What Is Behavioral Targeting?

Advertising can be a challenging endeavor. Carefully crafted campaigns can often fall short of desired goals, with no apparent reason. Marketers can easily reach the wrong audience or fail to deliver the correct message that can covert or engage consumers.

Today, random targeting is a thing of the past. Marketers have a variety of methods to ensure that the right message reaches the right person at the right time. Advances in behavioral tracking and the increase of powerful datasets have enabled advertisers to boost conversion rates across both online and offline campaigns.

Campaigns that use behavior tracking and utilize behavioral targeting are yielding incredible results.

Table of Contents

What is behavioral targeting

Behavioral targeting is a marketing strategy that uses historical behavior to personalize the types of ads consumers see.

Historical behavior is sourced through powerful datasets that illustrate how audiences behave. Marketers can then use this to create ads and campaigns that match each consumer’s actual behavior.

Behavioral targeting involves building up a detailed user profile and using this to deliver better messaging and better timing. It limits the possibility of advertisers delivering irrelevant ads and helps to boost advertising campaign KPIs.

What are the benefits of behavioral targeting

Behavioral targeting is a powerful marketing tool that is rooted in the modern, data-centric world that we live in. But it isn’t all about using numbers and tech. Behavioral targeting provides value to both advertisers and consumers.

Advertiser benefits

Improved engagement for advertisers

Understanding consumer habits helps advertisers to identify audiences that have engaged with specific products or touchpoints. It also helps to identify audiences that are in the right moment or behavior for a particular campaign. Targeting users with no behavioral intent or brand awareness will limit engagement. Using behavioral targeting will increase a number of critical metrics, such as clicks or conversions.

Matching consumer needs with creatives and messaging

Personalized messaging converts more users and ultimately reduces the amount of wasted ad spend. Relevant ads are much more likely to move consumers along the purchase funnel than generic ads that are not personalized. Ads that align with a consumer’s previous behavior are much more likely to convert than ones that don’t.

Improving the bottom line

Ultimately advertisers want to get the best possible return on investment on their campaigns. Delivering ads that match with audiences previous behavior is more likely to drive conversions than ones that are generic. With behavioral targeting, companies can see a rise in new business, repeat customers, engagement, and other key metrics.

Consumer benefits

An improved ad experience

Consumers aren’t always keen on giving up their personal data. But they also dislike ads that aren’t relevant or ads where the experience is unengaging. That’s why, when surveyed, more consumers prefer personalized advertising. This personalization ultimately improves their experience.

Better efficiency

Ads can be a quick route to purchase, providing a fast way of identifying the best product for their needs without a long searching process. This increases efficiency for consumers, allowing them to get to storefronts quickly and finding the most relevant products, rapidly.

Awareness of new products

By seeing ads that are personalized to them, consumers can keep up to date with new products that interest them. Retargeting based on behavior can also help to complete purchases that a user was distracted from.

Publisher

As well as behavioral targeting benefits the advertiser and the consumer, it also helps the publisher. Where these publishers use ad monetization as a revenue stream, the ads mustn’t be irrelevant to the user as it might reduce engagement with their product, app, or publication.

How does behavioral targeting work in 2021

The process of behavior-based targeting on the highest level consists of collecting information about a user or a person and then using this information to deliver ads that match this information.

Collecting information can be done in many ways, and it can come from many different sources. Often a data management platform (DMP) is used to aggregate this information for advertisers.

Here are some common data sources that are used for behavioral targeting:

CRM
Apps
Websites
Marketing systems
3rd party data providers
Marketing surveys

These sources provide a huge variety of data that includes:

Website cookie data

Data on how users behave and interact with websites is a valuable method of behavioral segmentation. Users spend a lot of time browsing the web, so the information is rich – pages visited, for how long, in which regions. Therefore these insights can provide a lot of information that is useful to boost engagement and conversions.

Mobile device data

Cookies also work on mobile devices. Understand the behavior of the potential customer on a mobile device can help to understand which format and which message could work best in an advertising campaign.

These web-based insights can be combined with social signals, check-ins, and mobile purchases to understand the best way to target audiences.

Geographic location

Anonymized location can be extremely valuable for advertisers. Especially when accurate and precise. Since the early days of bidstream datasets, device behavior can be accurately tracked to build up detailed profiles of behavior than can form powerful, behavioral-based segments for advertising.

Subscription data

Businesses that have some log-in system require the users to enter details and information about themselves. These fields can be used to understand the users, with address, interests, and contact details help with behavioral targeting. Let’s say you are looking to purchase a Notion template, it makes sense to pre-fill any forms with relevant subscription data, if you have it.

Demographics

DMPs and other marketing software can collect large amounts of demographic segmentation information, such as age ranges, interests, and gender, to create a detailed profile of audiences. This process usually works without using personal information but these ranges are used to create campaigns that can communicate more personally with audiences.

The process of behavioral targeting

The data collection process

User data can come from several different sources. Depending on the source, there are many different ways to collect data. For website behavior, a pixel is used. This process creates and updates cookies that understand how the user interacts with the site. Apps have a similar process. SDKs can collect other behavioral information, such as location data.

This data is usually stored in a DMP, but there are other adtech solutions for storing this information.

Organization and segmentation

Once this behavioral information exists in a central location, the next step is to sort individual users into groups that share the same behaviors.

This segmentation varies significantly depending on the company, product, or goals. For example:

Potential customers that go to the gym
Visits gym location 2 times a month
Current customers who like meat
In CRM and visited meat weekly delivery page
Users who are interested in SEO (maybe even more specific, like a this one, this Bristol SEO agency, or even a industry specific one like this one)
Existing customer who have read at least one blog post related to SEO trends 2020

Delivery and application of behavioral targeting in advertising campaigns

Specific ad campaigns are delivered to match each segment. This process makes the advertising more relevant for each segment and increasing the chance of engagement and boosting conversions.

Activating behavioral targeting

All of this behavioral data can be used across multiple campaigns and in different advertising channels. That’s the benefit of having a centralized place to store the data.

There are multiple ways to activate this data to create behavioral-based ad campaigns that deliver. Here are some examples of how to enable behavioral targeting to drive engagement and increase conversions.

Examples of behavioral targeting

Cross-selling and upselling

Knowing what your customers like and understanding how they interact with your business is a powerful way of knowing which additional products to promote to them. If you can link product A and B, then your audience that has shown interest in product A that are likely to engage with a campaign promoting product B.

Behavioral targeting in targeted email campaigns

That’s right, and behavioral targeted email campaigns doesn’t just sit in the world of programmatic media advertising. Creating personalized email campaigns based on how your audience is using your site or app is a great way to start.

Examples include targeting cart abandonment sessions, including viewed products in routine updates or directly linking content related to what your audiences have already read rather than generic content. Behavioral targeted email campaigns is a powerful way to increase email productivity and boost your targeting options.

Remarketing with behavioral targeting

An advantageous and accessible way of using behavioral targeting is to retarget. By identifying users that visit your site, you can reach them on other websites to encourage them to visit again and complete goals.

The most common solutions for this are facebook and google as they have simple to install tracking pixels that can understand users that visit specific pages on your site. You can then activate these segments directly in their platforms.

Location-based targeting

Location-based targeting is an excellent way of reaching audiences based on their real-world behavior. You can retarget audiences that have visited your physical stores, or a competitive store. This can also be applied to e-commerce and other online stores.

These targeting campaigns can be useful because the insights are related to how consumers behave in the real-world. This allows you to create compelling segments based on how people behave over time.