CES 2025 will be an exciting opportunity to explore how we can work together to shape the year ahead. Here are four themes we expect to take center stage at the event.
“There is no better way to kick off the calendar year than with clients and industry peers that are excited to collaborate on new business opportunities. People come straight off the holidays energized by CES and with a pipeline of deals to work on for the coming month. In-person meetings always trump virtual calls and everyone in the industry comes together to make it a fruitful week.”
Crystal Jacques, Head of Enterprise Partnerships
1. Addressability in a signal-loss world
Addressability has become a cornerstone in AdTech as brands aim to deliver personalized experiences while navigating evolving privacy regulations and signal loss. This shift has prompted advertisers to rethink how they reach and engage audiences. In this environment, alternative identifiers such as UID2 and ID5 have gained traction, offering brands new avenues to target consumers across platforms while respecting privacy. Addressability has shifted from a straightforward tracking mechanism to a multifaceted strategy that combines identity solutions, contextual insights, and collaboration across the ecosystem.
ID Bridging and the new OpenRTB 2.6 specs
As the industry loses identity signals, it becomes increasingly difficult to identify audiences on the supply-side and make them reachable for the demand-side.
The supply-side has used the practice of ID bridging to do just that. ID bridging is the supply-side practice of connecting the dots between available signals to infer a user’s identity and communicate it to prospective buyers. This practicesparked debate, as buyers want full transparency into the use of a deterministic identifier versus an inferred one.
“The OpenRTB 2.6 specifications are a critical step forward in ensuring transparency and trust in programmatic advertising. By aligning with these standards, we empower our partners with the tools needed to navigate a cookieless future and drive measurable results.”
Michael Connolly, CEO, Sonobi
The industry needs widely accepted standards, and that’s what we believe the industry has with the IAB Tech Lab’s OpenRTB 2.6. The specifications dictate the data the supply-side needs to include in the Primary ID and Enhanced Identifier (EID) fields. In doing so, the demand-side receives more transparent information on when bids have inferred IDs and where they came from.
As authenticated signals decrease due to cookie deprecation and other consumer privacy measures, we will continue to see a rise in inferred identifiers. Experian’s industry-leading Digital Graph has long supported both authenticated and inferred identifiers, providing the ecosystem with connections that are accurate, scalable, and addressable. Experian will continue to support the industry with its identity resolution products and is very supportive of IAB’s efforts to bring transparency to the industry around the usage of identity signals.
2. Commerce media consolidation
As the world of commerce media expands beyond traditional retail media, we’re seeing a surge of networks across various verticals—financial, travel, and beyond—all competing to capture shoppers’ attention. With each company independently building its own media network, the need for strategic partnerships has never been more evident. Key players face challenges in scaling these networks and meeting growth targets due to infrastructure and funding limitations. In response, the industry is shifting toward partnerships – and potentially consolidation – to create networks that allow advertisers to reach customers across the entire shopping journey – from digital to in-store.
To succeed, commerce media networks must form strategic partnerships to enhance their data and identity capabilities and provide advertisers with a complete view of their customer.
“With annual growth in billions of dollars, the revenue potential for RMNs is massive. Organizing customer data, segmenting customers, generating insights, creating addressable audiences, and activating campaigns are all critical steps for a RMN to realize that revenue potential. RMNs should select a partner that provides the data, identity and analytical resources to create the winning formula for marketers, customers and retailers.”
Steve Zimmerman, Director of Analytics
With Experian’s expertise in data and identity solutions, commerce media networks can overcome data fragmentation, create high-quality audiences, and maximize addressability across their entire customer base. This collaborative, partner-led approach empowers retailers to utilize their first-party customer data but not be limited by in-house resources. As the commerce media space matures, those who embrace these partnerships and data-driven solutions will be well-positioned to capture the full potential of this expanding market.
3. Navigating complex privacy regulations
With privacy concerns intensifying, consumers are more conscious about data usage, and a series of state-level privacy laws are poised to take effect across the U.S. Multiple state-level laws makes compliance more challenging for marketers since no two laws are the same. While a federal privacy law remains unlikely for 2025, discussions around data ethics, compliance, and transparency will be prominent at CES, especially as a new administration assumes office.
Our privacy-forward audience solutions
Our Geo-Indexed and Contextually-Indexed Audiences help marketers reach the right consumers while prioritizing data privacy. Created without sensitive personal information, these audiences utilize geographic and contextual signals – not personal identifiers — to offer relevant targeting. These new tools provide both privacy and accuracy, giving advertisers and publishers a competitive edge.
“By embracing innovations in geo-based targeting and adhering to responsible data strategies, you can not only comply with these laws but continue to reach your intended audiences effectively.”
