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Digital advertising experienced a transformative shift in 2023, with retail media networks emerging as a focal point for advertisers seeking precision and efficacy. These networks defined how brands connect with consumers, utilizing the unique environment of digital storefronts to deliver targeted and personalized advertisements. Below, we’ll discuss the diverse landscape of retail media networks, examples of these platforms, and how Experian is at the forefront of empowering advertisers within this evolving marketing ecosystem.
What are retail media networks?
A retail media network (RMN) is an advertising platform retailers use in their digital storefronts or online platforms. It lets brands and advertisers promote their products or services directly within the retail environment where consumers make purchasing decisions. Unlike traditional advertising channels, RMNs use the retailer’s first-party data to offer targeted and personalized advertising experiences.
How important is it to advertise with RMNs?
RMNs offer advertisers a unique advantage — a rich set of first-party data on consumers, both on and off the platform. On-platform data includes user engagement insights, demographic information, and behavioral patterns. RMNs offer off-platform first-party data, such as cross-channel integration and CRM data integration. This data is especially important as the industry sees a shift away from the reliance on third-party cookies.
One of the key challenges brands face is the lack of tracking abilities through the customer journey. However, the closed-loop measurement and attribution capabilities within RMNs help advertisers track the entire consumer journey, linking campaign spend directly to final sales and in-store purchases. The precision and accountability offered by RMNs make them a crucial strategy in the ever-evolving world of digital advertising.
Trends with big RMNs
Here is a list of retail media networks and their performance in 2023. The information below offers insights into their reach and effectiveness in driving sales and brand visibility.
Amazon
According to Pacvue’s Q4 guide, Amazon Media Network experienced a year-over-year decline in its daily spend. However, a notable quarterly increase of 3.2% suggests a recent expansion in this ad type. The current average CPC for Amazon-sponsored products is $1.21, marking a substantial 7.1% year-over-year increase. Return on ad spend (ROAS) showed a 1.5% year-over-year decrease but increased by 6.1% quarter-over-quarter, potentially caused by more efficient campaigns. The beauty category showed a particularly strong performance with a remarkable 69.4% year-over-year increase.
Walmart
Walmart’s advertising revenues are surging at a rate twice that of Amazon, according to the Pacvue Q4 report. This quarter, the Walmart Media Network experienced a substantial 40% boost in ROAS, now at $6.93. This advancement can be attributed to strategic adjustments in the algorithm and bid rules and the incorporation of new bid features. Walmart’s CPC also witnessed a noteworthy 18.3% year-over-year decrease and a 14.5% year-over-year surge in average ad spend. Walmart’s growth trajectory emphasizes the shift in consumer behavior toward product discovery, as many consumers research products on the website before purchasing.
Kroger
Kroger developed an advanced retail media network that launched in October 2023. Their platform offers advertisers a more streamlined way to activate, measure, and optimize their campaigns, leading to improved advertising performance. The self-serve advertising platform lets advertisers promote products across the Kroger family of brands. Kroger is the biggest grocery chain in the country with a strong first-party shopper data set, providing more advanced audience targeting than many other grocery RMNs.
Target
Target launched its retail media network, Roundel, in 2016 to enhance the connection between brands and guests through curated media experiences. Roundel uses Target’s rich insights to create personalized advertising campaigns, reaching guests across several platforms and premium publishers. Over the past two years, Roundel has experienced over 60% growth, delivering over one billion in value for Target in 2021 and 2022. With a team of over 500 members, the platform differentiates itself by offering easy-to-use advertising solutions to brands of all sizes. Target plans to launch Roundel Media Studio, a self-service buying tool, in early 2024.
Marriott
In partnership with Yahoo, Marriott has created a travel media network that lets advertisers target consumers based on the hotel chain’s guest data. This collaboration allows ads to be strategically placed on various platforms, including the hotel’s websites. Marriott Media Network’s rollout will start on mobile platforms similar to traditional RMNs. Over time, it will extend to include ad placements on TV screens in guest rooms, Wi-Fi portals, and various digital screens in other areas, like lobbies and bars. This innovative approach in the hotel industry offers marketers diverse opportunities to reach their target audience.
Nordstrom
Nordstrom Media Network has shown considerable success, generating over $40 million in revenue and collaborating with several brand partners. Introduced in 2019, this network initially experimented with off-site campaigns and later expanded to on-site sponsored ads in 2021. Nordstrom Media Network offers data from 32 million customers and digital properties with nearly two billion annual visits. The network’s focus on personalizing the customer experience helps it stand out in the competitive retail media space and makes it a valuable player in the evolving digital advertising landscape.
CVS
With CVS Media Exchange, advertisers have access to a data set of 74+ million customers. This platform creates tailored campaigns for companies, helping their ads reach customers at the most critical points in their shopping journey. With options like display, video, audio, social, and in-store ad options, advertisers are seeing increases in product purchases and brand awareness.
