Originally appeared on Total Retail
Retail media networks (RMNs) continue to demonstrate how they can be a powerful monetization driver for retailers, creating a win-win-win for everyone involved. Retailers can monetize their valuable first-party data as well as their online and in-store inventory, while customers benefit from timely, relevant content that enhances their shopping experience. At the same time, advertisers can reach highly targeted audiences at critical moments near the point of purchase
Achieving this type of success requires overcoming challenges around fragmented and incomplete first-party data, which can limit a retailer’s ability to organize and use their data effectively. Additionally, many RMNs lack the analytical capacity to generate customer insights, build addressable audiences, and accurately measure success. To realize the full potential of their platforms, RMNs need partners that provide complementary data, strong identity solutions, and the expertise to transform insights into actionable strategies. This allows RMNs to drive winning outcomes for themselves, marketers, and their customers.
Here are the five steps an RMN should consider when selecting the right partner.
1. Build an identity foundation
First, the right partner needs to be able to organize and clean customer data. Given the millions of customer records and data points that a retailer has, RMNs need to make sure their data is highly usable. Whether it is a known customer record or an unknown customer with incomplete data, partners should fill in missing information and connect fragmented customer records to a single profile. For example, RMNs need to know that a purchase made in-store is by the same customer who bought online. The best partners will then organize those profiles into households since targeting (and purchasing) is often done at the household level. Without a strong identity foundation future steps of segmentation, insights, audience creation, and activation will not be successful.
Experian identity
Experian’s identity solutions provide RMNs with a comprehensive and accurate view of their customers across both offline and digital environments. We clean an RMN’s first-party data and organize their customer records into households since targeting is often done at the household level and purchases are made at the household level.
Using Experian’s Offline and Digital Graphs we work with the RMN to fill in the missing information they have on their customers (e.g. name, address, phone number or digital IDs like hashed emails, mobile ad IDs, CTV IDs, Universal IDs like UID2 or ID5 IDs). This ensures that the retailers’ entire customer base can be reached – and measured – across devices and channels.
2. Segment your customers
An RMN’s ability to segment its customer base and derive insights depends on the availability and usability of their data assets – not to mention some serious analytical chops. Some RMNs will split their customers into different product segments based on what’s relevant to an advertiser. For example, a home improvement retailer may segment customers by who is buying DIY supplies versus improvement services. Other RMNs may develop custom segments from their customer data and third-party data sources, so that advertisers can personalize their marketing based on life stage, age, income level, geography, and other factors. Either approach is effective but requires working with a partner who has high quality data and deep analytical expertise to develop those segments.
Segment with Experian
Experian Marketing Data helps an RMN learn about their customer beyond their first-party data. With access to 5,000 marketing attributes, RMNs can fill in the holes in their understanding of a customer. We provide them with demographic, geographic, finance, home purchase, interests and behaviors, lifestyle, auto data and more. RMNs can use this enriched data set to create addressable audience segments.
3. Generate actionable insights about these segments
Once the RMN determines how they will segment their customers, they can utilize demographic, attitudinal, interest, and behavioral data from a trusted partner to develop a customer profile that compares its customers against a relevant sample of consumers. Here, the RMN will gain insight that will help them answer questions about its customers. Examples include:
- What age and income groups are more likely to purchase my product?
- What is the current life stage of my customers – do they have children, are they married, are they empty-nesters?
- Is price or quality more important to customers in their decision-making process?
- What sort of activities do my customers enjoy?
- How frequently do my customers shop for similar merchandise?
- What media channels do my customers use to get their information?
Expanded insights with Experian
With Experian’s advanced customer profiling, RMNs can go beyond basic customer segmentation. We build detailed customer profiles by utilizing accurate, attribute-rich consumer data, so RMNs can gain a more comprehensive understanding of their customer’s preferences, life stages, and purchasing behaviors. Having this insight enables the RMN to:
- Design a targeted email campaign promoting home essentials to recently married new homeowners.
- Develop a social media post announcing the opening of a new hardware store to users within a specific location interested in do-it-yourself products.
- Create brochures and flyers at a local community event tailored towards parents with small children that promote equipment for youth sports leagues.
