Data source

LinkedIn Pages data model: follower statistics and daily follower gains

LinkedIn reports a page's followers in two ways: a lifetime snapshot split into segments such as seniority, industry and country, and the followers gained in each time range, organic and paid.

Open source. OWOX Data Marts is open source: you can read the code that loads and models your data, and run it yourself.
You own the data. LinkedIn Pages tables load into your data warehouse, under your account. If you leave OWOX, they stay where they are.
MCP-ready. Once the data is in, Claude or ChatGPT can work from your Data Marts through OWOX MCP.

Hand this to your AI

Don't wire up LinkedIn Pages by hand. Have your AI assistant load it into your data warehouse.

Your assistant sets up the LinkedIn Pages connector with you and loads the tables you pick; OWOX keeps them in your data warehouse, ready to use.

The prompt

set up the LinkedIn Pages connector in OWOX Data Marts, let me pick the tables I need, load them into my data warehouse and show me the first rows

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The LinkedIn Pages data model

2 tables18 fields0 joinsView on GitHub

Follower Statistics describes the audience as it is today: one row per page, category and segment, where the category is seniority, industry, function, company size, country, region or association type, and the segment is usually a LinkedIn URN such as urn:li:seniority:3.
Time-Bound Follower Statistics charts growth: one row per page and time range, with the followers gained, organic and paid.
Both carry the page's organization_urn, but neither is unique on it, and a join on the page alone would multiply rows.
For the demographic splits LinkedIn puts organic and paid followers together in organic_follower_count, so the audience is read from organic_follower_count, and paid_follower_count is worth reading only where LinkedIn fills it.

Land both tables in your data warehouse and put a Data Mart on whichever one a report needs.

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Why OWOX

What OWOX adds to LinkedIn Pages follower data

A LinkedIn company page's follower numbers are easy to look at and hard to keep: the audience table is a snapshot of the moment, and the growth table is split into ranges. Loading both on a schedule into your data warehouse lets the social team and the analysts read the same figures.

The page, not the ads. This source is the company page. Campaign cost and clicks come from the LinkedIn Ads source, and both can land in one data warehouse, so organic followers and paid followers sit beside what the ads cost.
Organic and paid, apart. The time-bound table splits each range's follower gain into organic and paid, so the share of growth that was paid is a single division.
Segments as rows. Seniority, industry, function, company size and country arrive as rows you can group and chart. The values are LinkedIn's own codes and URNs, so keep their names in a lookup table and join them in SQL.
Two tables, two questions. Use the snapshot to describe who follows the page and the time-bound table to chart how fast it grows. The seven follower_counts_by_* columns in the time-bound table come back empty from LinkedIn, so ignore them there.
Reports for the people who ask. A Data Mart over these tables can feed a dashboard for the social team or a spreadsheet for the monthly deck, from the same numbers.

Endpoints

LinkedIn Pages Endpoints

Documentation

2 LinkedIn Pages endpoints you can import. Each lands in its own table in your data warehouse.

Follower Statistics
Lifetime follower counts broken down by segment — seniority, industry, function, geography, and association type.
6 fields
Time-Bound Follower Statistics
Daily follower gains broken down by organic and paid — tracks how your audience grows over time.
12 fieldsTime series

Follower Statistics schema

LinkedIn Pages Follower Statistics schema

6 fieldsSchema on GitHublinkedin_pages_follower_statistics

Lifetime follower counts broken down by segment — seniority, industry, function, geography, and association type.

Questions this table answers

What share of followers has each seniority level?
Which industries and countries have the most followers?
How many followers fall in each company-size range?

LinkedIn Pages Follower Statistics fields
Field	Type	Description
`organization_urn`PK	STRING	Organization URN
`category_type`PK	STRING	Type of follower category (followerCountsByAssociationType, followerCountsBySeniority, etc.)
`segment_name`PK	STRING	Name of the segment identifier (associationType, seniority, industry, function, staffCountRange, geo)
`segment_value`PK	STRING	Value of the segment identifier (e.g., urn:li:seniority:3, EMPLOYEE, etc.)
`organic_follower_count`	INTEGER	Count of organic followers in this segment
`paid_follower_count`	INTEGER	Count of paid followers in this segment

Time-Bound Follower Statistics schema

LinkedIn Pages Time-Bound Follower Statistics schema

12 fieldsTime seriesSchema on GitHublinkedin_pages_follower_statistics_time_bound

Daily follower gains broken down by organic and paid — tracks how your audience grows over time.

Questions this table answers

How many followers did the page gain per week, organic and paid?
On which days did the page gain the most paid followers?
What share of the growth over the last quarter was organic?

LinkedIn Pages Time-Bound Follower Statistics fields
Field	Type	Description
`organization_urn`PK	STRING	Organization URN
`time_range_start`PK	TIMESTAMP	Start timestamp of the time range
`time_range_end`PK	TIMESTAMP	End timestamp of the time range
`organic_follower_gain`	INTEGER	Number of organic followers gained during the time period
`paid_follower_gain`	INTEGER	Number of paid followers gained during the time period
`follower_counts_by_association_type`	OBJECT	Followers segmented by association type (empty in time-bound responses)
`follower_counts_by_seniority`	OBJECT	Followers segmented by seniority (empty in time-bound responses)
`follower_counts_by_industry`	OBJECT	Followers segmented by industry (empty in time-bound responses)
`follower_counts_by_function`	OBJECT	Followers segmented by function (empty in time-bound responses)
`follower_counts_by_staff_count_range`	OBJECT	Followers segmented by staff count range (empty in time-bound responses)
`follower_counts_by_geo_country`	OBJECT	Followers segmented by country (empty in time-bound responses)
`follower_counts_by_geo`	OBJECT	Followers segmented by geographic area (empty in time-bound responses)

What LinkedIn Pages data answers

Across the tables

Which seniority levels, industries and countries do the page's followers come from?
How many followers does the page gain per week, organic and paid?
How does the follower mix change over time as the page grows?

Industry data models that use LinkedIn Pages