Cuebiq’s mission, as an offline intelligence and measurement company, is to quantify how digital marketing impacts offline consumer behavior. This case study shows how Cuebiq partnered with Experian to continue delivering in-store lift analyses despite signal loss. To achieve this, Cuebiq used Experian’s Activity Feed to resolve digital ad exposures to mobile ad IDs, so that marketers could know the effectiveness of their media campaigns on in-store visits and purchases.
Even as Google backs away from third-party cookie deprecation, the need for flexible, future-proof identity solutions remains. By working with Experian, Cuebiq could help their clients more accurately measure their campaigns and optimize their media.
Challenge: Increasing match rates across digital platforms
Cuebiq wanted to enhance how well they connect digital ad exposures, across web, mobile, and connected TV (CTV), to mobile ad IDs (MAIDs), of consumers who visited their clients’ stores. They needed a single technology partner who could collect data across these environments and improve these connections.
With the ability to resolve exposures to households, individuals, and MAIDs to then facilitate attribution of digital exposures to offline store visitation, Cuebiq could continue to provide accurate reports on how digital ads impact offline consumer behavior. This clarity in data enables their clients to fine-tune their marketing strategies.
Cuebiq’s key objectives included:
- Resolving digital exposures to MAIDs
- Increase overlap of offline and online data
- Improving the effectiveness of offline measurement offerings
Activity Feed: The solution to increase match rates
Experian’s Activity Feed pulls together fragmented digital event data from all digital channels, including browsers like Safari and Firefox that restrict traditional tracking methods. Activity Feed ingests and ties digital ad exposure and website activity data to household or individual profiles hourly, helping client’s associate ad exposures to impact by a household or individual. Activity Feed plays a crucial role in overcoming fragmented data and helping marketers accurately measure their cross-channel marketing efforts.
Cuebiq used Activity Feed to resolve exposure data from all environments, even cookieless ones, to a single household or individual and saw significantly higher match rates. Cuebiq received their clients’ ad exposure data resolved to mobile ad IDs (MAIDs) and correlated it to their clients’ in-store visitation and sales. To do so, Cuebiq implemented the Experian pixel, which they placed to track all their marketers’ impressions (mobile, CTV, web traffic, etc.).
The Experian pixel collects information in real-time, such as:
- Timestamp
- Cookies
- Device ID (MAID/CTV) when available
- IP address
- User-Agent
- Impression ID
“Before we started working with Experian, we couldn’t fully maximize ad views across the complex digital landscape. In just a few weeks, they were able to maximize the match rate across the fragmented digital inventory, solving a huge problem when it comes to cross-channel attribution.”
Luca Bocchiardi, Director of Product, Cuebiq
Results
Activity Feed combines separate data streams and matches them back to a household. This enables Cuebiq to expand household IDs and accurately identify MAIDs that are seen in-store for cross-channel measurement. Over a 21-day period, Cuebiq passed ~1 billion events to Experian. Activity Feed resolved 85% of total events to a household, 91% of which were tied to MAIDs.
By implementing Activity Feed, Cuebiq was successfully able to:
- Gain clearer insights into the success of their client‘s campaigns
- Match consumer engagements in a privacy-compliant manner
- Tell the story of the key performance indicators (KPIs) related to their marketing efforts
A solution for measurement across cookied and cookieless environments
Activity Feed is prepared for whatever the future of signal loss holds in store, capable of using third-party cookies and alternative IDs, like UID2.0s, ID5 IDs, hashed emails, and IPs for identity resolution. Experian remains fully committed to exploring a suite of next-generation solutions and prioritizing continued testing of different industry solutions to help customers maintain consumer visibility amidst signal loss. We’ve identified six viable alternatives to third-party cookies, how these alternatives fall short, and how Experian can help you navigate these alternatives.
“Experian’s customer service is extremely efficient and collaborative. We trust them to keep putting our business first long-term.”
Luca Bocchiardi, Director of Product, Cuebiq
Download the full case study to discover how Cuebiq used Activity Feed to overcome their challenges. Your path to maximizing match rates and resolving data from cookieless environments starts here.
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About Cuebiq
Cuebiq is transforming the way businesses interact with mobility data to providing a high-quality and transparent currency to map and measure offline behavior. They are at the forefront of all industry privacy standards, establishing an industry-leading data collection framework, and making it safe and easy for businesses to use location data for innovation and growth.
To learn more, visit their website at www.cuebiq.com
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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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