Marketing has long been associated with consumer sentiments. Whether it is digital or conventional marketing, understanding consumer behavior and presenting a solution catered to their needs lies at the forefront of any marketing venture. In the era of digital marketing, personalized marketing has proven to be monumental in driving the growth of a business. And in this attempt at running personalized marketing campaigns, companies tend to rely on one key variable – Behavioral Targeting in Digital Marketing.

Digital marketing, as the name suggests, is based on online promotion of products to users who are present across those online platforms. Behavioral targeting leverages user behavior, their web usage patterns and their preferences to display advertisements of products or services that would be suitable for the end user. This enables personalized selling by showing the consumers the products or services they are most likely to be interested in. This helps increase the brand’s reach to the right audience, boosting engagement, conversion rates and overall customer experience.

This blog will cover the following topics:

1. What is Behavioral Targeting in Digital Marketing?
2. The Process of Behavioral Targeting
3. Types of Behavioral Targeting
4. Benefits of Targeting Based on User Behavior
5. Challenges in Behavioral Targeting
6. Best Practices in Implementation of Behavioral Targeting
7. Guide on How to Organize Your Audience
8. Conclusion
9. FAQs

Let us deep dive into each topic to learn more.

What is Behavioral Targeting in Digital Marketing?

Behavioral Targeting is a technique in digital marketing that involves understanding the end user and their interests. This is done by collecting the user’s data like their search history, preferences, likes and dislikes, purchase patterns and their interactions with ads. Once this data is gathered, a marketer uses this data to figure out the user’s interests and builds a user profile, based on which they show relevant ads to the user.

The ads thus shown to the user are based on their preferences and have a high chance of fulfilling their some kind of requirement, thereby delivering a personalized and tailored experience.

The Process of Behavioral Targeting

Behavioral targeting in digital marketing involves the following steps:

1. Collecting User Data:

This can be done using various tools based on the platform, like Google Analytics, Meta Pixel, etc. This data includes information like the user’s browsing patterns, search history, how long they stay on a page for, past purchases and what links they have clicked on or showed interest in. Many websites store this data in the form of cookies.

2. Segmentation:

Segmentation is a process that involves grouping like minded individuals together in different groups. This enables a marketer to show ads relevant to the right audience. For example, people who frequently travel overseas would be a relevant target for real estate advertisements, as they hold the investment capabilities. Thus, segmentation is a crucial aspect of behavioral targeting in digital marketing.

3. Showing the Ads:

This process involves displaying the ads to the relevant groups and analyzing their behavior towards the advertisements. This allows for a marketer to continuously boost their understanding of user preferences and achieve a stronger hand at personalization. Additionally, different websites employ different machine learning and artificial intelligence algorithms to analyze the behavior towards ads and evolve with time by incorporating the necessary changes.

Types of Behavioral Targeting

1. Website Behavior:

This type of behavioral targeting in digital marketing focuses on the customer’s behavior related to on-site activities. For example, if a person is surfing through an e-commerce store and showing interest in a certain category of products, the website can show more similar products to the customer. This can be furthered to the next step where the advertisements of those relevant products can be shown to the user on other websites when surfing through the web.

2. Purchase Behavior:

This type of behavioral targeting in digital marketing involves showing relevant ads to the user based on their past purchases. For example, if a user shows interest in traveling and has purchased travel related gear or equipment, a marketer can target this interest and show other travel related products advertisements to the user.

3. Email behavior:

This type of behavioral targeting in digital marketing focuses on the response of a user towards email based marketing campaigns. The behavior of users towards certain emails, whether they open the mail or not and how they interact with the data enclosed within the thread helps a marketer understand their preferences better and increase relevance in their campaigns further.

4. Content-Based Behavior:

With increasing content consumption among users, whether it is through social media or videos and blogs, content-based behavior has turned out to be a dramatic influence when it comes to behavioral targeting in digital marketing. Content consumed by a user gives deep insights into their preferences and these can be further analyzed to not just fulfill needs but also desires of a user when it comes to showing relevant ads. For example, if users shows interest in football related content, brands providing related merchandise can significantly gain popularity among such users.

Benefits of Targeting Based on User Behavior

1. Relevance:

Behavioral targeting in digital marketing based ads are designed on the user’s interests and therefore they are much more relevant than conventional marketing techniques. The user can better relate to these ads on a personal level as they fulfill a specific requirement of the user.

2. Improved Customer Experience:

Ads targeted based on user’s behavior not just show the relevant products or services to the user but also enhance their experience by removing irrelevant ads and preventing workflow disruption. The user thus appreciates the ads relevant to them and this enhances their overall experience.

3. Better Conversion Rates:

Since the ads are relevant to the consumer and target one of their interests or requirements, behaviorally targeted ads result in better conversion rates. Users are more likely to click on the ad and end up being involved with the brand.

4. Reduced Ad Expenditure:

Behavioral targeting in digital marketing helps create advertisements that result in better budget management since the marketer ends up spending less on irrelevant advertisements and narrows down their audience to specific users who are more likely to be interested in the product or service.

5. Better Remarketing:

Since behavioral targeting in digital marketing shows ads to the relevant audience, a marketer can analyze this output and understand the user preferences and how they evolve with time. This enables the marketer to target the relevant audience again when remarketing the product or service, thereby increasing advertisement turnover and improving the overall remarketing experience.

“Those who leverage consumer data in their marketing campaigns outperform their competitors by 85% in sales growth and more than 25% in gross margins.”