Jeremy Meade, VP, Marketing Data & Operations
As privacy regulations evolve, marketers need trusted allies who can provide transparent, compliant solutions. With deep roots in data protection and security, you can confidently partner with Experian as we proactively stay ahead of regulations and strictly follow all consumer privacy laws.
4. Rise of curation
As privacy regulations and signal loss reshape the AdTech ecosystem, curation can optimize programmatic campaigns by connecting advertisers with valuable audiences. This emerging trend utilizes audience, contextual, and supply chain signals to curate high-quality inventory packages for advertisers. By blending insights with inventory, curation ensures greater addressability, efficiency, and performance for both advertisers and publishers.
Supply-side platforms (SSPs) are taking a more active role in curating audiences and inventory. SSPs now collaborate with data providers to match buyer and publisher first-party data in real-time, creating curated private marketplaces (PMPs) that deliver transparency, efficiency, and improved match rates. SSPs can send deal IDs to multiple DSPs, which allows advertisers to deploy audience-based campaigns without restrictions on which DSPs or identifiers can be used.
However, curation isn’t without challenges. It can add complexity, lead to redundant buys, and even reduce publisher control over inventory. Transparency, quality benchmarks, and strategic partnerships will be critical for maximizing the benefits of curation in 2025.
Experian, in partnership with Audigent and others, is at the forefront of enabling privacy-forward curation strategies. Experian and Audigent’s combined capabilities bring together first-party publisher data, contextual signals, and advanced identity resolution to create curated PMPs that empower marketers to deliver precise, impactful campaigns.
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Published in MediaPost With the explosion of smartphones and digital tablets and the steady rise of Internet-connected televisions, gaming consoles, and more, consumers are increasingly watching online video when and where they want. New research from Experian Marketing Services on cross-device video found that as of October 2013, 48% of all U.S. adults and 67% of those under the age of 35 watched online video during a typical week, up from 45% and 64%, respectively, just six months earlier. At the same time, the share of households considered “cord-cutters” — those with high speed Internet but no cable or satellite TV — is on the rise, and that has a real impact on marketers and on the medium of television, the recipient of the largest share of advertising dollars. While the growing trend in cord-cutting is understandably disturbing to cable and satellite companies and disruptive to the television advertising revenue model overall, the growth in online viewing creates opportunities for marketers. Online video viewers can be more easily targeted and served up advertising that is more relevant, responsive and measureable. Marketers can also be more confident that their online ad was actually seen given that viewers are typically unable to skip ads. And while CPMs for online video ads may generally be lower than those of TV, marketers can use that savings to negotiate costs based on clicks or transactions rather than impressions, giving them a better picture into audience interest and insights to inform their budget allocation. Expect “Cutting the cord” to continue Today, over 7.6 million U.S. homes or 6.5% of households are cord-cutters, up from 5.1 million in 2010 or 4.5% of households. One thing enabling consumers to cut the cord is the rise in Internet-connected TVs, which allows viewing of Internet video on demand without sacrificing screen size. In fact, a third of adults (34%) now have at least one TV in the home that is connected to the Internet either directly or through a separate device like an Apple TV or Roku, up from 25% in 2012. With the launch of devices like Google’s Chromecast and the Amazon Fire TV, those numbers are sure to rise even more in the months and years ahead. Cord-cutters like the bigger screen Our analysis found that the act of watching streaming or downloaded video on any device is connected to higher rates of cord-cutting but the act of watching on a television is the most highly correlated. In fact, adults who watch online video on a television are 3.2 times more likely than average to be cord-cutters. Those who watch video on their phone (the device identified in the analysis as that most commonly used for watching online video) are just 50% more likely to be cord-cutters. Millennials are more likely to be cord-cutters We found that households with an adult under the age of 35 are almost twice as likely to be cord-cutters. Throw a Netflix or Hulu account into the mix and the rate of cord-cutting among young adult households jumps to nearly one-in-four. Given these surprising stats, many Millennials may be cord-cutters without ever having “cut” a cord. And that’s an important trend to watch since it means a significant portion of this generation will never pay for TV. Millennials are also the most device-agnostic, with over a third saying they don’t mind watching video on a portable device even if it means a smaller screen. That’s more than double the rate of those ages 35 and older. This decentralized viewing can create headaches for marketers who need to start a relationship with Millennials during this stage of their lives when they’re most open to trying out new brands and have yet to settle down. On the plus side, marketers who do manage to reach this audience will find them much more open to advertising than average. In fact, Millennials are more than four times more likely to say that video ads that they view on their cell phone are useful. So while the challenge is big, so is the potential reward.
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.