What is behavioral targeting and how does it work?

Behavioral targeting has become a key approach in digital advertising, allowing advertisers and publishers to create more personalized experiences based on how users interact with websites, apps, and online content. By analyzing behavioral data, companies can better understand audience interests, improve ad relevance, and create campaigns that are more likely to engage users.

In this article, we’ll explore how behavioral targeting works, the main types and benefits of this approach, and how privacy changes are influencing the future of behavior-based advertising.

What is behavioral targeting?

Behavioral targeting (also known as online behavioral advertising) is a method that allows advertisers and publishers to display relevant ads and marketing messages to users based on their web-browsing behavior. Broadly speaking, this form of targeting typically relies on data connected to a user’s behavior, such as:

• Pages viewed
• Previous search terms
• Amount of time spent on a website
• Ads, content, and buttons clicked
• Last date of website visit
• Other information about their interactions with the website

What’s the difference between behavioral targeting and online behavioral advertising (OBA)?

The main difference between behavioral targeting and online behavioral advertising (OBA) is that behavioral targeting is the technique used to analyze user behavior, while OBA is the advertising approach that uses this technique to deliver personalized ads.

Behavioral targeting relies on data such as browsing activity, searches, clicks, and purchase history to identify user interests and audience segments. OBA applies these insights to display more relevant ads or personalized content, such as product recommendations, across digital channels.

Types of behavioral targeting

There are two main types of behavioral targeting: onsite and network. The difference between them comes down to where data is collected and how it is used.

Onsite behavioral targeting

Onsite behavioral targeting happens within a particular site and is typically implemented as part of website personalization. Ads are displayed to the user based on behavioral data and/or other information about the visitor gathered on the pages of the same site. This method plays a significant role in building a more streamlined and relevant experience for the users.

Onsite behavioral targeting allows advertisers and publishers to display relevant content, recommended products, and promotions to users who are visiting the site. This way, users are more willing to engage with the site, spend more time browsing, and convert (i.e. perform a desired action like making a purchase or signing up for a newsletter).

Network behavioral targeting

Network behavioral targeting uses behavioral data collected across multiple websites to create audience segments based on factors such as interests, purchase intent, and online behavior. Unlike onsite behavioral targeting, which relies on data gathered from a single website, network behavioral targeting allows advertisers to reach users across different sites and deliver more personalized ads.

This data does not include information like people’s names, email addresses, or telephone numbers, but may involve device-identifying information such as IP and MAC addresses, cookies, or other device-specific IDs. Algorithms analyze this data and assign users to specific segments based on their demonstrated web behavior. These segments can then be used to display customized ads that users are more likely to engage with.

An example would be a user seen on a number of automotive sites, business sites, and male-fashion sites. A reasonable guess would be that the user is male. The advertiser can buy this segment — typically provided by data management platforms (DMPs) that are integrated with and sell to demand-side platforms (DSPs) — to target the relevant audience.

How does behavioral targeting work?

The behavioral targeting process works by collecting and analyzing information about users’ online activities, then using these insights to create audience profiles and deliver more relevant ads. Gathering behavioral data — a prerequisite for effective behaviorally targeted ads — can be performed in multiple ways, but usually a DMP is needed to aggregate the behavioral data about site visitors. DMPs are responsible for collecting, storing, and organizing data for advertisers.

The data used for behavioral targeting can come from a range of sources, including websites, mobile apps, CRM systems, and other marketing-automation systems, and can include:

• User login information (for registered users)
• IP address and geolocation
• Pages (or products) viewed on the site
• Duration of visit
• Clicks
• Recency of visit
• Interaction with elements of the site
• Previous purchases
• Demographics
• Content read
• Sections of the page regularly visited by a user
• Searches within the site
• Websites they’ve visited

Almost all advertisers and publishers are able to gather some onsite data on their customers and visitors. Knowing how to leverage the information towards achieving specific marketing goals is critical for effective behavioral targeting. Taking advantage of the method is an easy way to boost conversion rates.

The behavioral targeting process

1. Collection and analysis of data

User data is collected from a range of sources, but is typically done via tracking pixels (also known as third-party cookies) and stored in a DMP or other AdTech platform like a DSP. The more data, the more accurate the targeting. The collected data is then analyzed and used to create user segments.

2. Segmentation

Users are clustered into segments by behavior (for example, people who travel a lot, people who like bikes, people who often return to the same product category, etc).

