Audience building and matched audiences

Write a short profile of the person who signs or influences the deal. Start with your best five customers. What industry are they in, how large are they, and what job do the contacts hold? Write the pattern in two lines.

Example: marketing and sales leaders at software companies with 50 to 500 staff in the UK and Netherlands. If you cannot write it in two lines, the audience will be vague too.

Job titles are messy. The same role appears as "Head of Growth" in one company and "Marketing Manager" in another. Job function and seniority tend to give you more reach with less noise, so start there. Add titles only to narrow it further.

For companies, use industry, company size and location. Add company names or lists only for a deliberate account-based campaign. The platform and attribute set are in Campaign Manager setup, and the wider picture is in the LinkedIn Ads tool page.

Campaign Manager shows an estimated audience size as you build. Use it as a guide. For a cold campaign, you want enough people for the algorithm to find the best responders, and I would not go narrower than a few tens of thousands unless it is account-based.

If the number is tiny, remove the least important filter. If it is huge, add one filter that reflects real buying power. Narrow the audience, but not as far as you think explains why stacking filters backfires.

Exclusions save money. Remove current customers, your own staff, competitors and your agency partners. If a job title appears among your candidates that only students or job seekers hold, exclude it.

Exclusions also let you keep different campaigns apart. A warm campaign must not compete with a cold one for the same people.

A matched audience built from a contact list lets you reach people you already know. Export from your CRM, in HubSpot or Pipedrive, the segments that matter: open deals, past leads who went cold, and customers for exclusion.

Use work email addresses where you have them, because personal addresses match less often. Remove duplicates, old contacts and anyone who has opted out. Some CRMs can sync lists to LinkedIn automatically, so check yours before you do it by hand.

Upload the file in Campaign Manager. The match rate is the share of your contacts that LinkedIn could find. A partial match is normal. Very low rates usually mean the file contains personal emails or old addresses.

Matched audiences also need a minimum number of matched members before they can be used, so very small lists may not qualify. Combine segments if you run into that limit.

If you sell to a defined set of companies, upload a company list. Take the target accounts from your CRM or from LinkedIn Sales Navigator, and then add job function filters to reach the right people inside them. This is a smaller, more expensive audience that suits higher-value deals.

Run three tiers.

• Cold: firmographic targeting with no prior contact.
• Warm: contacts from your list and visitors to your website, covered in Retargeting setup.
• Excluded: customers and anyone you do not want to reach.

Give each tier its own campaign, so you can set different messages and budgets. Cold audiences need ideas and insight, and warm ones can handle a direct offer.

Use a naming pattern such as Type, Source, Date. For example, "Contacts, HubSpot open deals, 2026-10". Refresh lists every month, because stale lists show ads to people who already bought.

• Building a very narrow audience on titles alone.
• Forgetting to exclude customers.
• Uploading a list full of personal email addresses.
• Mixing cold and warm people in a single campaign.
• Never refreshing uploaded lists.

Each audience has a clear purpose and a name. Cold audiences are big enough to leave the learning phase, and match rates on uploaded lists are healthy. Cost per click and cost per opportunity differ by tier, and the warm tier is cheaper, which tells you the layering is doing its job.