While many factors contribute to the success of an ad campaign, one of the most crucial parts is communicating with the right audience. Conveying your message to the wrong people will likely undermine a digital marketer’s return on ad spend (ROAS).
More personalized marketing campaigns have traditionally gained more traction with buyers and, with data intelligence, it has become easier for publishers and marketers to adopt more targeted advertising. This is where behavioral targeting comes in.
Behavioral targeting uses data intelligence and advanced tracking systems to help display relevant ads to target audiences. Advertisers no longer need to plan hit-or-miss campaigns based on speculation as in traditional advertising, while publishers can ensure more relevant and therefore engaging user experiences for their visitors.
In this article, we guide you through the essentials of behavioral targeting, so you understand how it works and if it’s suitable for your advertising campaigns. Furthermore, as there’s a growing concern about privacy and the collection of private data, we also discuss how the process fits into the future of digital advertising.
What Is Behavioral Targeting?
Behavioral targeting is the process of identifying particular sets of customers based on their online activity, which helps advertisers place the right ads in front of the right users.
Behavioral targeting relies on information about a user's web browsing behavior, such as search history, web pages visited, clicks made, and website interaction, to identify which advertising to display.
For example, if you’re planning an ad campaign for your cosmetics brand it would make sense to target those people that frequently look for beauty products online as they’ll likely be the easiest audience to convert into customers.
Behavioral targeting ensures your advertising messages are delivered to this audience when they visit a website, regardless of said site’s content. Making your ads appear in front of those most likely-to-buy is a great way to drive your campaign in the right direction.
How Behavioral Targeting Works?
The behavioral targeting process involves collecting data, sorting it, and delivering customized marketing messages to individual users. Typically, behavioral targeting works in three steps.
Data Collection
User information is a critical element of behavioral marketing. Better data from the behavioral target market ensures more successful targeting campaigns. Therefore, the first step of the behavioral targeting process involves data collection.
In this step, data is collected from various sources, such as mobile apps, mobile device data, websites, third-party data providers, CRM systems, marketing surveys, etc. Since data comes from different sources, it can be collected in multiple ways.
For instance, websites use tracking pixels or cookies for consumer behavior tracking and apps on mobile devices track geographic locations through GPS. Such data is then stored on data management platforms (DMP) or advertising technology (adtech) platforms for marketing automation systems.
Segmentation
The second step involves data segmentation where users are sorted into various consumer groups based on the collected data. Using the aforementioned cosmetics brand campaign example, you can segment users into different categories according to what type of beauty product they are looking for.
People can be segmented into those looking for night creams and those in need of lipsticks. You will also group people based on those who have already purchased your product.
Targeting
Targeting is the third and final step of the process. In this step, the advertisers choose a specific group to target once the data is collected and users are segmented accordingly.
The primary aim of this step is to convey tailored advertising to the most relevant user. Successful behavioral targeting matches the interests and behavior of the visitors the next time they visit the website. It will ultimately help improve businesses’ conversion rate.
Types of Behavioral Targeting
Behavioral targeting is generally done within a particular website or across multiple websites and platforms and, as such, can be divided into two types: Onsite and network behavioral targeting.
Onsite Behavioral Targeting
Onsite behavioral targeting uses the behavioral targeting method within a particular site and focuses on providing a tailored online experience for users.
The site owner may display advertising and product suggestions to the users based on site-specific behavioral data. This strategy can make business sites more engaging to visitors, influencing them to spend more time there.
Onsite behavioral targeting analyzes data, such as frequently visited pages, what page your visitor is currently on, where your visitor is from, traffic source, how much time they spend on your website, and the type of device they used to visit your website to help create more personalized ad experiences for returning visitors. Personalized experience contributes to improved user engagement and ultimately leads to a better conversion rate.
Network Behavioral Targeting
Onsite behavioral targeting may not always provide sufficient data analysis. In that case, advertisers need to turn to the collection and sharing of data from multiple platforms — or network behavioral targeting.
Network-based targeting relies on user data recorded across multiple platforms.
