In recent years, personalized marketing has become a crucial investment for businesses to engage their customers. According to a survey, 72% of consumers say they only engage with personalized messaging, 80% of frequent shoppers only shop with brands that personalize the experience and 66% even said that encountering content that isn’t personalized would stop them from making a purchase.

Top brands are recognizing the power of personalized experiences. 51% of marketers assert that personalization across multiple touchpoints increased ROI by 300% and more. Marketers heavily rely on third-party cookies as the primary means of tracking and understanding consumer behavior.

However, with stringent privacy controls and cookies soon becoming obsolete, businesses must find new ways to deliver personalized marketing experiences that respect customers' privacy.

• Browsers like Safari and Firefox have already restricted third-party cookies, and Google has announced plans to eliminate them altogether.
• Apple's recent iOS14 update introduced the App Tracking Transparency feature, making it easier for users to opt out of sharing and tracking their data across various apps.
• Regulations like the California Consumer Privacy Act (CCPA) and the General Data Protection Regulation (GDPR), among others, will require ad platforms to obtain explicit user consent to collect, share, and utilize data generated from their digital interactions.

Although these moves are aimed to enhance user privacy by reducing cross-site tracking, it also limits the brands’ ability to meet consumer demands by delivering 1:1 tailored content and experiences. In this blog, we will discuss 5 strategies that will enable businesses to navigate the idea of a hyper-personalized future without cookies.

How to execute hyper personalized marketing without third party cookies?

First party data

According to a study by Adobe, first party data is becoming increasingly valuable to businesses in the post-cookie era. By collecting consumer data through opt-in forms, surveys, and other consent-based methods from websites, apps, and mobile browsers, organizations can capture an accurate and detailed view of the customer – a single source of truth.

Since data is gathered directly from the source, the company can maintain control over its quality and accuracy. It includes information such as contact details that customers provide when they sign up for a service, make a purchase, or create an account, data on user behavior, products or services sold, including transaction details, order history, and revenue generated.

These insights enable marketers to visualize the past, present, and future of the customer relationship with the brand and target audiences in an intuitive way.

Learn how to unlock customer intelligence with data.

Contextual advertising

Contextual advertising is a form of cookieless advertising that focuses on displaying advertisements based on the content and context of the web page or the online environment in which they appear, rather than relying on a user's past browsing history or personal information.

For example, if a web page discusses travel destinations, contextual ads might promote travel-related products or services. This approach can be effective because it delivers highly personalized messages to their target audience while respecting privacy concerns and data regulations. Here are some tips for effective advertisement:

• Choose highly relevant keywords related to your product or service to target the right audience within specific content contexts.
• Ensure that your ad content aligns seamlessly with the topic of the web page or app where it appears to enhance engagement and relevance.
• Continuously experiment with different ad variations to identify what resonates best with the context and generates the highest performance.
• Use tools to prevent your ads from showing up on pages with inappropriate or offensive content, protecting your brand's reputation.
• Regularly analyze performance data to refine your contextual advertising strategy, optimizing for better results over time.

According to a Global Industry Analysts report, the global contextual advertising market is projected to reach $335.1 billion by 2026.

AI and machine learning

AI and machine learning models help marketers navigate privacy regulations by reducing the reliance on intrusive tracking methods. These technologies can analyze large amounts of data accurately and provide deep understanding of audience's behavior and preferences, even without accessing individual user data.

For example, Google's Federated Learning of Cohorts (FLoC) employs machine learning algorithms to group individuals exhibiting similar browsing patterns into cohorts. Instead of tracking individual users and their online activities, FLoC focuses on identifying collective trends and interests. This approach respects data privacy of users while still allowing marketing teams to deliver tailored content and advertisements to these cohorts.

NLP-powered AI can also be used to identify the common problems and challenges that customers are facing. It provides insights into user sentiments and trends by analyzing text data, such as social media posts, reviews, and comments. Marketers can then use this information to create content that resonates with their audience.

Explore advanced personalization trends that will become norm in 2024.

Lookalike targeting

Lookalike targeting allows brands to expand their customer base using their current customer data, known as the seed audience. By studying this group of existing or interested customers, businesses find shared characteristics and traits. They then use this data to discover new customers and create marketing campaigns to target individuals who share these traits. This process utilizes various data sources such as:

• Customer data (e.g., purchase history, website behavior, demographics)
• Social media data (e.g., interests, likes, shares)
• Publicly available data (e.g., census data, government records)

By using this approach, businesses can allocate their advertising budgets more effectively, resulting in increased sales, improved customer acquisition cost, and ultimately, higher profitability.

User-generated content

Finally, user-generated content can be a powerful tool for creating personalized experiences that build long-term customer relationships. By encouraging customers to share their personal stories and experiences related to a brand's products or services, businesses can develop a sense of community and active engagement for their brand.

This can be particularly effective in a cookie-less world, where customers are often cautious about sharing their personal data. However, when they are invited to share their experiences with a brand, it's a different story.

Here are some tips for encouraging customers to share UGC:

• Make it easy for customers to share UGC. Add social sharing buttons to your website and product pages. You can also encourage customers to share photos and videos of themselves using your products or services on social media.
• Run contests and giveaways. This is a great way to incentivize customers to share UGC. For example, you could run a contest where customers can submit photos or videos of themselves using your products or services for a chance to win a prize.
• Feature UGC on your website and social media pages. When customers see that you are featuring their UGC, they are more likely to be encouraged to share more content.
• Respond to UGC. When customers share UGC, be sure to respond to it. This shows customers that you value their feedback and that you are paying attention to them.

Learn how to activate content personalization at scale with atomic content structures.

Conclusion

Personalization is here to stay, and while this era of cookie-less browsing and regulatory shifts present challenges, it also encourages brands to explore fresh, innovative ways to connect with their customers effectively - delivering the right content, at the right time, and with the right message. The key is prioritizing transparency and trust and using data to respect customers' privacy and preferences.

Businesses should focus on formulating a forward-looking web content personalization strategy for the coming years. As it is not a one-size-fits-all approach, it is important to experiment with different personalization techniques and technologies to identify the most effective strategies to adopt and expand upon in the future. This iterative approach will help them remain agile and responsive in an ever-evolving landscape.

As a digital customer experience company who has helped multiple businesses improve their digital customer experiences, we take a business-first approach with TTV. It is a path-to-revenue maturity model, enabling personalization, immediate gains, and then continued fine tuning. If you're ready to start your cookieless personalization journey, reach out to us today and unlock the potential of your brand with a customized marketing strategy.