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Demographic segmentation can be divided into two main categories: static segmentation and dynamic segmentation.

  • Static segmentation is based on factors that are fixed and unchanging, such as age or gender.

  • Dynamic segmentation considers factors that may change over time, such as location, education, or income level.

By combining both types of segmentation, marketers can gain a more complete understanding of their customers and target them with more tailored campaigns.

Illustration representing age, gender, income, education, occupation, religion, ethnicity, family status, and geographic location as traits for demographic segmentation
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This is just one way marketers can use segmentation. Here are a few other common forms of segmentation:

  • Psychographic segmentation: Characteristics such as lifestyle, values, attitudes, interests, and personality traits. For example, a travel company might target adventure seekers who are interested in outdoor activities and have a high tolerance for risk.

  • Behavioral segmentation: Consumer behavior such as buying habits, brand loyalty, and product usage. For example, a SaaS platform may have different audiences, including agencies and consulting firms that deploy the platform for their clients and have multiple seats and use cases. They may market to these customers differently than those with verticalized use cases.

  • Firmographic segmentation: Company characteristics such as size, industry, and location. For example, a software company might target its marketing toward small businesses (5-100 employees) in the HR industry that have raised a series A funding round. Firmographic segmentation is like demographic segmentation at the company level, and it's primarily used in B2B marketing and sales (especially for account-based marketing).

The most advanced marketing programs use a combination of segmentation types to increase the chances that a campaign will resonate with a particular audience. 

For example, product managers can identify users who have taken a specific action in their app (behavioral segmentation) and combine that with firmographic data (the user works at a tech company with 500 employees) and psychographic data to identify them as a product-qualified lead and push them to an upsell campaign.

 

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Step 1 - Gather existing customer data

Marketers can gather existing data about their customers from various sources such as surveys or their website analytics tools of choice.

Advertising platforms, such as LinkedIn Ads, provide useful demographic data as well.

LinkedIn Ads offers a website tag for identifying demographic characteristics of website visitors, simplifying segment identification and targeted campaign creation.


Website owners and marketers can gain a deeper understanding of their audience's job title, industry, company size, location, and seniority level.

The tool works by using LinkedIn's zero-party data to analyze the characteristics of the people who visit a particular website.

This data is then presented in a dashboard that displays various metrics and insights about the audience, including a breakdown of their job titles, industries, company sizes, and locations. 

It also includes information on the seniority level of visitors, which can be particularly useful for B2B businesses looking to target decision-makers and influencers.

LinkedIn Website Demographics, in combination with any other website analytics tools in use at a company, will provide sufficient information to identify segments to use in campaign targeting.

Next, marketers can set parameters in their ads to target these segments on LinkedIn. LinkedIn Ads allows you to target ads and campaigns based on a wide range of demographic criteria, primarily focusing on job-related demographic dimensions such as job function, job title, company, company industry, job seniority, company size, location and country.


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Using LinkedIn Ads, marketers also get granular tracking across targeted campaigns. Metrics on ads include:

  • Impressions: The number of times your ad was displayed

  • Clicks: Total chargeable clicks based on your campaign’s objective

  • Average CTR: Percentage of chargeable clicks relative to impressions (clicks divided by impressions)

  • Conversions: The total number of times people took a desired action after clicking on or seeing your ad

  • Conversion rate: Percentage of conversions relative to clicks (total conversions divided by clicks)

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