Bridging disparate data in a fragmented world
In today’s world, consumers engage with brands across multiple platforms, including social media, online marketplaces, in-store experiences, and customer service touchpoints. However, the main challenge for marketers and advertisers is the fragmentation of customer data across these different channels. Each platform generates its own set of data, which is stored in different databases and formats. Integrating these various data sources to create a unified view of the customer is a complex task involving technology and understanding customer behavior across different digital and physical channels.
Businesses must link these data fragments to avoid creating a disconnected customer experience. For example, a person may browse products on a mobile app, ask questions through a customer service chat, and eventually purchase in an online marketplace. Traditional data analysis methods often need to recognize these activities as those of a single customer, which can result in missed opportunities to deliver personalized customer experiences across the customer journey.
Identity resolution: The key to a unified customer experience
Connecting online interactions across various platforms is a challenge for brands. Identity resolution enables enterprises to overcome this challenge by stitching together disparate signals and records to orchestrate experiences and analyze outcomes more effectively. By pairing Experian’s identity capabilities with AWS Clean Rooms, enterprises can securely collaborate with their partners to derive deeper insights without exposing sensitive underlying data sets.
This partnership between AWS and Experian enables effective matching between disparate data sets, bolstering privacy-enhanced media planning, insights, data enrichment, media activation, and measurement use cases. Depending on their distinct needs and existing identifiers, customers can use two specific offerings of Experian’s identity resolution solutions paired with AWS Clean Rooms.
Experian’s identity resolution products ensure a frictionless brand experience across various channels, enhancing the customer journey from start to finish. Brands can employ our adaptable identity resolution solutions to forge connections between contextual, behavioral, lifestyle, and purchase-based data sources, assembling comprehensive customer profiles. Use dependable digital data to make informed decisions and elevate consumer engagement. Advanced deterministic and probabilistic features, combined with data science and cutting-edge technology, work hand in hand to mitigate risk and uphold data privacy.
Such recognition enables a more comprehensive understanding of your clientele, fostering trust and amplifying campaign effectiveness by utilizing securely managed, standardized customer data. With this strategic approach, businesses can achieve their objectives regulatory-compliant.
The consumer perspective: Why consistency matters
Data fragmentation can lead to inconsistent experiences for consumers, which can be frustrating and erode brand trust. For instance, imagine receiving a promotional email for a product you already purchased through an app or being targeted for a product you decided against.
Consumers are increasingly tech-savvy and demand a seamless, integrated experience regardless of how they interact with a brand. They want to feel valued and recognized at every touchpoint and don’t care about the complexities of data analytics. As a result, brands face significant pressure to get identity resolution right.
Data security and privacy: A Fort Knox for your data
AWS Clean Rooms empowers their customers to establish a secure data clean room within minutes, facilitating collaboration with any other entity within AWS. This fosters the generation of unique insights regarding advertising campaigns, investment decisions, clinical research, and more. With AWS Clean Rooms, the need to store or maintain a separate copy of data outside the AWS environment for subsequent dispatch to another party for consumer insight analysis, marketing measurement, forecasting, or risk assessment becomes obsolete.
AWS Clean Rooms provides an expansive set of privacy-enhancing controls for clean rooms. This includes query controls, query output restrictions, and query logging that allows customers to tailor restrictions on the queries executed by each clean room participant. Moreover, AWS Clean Rooms include advanced cryptographic computing tools that maintain data encryption—even during query processing—to adhere to stringent data-handling policies. This process employs a client-side encryption tool—an SDK or command line interface (CLI)—that utilizes a shared secret key with other participants in an AWS Clean Rooms collaboration.
With a wealth of expertise in data privacy management, Experian enhances campaign effectiveness and fosters trust by managing standardized customer data securely. By using the identity graph, you can preserve a unique identity for each customer. This strategy enables you to comprehensively understand your clientele and reach your business objectives in a regulatory-compliant manner.
The future of data-driven marketing starts here
AWS customers can use AWS Clean Rooms to establish their own clean rooms in mere minutes, initiating the analysis of their collective data sets without sharing their underlying data with each other. Customers can use the AWS Management Console to choose their collaboration partners, select data sets, and configure participant restrictions. With AWS Clean Rooms, customers can effortlessly collaborate with hundreds of thousands of companies already using AWS without needing to move data out of AWS or upload it to a different platform. When running queries, AWS Clean Rooms accesses data in its original location and applies built-in, adaptable analysis rules to assist customers in maintaining control over their data.
