Analytics

By the end of this page, you can read who saw a LinkedIn ad, by job title, seniority, industry and company, from GET /v1/ads/{adId}/analytics.

Before you start

You need the Zernio _id of an ad (Create ads).

Read ad analytics

Standard metrics (spend, impressions, clicks, CPC, CPM) come rolled up on GET /v1/ads, GET /v1/ads/tree and GET /v1/ads/{adId}.

The firmographic layer is what is LinkedIn-specific, and it comes from the breakdowns below.

Firmographic breakdowns

Call GET /v1/ads/{adId}/analytics with breakdowns, a comma-separated list of LinkedIn dimensions.

The parameter is optional. Without it, the response is summary and daily for the range and no breakdowns object.

Each dimension you list costs one more call to LinkedIn, so ask only for the ones you read:

import Zernio from '@zernio/node';

const zernio = new Zernio();

const { data: insights } = await zernio.adinsights.getAdAnalytics({
  path: { adId: '66f0a1b2c3d4e5f6a7b8c9d0' },
  query: { fromDate: '2027-01-01', toDate: '2027-01-31', breakdowns: 'job_title,seniority,company_size' }
});

console.log(insights.analytics.breakdowns.seniority);

Response (200), trimmed to the summary and one breakdown:

{
  "ad": { "id": "66f0a1b2c3d4e5f6a7b8c9d0", "name": "Spring launch (single image)", "platform": "linkedin", "status": "active", "currency": "USD" },
  "analytics": {
    "summary": { "spend": 412.5, "impressions": 38210, "clicks": 512, "ctr": 1.34, "cpc": 0.81, "cpm": 10.8, "engagement": 640, "conversions": 12 },
    "daily": [
      { "date": "2027-01-01", "spend": 13.4, "impressions": 1240, "clicks": 17 }
    ],
    "breakdowns": {
      "seniority": [
        { "value": "urn:li:seniority:6", "name": "Senior", "spend": 210.1, "impressions": 19800, "clicks": 270, "ctr": 1.36, "cpc": 0.78, "cpm": 10.6, "engagement": 330 }
      ]
    }
  }
}

Each breakdown row carries value (LinkedIn's URN) and a name resolved server-side. Job titles, companies and industries all come back human-readable. Rows are sorted by impressions.

Without fromDate and toDate, the range is the last 90 days. The range is capped at 730 days.

When the account connects, Zernio imports its last 90 days of metrics. summary and daily hold no data for days before that, because only Meta backfills an older range on request. Breakdowns are read live from LinkedIn, so they cover the whole range.

Campaign level. The same breakdowns parameter works on GET /v1/ads/campaigns/{campaignId}/analytics. For LinkedIn, the campaign id is the Campaign Group.

That endpoint also serves Meta's demographic breakdowns. So both endpoints validate against every platform's dimensions at once.

Other platforms' dimensions. A Meta or TikTok dimension such as age on a LinkedIn ad is accepted and then dropped. The response is a 200 with no breakdowns object.

LinkedIn constraints

• Firmographic pivots are aggregated over the whole requested range. LinkedIn only serves them with timeGranularity: ALL, so there is no per-day series per job title.
• Demographic pivots lag 12 to 24 hours.
• LinkedIn omits segments with fewer than 3 events, so small campaigns return short lists.

Conversion attribution

Conversion-level metrics (post-click and view-through conversions, conversion value, cost) are read per conversion rule from the attribution metrics endpoint.

If it fails

The 400 lists every accepted dimension:

{
  "error": "Invalid breakdown: job_titles. Supported: age, gender, country, publisher_platform, device_platform, region, platform_position, impression_device, video_asset, image_asset, body_asset, title_asset, country_code, platform, ac, language, job_title, job_function, seniority, industry, company, company_size.",
  "type": "invalid_request_error",
  "code": "invalid_field_value",
  "param": "breakdowns"
}

Related

• Conversions API: attribution read-back per rule.
• Get ad analytics and Get campaign analytics: every metric in summary.
• Get campaign tree: rolled-up metrics per level.