4. Create high quality lookalike audiences
The RMN now knows what distinguishes their customers from other consumers and can create audiences that enable advertisers to run personalized marketing campaigns at scale. RMNs can do this in several different ways:
- Work with a data provider who can create custom audiences for the RMN (e.g., Ages 40-49 and Leisure Travelers and past purchase of travel item)
These custom audiences are created by joining multiple first- and third-party data attributes found to be significant in the customer profile or using machine learning techniques to develop a custom audience unique to the advertiser.
Custom audiences with Experian
With an enriched understanding of their customers, RMNs can create addressable custom audience segments, including lookalike audiences, for advertisers.
5. Expand addressability of audiences and activate on multiple destinations
Once audiences are created, RMNs will want to increase a marketer’s reach across on-site and off-site channels. With the right identity graph partner, an RMN can add digital identifiers to customer records that enable activation across media channels, including programmatic display, connected television (CTV), or social. RMNs should work with identity providers that are not reliant on third-party cookies. They should select partners that offer more stable digital IDs in their graph like mobile ad IDs (MAIDs), hashed emails (HEMs), CTV IDs, and universal IDs like Unified I.D. 2.0 (UID2).
Experian powers data-driven advertising through connectivity
Using Experian’s Digital Graph, RMNs expand the addressability of their audiences by assigning digital identifiers to customer records. Marketers will be able to reach an RMNs customers onsite as well as offsite since Experian provides several addressable IDs.
Audiences can be activated across an RMNs owned and operated platform as well as extended programmatically to TV and the open web through Experian’s integrations across the ecosystem.
Maximize your RMN’s revenue potential with Experian
Organizing customer data, segmenting customers, generating insights, creating addressable audiences, and activating campaigns are all critical steps for an 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.
Experian’s data and identity solutions are designed to help RMNs maximize their revenue potential.
Reach out to our team to discover how we can support your path to RMN success.
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2023 has been an unprecedented year for AdTech. With new challenges arising every day — from ongoing signal loss to changing consumer privacy regulations– staying on top of trends is more important than ever before. To help you stay informed on successful tactics from across our ecosystem we’ve compiled a list of our top five 2023 AdTech blog posts. Keep reading to learn about the top themes from CES and Cannes this year, why contextual targeting is so popular, and more – so you can remain competitive in today's rapidly changing environment. #5 CES 2023: Clean rooms, activation, and more Experian attended CES in January to kick off the AdTech year, connecting with partners, clients, and industry leaders to understand their challenges and goals. Discussions were focused on clean rooms and digital activation to address data deprecation and consumer privacy. Clean rooms have the potential to standardize data and address interoperability issues. Digital activation was predicted to increase significantly in 2023, with more focus on demand-side, video, and supply-side platforms. Did digital activation increase in 2023? Download our 2024 Digital audience trends and predictions report to find out. Read our full 2023 CES recap here. Meet with the Experian team at CES 2024 CES is around the corner, and we are looking forward to the opportunity to connect with you in our suite at the Aria Hotel & Casino in Las Vegas, January 9-12. There is no better place to connect and discuss the latest industry trends and innovations. Let’s start the conversation! Book a meeting with our team #4 Experian identity resolution now available in AWS Clean Rooms Earlier this year, Experian announced that our identity resolution solution is now available in AWS Clean Rooms. Through this new partnership, customers can pair Experian's identity capabilities with AWS Clean Rooms to safely collaborate and access deeper insights without exposing sensitive data. Check out the full announcement to hear from Kalyani Koppisetti, Principal Partner Solution Architect at AWS, Matt Miller, Business Development Principal at AWS, and Tyler Middleton, Sr. Partner Marketing Manager at Experian. #3 Four key themes from Cannes Lions 2023 At Cannes Lions 2023, discussions revolved around four main themes: Signal loss: Experts discussed the importance of adapting paid media strategies to align with consumer behaviors. Collaboration: Discussions highlighted the need for industry players to collaborate and focus on solutions that benefit all stakeholders in the ecosystem. Personalization: This was a key topic and emphasized the growing significance of tailored content, data-driven insights, and first-party data solutions for advertisers adapting to cookie deprecation