Data to AI™ / Claude/Facebook Public Data
Ask Claude how your Facebook Page stacks up against rival brands on audience, buzz and post engagement, using the same public fields for every Page you track.
Better answers, fewer tokens.
Claude
How does our Facebook Page compare with two competitors on audience and buzz?
Bluebird Roasters has the largest audience, but Kettle & Co gets people talking: its Talking About Count is 4.1% of its Fan Count, against 1.6% for Bluebird and 2.3% for our Page.
| Name | Fan Count | Talking About Count |
|---|---|---|
| Northwind Coffee (us) Profile | 48,200 | 1,110 |
| Bluebird Roasters Profile | 93,500 | 1,490 |
| Kettle & Co Profile | 31,800 | 1,300 |
Each Page is its own source with its own Page Identifier; Profile values are current as of the last extraction, not summed over time.
Facebook Public Data reads the public profile and posts of any Facebook Page you name by its Page Identifier, including competitors' Pages. Marketing teams use it to benchmark audience size, posting cadence and post engagement against other brands.
Compare Fan Count, Followers Count and Talking About Count in Profile for our Page and every competitor Page, and rank them by Talking About Count as a share of Fan Count.
Before the quarterly brand review, the social lead asks Claude for one table instead of visiting five rival Pages, and spends the meeting on why a smaller competitor gets more conversation.
List the 15 Posts from Bluebird Roasters with the highest Likes Total Count plus Comments Total Count since June, then group their Message text into recurring themes.
A content strategist sees which topics and offers earn attention on a competitor's Page and brings three tested angles into the next editorial planning session.
Use the dataddo server to read About, Category List Name and Link from Profile for all tracked Pages and write briefs/competitor-positioning.md with one section per Page.
A marketing operations manager runs Claude Code in the campaign brief repository, so every new brief starts from current competitor positioning with links to the Pages.
Data to AI™ is priced per seat, like the AI assistants your team already uses, with ~25% off on annual billing. Need tailored contracts or volume pricing? Talk to us about Enterprise.
Serve governed business data to Claude, ChatGPT and other AI tools over MCP.
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| Without Dataddo |
With Dataddo
|
Outcome for you | |
|---|---|---|---|
| Audience benchmark | Someone opens each competitor Page, notes follower numbers by hand and pastes a stale table into the chat once a quarter. | Profile carries Fan Count, Followers Count and Talking About Count for every tracked Page, so Claude compares them from the last scheduled run. | Benchmark without manual copying |
| Post engagement of rivals | Top competitor posts are judged by eye while scrolling, and comments or shares are rarely counted. | Posts carries Likes Total Count, Comments Total Count and Shares Count per post, with Message and Permalink URL for context. | Best rival posts ranked |
| Posts tied to the right Page | Screenshots and copied post text lose track of which brand published what and when. | From Id in Posts matches ID in Profile and Created Time dates every post, so Claude attributes each post to its Page. | Clean attribution by Page |
| Token consumption | Claude spends tokens exploring raw Facebook Public Data columns, sampling rows and retrying until it understands the data. | Field definitions and relations are supplied up front, so the model skips the exploration and goes straight to the answer. | Fewer tokens per answer |
| Answer quality | Prone to wrong joins, invented fields and numbers that are hard to check. | Answers grounded in defined fields. In the Dataddo benchmark, 78.5% of questions were answered correctly, against 65.5% with plain CSV files. | Better answers |
The Facebook Public Data datasets marketing teams use most, with their real field names. Claude queries them by name through the Dataddo semantic layer.
| Dataset | Metrics and attributes |
Ask Claude
|
|---|---|---|
| Posts |
|
Which competitor posts got the highest Likes Total Count and Comments Total Count in the last 90 days, and what did their Message say? |
| Profile |
|
How does our Fan Count compare with the Fan Count and Followers Count of each competitor Page? |
We asked 43 pre-registered questions of three real datasets - Google Search Console, HubSpot deals and Google Ads - and delivered the same rows to the same model in four ways. Only the data layer changed.
of questions answered correctly - the best of the four delivery methods tested
fewer confidently wrong answers - 14.0% of runs against 24.0% and 26.3%
more correct answers on messy CRM data - better on 8 questions, worse on none
Same model, prompts and rows in every condition; 759 graded runs, ground truth frozen before any run. On Google Search Console alone, documented CSV files did as well as Data to AI™ - the advantage comes from messier data such as HubSpot deals.
Read the benchmark →In Dataddo, create a Facebook Public Data source for each Page you want to benchmark, entering its Page Identifier and choosing Posts and Profile. Attach the flows to a Claude destination or AI Model, then add Dataddo Data Access from the Claude connectors directory and sign in with your Dataddo account.
Any Page you set up as a Facebook Public Data source. Enter its Page Identifier from the Page URL, for example dataddo from facebook.com/dataddo, or its numeric page ID. Each source covers one Page.
No. You authorize the source with your own Facebook login, Facebook Custom app credentials or Meta Admin Center, and enter the other Page's identifier. The connector reads that Page's public data.
No. Posts includes public counts such as Likes Total Count, Comments Total Count and Shares Count, but no reach or impressions. For insights about your own Pages, use the Facebook Organic connector.
As current as the last run. Profile has no date range: every run reads current values, and the dataddo_extraction_timestamp column shows when each row was read, so Claude can state the date of its figures.
Yes. On Team and Enterprise an Owner adds Dataddo Data Access once, and each member signs in with their own Dataddo account, so everyone reaches only the flows their account can see.
No. Claude queries extracted data through the semantic layer by entity and field name. Dataddo never accepts SQL from the model, and nothing is written back to Facebook.
