data lakes, with native sensitive data hashing.
See What Other Organizations Have Achieved with Dataddo
80%
less
pipeline
maintenance
2.5
man-days
per week
saved
3x
Faster
data
collection
Our Customers Love Us
Amalia Bornstein
Global Social Content and Marketing Data Analyst
Uber Eats
“The data team at Uber Eats appreciates Dataddo's user-friendly interface that is designed for operation by non-technical team members in an order to minimalize the need for excessive training to support efficient project delivery.”
Andrew Hart
Chief Operations Officer
Sat 7
“Working with Dataddo has greatly simplified our reporting and given us access to trend data and insights that we were previously unable to generate.”
Vahan Petrosayan
Director of IT & Infrastructure
Search Engine Journal
“With Dataddo, all of my questions get answered faster …[and it's] fun to play with data now.”
Michael Guntenaar
CTO
ID&T Group
“Dataddo opens up gates and takes away the hurdles of working with data.”
Laurent Partouche
CPO
FoodChéri & Seazon
“We chose Dataddo for its user-friendliness, automatic transformations, clear pricing policy, and the quality of the human relationship that was established from our first exchanges.”
Natheer Maloon
Technology Solutions Manager
Boldr
“Dataddo support proved immensely valuable throughout the implementation phase. 9.5 out of 10.”
Zdeněk Hejnak
Data Development Team Leader
Livesport
“We save about 70% of the time it would otherwise take to ingest all our data, or 3-4 full-time equivalents, and spend this much more time on data analytics and activation. We only have one full-time data engineer, who does more than just collect data, while our BI team consists of 11 members.”
Greg Senior
Business Operations Manager
Farm Focus
“Appreciate all the help and support for us. A refreshing level of service from a tech company! Thank you!”