and the evolving consumer privacy landscape. Balancing AI and creativity: Attendees explored how to balance AI capabilities and nurture creativity while maintaining a human touch. Cannes 2024 will be here before we know it and Experian will be there. To get ready, check out this post by Tyler Middleton, Sr. Partner Marketing Manager, to hear from a first-time Cannes attendee, #2 Three key insights from our 2023 Holiday spending report Experian's annual Holiday spending trends and insights report analyzed recent trends, consumer spending habits, and anticipated what was to come in the 2023 holiday shopping season. This blog post covered three key insights from our report: Consumers are starting their holiday shopping earlier, particularly with online sales. Online sales have been increasing year-over-year, surpassing in-store sales. Spending during the 2022 holiday season was lower than in previous years but is expected to be on par with what was seen in 2023. For advice from our experts and access to all of our predictions for this year’s holiday shopping season, download our 2023 Holiday spending trends and insights report today. #1 How contextual ad targeting addresses signal loss Our most viewed blog post of 2023 was How contextual ad targeting addresses signal loss. Marketers are seeking new solutions due to signal loss caused by the phasing out of third-party cookies. Contextual ad targeting offers a way to combine contextual signals with machine learning for more accurate targeting. Experian's Jason Andersen and Yieldmo's Alex Johnston discuss the challenges of signal loss, addressability, the importance of good creative, and tips for digital ad success in this blog post. By understanding contextual advertising, marketers can create powerful and effective campaigns to reach target audiences. Subscribe to our newsletter Sign up for our email newsletter to receive our latest blog posts, product and partnership announcements, thought leadership, and more straight to your inbox. Subscribe Latest posts
In this article… Why AI and CTV are a great match The rising popularity of CTV How is AI already being used in CTV? Demand-side platforms Artificial intelligence (AI) and connected TV (CTV) have a perfect synergy that’s revolutionizing how advertisers connect with their audiences. CTV serves as a medium for streaming content, while AI acts as a sophisticated technology that improves the performance of CTV advertising campaigns. The integration of these two technologies has paved the way for advertisers to reach their target audience more effectively, making CTV advertising a powerful and efficient tool. In this blog post, we’ll dive into how these technologies work together — and why you should jump on board with AI for CTV advertising if you haven’t already. Why AI and CTV are a great match CTV and AI are transforming how advertisers connect with their audiences and improving the performance of their advertising campaigns in the CTV space. They work together to make advertising smarter and more enjoyable for everyone involved. AI uses sophisticated computer programs to analyze and understand data, while CTV refers to the streaming services that consumers use at home. But what makes them a great match in advertising? AI uses data to determine which TV ads are most exciting and relevant to certain people, and it can even adjust ads in real time to ensure viewers are always getting the most personalized experience. AI can provide suggestions to viewers based on previously watched content to help them find what they’d enjoy watching next. To sum it up, AI allows for: Precise targeting: AI uses data to determine which TV ads are most exciting and relevant to certain people. Personalization: AI can adjust ads in real time to ensure viewers are always getting the most personalized experience. Effective ad insertion: AI can provide suggestions to viewers based on previously watched content to help them find what they’d enjoy watching next. CTV facilitates these AI-driven strategies for enhanced user engagement and satisfaction. The rising popularity of CTV CTV has become increasingly popular as people change the way they watch TV. Instead of the traditional approach, more viewers are now choosing CTV platforms for their entertainment. One of the main reasons for this shift is that CTV offers greater flexibility and lets viewers watch content at their convenience. The ability to skip ads on many CTV platforms also improves the experience. CTV offers a great opportunity to interact with your target audience in a more engaging way. CTV allows for highly targeted advertising capabilities so you can reach specific demographics and households with tailored messages. Additionally, CTV provides valuable data insights that enable you to measure campaign effectiveness accurately. If you haven’t embraced this advertising channel yet, you may be missing out on a growing and engaged audience. Here are three reasons you should add CTV to your advertising strategy. Global video ad impressions As a global platform, CTV has the unique ability to reach audiences worldwide. Unlike traditional TV, CTV transcends geographical boundaries and brings marketers a global audience, which