Every number here comes from my own LinkedIn export, converted to parquet and queried in your browser. The charts render server-side; the engine loads afterwards, only to power the controls. Each tile will show you the SQL behind it.
SELECT impressions, members_reached, total_followers
FROM overview
ORDER BY snapshot_date DESC LIMIT 1;
Daily impressions
7-day averageSQL
SELECT day, impressions, engagements, new_followers
FROM daily
WHERE day >= ? -- period selector
ORDER BY day;
By month
impressions
Jul '25
Aug
Sep
Oct
Nov
Dec
Jan '26
Feb
Mar
Apr
May
Jun
Jul
Aug
SQL
SELECT date_trunc('month', day) AS month,
sum(impressions) AS impressions
FROM daily
WHERE day >= ?
GROUP BY 1 ORDER BY 1;
By country
followers, from top metros
India37%
United States16%
United Kingdom2%
Singapore2%
Not disclosed43%
LinkedIn breaks out only the top metro areas, so 57% of the audience can be attributed to a country. The rest is not reported.
SQL
-- LinkedIn gives metro areas, not countries. The country
-- column is mapped on import, so the gap stays visible.
SELECT country, sum(percentage) AS pct
FROM audience
WHERE demographic_kind = 'audience'
AND category = 'Location' AND country <> ''
GROUP BY 1 ORDER BY pct DESC;
SELECT coalesce(nullif(matched_title,''), topic_slug) AS title,
impressions, engagements,
round(engagements * 100.0 / nullif(impressions,0), 2) AS rate
FROM top_posts
ORDER BY impressions DESC LIMIT 10;
Audience
share of followers
Seniority
Senior44%
Entry13%
Director11%
Manager7%
VP6%
CXO5%
Owner3%
Partner2%
Industry
IT Services and IT Consulting36%
Software Development21%
Financial Services4%
Human Resources Services3%
Staffing and Recruiting3%
Technology, Information and Internet3%
Business Consulting and Services2%
Banking1%
Hospitals and Health Care1%
Semiconductor Manufacturing1%
Job title
Software Engineer6%
Founder3%
Chief Executive Officer2%
Co-Founder2%
Project Manager2%
Solutions Architect2%
Data Engineer1%
Professor1%
Architect< 1%
Company
Pentaho3%
Hitachi Vantara2%
HCLTech1%
IBM1%
Tata Consultancy Services1%
Accenture< 1%
Cognizant< 1%
Infosys< 1%
Vmoksha Technologies Pvt. Ltd< 1%
Company size
10,001+ employees29%
1,001-5,000 employees9%
51-200 employees9%
11-50 employees8%
2-10 employees8%
5,001-10,000 employees8%
201-500 employees7%
501-1,000 employees5%
0-1 employees1%
SQL
SELECT category, value, percentage
FROM audience
WHERE demographic_kind = 'audience'
AND snapshot_date = (SELECT max(snapshot_date) FROM audience)
ORDER BY category, percentage DESC;
Who saw the posts
share of viewers
LinkedIn reports this separately from the follower breakdown above: these are the people a post actually reached, most of whom do not follow him. It is the wider, less self-selected group of the two.
Seniority
Senior46%
Entry22%
Manager8%
Director6%
VP2%
CXO1%
Owner1%
Training1%
Partner< 1%
Industry
IT Services and IT Consulting41%
Software Development19%
Technology, Information and Internet5%
Financial Services4%
Banking2%
Data Infrastructure and Analytics2%
Hospitals and Health Care2%
Business Consulting and Services1%
Telecommunications1%
Job title
Software Engineer12%
Data Engineer6%
Solutions Architect2%
Architect1%
Data Architect1%
Data Scientist1%
Full Stack Engineer1%
Project Manager1%
Company
Tata Consultancy Services2%
Accenture1%
Cognizant1%
Deloitte< 1%
IBM< 1%
Infosys< 1%
Microsoft< 1%
Oracle< 1%
Company size
10,001+ employees40%
1,001-5,000 employees12%
5,001-10,000 employees7%
51-200 employees7%
11-50 employees6%
201-500 employees6%
501-1,000 employees5%
2-10 employees3%
Location
Greater Bengaluru Area10%
Greater Hyderabad Area5%
New York City Metropolitan Area4%
Dallas-Fort Worth Metroplex3%
Greater Chennai Area3%
Pune/Pimpri-Chinchwad Area3%
San Francisco Bay Area3%
Washington DC-Baltimore Area3%
Greater Delhi Area2%
SQL
-- Same table, the other population: people who saw a post,
-- whether or not they follow him.
SELECT category, value, percentage
FROM audience
WHERE demographic_kind = 'content'
AND snapshot_date = (SELECT max(snapshot_date) FROM audience)
ORDER BY category, percentage DESC;
Source: LinkedIn aggregate analytics export, snapshot 2026-08-02. Imported with scripts/import-linkedin-analytics.mjs and published as CSV and parquet. Engagement figures are LinkedIn's own; nothing here is modelled or estimated.