The problem this solves
A comparison campaign wants an audience of companies that already use the thing you compare against. Interest targeting approximates this badly - it reaches people curious about the category, including your own customers and people who chose a third option. Technographic detection identifies the companies that actually run <competitor tool>, and a company-matched audience puts the comparison in front of everyone at those accounts.
Size and region keep the audience honest. Detection across the whole market includes companies far too small or too large for your product, and impressions on them cost the same as impressions on fits. Cutting to 100-5000 employees in <region> before the audience is created keeps the spend on the segment where the comparison can lead to a switch.
How the mission runs
- Detect the competitor across the market. The Audience Agent uses technographics to find companies where <competitor tool> is detected, recording the property and first-seen date and marking stale detections so they can be excluded.
- Cut to size and region. Firmographics keep companies with 100-5000 employees headquartered in <region>, and current customers are removed through the CRM connection. Counts at each stage go into the report.
- Stage the company-matched audience. The companies are staged as a LinkedIn company-matched audience named <name> on your connected ad account, shown with the count, and created on approval.
- Report the matched count to #paid. Once LinkedIn finishes matching, the matched company count is posted to #paid with the audience name, and the companies are saved as a list so outbound can work the same accounts.
The prompt
This is the exact objective the agent receives. Swap the obvious placeholders for your own domain, segment or channel and run it as-is from the console, Slack, or the API.
What comes back
A LinkedIn company-matched audience named <name> on your connected account made of companies running <competitor tool> with 100-5000 employees in <region>, with the matched company count posted to #paid and the underlying companies saved as a list with their detection evidence. The report gives the total detected, the count after the size and region cut, and the matched count.
Make it yours
- Add the tool owners as a contact-matched audience so the people who administer the incumbent see the comparison too.
- Layer intent data to keep only companies also researching your category, which makes the audience smaller and warmer.
- Build the same audience on Meta or export it for Google Customer Match.
- Refresh monthly so companies that dropped the competitor leave the audience and new adopters join.
- Rebuild quarterly and compare the matched count to see whether the competitor's footprint in your segment is growing or shrinking.
Frequently asked questions
How accurate is the detection?
Each detection carries the property where the tool was seen and the dates, and the agent excludes stale or single-property detections if you ask for a strict audience.
Is a company audience better than a contact audience here?
For awareness of a comparison, the company audience reaches the whole account; for a direct switch offer, the tool owners as a contact audience convert better. Many teams run both.
Are there restrictions on comparison advertising?
Ad content rules are the platform's and yours; the mission only builds the audience.
Why cut by region?
Ad accounts usually serve specific markets, and companies outside them add cost without pipeline; the region filter uses firmographic HQ data so the audience matches the campaign's geography.
Can I keep companies where the detection is uncertain?
Yes. Ask for them and they are included with a lower-confidence label in the saved list, though the audience itself does not distinguish them.
How often is detection updated?
Technographic data refreshes continuously; each rebuild reads the current state, and the first-seen and last-seen dates on the saved list show how current each detection is.