makes it an ideal channel for global ad campaigns. No matter your target audience, they’re consuming content on CTV. In fact, a recent study showed that 51% of global video ad impressions came from CTV in 2022. This abundance of global video ad impressions generates vast amounts of data, which AI can process in real time to help you make data-driven decisions and optimize your campaigns for diverse international audiences. AI can analyze viewer data from various regions, identify audience preferences and behaviors across borders, and tailor ad content accordingly. These data analysis capabilities ensure your ads get in front of the right viewers. Viewers prefer ad-supported CTV In 2020, the viewing time of ad-supported CTV surged by 55% while subscription video on demand decreased by 30%, according to TVision Insights. Viewers have a well-established preference for ad-supported CTV due, in part, to cost-effective access to premium content. Viewers are more engaged and less resistant to ads, as AI tailors ad content to viewer preferences and behavior to enhance ad relevance. AI-powered insights can also aid in viewer retention and help you optimize your CTV campaigns. By accommodating viewers’ preference for ad-supported CTV and harnessing AI to improve the ad experience, you’re more likely to be successful in your marketing efforts. CTV outpaces mobile and desktop for digital video viewing eMarketer recently reported that U.S. adults spend 7.5+ hours each day on CTV — more than half of their digital video viewing time. Comparatively, they only spend 37.5% of their viewing time on mobile and 10% on desktops and laptops. These statistics demonstrate that CTV has become the preferred platform for digital video consumption, as viewers enjoy larger screens with superior quality for an immersive experience. It's important to note that AI is an essential CTV marketing tool, as it allows for precise targeting and content optimization. By utilizing AI on CTV, you can take advantage of this trend and deliver more engaging and effective campaigns to a growing and engaged audience. How is AI already being used in CTV? CTV has been integrated with AI across various facets and has revolutionized the television landscape. Here's a look at how AI is already shaping the CTV experience: Generative AI ads Generative AI ads are taking CTV personalization to a whole new level. These innovative ads are customized versions of the same CTV ad to suit individual viewers. Some AI tools can generate several versions of the same CTV ad — swapping the actor’s clothing and voiceover elements like store locations, local deals, promo codes, and more — and can create up to thousands of personalized iterations in just a few seconds. Such capabilities are a game-changing approach to connecting with your audience. Next, we dive into the advantages and impact of generative AI ads, and explore their transformative role in CTV advertising. Contextual ads vs personal data Generative AI ads use personal data, such as viewing history and demographics, to create highly personalized ad experiences. This sets them apart from contextual ads, which rely solely on the content being viewed. Using AI to harness this data, you can move beyond traditional contextual targeting and ensure your ads connect with viewers on a more individualized level. Generative AI ads can be used to A/B test Generative AI ads are not just about personalization; they also open the door to A/B testing. Being able to create several versions of one ad quickly allows you to experiment with various ad elements, such as messaging, visuals, and calls to action, to identify what works best for different segments of your audience and drives the best performance. This flexibility is especially valuable for refining ad campaigns and maximizing their impact. What’s next for AI-generated ads like this? The potential of AI-generated ads is exciting. As AI technologies constantly advance, we can expect even more personalized and automated CTV advertising. It’s a good idea to keep up with the latest AI-driven innovations to create more effective ad campaigns in the fast-evolving CTV space. The possibilities are endless, and you’ll likely find the most success when you embrace AI in CTV advertising. Optimize streaming quality AI helps viewers enjoy more seamless CTV experiences. By assessing network speed and user preferences, AI optimizes video quality in real time to reduce buffering interruptions. For instance, streaming platforms use AI to adjust video settings based on a user's connection speed. This guarantees an uninterrupted and enjoyable viewing experience. Review content for compliance AI also has a part to play in quality assurance and compliance management. It assesses content alignment with technical parameters and moderates compliance with local age restrictions and privacy regulations. This means AI can identify and filter out unsuitable content to provide a safer and more enjoyable viewing environment for audiences while safeguarding brands from association with undesirable material. Voice command AI-powered voice command technology is increasingly used to control CTV viewing. This technology is embedded in streaming devices and