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The widest demographic reach

Facebook Data, Delivered

Public Facebook content and engagement metrics, normalised to the same schema as every other platform we cover and pushed into your stack. Nothing to build, nothing to maintain.

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source specification

Source
facebook.com
Objects
Page posts, Public Pages, Public Group posts, Comment threads, Reaction and share counts
Formats
JSON · CSV · Parquet
Refresh
Continuous to daily
Scope
Public content only

about the platform

What makes Facebook different

Facebook is easy to write off as the platform your younger customers have left, and that reading misses what makes it commercially distinctive: it still reaches demographics that no other network covers with the same depth, particularly outside the twenty-five to thirty-four band that dominates every other platform. Its structure is also different — Pages behave like public business profiles, and public Groups behave like closed-ish communities that happen to be readable, which is where a great deal of local and category-specific discussion actually lives. The reaction taxonomy is unusually informative too, since a post with a thousand angry reactions and a post with a thousand likes are telling you opposite things.

why teams track it

Why Facebook data is worth having

For brands whose customers are not exclusively young and urban, Facebook is frequently the largest single public source of discussion about them. Local businesses, home and auto categories, healthcare, and financial services all skew heavily here, and public Group discussion in those categories carries purchase-intent signal that simply does not exist on Instagram or TikTok.

Visit facebook.com

applications

What teams build on Facebook data

Reaction sentiment without a classifier

The reaction breakdown is sentiment that the audience labelled themselves. A spike in angry reactions on a competitor’s announcement is a cleaner signal than anything a sentiment model would infer from the comment text.

Public Group discussion mining

Local buy-and-sell groups, category enthusiast groups, and regional community groups carry purchase intent and vendor recommendations that never surface on any other platform.

Local and multi-location brand monitoring

Franchise and multi-location businesses have a Page per location, and monitoring them together shows which sites are generating complaints and which are generating advocacy.

Reaching under-covered demographics

If your customers are over forty, or outside major metros, this is where the public conversation about your category is happening — and where most social listening setups are not looking.

Competitive campaign tracking

Competitor Page posting cadence, message framing, and the reaction and comment response each post draws, tracked continuously rather than sampled.

Crisis and complaint early warning

Comment volume and negative reaction share on a Page post move within hours of a product problem, which is usually well before the support queue reflects it.

what you get back

Fields in the Facebook feed

Platform-specific detail on top of the unified social schema, so a dashboard built on one platform works on the next without a rewrite.

  • Page post text, attached links, and media type
  • Full reaction breakdown — like, love, care, haha, wow, sad, angry
  • Comment and share counts per post
  • Public Page attributes — category, verification state, follower count
  • Public Group post content with community name and posting timestamp
  • Comment threads with author handle and reply nesting

Public surfaces only

We collect what a logged-out visitor can see. No authentication is bypassed, no private content is touched, and no attempt is made to deanonymise anyone.

One schema across platforms

A post from any network arrives with the same field names, so adding a platform does not mean rewriting anything downstream.

Deletion propagates

When content is removed at source it drops out of subsequent deliveries, and retention windows on delivered data are configurable per engagement.

10+
Platforms covered
<60s
Detection latency
3
Delivery formats
99.9%
Uptime SLA

related sources

Tracked alongside Facebook

One platform is a partial view. These deliver on the same schema, so combining them is a configuration change rather than a project.

X (Twitter)

Real time, in public

YouTube

Long-form, and searchable

LinkedIn

The professional graph

All platforms

Instagram, TikTok, X, YouTube and more

49 retail sources

Pair social signal with catalogue and price data

AI datasets

Use this feed as model training data

See every data product

questions

Frequently Asked Questions

Everything you need to know before you send us your first request.

From public Groups, yes — those whose posts are visible without joining or logging in. Private and closed Groups are out of scope, and we do not join Groups to gain access to them. Where a category’s discussion happens in private Groups we will say so during scoping rather than let you assume coverage you are not getting.
Direction. A thousand likes and a thousand angry reactions are the same engagement number and opposite outcomes, and any metric that collapses them into "engagement" destroys the most useful thing on the post. We deliver each reaction type as its own field so you can weight them however your analysis needs.
It depends entirely on who your customers are, and we would rather say that than sell you coverage you do not need. For categories skewing over forty, for local and regional businesses, and for most of home, auto, health, and financial services, it is often the largest public discussion source available. For a youth-skewed streetwear brand it is usually not, and TikTok and Instagram are the better spend.
We treat user-generated content as containing personal data by default rather than assuming otherwise. Collection is limited to public surfaces, deletion at source propagates through to subsequent deliveries, retention windows are configurable per engagement, and a DPA is signed before any delivery begins.
Into the systems you already run. Normalised records land as JSON, CSV, or Parquet in S3, GCS, or Azure Blob, or straight into Snowflake or BigQuery, on whatever cadence you set. Webhooks push matches to your endpoints as they are detected, which is how most customers wire alerting. A solutions engineer sets the schema, cadence, and destination with you during onboarding.
Keeping the collector working is our responsibility. Extractors are monitored continuously, and when the platform changes its structure we patch upstream while the schema we deliver to you stays fixed. If a change causes a coverage gap we tell you which window was affected rather than quietly returning fewer records.
Pricing is scoped per engagement — the number of tracked terms, handles, or communities, the refresh cadence, and the delivery destinations involved. Historical backfill is quoted separately. Every engagement starts with a free sample run against your own brand terms, so you can judge the data before committing.

Still have questions?

Talk to an engineer

Ready to Get Started?

Talk to us about your sources and volume. We'll return a sample dataset from your target sites before you commit to anything.

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