6 Proven Types of Targeting in Marketing

Apr 1, 2024
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These types of targeting in marketing are the most effective at helping brands reach their desired audience.

From demographic targeting to contextual campaigns, these techniques are effective for reaching an audience

Every marketer needs to be well-versed in the various types of targeting to ensure successful digital advertising campaigns. Targeting techniques increase the chance of conversion by ensuring the right message reaches the right person. Additionally, it allows marketers to personalize their campaigns, creating a more engaging and relevant experience for consumers.

The following types of targeting in marketing can help brands reach their desired audience effectively.

Want to dig deeper? Check out The Complete Guide to Understanding Targeting in Marketing.

Proven Types of Targeting in Marketing to Know

Data-based Targeting

In the world of advertising, data targeting has become an essential tool for reaching target markets at scale. There are different types of data that advertisers can utilize to maximize the impact of their campaigns.

One type is demographic or demo targeting, which involves tailoring advertisements based on specific demographic characteristics such as age, gender, income, and location. By understanding the demographic profile of their target audience, advertisers can create personalized advertisements that are more likely to resonate with the intended recipients.

Another category is behavioral targeting, which focuses on tracking and analyzing consumer behavior online. This includes tracking the websites visited, the searches made, and the products or services purchased. By collecting and analyzing this data, advertisers can create targeted advertisements that align with the interests and preferences of the target market.

Interest-based targeting is another effective method, which involves displaying advertisements based on the individual's interests and preferences. This category relies on data from social media interactions, online content consumption, mobile app usage, and other online sources. By understanding the specific interests of their target audience, advertisers can deliver highly relevant advertisements that are more likely to capture their attention.

It is important to note that while data-driven advertising strategies offer immense benefits, transparency is crucial. Advertisers must prioritize consumer privacy and openly communicate how data is being collected and used. This not only builds trust with consumers but also ensures that their personal information is protected. By emphasizing transparency within a concentrated targeting strategy, advertisers can put consumer minds at ease and create a positive experience for their target market.

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Retargeting is a powerful strategy in online advertising that aims to reconnect with users who have visited a website but left without making a purchase. This technique maintains brand visibility to maximize the chances of reacquiring and converting those potential customers.

The main purpose of retargeting is to reach the majority of users who, statistically, do not convert on their first visit. Research shows that about 98% of website visitors leave without taking any action. This is where retargeting steps in to bridge the gap and bring these visitors back through strategically placed ads across various websites they subsequently visit.

Increasingly recognized as an effective tactic, retargeting has proven to be highly successful in driving conversions. Studies reveal that retargeted consumers are 70% more likely to convert compared to the effectiveness of targeting cold traffic. This enhances the immense potential and impact of campaign targeting by ensuring that ads are shown to consumers who have already expressed some level of interest in a product or service.

IP Targeting

IP targeting is a method used by advertisers to deliver personalized content to users based on their IP addresses. IP addresses are unique numerical identifiers assigned to devices connected to the internet, which are then matched with user profiles. This method also allows for cross device targeting that applies across platforms within a single home.

In the IP targeting process, IP addresses are first collected and compiled into a list. Advertisers may obtain these IP addresses through various means, such as website registrations, app installations, or data providers. Once a list of IP addresses is obtained, it is uploaded to an advertising platform or service.

The matching of IP addresses with user profiles occurs through the use of cookies or other tracking technologies. When a user visits a website or interacts with an ad, their IP address is recorded and associated with their browsing behavior or personal information. This allows advertisers to deliver personalized content to specific IP addresses based on their demographics, interests, and preferences.

However, in Europe, IP targeting faces limitations due to regional data privacy laws, such as the General Data Protection Regulation (GDPR). These laws restrict the collection and processing of personal data, including IP addresses, without explicit user consent. Advertisers in Europe must comply with these regulations by obtaining user consent or using alternative targeting methods that do not rely on IP addresses, such as contextual targeting.

Contextual Targeting

Contextual targeting is one of the most popular types of targeting in marketing, delivering ads to audiences based on the content of the websites they visit. It can be divided into two tactics: site targeting and category targeting.

Site targeting involves selecting specific websites or channels where advertisers want their ads to appear. It allows advertisers to focus their campaigns on relevant sites that align with their target audience and brand values. By handpicking websites, advertisers can ensure that their ads are displayed in a suitable and trusted environment. This tactic provides a more direct approach to reaching the desired audience and can be particularly effective for campaigns that require a high level of control.

On the other hand, category targeting lets advertisers target channels that broadly address an audience’s interests. Advertisers can choose relevant categories that best match their target audience, and their ads will be displayed across a range of websites within those categories. This tactic provides a wider reach and potential exposure to a larger audience within the selected categories.

Contextual Keyword Targeting

Contextual keyword techniques deliver ads through search engines that relate to specific keywords. It allows advertisers to reach their target audience more effectively by displaying ads on websites or in content that aligns with the chosen keywords.

The advantages of contextual keyword targeting over contextual site or category targeting are numerous. Firstly, contextual keyword targeting provides granular and precise targeting, allowing advertisers to focus their ads on specific keywords that are most relevant to their product or service. This ensures that the ads reach an audience that is more likely to be interested in what is being advertised, increasing the likelihood of conversions and sales.

The process of selecting keywords begins with identifying the specific words or phrases that are most relevant to the advertised product or service. Advertisers must consider the preferences and search behaviors of their target audience to identify appropriate keywords. Once the keywords have been chosen, the next step is to scan websites for available ad placements that match those keywords. This can be done by using tools and technologies that crawl multiple websites and extract information about the content and context of each page.

Implementing a probabilistic algorithm is the next step in contextual keyword targeting. This algorithm uses machine learning and statistical techniques to define and categorize the page and impression based on the selected keywords. It analyzes the content on the page, the user's browsing behavior, and other relevant factors to determine the likelihood of the page being a good match for the chosen keywords. This probabilistic approach ensures that the targeting is accurate and maximizes the probability of reaching the desired audience.

CRM Targeting

CRM targeting is a strategy used in account-based marketing campaigns to identify and engage with specific individuals or organizations within a target market. This approach allows marketers to focus their efforts on high-value accounts that are most likely to convert into customers.

CRM targeting works by leveraging customer relationship management (CRM) data to select and prioritize target accounts. The CRM data includes information on customer demographics, previous interactions, purchase history, and any other relevant information. By analyzing this data, marketers can identify the key attributes and characteristics of their ideal customers, such as industry, company size, or job title.

The benefits of CRM targeting in account-based marketing campaigns are numerous. Firstly, it allows marketers to allocate their resources more effectively, as they can concentrate their efforts on the accounts with the highest potential for success. By prioritizing the most relevant accounts, marketers can save time and money, ensuring a higher return on investment.

Secondly, CRM targeting enables personalized and tailored marketing messages that resonate with the target accounts. Understanding the specific needs, preferences, and pain points of the account enables marketers to create highly relevant and engaging content, increasing the chances of conversions.

Additionally, CRM targeting allows marketers to track and monitor the customer journey more effectively. By analyzing website activity, email communication levels, and other interactions, marketers can deliver ads and content that are timely and contextually appropriate. This personalized approach enhances the customer experience and builds stronger relationships.

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