Instacart
Instacart has a retail media network through its own platform and a tool called Carrot Ads, which helps grocery store chains develop RMNs through Instacart. It has a network of over 1,400 retail brands, helping advertisers reach their target audience. Advertisers have access to insights and automation to create relevant ads and track their progress.
Companies like Sprouts are using Carrot Ads to create and grow their own RMNs. Together, Instacart and Sprouts offer brands a unique opportunity by facilitating targeted online campaigns on Sprouts’ website. This collaboration provides access to metrics like sales and ROAS, offering a comprehensive view of campaign performance.
DoorDash
DoorDash offers a comprehensive suite of advertising tools for restaurants and brands to expand their reach on the DoorDash marketplace. This flexible advertising platform extends across diverse categories, like restaurants, grocery, convenience, alcohol, and more. The platform has demonstrated success with an average return on ad spend of 4.1x from sponsored product campaigns and an average of 70% new-to-brand customers.
Reasons behind these trends
The surge in advertising trends within RMNs can be attributed to several critical factors, including the following:
Rising retail media competition
The competitive landscape within the retail world has intensified, with major players competing for a larger share of the advertising pie within their respective RMNs. This surge in competition among retailers like Lowe’s One Roof, Sprouts, 84.51, and Albertson’s Media Collective has led to a continual evolution of features and capabilities. Advertisers benefit from this competitive spirit because it drives innovation and offers enhanced tools and opportunities to refine their advertising strategies. The competitive edge creates an environment where RMNs continually improve and adapt to meet the needs of both advertisers and consumers.
Third-party cookie deprecation
Major web browsers are getting rid of third-party cookies, so advertisers must reevaluate their targeting and tracking strategies. Because of this, the first-party stronghold of RMNs is particularly valuable. Advertisers can rely on their reservoir of first-party data with RMNs to maintain effective audience targeting and measurement capabilities. The emphasis on first-party data aligns with advertisers’ needs in the post-cookie era, making RMNs crucial partners in the pursuit of effective and privacy-conscious advertising solutions.
Crafting your RMN ad strategy
Crafting an effective RMN ad strategy is a multifaceted process that involves careful planning. You start with clean, scaled, and scoped data, then everything waterfalls from there. When done correctly, you reach the right audience, your ROAS/ROI results improve, your marketing spend is more effective, and your advertisers want to spend more with your RMN. Here are steps to consider when developing your RMN ad strategy.
Choose the best RMN partner for your needs
Selecting the right partner is a critical first step. Ensure your partner seamlessly integrates with your existing MarTech stack, avoiding any additional workload for your existing team. A symbiotic relationship with your RMN partner enhances collaboration and streamlines your advertising initiatives.
Experian’s comprehensive data and identity solutions can help RMNs maximize their opportunity, with our new solution tailored to enhance RMNs’ strength in first-party shopper data. Experian’s solution helps RMNs unlock expanded customer insights, enriched audiences for activation, identity resolution for cross-channel audience targeting, and real-time measurement and attribution. This comprehensive solution is designed to help RMNs capture more advertising revenue. Our goal is to ensure you capture the most advertising dollars and make your RMN operate at its peak performance.
Utilize third-party data
One of the cornerstones of an effective RMN strategy is the integration of third-party data. This is where Experian steps in as a critical ally. Experian’s robust third-party data solutions can enhance an RMN’s first-party data to create more scale and scope for RMN audiences. This, in turn, will open up more opportunities for advertiser investment.
Utilize first-party data
The main advantage of RMNs is the access to first-party data. Advertisers can use this data to create personalized and targeted campaigns. By tailoring your messages based on consumer expectations, preferences, behaviors, and purchase history, you create a more engaging and relevant ad experience. This not only boosts the effectiveness of your campaigns but also fosters a deeper connection between your brand and the audience.
Promote relevant products
Personalized ads are crucial for capturing audience attention and driving conversions. With retail media platforms, advertisers can personalize their campaigns to individual shoppers. Promoting products that align with your audience’s specific needs and preferences increases the likelihood of conversions.
Consider the consumer journey
Strategic ad placement within the consumer journey is pivotal. Consider targeting consumers late in the decision-making process when they’re in a shopping mindset. Placing ads at this point in the customer journey increases the chance of converting prospects into customers. Understanding the customer journey within an RMN system allows for a more targeted and impactful advertising strategy.
Measure data and adapt
The final step in the process is continuous measurement and adaptation. Retail media platforms include powerful analytics tools that let advertisers track and analyze ad performance in real time. Use these insights to adapt your strategy. A data-driven approach ensures your campaign remains responsive to the changing marketing dynamics.
Elevate your advertising strategy with Experian
Transform your advertising strategy with Experian’s cutting-edge Consumer View solutions. These advanced tools excel in audience segmentation and easily integrate your first-party data with our comprehensive third-party insights. This ensures the seamless activation of your data across online and offline channels. Experian also has custom audiences and audiences that are available on-the-shelf of most major platforms. This and our onboarding capabilities make Experian the perfect partner for your RMN strategy.
Connect with a member of our team today to take the next step in elevating your advertising 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. 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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.