3. Application of data

Ad campaigns are implemented to match a specific user segment, making the advertising more relevant for specific groups of users and increasing the likelihood of conversions and responses. Apart from using data collected by DMPs and other AdTech platforms, behavioral targeting can be enriched with data pulled from registered users’ profiles.

Registered users make a purchase in an online store. Those sales, along with the user’s site-navigation history, are often stored and analyzed to make targeted offers the next time the user comes online.

Unregistered users can be targeted using cookie information saved on the customer’s browser. When the user visits the site again, the cookie (unless it was deleted by the user) is sent to the web server, making it possible to target the user.

There is also a way to collect and track data through Internet service providers (ISPs) who perform methods like deep packet inspection to analyze their customer’s traffic and determine the types of websites they visit.

Then, the data is sold to marketing and ad-serving companies to deliver more personalized ads. This is a common practice, as many ad-serving companies buy the behavioral data from third parties like Nielsen (formerly eXelate) and dataLogix (now part of Oracle).

What’s the difference between behavioral targeting and contextual targeting?

The main difference between behavioral and contextual targeting is that behavioral targeting uses information about users’ online activity, while contextual targeting focuses on the content of the page where an ad appears.

Contextual targeting involves displaying ads that are relevant to the content of the page. Typically, this method of targeting doesn’t use information about users; it only takes advantage of the context of the ad. However, behavioral data can be used to improve the relevance of contextual ads.

Behavioral targeting allows advertisers and marketers to target individual users. The method is based on the premise that the ad should be relevant not to the page, but to the user who is visiting the page. Behavioral targeting has been widely used in online advertising and marketing for over a decade due to the growing availability of user data.

To be effective, behavioral targeting must have sufficient information about the user.

Benefits of behavioral targeting

Advertisers use behavioral targeting to deliver more relevant ads, improve user experiences, and create more effective campaigns by using data to understand audience interests and intent. The amount of data marketers have about users allows them to create detailed profiles and display ads that are relevant to specific user segments.

The premise behind behavioral targeting is that it benefits both the visitor and the site displaying the ads. Website experiences become more relevant and engaging, while users are more likely to interact with targeted ads and content. Implementing behavioral targeting can also contribute to higher click-through rates (CTRs) and improved conversion rates.

Today, behavioral marketing is not just about collecting explicit user information but also about analyzing data and drawing meaningful conclusions from user behavior.

Challenges of behavioral targeting and the impact of the GDPR

With the General Data Protection Regulation (GDPR) in effect, this targeting method may be challenged by stricter rules concerning storing cookies in a user’s browser. The GDPR may force marketers to relinquish much of their dependence on behavioral data and seek new targeting methods.

What should take the place of behavioral data collection in a post-GDPR world? How will digital marketers display the right messages to the right eyeballs at the right times? For many, the answer lies in contextual advertising.

The power of true contextual targeting is compliance with the GDPR due to its minimized reliance on personal data.

Contextual targeting allows companies to almost completely avoid the GDPR, provided they don’t collect or use any personal data. Many companies are already taking advantage of contextual targeting methods.

AccuWeather, for example, recently partnered with Comprendi, a company offering contextual advertising automation. The goal of the collaboration is to provide real-time ad-personalization algorithms. By tapping into information about allergies, migraines, driving, and lawn and garden forecasts, advertisers partnering with AccuWeather can display ads to specific audiences and locations influencing possible purchase decisions and interests (e.g. gardening, sunbathing, raincoats, trekking, etc).

Another example is Seedtag’s neuro-contextual advertising technology, which uses AI to analyze content and contextual signals to help advertisers reach relevant audiences without relying on traditional user identifiers.

Methods like these will certainly proliferate and become more advanced in the coming months. Also, we must not forget that the GDPR is in force in Europe and applies to EU residents and citizens, but behavioral targeting is still allowed in other parts of the world and used by major players in the online marketing industry, including Facebook and Google.

Getting the most from behavioral targeting

Behavioral targeting is most effective when it’s built on high-quality data, a well-defined targeting strategy, and a privacy-first approach. As customer expectations and privacy regulations continue to evolve, successful marketing strategies rely on balancing personalization with transparency and responsible data practices.

Whether you’re optimizing an existing AdTech platform or building new behavioral targeting capabilities, the right technology foundation can help you create more relevant customer experiences while improving campaign performance.

Ready to improve your behavioral targeting strategy? Contact our experts to build a custom solution tailored to your business goals.