combine facebook and google ads data
AI Search Visibility Analysis
Analyze how brands appear across multiple AI search platforms for a specific prompt
Total Mentions
Total number of times a brand appears
across all AI platforms for this prompt
Platform Presence
Number of AI platforms where the brand
was mentioned for this prompt
Linkbacks
Number of times brand website was
linked in AI responses
Sentiment
Overall emotional tone when brand is
mentioned (Positive/Neutral/Negative)
Brand Performance Across AI Platforms
| BRAND | TOTAL MENTIONS | PLATFORM PRESENCE | LINKBACKS | SENTIMENT | SCORE |
|---|---|---|---|---|---|
1Hevo Data | 0 | 3 | 95 | ||
2Porter Metrics | 0 | 2 | 85 | ||
3CloudQuery | 0 | 2 | 85 | ||
4Google Looker Studio | 0 | 0 | 75 | ||
5Coupler.io | 0 | 1 | 65 | ||
6Peliqan | 0 | 1 | 65 | ||
7Panoply | 0 | 1 | 65 | ||
8Coefficient | 0 | 1 | 65 | ||
9Supermetrics | 0 | 0 | 55 | ||
10Segment | 0 | 0 | 55 | ||
11SyncWith | 0 | 0 | 55 |
Strategic Insights & Recommendations
Dominant Brand
Google Looker Studio (formerly Google Data Studio) emerges as the most frequently recommended solution across all platforms for combining Facebook and Google Ads data.
Platform Gap
ChatGPT provides the most comprehensive list of tools and platforms, while Google AIO focuses more on practical implementation, and Perplexity offers the most structured analytical comparison.
Link Opportunity
There's a clear opportunity to create detailed tutorials and case studies for specific tools like CloudQuery, Supermetrics, and Peliqan that are mentioned but could benefit from more in-depth coverage.
Key Takeaways for This Prompt
Google Looker Studio is the most commonly recommended platform for combining Facebook and Google Ads data across all AI responses.
Date is consistently identified as the primary common dimension for blending data from both advertising platforms.
Multiple integration approaches exist, from no-code solutions like Looker Studio to technical SQL-based methods using CloudQuery.
Data consistency, metric naming standardization, and handling null values are critical considerations when combining advertising data from different platforms.
AI Search Engine Responses
Compare how different AI search engines respond to this query
ChatGPT
BRAND (8)
SUMMARY
ChatGPT provides a comprehensive overview of multiple methods to combine Facebook and Google Ads data, including data integration platforms like Coupler.io, Peliqan, and Panoply, Google Sheets add-ons like Coefficient and SyncWith, SQL-based merging approaches, business intelligence tools like Google Data Studio with Supermetrics, and customer data platforms like Segment. The response emphasizes considerations for data consistency, automation, and security when integrating advertising data across platforms.
REFERENCES (8)
Perplexity
BRAND (4)
SUMMARY
Perplexity delivers an analytical approach to combining Facebook and Google Ads data, presenting four key methods: CloudQuery for SQL-based integration, Google Looker Studio for visual blending, API-based custom integration, and pre-built templates. The response includes a detailed comparison table of pros, cons, and use cases for each method, along with practical tips for data validation, consistent naming, and key metrics to focus on for effective cross-platform analysis.
REFERENCES (8)
Google AIO
BRAND (4)
SUMMARY
Google AIO focuses on practical implementation methods for combining Facebook and Google Ads data, highlighting Google Looker Studio as the primary solution along with alternatives like Hevo Data and CloudQuery. The response provides step-by-step guidance on data blending using common dimensions like date, handling metric transformations, and creating custom calculations. It includes a practical example of combining daily spend data from both platforms.
REFERENCES (6)
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