Brands are increasingly focused on offering personalized experiences while respecting consumer privacy. Addressability enables them to reach specific audiences with relevant messages, and personalization crafts unique content that aligns with each audience’s interests and needs. By combining these strategies, brands can create more relevant and effective marketing campaigns.
With new regulations and signal loss reshaping the landscape, alternative identifiers like the ID5 ID and The Trade Desk’s Unified I.D. 2.0 (UID2) are gaining importance. These tools give advertisers a more holistic view of consumers across channels, enhancing personalization and addressability even as traditional third-party cookies lose relevance.
To shed light on this topic, we interviewed experts from Audigent, Basis Technologies, CvE, ID5, MiQ and others. They shared insights on navigating privacy, utilizing new identifiers, and enhancing personalization with consent. Drawing from their perspectives, we’ve identified five considerations to help brands adapt and succeed in this evolving landscape.
1. Embrace a privacy-centric approach
With the increasing focus on consumer data protection, prioritizing privacy in your addressability efforts is essential. Implement strict data guidelines to protect personally identifiable information (PII) and maintain compliance with state-specific regulations.
To achieve this, empower consumers by providing clear and transparent choices about data sharing and honoring their preferences. Avoid targeting based on protected categories or sensitive information. By adopting a privacy-first mindset, you can build consumer trust while still delivering relevant advertising experiences.
“It’s important to champion consumer privacy and the free internet. We need to strike a balance between the two. This balance is essential for our jobs, the economy, news, politics, and all the valuable content and information we rely on.”
Drew Stein, Audigent
2. Personalize with consent
Consumers are more willing to share their information when they see clear benefits. In fact, over half of shoppers—and two-thirds of Gen X and Millennials—express a desire to receive holiday shopping deals directly from their preferred brands1. By offering value through loyalty programs, special offers, or interactive platforms, you can personalize experiences without compromising privacy.
To implement this strategy, encourage consumers to share their preferences and needs by being transparent and giving them control over their data. This approach builds trust, empowers your audience, and enhances personalization.
“Building personalization based on the data consumers have consented to share should lead to a positive experience that drives better engagement because it’s relevant to them.”
April Weeks, Basis Technologies
3. Personalize with contextual targeting
Contextual targeting involves delivering ads based on the content users are currently engaging with rather than user identifiers. By focusing on personalization through contextual targeting and dynamic content, you can align your strategies with your audience’s real needs and interests. This approach allows advertisers to reach consumers on websites with more visitors matching the demographics, behaviors, or interests they want to target.
“Personalization absolutely can thrive. We have various solutions, all utilizing IDs for targeting and personalization. Beyond that, we can also personalize using context, geo-contextual data, and creative strategies.”
Georgiana Haig, MiQ
4. Use alternative identifiers
As advertisers move beyond third-party cookies, exploring alternative identifiers offers reliable means to connect with consumers. Options like email addresses or device IDs provide direct connections, improving targeting accuracy.
Utilize identity graphs to link different signals and identifiers to establish strong ties to individual users or households. This approach maintains, and can even enhance, your ability to reach the right audience and measure campaign performance.
“It’s not just about maintaining addressability. It’s about massively improving addressability. When we run tests with some of our clients, they’re seeing 30, 40, 50, 60% incremental reach by using ID5 versus cookies.”
Mathieu Roche, ID5
5. Build partnerships
Navigating the complexities of addressability doesn’t have to be a solo effort. Partnerships between brands, publishers, and tech providers can lead to innovative solutions that benefit everyone.
Consider engaging in data partnerships to access new audience segments without maintaining extensive data. Collaborations focused on your tech stack can enhance your ability to deliver personalized content effectively and at scale.
“The rise of second-party data partnerships is going to be an interesting trend over the next couple of years. And if you need mass scale across the world, I think that’s a much more cost effective and scalable way to do it.”
Paul Frampton, CvE
Steering toward success
The future of addressability and personalization hinges on your ability to adapt to the changing privacy landscape while delivering meaningful, personalized experiences. By focusing on these five key considerations, you can navigate the complexities of modern advertising, build stronger relationships with consumers, and drive sustainable growth.
Footnote
- Online survey conducted in June, 2024 among n=1,000 U.S. adults 18+. Sample balanced to look like the general population on key demographics (age, gender, household income, ethnicity, and region).
