Personalized marketing in a cookieless era: Proven tactics and strategies

Your audience doesn’t hate ads. They hate irrelevant and spammy ads. Imagine seeing the same T-shirt on every social media after you’ve already made a purchase. Or seeing ads for things that you don’t care about over and over again.

You can avoid wasting money and bothering your audience by using data strategically to create personalized customer experiences. In this article, we’ll discuss how you can achieve personalization even without third-party cookies.

How the decline of third-party cookies affects personalized marketing

Personalization used to largely depend on third-party cookies. Marketers tracked user behavior across the web and then served tailored messages wherever those users roamed. However, the cookie-based model is becoming shaky.

Major browsers like Chrome, Safari, and Firefox are now limiting, phasing them out, or sometimes they constantly change strategies like Google’s U-turn on 3rd-party cookies. Coupled with regulations like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), the “follow the user around the internet” model is not as reliable. Other factors include:

• Reduced cross-site tracking means marketers can no longer rely on aggregated data from multiple web domains, forcing them to find new ways to understand their audience.

Privacy awareness: Consumers are aware—and wary—of how brands collect data. Building trust now means showing you respect their choices and aren’t prying into unnecessary details.

Pro tip: Focus on ethically sourced, user-consented data, such as first-party data from your channels and zero-party data users willingly provide. This strategy respects privacy and typically yields more accurate insights.

Of course, this topic of third-party data goes beyond this, so if you want to learn even more, check out our third-party cookies comprehensive guide to learn what’s fact and fiction.

The impact of AI on data personalization

Recent studies (McKinsey & Company) show that quickly growing companies see 40% more revenue from personalization than slower-growing peers. Part of this growth includes using artificial intelligence for large-scale content creation and real-time decision-making in response to customer signals.Meanwhile, IBM found that going beyond basic segmentation to deliver predictive, user-specific offerings with AI can boost average revenue per user by 166%.

By crunching vast data sets, AI can identify subtle patterns, interests, or browsing behaviors that help you create micro-targeted experiences. Additionally, it offers:

• Hyper-personalization: AI can craft messaging unique to users' tastes, spending habits, or daily schedules. This goes beyond, say, offering a broad discount to “all new visitors.”
• Smarter automation: AI-driven marketing automation doesn’t just handle email sequences; it can also test messaging variations in real-time, adjusting campaigns based on immediate feedback.

Still, a recent BCG survey shows that 85% of global C-suite executives plan to increase AI spending, yet a significant portion is allocated to cost-saving measures rather than personalization. This approach is flawed.

According to the Harvard Business Review, personalization will emerge as the most thrilling and lucrative benefit of the upcoming AI boom—but only for those companies that prioritize it strategically.

Creative and practical ways brands are using personalization

You probably know about Netflix’s recommended shows or Amazon’s “Frequently Bought Together” features, but personalization can go far beyond these staples. Below are some creative approaches that stand out:

• Coca-Cola’s ‘Share a Coke’
  • What they did: Print common first names on soda bottles, turning each drink into a personal souvenir or a thoughtful gift.
  • Why it worked: By inviting people to “find their name,” Coca-Cola tapped into a sense of identity and community. The campaign generated user-generated content (UGC) on social media, as consumers happily shared photos of bottles bearing their names or friends’ names. This sense of belonging drove organic brand advocacy.
• Spotify’s “Wrapped” annual recap
  • What they did: At the end of each year, Spotify compiles user listening data into a playful, personalized summary called Spotify Wrapped. It reveals users’ top artists, songs, albums, and podcasts for the year and lets them share the results on social media.
  • Why it worked: The campaign turns raw user behavior into a highly shareable story. By tapping into personal data—like favorite genres and total minutes listened—Spotify generates buzz on social channels, making listeners feel proud to showcase “their” music identity. The exclusivity and year-end timing also foster an emotional connection, prompting users to celebrate their musical journey and, in turn, offering massive organic reach for Spotify. The success of Wrapped has even inspired other companies to create their own “annual recap” experiences for customers.
• Apple’s personalized landing pages
  • What they did: Detected your past browsing behavior—like checking out fitness gear—and presented related products (e.g., Apple Watch, workout accessories) on subsequent visits.
  • Why it worked: Apple made shopping feel intuitive. Apple reduced friction in the buyer's journey by guiding users directly to items that match previous interests. This approach respects user choice while gently nudging them toward relevant products.
• Insomnia Cookies’ post-purchase check-ins
  • What they did: After your first cookie order, Insomnia follows up with witty messages to remind you where you can satisfy your next craving.
  • Why it worked: The personalization is timely (catching you soon after enjoyment) and comedic (matching Insomnia’s playful brand tone). This approach extends the customer relationship beyond one purchase, nurturing higher repeat sales.
• Poly & Bark’s room designer
  • What they did: Displayed complementary furniture and decor items for customers viewing a specific piece, helping them “complete the look.”
  • Why it worked: Poly & Bark tapped into the user’s desire for a cohesive aesthetic. Customers felt guided—not pushed—toward other items that fit their style. This boosted the average order value and enhanced the shopping experience.
• YouTube’s music tailoring
  • What they did: Analyzed watch and search histories to offer mood-based or theme-based playlists, going beyond generic “Top Charts” recommendations.
  • Why it worked: By serving up playlists aligned with times of day, musical tastes, or user locations, YouTube Music created hyper-relevant listening sessions. Users felt the platform “understood” their personal context, increasing time spent in-app and loyalty to YouTube.

