A few weeks ago, Experian and OpenX hosted a supply-side think tank at our New York City office. Over 70 industry leaders met to talk about targeting in a cookieless future and how we can reach consumers in intentional ways.
Publishers and supply-side partners shared what challenges they face, what solutions they’re considering, and what the future holds once the third-party cookie begins to deprecate in 2024. In this blog post, we’ll cover the top challenges, cookieless solutions, and actionable strategies we discussed at the event that can help publishers, their partners, and agencies make informed decisions about how to navigate tomorrow’s digital ecosystem.
Four main challenges
Four main challenges were discussed at the event:
First-party data monetization
Publishers possess a wealth of first-party data, but collecting and centralizing this information can be difficult for actionable insights. Streamlining data centralization and organizing first-party data is crucial for effective decision-making. Even with a wealth of first-party data, it’s important to be aware of any blind spots in your data and enrich those gaps with data partners rooted in offline connections.
“We appreciate the opportunity to participate in the supply-side think tank led by OpenX and Experian, two industry leaders in navigating a cookieless future. We’re excited to collaborate with them on testing privacy sandbox APIs, identity resolution products, and audience development tools to enhance creator monetization and support an open internet amidst rapid technological and regulatory shifts.”
Patrick McCann, SVP, Research, Raptive
Lack of authenticated data and persistent IDs
The deprecation of third-party cookies means there will be a shortage of authenticated user data and persistent identifiers. Without this information, targeting and personalization become more challenging. Participants discussed the need to find alternative ways to gather and use personal data responsibly. It’s time to start evaluating data partners who have accurate, multi-source compiled, privacy-compliant data with the dedication to reach and recency.
Fragmentation and scale with alternative IDs currently in the market
The multitude of alternative identifiers in the market poses a challenge for publishers. Each of these identifiers comes with its own set of rules and integration processes, leading to fragmentation and complexity. Publishers must find ways to navigate this landscape. Look to ID agnostic partners who provide a way to access multiple IDs at scale.
“The industry needs a more streamlined standard to integrate alternative IDs, given the ongoing challenges of third-party cookie deprecation, measurement, and clean rooms. This burden falls heavily on product and engineering teams, who must prioritize and address these issues one at a time.”
Ryan Boh, Head of Identity, Lockr
Time
Cookie deprecation is almost here. It is crucial to organize your legal, engineering, and product resources, and align internal go-to-market strategies. Establish partnerships that work with your team to follow these timelines and help build phased or cohesive strategies to prepare for a path to monetization. It is imperative to establish a sense of urgency and not wait for others to take the lead. Start testing now to determine if your infrastructure is ready and capable. Many partners who attended the think tank offered insights on how they’ve been tackling challenges to help their industry peers.
Solutions and action plans for a cookieless future
Participants discussed ways they are starting to prepare for a cookieless future and other approaches on their roadmaps:
Work with data partners heavily rooted in offline data across the ecosystem
Enriching your first-party data with partners who rely on offline IDs can help bridge gaps in your audience knowledge. This approach allows you to build a more complete audience profile while third-party cookies are still operational.
Experian is rooted in deterministic offline data and has decades of experience managing it safely. We have insights on over 250 million U.S. consumers and 126 million U.S. households. With our digital technology assets, we bring in 4 billion devices and 1 trillion device signals to definitively connect offline records to online identifiers. With Experian identity widespread adoption throughout the industry, we’re able to provide a common language for us all to collaborate. Experian identity organizes people into households, links their digital devices and IDs to them, enriches their identity with behavioral attributes, and then makes this data actionable in any environment, all while maintaining consumer privacy and data regulations.
“Experian’s supply-side think tank provided a platform for publishers and AdTech companies to discuss the challenges posed by cookie deprecation, privacy regulation updates, and identity restrictions. It highlighted the need for AdTech companies to assist publishers in addressing anonymous users without requiring a value exchange — fostering a mutually beneficial and privacy-compliant open web solution.”
Anthony Caccioppoli, Head of AdTech & Solutions, Insider
Develop your own persistent ID
Creating and maintaining a proprietary persistent ID can be a valuable cookieless solution. It provides control and independence in the new environment post cookie, giving publishers the ability to maintain a consistent user profile.
Use your data to expand contextual targeting opportunities
Contextual targeting involves placing ads based on the content of the web page rather than user data. In the absence of cookies, this strategy can prove effective in reaching relevant audiences.
“The masking or deprecation of IP addresses will eventually impact the availability of addressable IDs in non-authenticated web environments. In addition to ensuring maximum resiliency of our Graph and increasing support for authentication-based IDs, we are also investing in research and development around the use of other signals, such as contextual data, to maintain behavioral targeting inside non-authenticated environments. We will be sharing our findings and future plans in this space in the coming months.”
Budi Tanzi, VP, Product, Experian
Facilitate a knowledge exchange
Reach out to your network to find out what others are testing and what’s working. Start collaborating with agencies and brands across the buy-side to meet their needs.
“The collaborative spirit displayed by our partners constantly inspires me. Listening to the obstacles our industry faces allows this community to build strong relationships, create action plans, and deliver true value.”
Carly Allcorn, Account Executive, Publisher & Supply-Side Partnerships, Experian
Invest in an identity graph
Invest in an identity graph provider to sync first-party cookies and addressable IDs. This ensures that your data remains accessible and actionable in a cookieless world.
“Many participants at our think tank with Experian expressed the need to find an identity solution while also exploring other ways they can start to address cookie deprecation while maintaining business as usual.”
Callie Askenas, Director of Publisher Development, OpenX
How Experian and OpenX can help
Graph from Experian captures all available digital identifiers in real-time and resolves them back to individuals and households. We’re signal agnostic, continuously expand the IDs we support, and futureproof identity resolution through a combination of deterministic, probabilistic, and cookieless identifiers.
Experian is a key player in OpenX’s OpenAudience solution and helps to power many of their data segments as well as their identity graph. While OpenX collaborates with a variety of providers and operates a fully interoperable platform, Experian remains valuable to the core technology within OpenX’s supply-side platform (SSP).
Experian can help you prepare for the cookieless future
It’s clear that the cookieless future poses some unique challenges for publishers, but there are solutions. Publishers and their supply-side partners can come up with strategies to target consumers in intentional ways by continually testing multiple identifiers and cookieless solutions, developing their own persistent ID, creating velvet rope content, and returning to contextual targeting. Collectively, these actionable strategies can help ensure that publishers have a more successful transition into a cookieless future.
Experian has been preparing for signal loss for quite some time and we continue to make substantial investments to ensure our resiliency and the resiliency of our customers. We continue to diversify our signal creating profiles with more persistent identifiers which allows us to pair authentication-based universal identifiers such as UID2 into our Graph seamlessly.
Experian is ready and we are here to navigate the future of privacy together.
To find out more about how Experian can help you prepare for the cookieless future, get in touch with a member of our team today.
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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. 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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.