As technology reshapes our media experience, TV remains a powerful channel for content consumption. In our next Ask the Expert series, we dive into a pivotal subject – the convergence of TV, linear (conventional broadcast and cable TV), and digital marketplaces.
In this Q&A segment, we’re joined by two industry experts, Dan Hickox, VP of Development & Partnerships at 605, an iSpot.tv Company, and Chris Feo, Experian’s SVP of Sales & Partnerships, who guide us through an engaging discussion on convergent TV, attribution, measurement, and safeguarding personal data in the evolving landscape of TV advertising.
How convergent TV is changing the future of advertising
The convergence of traditional TV and digital streaming platforms presents an innovative opportunity for advertisers to engage their target audience. With convergent TV, you can create campaigns that bridge the gap between linear and streaming, ensuring your message reaches your target audience while avoiding ad fatigue.
Along with high-quality content, extensive inventory, and targeting capabilities, convergent TV offers advanced measurement and attribution tools that will empower you to optimize advertising campaigns for maximum impact. You can make better decisions regarding when and where to strategically allocate your advertising budgets with effective TV measurement and attribution.
Attribution in converged TV
TV attribution involves tracing consumer actions and uncovering valuable insights into their behavior. With these insights, you can gain a clear understanding of the audience exposed to your ads and their actions in response. Lean into data attribution tools to track your target audience throughout the customer buying journey.
Measurement in converged TV
In contrast, TV measurement enables the tracking of performance TV advertising campaigns to assess campaign effectiveness. Through converged TV measurement solutions, you can rely on a singular data source, unifying different channels, devices, and metrics for actionable insights. This analysis will give you insights into the audience reached, their location, and the resulting actions taken.
TV attribution’s impact on cross-channel media
Embracing an omnichannel advertising approach is vital. Evaluating advertising campaigns across various platforms and devices – including linear, TV, and digital channels – is essential for identifying the channels that drive revenue for your businesses. Converged TV and digital streaming enable you to control ad frequency across all channels, enhancing the cross-screen experience. This convergence paves the way for a more comprehensive and holistic future in advertising. Here are three ways TV attribution impacts cross-channel media.
Identify the most effective channels
TV attribution offers a significant advantage in determining the channels that generate the most conversions. By using this data, you can make informed choices about budget allocation to achieve maximum impact.
Deliver a seamless customer experience
Consumers demand consistency in their brand interactions. TV attribution can help you by guiding the optimal timing and placement of ads, resulting in a more seamless viewing experience. This synchronization can significantly enhance customer loyalty and retention.
Enhance marketing effectiveness
By identifying the most effective channels and refining campaign strategies, TV attribution can significantly improve the success of marketing campaigns. The outcome is a measurable increase in sales and revenue, demonstrating the impact of informed and data-driven advertising.
Audience-based targeting across linear and digital ecosystems
It’s crucial to comprehend and connect with the appropriate audience. The emergence of linear and digital platforms has required the development of audience targeting. Across these two ecosystems, audience-based targeting aims to enhance this process by concentrating on specific audience segments rather than general demographics or programming.
Benefits of audience-based targeting
There are four key benefits of audience-based targeting across the TV ecosystem.
Personalization at scale
Digital platforms have conditioned users to expect tailored experiences. Audience-based targeting ensures ads resonate with individual preferences and behaviors, even within the vastness of linear TV.
Combining data from both linear and digital sources makes it possible to segment audiences more precisely. This results in advertising content tailored to each individual, making it more relevant and personalized.
Optimized ad spend
Improve your return on investment by targeting specific audience segments more likely to convert, ensuring your messages reach suitable viewers.
In contrast to traditional TV purchasing, where advertisement slots are bought based on a show’s overall demographic, audience-based targeting focuses on the viewers’ behavior and interests, regardless of the program they are watching.
Unified measurement and analytics
When combining traditional and digital methods of reaching target audiences, it is essential to have a consistent approach to measuring success. By doing this, you can gain insight into how well your ad campaigns perform across different platforms and the frequency with which they are being seen.
By comprehensively understanding audiences within different ecosystems, you can adjust your strategies in real time, guaranteeing that your campaigns remain flexible and successful.
Enhancing the viewer experience
Audience-based targeting benefits viewers by reducing the number of irrelevant ads they see. As a result, viewers can have a more pleasant experience while watching content, which may discourage them from skipping ads and increase their engagement with the content.
Future-proofing and safeguarding data
Businesses are focusing on future-proofing for data privacy, and safeguarding individual data is becoming more significant than ever before. Now’s the time to embrace new methods that protect your data privacy while ensuring that measurement remains accurate. Experian offers privacy-safe solutions to help businesses preserve precise measurement, even with fewer cookies.
“What we’re working toward is future-proofing ourselves. To do that, we work with partners like Experian who are already thinking forward, and with your pixel technology, we can capture and resolve the identifiers that we know will be around for a while.”
Dan Hickox, VP, Solutions Consulting, Development & Partnerships, 605
How Experian and 605 work together
605 is an independent TV measurement and analytics company providing solutions for advertising, content measurement, attribution, planning, optimization, and media transactions.
“We partner with great identity partners, such as Experian, that really help us act as the connecting glue across different data touch points. So what it really is, is the ability to have holistic measurement across the different channels, across the different audiences and it starts out with the ability to be able to take disparate data sources and match them together.”
Dan Hickox, VP, Solutions Consulting, Development & Partnerships, 605
605 and Experian have a strong partnership that enables 605 to enhance its data through Experian’s Consumer Sync and Pixel solutions.
- Consumer Sync – 605 utilizes Experian’s Consumer Sync to ensure their data is privacy-compliant and deterministic across all sources. 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.
- Web Pixel Attribution – 605 utilizes Experian’s pixel solutions to generate web pixel attribution reports on a client-by-client basis – for linear, TV, and cross-platform reporting. 605’s reporting capabilities allow customers to understand their marketing campaigns’ true impact and precisely identify high-performing strategies. With the Experian pixel, partners like 605 can learn more about anonymous website visitors by linking associated demographics and behavior attributes, build audience segments based on the highest cart value customers, and more.
The 605 and Experian partnership work hand in hand to make linear TV as actionable as digital media for you. Customers can prove the effectiveness of their marketing tactics and gain actionable insights to deliver highly impactful campaigns.
Watch the full Q&A
Visit our Ask the Expert content hub to watch Dan and Chris’s full conversation about TV measurement, data analytics, privacy regulations, and the evolving landscape of TV advertising in the digital age.
About our experts
Dan Hickox, VP, Solutions Consulting, Development & Partnerships, 605
As the Vice President of the Solutions Consulting team, Dan collaborates with sellers to turn prospective opportunities into long-term client relationships. He leads new initiatives and drives partnerships that expand 605 capabilities and improve marketplace positioning.Dan brings over a decade of cross-channel media experience in advanced analytics, media optimization, data integration and statistical analysis to 605.
Chris Feo, SVP, Sales & Partnerships, Experian
As SVP of Sales & Partnerships, Chris has over a decade of experience across identity, data, and programmatic. Chris joined Experian during the Tapad acquisition in November 2020. He joined Tapad with less than 10 employees and has been part of the executive team through both the Telenor and Experian acquisitions. He’s an active advisor, board member, and investor within the AdTech ecosystem. Outside of work, he’s a die-hard golfer, frequent traveler, and husband to his wife, two dogs, and two goats!
Latest posts
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.