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.
Field prefix in Adverity |
What it is called in LinkedIn Campaign Manager |
Equivalent on other platforms |
|---|---|---|
|
Campaign |
Campaign |
|
Ad Set |
Ad set or ad group |
|
Ad |
Ad |
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.
Note
campaign_group fields are only available when Pivots is set to
CAMPAIGN or CAMPAIGN_GROUP. At any other pivot they cannot be
collected, so if you need campaign names alongside a different breakdown,
collect them in a second datastream and join the two.
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:
Important
A demographic pivot, whose name begins with MEMBER_, can only be selected
on its own. Combining one with any other pivot causes LinkedIn to reject the
request with an error stating that the pivot is not a valid enum symbol.
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
Note
LinkedIn does not offer age or gender breakdowns for reporting. These are available as targeting criteria, but not as a reporting pivot, so they cannot be collected regardless of datastream configuration.
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:
Metric |
What it counts |
|---|---|
|
Leads submitted through a LinkedIn Lead Gen Form. This is the figure most people mean by “leads” |
|
Lead Gen Forms opened, whether or not they were submitted |
|
Leads whose submitted email address is a work address |
|
Contact details shared in response to a Message Ad |
|
Interest clicks on a Message Ad |
|
Leads for LinkedIn Talent products |
Each of these also has a viral counterpart, which counts activity on organic
shares of the sponsored content rather than on the ad itself.
Note
These are lead counts. The details submitted in the form — name, email, and the answers to your own questions — come from the separate LinkedIn Lead Gen Forms (Lead Sync) connector, and cannot be collected through LinkedIn Ads.
Reporting on reach#
approximateMemberReach is an estimate of unique members, and LinkedIn only
provides it for date ranges of up to 92 days.
Warning
Reach values cannot be added together. When a data extract is grouped, the values in this column are summed, which double counts every member who was reached more than once. Use it only at the granularity you collected it at, and do not aggregate it further in a transformation or dashboard.
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.