This method collects online data through cookies and IP addresses and then sorts the users into distinct categories based on their data without tracking their personal information, such as name, address, and phone number. Algorithms can determine a user's age, gender, and potential purchasing choice.
Why is Behavioral Data Important?
Understanding customer behavior is a tried and tested method for advertisers. It helps them understand their customers' buying patterns and then create improved marketing strategies.
Identifying the ideal customer’s behavior can play a crucial role in improving conversions, engagement, and retention.
Behavioral data can play a vital role in your organizational growth and its long-term relationship with the customers. Once you have access to your client’s data, you have answers to so many questions that go beyond how a consumer interacts with your business. With behavioral data, you can:
Glean Better Customer Insights
Behavioral data provides you with in-depth information about your customers, allowing you to better understand them as well as their pain points, motivation, and beliefs.
Understanding clients on an individual level means you can create customized ads for them. When you know what they are looking for, it can revolutionize how you plan your marketing campaigns and the way you interact with them.
Make Informed Marketing Decisions
By using the power of data to anticipate each person's preferences and intentions, you can make accurate forecasts based on your customer’s individual purchasing behaviors.
For instance, you can forecast the segment that will most likely buy your beauty products with behavioral data. That way, you can add the segment to a targeted campaign for your product.
Take Effective Actions
As a marketer or a business owner, being assured of conveying your messages to your targeted customers is already an impressive achievement. Nevertheless, the importance of behavioral data is beyond that. Behavioral data helps you to take the right action when needed.
Behavioral data also helps you to forecast future activities by anticipating the wants and needs of your customers. With this, you can plan effective long-term marketing strategies.
With the data you have at your disposal, you can also serve your customers at the next level by identifying and solving their problems. After all, modern customers prefer doing business with companies that value them (PDF download).
Benefits of Behavioral Targeting
From delivering ads more effectively to easing users’ online buying process, online behavioral advertising offers many perks to both advertisers and consumers. Some of these benefits include:
Better User Engagement
Behavioral data informs advertisers on the marketing materials customers engage with more often. It helps marketers create and deliver personalized ads to online users, contributing to better engagement.
Increased Ad Click-Through Rates
Users interested in personalized ads are more likely to click for additional information. According to a recent study by Emerald Publishing, behavioral advertising has much higher click-through rates (CTRs) than non-targeted advertising.
Improved Conversion Rates
By design, behavioral advertising displays targeted ads that resonate with individuals. For instance, displaying a night cream ad to someone who has been searching for it online means they’re more likely to click the ad. This improves the chances of a successful conversion.
A More Efficient Buying Process for Users
Online behavioral advertising can help guide consumers by simplifying the buying process.
Because ads are delivered based on a user’s online activity, these ads may present a more convenient purchasing route than using search engines to search for a good or service. This is an even more attractive option for time-poor consumers.
Disadvantages of Behavioral Targeting
Though it helps create more effective ad campaigns, behavioral advertising has been a subject of criticism, especially in terms of how data is collected.
With the growing concern over data privacy, behavioral advertising has been at the center of public discussion for a number of years. Some of the commonly cited problems of behavioral advertising include:
Privacy Concerns
Although behavioral advertising delivers highly personalized ads, the way it collects private data has concerned some people. This has led to a growing argument that the privacy of individuals is being violated.
As a result, more people are installing ad-blocking software to prevent cookies from collecting personal data.
Fear of Data Exploitation
The collection of personal data on a major scale may lead to many possible risks, such as security breaches or the large-scale trade of private data.
Therefore, behavioral advertising’s approach to personal data collection has stoked global cybersecurity concerns.
With Cookies Ending, What Does the Future Hold for Behavioral Targeting?
With Safari and Firefox already blocking third-party cookies and Chrome planning to follow soon, the future of behavioral tracking—and online advertising as a whole—is set for a major disruption.
For many years, tracking cookies, and the data they collected, have helped advertisers create personalized ad campaigns for their audience. But with cookies on the verge of retiring in the face of growing public pressure, the question is: How will the digital marketing industry cope with this change?