smart TVs and allows viewers to interact with their CTV content through voice-activated commands. This personalizes the viewing experience and improves convenience, as it eliminates the need for remote controls. CTV-integrated voice assistants like Google Assistant, Amazon Alexa, Apple Siri, and Samsung Bixby offer a more human-like interaction with the television, allowing users to give commands and receive tailored responses. Content recommendations AI can offer content recommendations that provide viewers a more personalized and engaging experience. Major over-the-top (OTT) services like Netflix, Hulu, and Amazon Prime use AI-driven data analysis to deliver tailored content suggestions to their audiences. By analyzing user habits in detail, AI can recommend content based on factors such as actors, genres, reviews, and countries of origin. This personalized approach helps viewers discover content that matches their preferences and enhances their viewing experience. Advertising Programmatic ad buying, driven by AI, automatically matches ad placements to specific audience segments based on behavioral patterns. It improves ad delivery by moving away from gross rating points (GRP) to more intelligent and targeted placements. This benefits marketers by ensuring ads are seen by the right people at the right time. It’s also cost-effective for publishers, as it maximizes the sale of ad spots to suitable buyers. Automatic content recognition (ACR) technology, which AI powers, is integrated into smart TVs and streaming devices to improve ad relevance. It provides contextual targeting and extends the reach of ads across multiple devices. For example, platforms like Roku use ACR data to display ads to viewers who haven’t seen them on traditional TV. Similarly, Samba TV retargets mobile users based on IP address and aligns their viewing habits with their smart TVs. Demand-side platforms CTV advertising relies heavily on demand-side platforms (DSPs) to efficiently manage and optimize ad campaigns. These platforms use machine learning and AI in several important ways: Using machine learning and AI to address data fragmentation Data is abundant but fragmented when it comes to CTV advertising. DSPs are flooded with a massive amount of data, including information about households, viewer behavior, and viewing patterns. This data is far too much for manual analysis to handle effectively, which is where AI comes in. By integrating machine learning algorithms into DSPs, AI can harmonize this fragmented data and provide valuable insights and a holistic view of your audience. AI can process zettabytes of data in real time, which streamlines the decision-making process and empowers you to compete quickly for limited CTV impression opportunities. Predicting advertising outcomes with AI AI is quickly changing the way we predict and optimize advertising outcomes. TV buying and optimization platforms are now using AI to improve ad performance. With machine learning, these platforms can anticipate which ad creatives will produce the best results based on various non-creative factors. These include the context of the ad, the audience's profiles, the time of day it is displayed, and the frequency of the ad display. By relying on AI to make these predictions, you can make sure your campaigns are highly optimized for success and deliver more relevant, compelling ads to viewers. Optimizing generative ads AI is also driving optimization in generative ads. These personalized versions of the same CTV ad can be tailored to suit individual viewers. By utilizing AI-driven analytics, DSPs can process extensive amounts of data in real time and optimize generative ads to ensure they align with viewers' preferences and behaviors. This level of personalization is a game-changer in CTV advertising that boosts engagement and delivers content that truly resonates with the audience. Add AI to your CTV strategy today Integrating AI into your CTV strategy can help you stay competitive and ensure your ad campaigns are effective and engaging. At Experian, we’re ready to help you elevate your CTV advertising and implement AI as part of your strategy. Our solutions, such as Consumer View and Consumer Sync, provide valuable audience insights, enhance targeting capabilities, and optimize engagement on TV. Plus, our partnerships with leading media marketing solutions can help you achieve greater success through effective advanced television advertising. As you incorporate AI into your CTV strategy, you’ll be able to make more data-driven decisions, deliver more relevant content, and reach the right audience at the right time. Explore Experian's TV solutions and empower your CTV advertising with AI today. Start exploring Latest posts