What’s the lesson? Each example respects the user’s context, whether it’s their name, music preferences, or home decor tastes, and transforms that insight into a meaningful experience. Coupled with a strong first-party data strategy, these tactics deliver higher engagement, greater trust, and more sales.

Tools and technologies to simplify personalization

Many marketers are worried about how privacy laws and the phase-out of third-party cookies will impact their ability to create personalized experiences. According to our 2025 Marketing Data Report, 43% worry about accurate audience building.

Tools and techniques exist to help you gather—and safeguard—reliable user data in ways that let you deliver personalized experiences without infringing on privacy. Here are four key areas to consider:

1) First-party and zero-party data

What it is: First-party data is information collected directly from your websites, apps, and CRM systems. Zero-party data goes a step further—your customers voluntarily share it, such as preferences or quiz answers.

Why it matters: These data types provide accurate insights into your audience without relying on external providers. This approach also helps you create personalized campaigns based on real interests or explicit user consent, powering strategies like segmented emails or Spotify-like year-end recaps.

Practical tip: After collecting first- or zero-party data, ensure it’s high-quality and well-governed. That data can power personalizations across channels, from curated email content to dynamic onsite recommendations. For more on data strategies, read our guides on first-party data strategy and zero-party data.

CTA: https://supermetrics.com/platform/custom-data-import

2) Contextual advertising

What it is: Contextual advertising places ads on pages where the content matches your product, rather than relying on user-based cookies or profiling. For instance, a hiking gear ad might appear on an outdoor travel blog.

Why it matters: With heightened privacy concerns and the decline of third-party cookies, contextual advertising offers a compliant alternative. You tailor ads to a page’s context, giving readers relevant promotions without intrusive user tracking.

Contextual advertising is especially effective in industries like healthcare, finance, or travel—areas with plenty of niche content. It fosters brand safety and can lower costs by focusing on editorial alignment instead of expensive user data.

Practical tip: Review your site’s or partner sites’ content categories to see how to place ads natively. This method also enhances user experience, since they see ads tied directly to the page topic, not random retargeting.

3) Server-side tracking

What it is: Instead of relying on user browsers for data (which can be blocked or expire quickly), server-side tracking collects info in your server environment. That means you decide how much data to share with external partners.

Why it matters: Server-side tracking helps remedy reduced targeting effectiveness as cookies fade by securing more accurate data and bypassing some browser restrictions. With fewer third-party cookies in play, properly implementing server-side tracking can help maintain audience insights. This is particularly helpful for eCommerce sites that must keep retargeting robust and consistent.

Practical tip: Although more technical, server-side setups are a game-changer for data continuity. They give you direct control over how data is collected and shared, limiting the signal loss that can happen with client-side scripts.

4) Conversions API

What it is: A secure channel that lets you transmit conversion data directly from your systems—like CRM or server logs—to marketing platforms. For instance, connecting your CRM to Meta or Google ensures these platforms have accurate event data without relying on cookies.

Why it matters: With Conversions API, you can build robust custom audiences, run more accurate lookalike campaigns, and track offline conversions. This approach keeps your data under tighter control and reduces concerns about partial data or inaccurate audience building.

Practical tip: Ensure user permission and compliance structures are in place. If you’re sending CRM data, you need the proper rights. When used responsibly, the CAPI can lift ad performance while respecting privacy.

CTA:

Explore the 2025 Marketing Data Report

Discover key insights from hundreds of marketers in the 2025 Marketing Data Report. Learn how top marketing teams adapt to a privacy-first world—and how you can do the same.

Best practices for personalization in marketing

To get the most out of personalized marketing, keep these best practices in mind:

• Set clear goals and objectives: Know what success looks like—whether it’s boosting conversions by 10% or cutting cart abandonment in half. Without clear KPIs, your personalization efforts may wander aimlessly.
• Segment your audience: Go beyond demographic data. Segment by behavior, purchase history, or engagement level. The more precise your segments, the more relevant your messaging becomes.
• Establish baseline metrics: Before launching personalization, gather baseline data on current conversion rates, site traffic, or average order value. Measuring improvements is only meaningful if you know where you started.
• Create tailored content for each segment: Don’t just rename the subject line. Adjust offers, landing pages, and product recommendations to resonate with each group’s pain points and aspirations.
• Test and optimize: Even the best personalization strategy needs iteration. A/B tests different messages, design variations, or CTA placements. Double down on what works and pivot quickly from what doesn’t.

Deliver the right message to the right audience

Personalization has always been central to effective marketing—finding the right message for the right people at precisely the right time. With the phase-out of third-party cookies, first-party and zero-party data remain reliable, privacy-friendly ways to deliver meaningful, relevant experiences.

That said, personalization requires more than data. You’ll need clear goals, strong data management, the right marketing automation tools, and ongoing performance checks to refine your tactics. When you strike this balance, you’ll see higher conversions, deeper customer loyalty, and a measurable impact on your bottom line.