Google has been working on its open-source Privacy Sandbox initiative since 2019 to address this very issue and, after having first tested the Federated Learning of Cohorts (FLoC), the search giant is now exploring the Topics application programming interface (API).
FLoC was developed as a means of grouping web users into groups based on each individual browsing activity. This would both protect an individual’s privacy while also giving publishers and advertisers a means to conduct targeted advertising.
Development on FLoC has ended and Google is now working on Topics, which it unveiled in January 2022. The new proposal will see Chrome determine a handful of topics based on your past week’s browsing, with those topics kept for three weeks before being discarded and new ones selected. The topics remain on your local computer and will not be processed by a server.
Topics, which is supposed to be an opt-out setting in Chrome, is just one strategy currently under development to help with the end of tracking cookies. Publishers might also consider targeted email campaigns, reviving traditional questionnaire forms, or adopting marketing alternatives such as contextual advertising.
Will Contextual Targeting Replace Behavioral Targeting?
Third-party cookies are on their way out. Therefore, it’s probably time to think about implementing a different ad strategy for the future if your ad campaigns rely on third-party data.
The comparison between contextual and behavioral targeting has been a subject of discussion among marketers for a long time. But as we move into a cookie-less future, contextual targeting will likely have an upper hand.
So, will it replace behavioral targeting? It just might.
What is Contextual Targeting?
Contextual targeting refers to placing an advert on a website based on its content. In this method, the ad’s content is closely related to that of the website.
Returning once more to the cosmetics brand example, contextual advertising would allow you to place your advert on healthcare sites or beauty blogs. Search engines also use this approach to display adverts on their result pages by matching the search query's keywords to the ad's content.
Instead of leveraging user data that has been collected and analyzed over time, contextual targeting uses session data to evaluate user interests. This form of targeting addresses privacy concerns and regulations since it uses data generated from in the moment user activity rather than historical behaviors.
Contextual Targeting’s Benefits
No Need for Personal Information
Since contextual targeting relies on keywords and other factors rather than a user’s personal information, it doesn’t require cookies or a user’s personal information to place ads of relevant products. This means that publishing an advert is more efficient and compliant with privacy regulations such as the EU’s General Data Protection Regulation.
Easier and More Efficient Implementation
Contextual advertising doesn’t require a vast amount of user data. Therefore, it’s easier to implement than behavioral targeting.
Furthermore, you don’t need a whole team or advanced tools to publish your ad with this method, potentially saving you time and money.
Contextual Data Can Be More Effective
With technology advancements, consumers now shop at a faster pace and their past behavior may not always indicate present needs.
Additionally, external factors, such as weather and events, also influence a buyer’s purchasing decisions. In these scenarios, contextual ads can be much more effective than behavioral targeting.
Advanced AI Can Make a Difference
AI is smarter than ever before and, in terms of contextual targeting, it can now effectively analyze page content and place your ad in front of target audiences.
AI has help to improve conversational marketing, thereby allowing marketers to understand clients' requirements on a deeper level. This, in turn, can support the development of more accurate trend forecasting.
Furthermore, as chatbots continue to evolve they can be expected to eventually provide a complete end-to-end customer service.
AI has also effectively eliminated the manual work involved in collecting data and segmenting audiences based on their past activities.
Final Thoughts
Over the years, behavioral targeting has been an effective method for conveying a brand's messages to the right audience in the digital world. However, the death of third-party cookies is set to transform the digital advertising landscape.
Both marketers and publishers should be looking to incorporate alternative ways to deliver relevant ads to potential customers.
Automation has made it easier than ever to make marketing forecasts and informed marketing decisions. That might be one of the reasons why more advertisers are planning to incorporate contextual advertising in future campaigns.
It may be the perfect time for you to shift to a new method of advertising that doesn’t rely on personal data.
Publift helps digital publishers get the most out of the ads on their websites. Publift has helped its clients realize an average 55% uplift in ad revenue since 2015, through the use of cutting-edge programmatic advertising technology paired with impartial and ethical guidance.
If you’re making more than $2,000 in monthly ad revenue, contact us today to learn more about how Publift can help increase your ad revenue and best optimize the ad space available on your website or app.