Coupled with Experian’s trusted data privacy management and unique Experian ID, businesses can effectively manage customer data, secure partners’ communication, and achieve regulatory-compliance objectives. This combination allows companies to use data-backed insights to supercharge their marketing initiatives, resulting in more meaningful customer interactions, improved match rates, and business success.
About the authors
Kalyani Koppisetti, Principal Partner Solution Architect, AWS
Kalyani Koppisetti is a technology leader with over 25 years of experience in the Financial Services Industry. In her current role at AWS, Kalyani advises financial services partners on best-practice cloud architecture. Kalyani works closely with internal and external stakeholders to identify industry technical trends, develop strategies, and execute them to help Financial Services Industry partners build innovative solutions and services on AWS. Technical and Solution interests include Cloud Computing, Software-as-a-Service, Artificial Intelligence, Big Data, Storage Virtualization and Data Protection.
Matt Miller, Business Development Principal, AWS
In his role as Business Development Principal at AWS, Matt drives customer and partner adoption for the AWS Clean Rooms service specializing in advertising and marketing industry use cases. Matt believes in the primacy of privacy-enhanced data collaboration and interoperability underpinning data-driven marketing imperatives from customer experience to addressable advertising. Prior to AWS, Matt led strategy and go-to-market efforts for ad technologies, large agencies, and consumer data products purpose-built to inform smarter marketing and deliver better customer experiences.
Tyler Middleton, Sr. Partner Marketing Manager, Experian Marketing Services
Tyler Middleton is the Partner Marketing Lead at Experian. With almost 20 years of strategic marketing experience, Tyler’s focus is on creating marketing strategies that effectively promote the unique value propositions of each of our partners’ brands. Tyler helps our strategic partners communicate their mutual value proposition and find opportunities to stand out in the AdTech industry. Tyler is an alumnus of the Seattle University MBA program and enjoys finding new marketing pathways for our growing partner portfolio.
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In our Ask the Expert series, we interview leaders from our partner organizations who are helping lead their brands to new heights in AdTech. Today’s interview is with Samantha Zhang, Senior Data Scientist, and Jim Meyer, General Manager of the DASH TV Universe Study at the Advertising Research Foundation (ARF). DASH is an annual tracking study conducted by the ARF to define and better understand TV audience behavior and household dynamics. What does DASH measure, and how does it help the industry understand TV consumption today? By capturing hundreds of individual- and household-level data points from each respondent in a rigorous and nationally projectable sample, DASH creates a comprehensive picture of U.S. consumer TV “infrastructure” – how America watches. Core elements in DASHElements that create context in DASHTV setsLocation | brand | smartness | service modes | sources DemographicsConnected devices Game consoles |video players | streaming devicesYesterday viewing Daypart | TV/device genre | Out-of-home viewingMobile devicesOwners | sharing usersShoppingOnline and in-store | Exposure to major RMNsInternet serviceModes | ISPs | connectivity by device Streaming audio Streaming TVSVOD/AVOD tiers and sharing | FAST Email accounts and apps Live TV Modes of access | including casting from devices Social media For example, DASH gathers: Data on every TV set, including brand, room location, age, “smartness,” and connection devices and modes Household connectivity and video service data, even in homes with no TV set Internet Service Providers (ISP) and TV service usage, including Multichannel Video Programming Distributors (MVPDs), virtual vMVPDs, streamers (ad-supported and premium), and Free Ad-Supported Television (FAST) channels Person-level ownership and usage of video-capable mobile devices, including smartphones, tablets, and laptops Measures of viewing and co-viewing across dayparts, devices, and services Additional modules covering shopping and retail media networks, streaming audio, social media, email, and apps Broad coverage and granularity make DASH a uniquely robust source of truth for practitioners across the industry, including measurement experts and ad programming strategists. DASH also reports regularly (and publicly) on key industry dynamics. DASH identified a growing segment of device-only viewers – now nearly 9 million households that watch TV, but do not own a TV set – and highlighted the implications of that trend for traditional ratings systems based only on households with TV sets. Households (HHs – million)2025 HHs (M) U.S. penetrationChange vs. 2024 (M)Total US134.8100%+2.7Connected TV (CTV)114.685%+2.1TV (Set)124.292.2%+1.1Device-only8.86.6%+1.6TV-Accessible133.198.7%+2.7 