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Published in AdExchanger. “Data-Driven Thinking" is written by members of the media community and contains fresh ideas on the digital revolution in media. Today’s column is written by Tom Manvydas, vice president of advertising strategy and solutions at Experian Marketing Services. The proliferation of connected electronics has spurred new interest in device-recognition technologies even though they have been in use since the 1990s. As we enter the “Internet of Things” era, device recognition will significantly impact the ad tech ecosystem. Many network advertising technologies are becoming obsolete as cookie blocking grows and the Internet becomes more mobile and device-centric. Device recognition will be yet another technology challenge for marketers but has the potential to overcome many key tracking, measurement and privacy issues with which data-driven marketers have struggled. By leveraging device recognition technologies, marketers can protect their investments in Web 2.0 ad tech, like multitouch attribution, and improve their overall digital marketing programs. Device Recognition Vs. Cookies Device recognition attempts to assign uniqueness to connected devices. By focusing on the device, you are able to “bridge” between browsers and apps, desktop to mobile and across OS platforms like iOS and Android. Device-recognition IDs function like desktop cookies for devices but with four important differences: 1. Coverage: Device-recognition methods are largely immune from cookie limitations. About half of mobile engagements on the Web do not involve cookies, while third-party blocking impacts up to 40% of desktop engagements. 2. Persistency: Device-recognition IDs can be more persistent and less fragmented than most desktop cookies. For example, Apple’s UDID or Android ID are permanent, and network node IDs like MAC addresses are near-permanent. Proxy IDs such as IDFA are persistent but can be updated by the device owner or ID provider. 3. Uniqueness: Devices are unique and cookies are fragmented. The digital media industry incurs substantial overhead cost and loss of efficiency when dealing with fragmented profiles and obsolete data caused by cookie churn. However, device-recognition methods are limited in their ability to recognize multiple profiles on shared devices. 4. Universality: Device-recognition technologies are universal and generally work across devices and networks. However, interoperability issues across device operating systems, such as iOS and Android, can limit the universal concept. There are many types of device-recognition technologies but two basic approaches to device recognition: deterministic and probabilistic, each with their pros and cons. Deterministic Approach: Accurate And Persistent But Complicated Deterministic device recognition primarily uses the collection of various IDs. While the mobile developer is familiar with the variety of IDs, it’s important that marketers become better-versed in this area. Examples include hardware IDs (including serial numbers), software-based device IDs (such as Apple’s UDID or the Android ID), digital data packet postal codes or proxy IDs (such as MAC addresses for WiFi or Bluetooth, IDFA for both iOS and Android and open-source IDs). Deterministic methods improve the accuracy of tracking, targeting and measurement over current cookie-based methods. They can improve the ability to more persistently manage consumer opt-outs. But the proliferation of device types limits the universality of deterministic device recognition. Without uniform standards across platforms, marketers need to account for multiple ID types. Also, deterministic device-recognition methods are not well developed for desktop marketing applications. The lack of interoperability across deterministic device IDs makes execution too complicated. Deterministic device IDs were meant for well-intentioned uses, such as tracking the carrier billing for a device. However, they present privacy and data rights challenges, leading to blocking or limited access by companies that control IDs. Probabilistic Device Recognition: A ‘Goldilocks’ Solution Probabilistic device recognition may be the ideal solution for a connected world that does not rely on cookies nor wants to use overly intrusive deterministic device recognition. Probabilistic device recognition is not a replacement for deterministic IDs. Instead, it complements their function and provides coverage when they are not available. The probabilistic approach is based on a statistical probability of uniqueness for any single device profile. This approach creates a unique profile based on a large number of common parameters, such as screen resolution, device type and operating system. This process can uniquely identify a device profile with 60% to 90% accuracy, compared to 20% to 85% accuracy for cookie-based identification methods. Probabilistic IDs are more persistent than cookies with better coverage, but less persistent than deterministic device IDs. The natural evolution of the device takes place over time and prevents persistent identification. Probabilistic device recognition can be universal and is not impacted by interoperability issues across platforms — the technology used to generate a probabilistic ID on one network can be the same technology on another network. Unlike some deterministic device recognition approaches, there is no device fingerprinting. Probabilistic device recognition accurately identifies profiles in aggregate, rather than a single device. That’s the inherent beauty of probabilistic device recognition: It can generate more accurate targeting results than cookie-based methods without explicitly identifying single devices. This is more than good enough for most marketers and significantly better than what’s available today. Another benefit is the absence of any residue on the device — no cookie files, flash files or hidden markers. Probabilistic methods can work on devices that block third-party cookies or connect to the Web without using any cookies. For example, you might have a hard-to-reach but valuable audience segment. Probabilistic device recognition could effectively increase your reach on this segment by 40% to 50% and increase the overall targeting accuracy by two times. Let’s say the actual population for this segment is 100,000 members. The typical cookie-based approach might reach 28,000 members but the typical probabilistic device-recognition approach could reach 65,000 members. A Decline In Hardware Entropy If you take a close look at the emitted data from today’s devices, it is not easy to analyze it for device identification. That’s because the data footprint of one device looks a lot like another. Device recognition augmentation methods can address this, such as device usage profiles, geo location clustering, cross-device/screen analytics or ID linkage for first-party data owners. In the short term, device-recognition technologies, particularly probabilistic methods, can greatly improve today’s digital marketing programs. Marketers should become fluent in their use cases and benefits. If 2013 was the year of mobile, I think we’ll see a surge in marketing applications based on device-recognition technologies in 2014. Follow Experian Marketing Services (@ExperianMkt) and AdExchanger (@adexchanger) on Twitter.