Challenges in Behavioral Targeting

Despite being an effective technique for running advertisements, behavioral targeting comes with some challenges of its own.

One major challenge in behavioral targeting in digital marketing is privacy concerns. Often, users are faced with the dilemma that their personal information is being tracked. Additionally, since behavioral targeting focuses on the user’s behavior, this can create doubts and questions in the minds of the user related to their privacy. This makes the user avoid such advertisements and also results in reporting. Moreover, it is also a big responsibility on a digital marketer to keep the user’s data private and in line with the data laws and guidelines.

Another major issue in behavioral targeting in digital marketing as faced by the user is ad fatigue. When a user is subjected to relevant ads repeatedly, this reduces their sensitivity toward the advertisements. This can result in lowered engagement over time. A marketer needs to be wary of evolving user preferences and thus change their advertisements from time to time.

According to Leadsquared, “74% of users believe there are way too many advertisements. For adults aged 35 and up, the percentage rises to 78. And 63% of users state that they tend to see the same ads multiple times.”

Lastly, behavioral targeting in digital marketing can also sometimes be inaccurate, in case the data collected is outdated or incorrect. This can lead to a waste of money and resources and affect customer experience, thereby being a challenge for both the marketer and the user.

Best Practices in Implementation of Behavioral Targeting

Implementing behavioral targeting in digital marketing for advertisements is a challenging and tricky concept, but when done rightly and in line with the data guidelines, it can provide excellent results. A few best practices that a marketer should follow for developing an implementation strategy are:

1. The first and foremost step should be to take user consent. This involves being transparent with the user by telling them what data of theirs will be tracked and taking permission from them to do so.
2. The second step is to effectively separate the relevant audience. This ensures that the ads reach the right people and minimum resources are used to provide the maximum output.
3. The last step in behavioral targeting in digital marketing is to effectively monitor the advertisements, test the creatives and make the necessary changes based on the advertisement analysis. Making necessary tweaks and changes and regularly conducting tests like A/B tests can help reduce ad fatigue, increase engagement and boost conversion rates.

Guide on How to Organize Your Audience

Marketers can organize their audience in two simple steps: Creation and Refinement

Creation involves creating a primary audience based on user behavior initially. It can be done by tracking the following data:

1. Types of pages visited
2. Length of visit sessions and bounce rate
3. CTR (Click-Through Rate)
4. Past purchase behavior
5. Browser history
6. Browsing patterns
7. Type of content they interact with
8. Frequency of visits
9. Type of ads they interact with
10. Emails opened and links clicked

Such data can provide strong insights into their interests and behavior.

The second step involves refinement. Marketers can use this data to further refine their audience and make sure their retargeting campaigns work better than the initial ones. This way they minimize the use of resources for maximum return on time and investment. Additionally, such insights in behavioral targeting in digital marketing can help a marketer further narrow down their audience in the following campaigns owing to the experience and insights they receive from user behaviors.

Conclusion

Behavioral targeting in digital marketing is an essential and life-changing tool that not only helps effective use of resources but also improves the customer experience, thereby being beneficial for both the marketer and the user. Conducting behavioral targeting rightly and in accordance with data protection guidelines can help achieve tremendous results over time, increasing engagement and conversion rates for the marketing campaigns. With increasing use of social media platforms and the large inclination of people towards content consumption, understanding their behaviors can bring significant benefits to a brand and its marketing endeavors.

Additionally, behavioral targeting in digital marketing is closely associated with machine learning and artificial intelligence algorithms, thereby being a highly relevant field in the near future. Overall, it can prove to be a differentiating factor between different marketing campaigns and help a marketer gain an edge over the competitors.

FAQs

Q1: How is behavioral targeting different from contextual targeting?

Ans: Behavioral targeting in digital marketing focuses on user behavior across the web and shows ads based on that behavior, whereas contextual targeting is based on the content of the website or page the user is viewing.

Q2: Is user consent necessary for behavioral targeting?

Ans: Yes, user behavior can only be tracked if the user gives the website permission to track it. Otherwise, it can raise legal concerns.

Q3: What are some commonly used tools for behavioral marketing?

Ans: The most commonly used tools are Google Analytics, Meta Pixel and retargeting tools like AdRoll.

Q4: How does behavioral targeting affect ROI?

Ans: Behavioral targeting in digital marketing reduces ad wastage by targeting only the relevant audience and providing better conversion rates, thereby enhancing ROI.

Q5: What is frequency capping?

Ans: Frequency capping helps to reduce the number of times the same ad is shown to a user, thereby reducing ad fatigue.

Q6: What is geolocation targeting in behavioral targeting?

Ans: Geolocation targeting involves showing ads relevant to a person’s location. This helps give local business a boost by showing ads to people nearby.

Q7: What kind of data is tracked for behavioral targeting?

Ans: User’s browsing patterns, search history, clicks on pages, time spent on a page, the type of content consumed or past purchases are some of the important attributes that are tracked for behavioral targeting.

Q8: Can behavioral targeting in digital marketing work on different devices?

Ans: Since all the devices are interlinked through the web and accounts, behavioral targeting works across all different devices in the same way.

Q9: Which type of businesses benefit the most from behavioral targeting?

Ans: Any business that can benefit from personalized recommendations can achieve great results with behavioral targeting. This is not industry specific and all businesses can reap its benefits.

Q10: What is the future of behavioral targeting in digital marketing?

Ans: In the future, behavioral targeting is likely to be enhanced with the use of artificial intelligence. But on the downside, with increasing strictness in data laws, it can face some restrictions over the long term.