The digital advertising landscape is undergoing a significant transformation with the gradual deprecation of third-party cookies. This shift necessitates the adoption of new strategies for audience targeting and data management. In our next Ask the Expert segment, we explore this evolution, discussing new strategies for audience targeting and data management in a world without cookies. We’re joined by industry leaders, Gabe Richman, Senior Director of Data Partnerships at The Trade Desk, and Chris Feo, Experian’s SVP of Sales & Partnership who spotlight The Trade Desk’s innovative approach to navigating a cookieless future. Tune in to our Q&A below to learn more about these topics and learn how the collaborative efforts of Experian and The Trade Desk offer a glimpse into the future of advertising. Cookieless IDs are the new face of identity in advertising Traditional tracking and targeting techniques are being replaced by more advanced and privacy-conscious methods. Unified I.D. 2.0 (UID2), led by The Trade Desk, exemplifies this shift, offering a new identifier based on encrypted email addresses or phone numbers. This approach not only caters to the evolving privacy regulations but also places greater control in the hands of consumers. UID2’s design fundamentally differs from cookies since it is rooted in transparency and consumer consent. UID2: A catalyst for industry-wide adoption UID2’s journey reflects a rising industry-wide recognition of its value across the industry. The adoption of UID2 by major publishers, demand-side platforms, and advertisers indicates a shift toward more sustainable and consumer-friendly approaches to identity in advertising. This is particularly evident in areas like connected TV (CTV), where UID2 is rapidly becoming a currency and standard. “The purpose of UID2 is not only to create a better ID for advertisers and publishers to achieve their objectives, but also to benefit the consumers. Unlike cookies, UID2 provides transparency and control to the consumers for the first time.”gabe richman, sr. director, data partnerships, the trade desk How Experian and The Trade Desk work together The partnership between The Trade Desk and Experian goes beyond adapting to the absence of cookies. Our joint efforts highlight a commitment to developing solutions that cater to advertiser’s needs while respecting consumer privacy, a balancing act becoming increasingly crucial in today’s digital ecosystem. The Trade Desk's emphasis on UID2 as a foundational element in the open web, campaign design, and activation is a testament to the potential of new identifiers in enhancing advertising efficacy. Similarly, our ability to utilize these identifiers to deliver detailed audience insights offers advertisers a powerful tool to remain effective in a post-cookie world. Experian’s role in the adoption of UID2 Experian's integration strategies have played a critical role in diversifying the applications of UID2. By partnering with The Trade Desk, we help broaden the reach and effectiveness of UID2 across various advertising channels. In terms of reach – by incorporating a prominent cookieless ID, we further amplify the reach of UID2. The increased adoption of this new ID allows the digital ecosystem the ability to interact using an alternative identifier, thereby broadening the potential audience. In terms of effectiveness – we help advertisers serve relevant ads to the right audiences, ensuring the relevance of the ads and control over their frequency. Targeting with Geo-Indexed audiences The Trade Desk works with Experian to ingest and host our syndicated audiences. This partnership gives The Trade Desk’s clients access to over 2,400 syndicated audiences that span across eight verticals. This includes access to our new Geo-Indexed audiences that allow brands to reach consumers and households based on geographic regions that over-index for a common set of attributes, ultimately offering brands a targeting solution that prioritizes both consumer privacy and accuracy. What a future beyond cookies looks like Looking ahead, the focus in advertising is not solely on replacing cookies but on a broader evolution of the industry. This includes continuing to apply machine learning technologies, like artificial intelligence (AI), to enhance ad personalization and effectiveness. The interplay between creative content, audience insights, and privacy-compliant targeting will become increasingly important as the industry evolves. As cookies become a thing of the past, the initiatives spearheaded by The Trade Desk and Experian will likely set the tone for the next era of digital advertising, and emerging solutions like UID2 are leading the way. Watch the full Q&A Visit our Ask the Expert content hub to watch Gabe and Chris' full conversation about cookieless advertising. In their conversation, Gabe and Chris share more about UID2, consumer transparency, and the importance of consumer data for targeted advertising. Watch now About our experts Gabe Richman, Sr. Director, Data Partnerships, The Trade Desk Gabe Richman is the Senior Director of Data Partnerships at The Trade Desk where he focuses on global identity strategy and platform partnerships as well as driving UID2 and EUID adoption across the broader ecosystem. Prior to joining The Trade Desk in 2021, Gabe held various roles in AdTech at HealthVerity, Wunderkind and LiveRamp. For the last decade Gabe has taken pride in helping advertisers and platforms alike demystify the complex identity landscape and embrace the change needed to preserve the open internet. Gabe is a graduate of the University of Maryland and resides in Los Angeles. 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