LinkedIn Ads: Tips and best practices

Understanding the LinkedIn campaign hierarchy

LinkedIn’s hierarchy is offset by one level compared with most other advertising platforms, and Adverity field names follow the LinkedIn API rather than the Campaign Manager interface. This is the most common source of confusion when reading a LinkedIn data extract.

So campaign.name returns the name of what Campaign Manager displays as an ad set, and campaign_group.name returns what it displays as a campaign. Both are correct, and neither is a mapping error.

Choosing pivots

The pivot determines which fields are available, not just how the data is grouped. You can select up to three, with one restriction that overrides everything else:

Two further restrictions are worth knowing before you configure a datastream:

• At the CARD_INDEX pivot, video metrics cannot be collected.

• At the MEMBER_COMPANY pivot, there are no start and end date fields, so the data cannot be broken down by date.

Collecting demographic breakdowns

LinkedIn exposes the following demographic pivots, each of which must be collected in its own datastream:

• MEMBER_COMPANY — company name

• MEMBER_COMPANY_SIZE — headcount band

• MEMBER_INDUSTRY

• MEMBER_JOB_FUNCTION

• MEMBER_JOB_TITLE

• MEMBER_SENIORITY

• MEMBER_COUNTRY_V2, MEMBER_REGION_V2, MEMBER_COUNTY — geography

At a demographic pivot the available fields are reduced: you get the standard account and campaign fields, the demographic value itself, and creative.id and creative.name. Campaign group, conversion and detailed creative fields are not available.

Demographic data is retained for 25 months, rather than the 10 years that applies to other LinkedIn data.

Choosing between the lead metrics

LinkedIn reports several different lead metrics, and they count different things:

Each of these also has a viral counterpart, which counts activity on organic shares of the sponsored content rather than on the ad itself.

Reporting on reach

approximateMemberReach is an estimate of unique members, and LinkedIn only provides it for date ranges of up to 92 days.

Interpreting blank and zero values

A blank name field means a name could not be retrieved, not that the data is missing. Names for campaign groups, creatives, conversions, companies and geographies are retrieved separately from the performance data. When the authorization has lost access to a specific object, the row is still collected, the name column is left empty, and a warning is recorded in the fetch.

A zero may mean no value was returned. Empty metric values are recorded as 0. This is worth checking before concluding that a campaign genuinely produced no conversions.

Keeping field selections small

LinkedIn limits how many fields it returns per request. A datastream that selects more than that still collects everything, but it takes longer and uses more of your LinkedIn quota. Select only the fields you need.

Working with rate limits

LinkedIn applies a daily quota that resets at midnight UTC. When it is reached, Adverity retries for several hours and then waits for the reset rather than failing the fetch, so a throttled datastream can stay pending for a long time before completing on its own.

To reduce the chance of hitting the quota, schedule datastreams that use the same authorization at different times, and avoid collecting more fields or larger date ranges than you need.

Understanding objective type

The Objective type setting only affects data collection when OBJECTIVE_TYPE is one of the selected pivots. In every other configuration the setting is ignored, and changing it has no effect on the data you collect.

Previewing an image

To preview an image, collect the creative.resolved_url dimension.