DASH called out the rise in app-based pay TV and proposed a new connection framework that better represents the modern TV world, in which linear and streaming overlap. DASH also defines the universes of households reachable with advertising. This graphic, for example, shows how all ad-supported linear and streaming properties in aggregate define the true scale of TV advertising. While 35 million households (and growing) are reachable only with streaming ads and 13 million (and falling) only with linear ads, most households are reachable with both, underscoring the importance of understanding the “overlap.” Who uses DASH data, and what decisions does it help inform? There are three primary users of DASH, each with its own use cases: Measurement providers, including Nielsen, use DASH to calibrate viewership data, turn household data into persons data (and vice versa) and estimate potential reached audiences–what the providers call media-related universe estimate (MRUEs)–for the calculation of ratings. Not surprisingly, measurement companies were the first to see the value that an independent TV universe study could provide. Media companies, including major broadcasters and streamers, use DASH to add context and color to their ad sales presentations – and to track the measurement providers, whose ratings play a major role in valuing ad inventory. AdTech companies, including Experian, use DASH to create high-value audience segments for activation. The recent accreditation of DASH by the Media Rating Council (MRC) and adoption by Nielsen as an input to its TV ratings have generated interest from a broad range of companies. We are actively pursuing new licensees and partners to make DASH more useful within, and even outside, the TV ecosystem. What does MRC accreditation signify, and why is it meaningful for DASH? MRC accreditation means DASH passed a rigorous audit conducted by Ernst & Young over many months, which validated our methodology, controls, and data quality. MRC accreditation establishes that DASH is an industry-standard dataset. While the service provider normally announces its own accreditation, the MRC took the unusual step of issuing its own release on DASH, announcing the accreditation of DASH for TV universe estimation and endorsing the study for broader, cross-media use. How does Experian use DASH data to build audiences? The segments combine specific TV usage habits and behaviors from DASH with Experian data on demographics, spending, and other contextual inputs to create a fuller view of consumer viewing behavior. They are designed to be valuable to advertisers in many categories and planning contexts – and to be customizable to fit advertisers’ media targets. The segments can be used to: Apply or suppress audiences to improve target coverage across a campaign Better align media and creative Reach elusive but high-value viewers, such as Ad Avoiders Drive valuable consumer behavior Achieve specific advertising objectives What are some practical use cases for DASH-based audiences? Here are some practical use cases for four different kinds of DASH segments in five different advertiser categories. Travel Co-WatchersA couples-only resort uses TV Co-Watching Households without Children to strengthen target reach and ad memory recallA big theme park destination uses TV Co-Watching Households with Children to reach families in moments of togetherness Home Entertainment TV Owners and Brand LoyalistsA premium TV manufacturer uses the overlap of Multi Brand TV Owners and Single Brand TV Loyalist Households to market its newest TV model to its most loyal consumers. Fast Food Screen Size ViewersA fast food chain with a high-impact new brand campaign uses Large Screen TV Viewers to better align the media and creativeThat same fast food chain uses Small-Screen TV Viewers to drive store traffic by increasing exposure of its retail campaign among on-the-go viewers Financial Services Cord Cutters A personal cost management app and a cash-back credit card target Streaming-First Cord Cutter Households to reach young, tech-savvy, cost-conscious consumers Thanks for the interview. Where can readers learn more about DASH? We started work on DASH seven years ago, and it’s been fun to watch it “grow up.” Our partnership with Experian is a big step toward putting DASH to work for advertisers and agencies. To learn more, visit our site at https://theARF.org/DASH or contact us at DASH@theARF.org. Contact us About our experts Samantha Zhang, Senior Data Scientist at ARF Samantha Zhang is a Senior Data Scientist at the Advertising Research Foundation working on the DASH TV Universe Study, with additional research spanning areas including attention measurement, digital privacy, and artificial intelligence. Jim Meyer, General Manager, DASH, at ARF Jim Meyer is general manager and co-founder of the ARF DASH TV Universe Study and managing partner of Golden Square, LLC, which advises media and research technology companies on growth strategy and development. Latest posts
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