According to Experian Marketing Services’ 2014 Digital Marketer: Benchmark and Trend Report, social media Websites are playing an increasingly important role in driving traffic to other Websites, including retail sites and even other social networking sites, at the expense of search engines and portal pages. For instance, as of March 2014, social media sites account for 7.72 percent of all traffic to retail Websites, up from 6.59 percent in March 2013. Further, Pinterest, more than Facebook or YouTube, is supplying the greatest percentage of downstream traffic to retail sites. According to the Digital Marketer Report, more retailers are directing their customers to social media within their email campaigns. In fact, 96 percent of marketers now promote social media in their emails, and it shows. In 2013, for instance, email Websites generated 18 percent more clicks to social networking pages than the year prior. Social drives more traffic to other social Websites Social media Websites are driving more and more traffic to other social sites. In 2013, 15.1 percent of clicks to social networking and forum sites came from other social networking sites, up from a 12.5 percent click share reported in 2012. Despite driving the greatest share of traffic to social networking sites with 39.1 percent of clicks, search engines’ share of upstream traffic to social declined a relative 13 percent year-over-year. Among the other top referring industries to social, only the portal front pages industry — which includes sites like Yahoo!, MSN and AOL and is closely affiliated with search engines — showed a drop in upstream click share providing further evidence that increasingly all (or most) roads lead to social. To learn more about key trends in social media traffic, including downstream traffic from social sites and the share of consumers accessing social media across multiple channels, download the free 2014 Digital Marketer: Benchmark and Trend Report.
Mother’s Day may not exactly be right around the corner, but the time to send your Mother’s Day emails sure is! Based on our analysis of 186 brands that sent Mother’s Day mailings in 2013, 75 percent of email volume and 80 percent of email-generated revenue occurred between May 1st and Mother’s Day (May 12, 2013). The highest revenue-producing days were five days before the holiday (Wednesday, May 8, 2013) and Mother’s Day itself. This year, the sentimental holiday falls one day sooner than last year (May 11), but you still have more than enough time consider these quick tips for easy wins while planning and executing your campaigns. Tip 1: Give them what they’re searching for Last year, online searches five weeks before Mother’s Day were dominated by searches for the date of the holiday. As such, we recommend including the date of Mother’s Day in your email subject lines, particularly those early in the season, when customers are searching online for, and opening emails with, that information. Tip 2: Set the tone early with your subject lines A sample of early season subject lines that outperformed the overall unique open rate included: Remember Mom on Mother’s Day, May 12 Get a head start on Mother’s Day (plus a gift for you) Just arrived: Mother’s Day Gift Sets To Mother, With Love Tip 3: When it comes to timing, it’s the thought that counts Think through the timing of your emails depending on order delivery deadlines. On May 8th of last year, the largest revenue producers for email were orders for flowers and gifts placed in time to be delivered by Mother’s Day. Email subject lines on May 8th included reminders of the delivery deadlines: Last Chance: Free Shipping/No Service Charge for Mother’s Day! ENDS TODAY: Enjoy Complimentary Second Day Delivery in Time for Mother’s Day Tip 4: Let them treat themselves On Mother’s Day, the top email revenue generators were “self-gifting” (treat yourself on Mother’s Day only), Mother’s Day online sales and free shipping, as well as e-gift cards: Free Shipping Today Only! Happy Mother’s Day You deserve a treat yourself! HAPPY MOTHER’S DAY! Treat yourself to 30% off today only Last Chance: eGift Cards in Time for Mother’s Day Other email performance highlights: Note: All email performance highlights are based on comparisons to Mother’s Day mailings without the highlighted feature from matched brands. To all those in the midst of Mother’s Day campaign planning, good luck and happy sending!