Personalization has always been on every marketer’s to-do list.
But in today’s fiercely competitive environment, simply keeping it on the list is no longer an option – it’s time to start actively using the information that you have to cater to your audience’s individual needs.
With every click, search, and purchase internet users make online, they leave behind a wealth of data and insights. This data can be used to personalize digital advertising campaigns and create more relevant and engaging experiences for specific audience segments.
This is also known as behavioral targeting.
In this post, you’ll learn what it is, why you should use behavioral targeting, how it differs from similar targeting options, and more – let’s dive in.
Behavioral targeting is a digital technique used by advertisers and marketers to deliver personalized content to their target audiences based on their online activities.
In other words, behavioral targeting considers what a user does (and doesn’t do) while browsing and enables advertisers to use this information to deliver targeted messages that resonate with the user’s interests and needs.
The primary purpose of behavioral targeting is to reach relevant users based on their interests, therefore, achieving higher engagement rates, increasing conversions, and boosting overall business growth.
“Online activities” is a very broad term; for some, it can be difficult to grasp the scope of the data being collected for behavioral targeting.
Does it include checking in at a cafe? Making a purchase on Etsy? Visiting an online pet store? And where is all this data stored?
First things first, there is no universal way to gather behavioral data. You can use multiple sources like mobile apps, CRM systems, websites, DMP (which is one of the most common ways to collect, organize, and store information for advertisers), and so on.
Whichever one you use, the data collected for behavior targeting can include the following:
It doesn’t mean advertisers collect or use ALL of this data, though. Sometimes it’s best to focus on specific data points only, and sometimes what works best is a combination of them.
Through practice, you will quickly start to understand what suits your brand best.
You already know that the core of behavioral targeting is data collection and what information is used for targeting.
But how does building a user profile based on their interests and preferences typically looks from opening a browser/app to receiving a targeted ad?
A profile that includes user interests, preferences, and online behavior is created based on the information collected. Such profiles are then clustered into user segments by behavior and stored in a database to be used for serving targeted ads.
Advertisers use these clustered segments to deliver ads that are more likely to resonate with specific users. For example, if you’ve been searching for tennis rackets online, you may start seeing ads from sports shops or other related products.
Over time, you’ll be able to measure the effectiveness of your ads and adjust the types of ads shown, their frequency, the channels you use to reach your target audience, and so on.
From everything we already know, it’s clear that to use behavioral targeting, advertisers need to categorize their audience into specific groups, which we also call audience segments, based on particular factors.
This way, as an advertiser, you can start delivering tailored messages and campaigns that resonate with the audience's unique needs and preferences – or, in other words, personalize – and do it with confidence, relying on data, not guesses.
What data plays the biggest role in this, and what are some of the most common types of behavioral segmentation?
Behavioral targeting is crucial for driving personalized ads as it tracks and analyzes consumers’ online behaviors and uses the information acquired to increase relevancy.
Personalization itself has always been important for any marketing efforts, although in the last few years, due to the global pandemic and shifts in consumer behavior, providing exceptional experiences became a must for standing out from the competition.
Here are some numbers to prove it:
All in all, behavioral targeting is the main tool for achieving the level of personalization that can positively impact your business, allowing companies to gather data and deliver ads for specific interests and needs.
There are two ways to do behavioral targeting, which are:
One of the key differences between these two is where and how the data is collected.
Onsite behavioral targeting focuses on collecting data about user behavior on a particular website or app. It involves such actions as pages viewed, products searched, time spent on the page, and similar.
The collected data can then be used to understand what users are interested in, what they prefer, and identify some behavior patterns. Then, this information can be used to deliver targeted content or offers to that user when they return to that site/app.
For example, if a user spends their time on the website looking for a new sweater, next time, they may see targeted ads or recommended products related to sweaters.
As opposed to onsite behavioral targeting, network behavioral targeting focuses on collecting data about a user’s behavior across multiple websites. Often, it helps to gather additional data and create a clearer image of the audience.
Actions involved in network behavioral targeting can vary from websites they visit and pages they view to searches made or content they interacted with.
The collected data is then used to create user segments and deliver targeted advertising on various websites.
For instance, if a user frequently visits cooking-related websites, they may be shown ads for kitchen gadgets on other websites they visit.
Behavioral targeting sometimes gets mixed with contextual targeting, as they both serve highly relevant ads to particular audiences. However, these two are not the same thing.
While using behavioral targeting, you can create and deliver ads based on the previous website visitor's behavior. With contextual targeting, the focus shifts to the website’s content.
For example, behavioral targeting allows you to deliver ads to people who recently showed interest in buying a lawn mower for their gardens. Meanwhile, using contextual targeting, your ads would appear on gardening-related websites, be visible to everyone who is looking for this kind of content and is more likely to find lawn mowers ads relevant.
Put simply, behavioral targeting involves specific user information and relies solely on user data; contextual targeting relies on the page’s content and doesn’t require any user data.
Amazon is one of the best examples to illustrate behavioral targeting. The Everything Store uses the collected data to display several different sections of offers, and personalized recommendations actually make up a significant portion of Amazon’s revenue.
To get you inspired, here are some ways how Amazon uses its recommendation machine:
User data on the internet is a sensitive topic and can raise many questions and concerns about privacy and data protection. These concerns are not always wrong, as there are both ethical and unethical ways to approach customer behavior tracking.
However, privacy topic isn’t an untamed area, and to address these concerns, various laws and regulations protect user privacy and data security.
For example, in the European Union, the General Data Protection Regulation (GDPR) requires companies to obtain consent from individuals before collecting and using their personal data. Similarly, the Federal Trade Commission Act (FTC Act) or Children’s Online Privacy Protection Act (COPPA) protects the privacy and security of user data in the US (different states might also put local privacy acts in place, e.g., California Privacy Rights Act).
So while behavioral tracking is regulated by law, works with user consent, and technically isn’t unethical, it is essential for brands to use it responsibly and transparently. Or in other words, find the right balance between the benefits of this targeting option, ethical concerns, and legal requirements surrounding the collection and usage of user data.
Behavioral data is becoming much more controlled and much less available for a few reasons:
Behavioral targeting is still something brands use a lot as it enables them to tailor their advertising campaigns to specific user behavior. Its effectiveness has been proven by companies of all sizes, and it continues to be a go-to choice for delivering highly relevant ads, at least for now.
It’s vital to remain (or become) transparent about user data collection and usage to gain users’ trust and avoid raising privacy concerns. It will most definitely pay off as by analyzing user behavior and preferences, advertisers can deliver targeted ads to consumers, resulting in better engagement and improved ROI.