
As Oracle exits the advertising space, we understand that this may present a challenge. Experian is here to support you with a seamless transition in your audience targeting. As one of Oracle’s primary data providers that powered their audiences, we’ve mapped Oracle audiences to Experian audiences, helping you to switch your audience targeting with no impact on your campaign’s performance.
In this blog post, we highlight four audience categories that we know marketers are actively seeking to replace and target: auto, restaurants, lifestyle and interests, and demographics.
Experian’s approach to best-in-class audience targeting
- Experian’s 2,400+ syndicated audiences are available directly on over 30 leading television, social, programmatic advertising platforms, and directly within Audigent for activation within private marketplaces (PMPs).
- Reach consumers based on who they are, where they live, and their household makeup. Experian ranked #1 in accuracy by Truthset for key demographic attributes.
- Access to unique audiences through Experian’s Partner Audiences available on Experian’s data marketplace, within Audigent for activation in PMPs and directly on platforms like DirectTV, Dish, Magnite, OpenAP, and The Trade Desk.
Experian’s audience solutions are rooted in offline, deterministic data — like name, address, phone number, and email — that rarely changes. Our deep understanding of people in the offline and digital worlds provides marketers a persistent linkage of known offline data and digital identifiers, which means you get accurate and consistent audience targeting across all channels.
Auto, Cars, and Trucks

As the premier auto partner contributing to Oracle auto segments, Experian can help you reach and target consumers based on their known and predictive auto shopping behaviors. Experian’s auto audiences are built utilizing insight from our North American Vehicle Database℠ and other data attributes from Experian Marketing Data to provide highly accurate audiences for digital and TV advertising.
Unlike some of our competitors who are also positioning themselves as a replacement audience provider, Experian owns all our Vehicle, Consumer, and summarized Credit data under one umbrella and refreshes our audiences every 30 days. This ensures tighter audience composition, superior data hygiene, and best in-class data fidelity, which means you get to target the most accurate audiences. With over 750 syndicated audiences segmented by make, model, price, vehicle age, fuel type, and more, our data is accessible through Experian’s distribution power across all platforms — digital, TV, programmatic, and social — allowing activation wherever our partners need it.
Here are the 10 most popular Experian audiences that align with Oracle’s auto audiences:
| Audience by Oracle | Experian audience |
| Audiences by Oracle > Auto, Cars and Trucks > In-Market > Body Styles > SUVs and Crossovers | Autos, Cars and Trucks > In Market-Body Styles > SUV and CUV |
| Audiences by Oracle > Auto, Cars and Trucks > In-Market > Body Styles > Trucks > Mid-Size Pickup Trucks | Autos, Cars and Trucks > In Market-Body Styles > Mid-Size Truck |
| Audiences by Oracle > Auto, Cars and Trucks > In-Market > Body Styles > Trucks > Full-Size Pickup Trucks | Autos, Cars and Trucks > In Market-Body Styles > Full-Size Trucks |
| Audiences by Oracle > Auto, Cars and Trucks > In-Market > Body Styles > SUVs and Crossovers > SUVs > Small to Mid-Size SUV | Autos, Cars and Trucks > In Market-Body Styles > Small Mid-Size SUV |
| Audiences by Oracle > Auto, Cars and Trucks > In-Market > Body Styles > SUVs and Crossovers > SUVs | Autos, Cars and Trucks > In Market-Body Styles > SUV |
| Audiences by Oracle > Financial Services > Insurance > In-Market > Auto Insurance | Lifestyle and Interests (Affinity) > In-Market > Auto Insurance |
| Audiences by Oracle > Auto, Cars and Trucks > Merchant Category Audiences > Auto Insurance High Spenders | Retail Shoppers: Purchase Based > Automotive (Cars & Trucks) > Auto Insurance: High Spenders |
| Oracle BlueKai > In-Market > Auto, Cars and Trucks > Condition > Used Cars > More than 5 years old | Autos, Cars and Trucks > In Market-New/Used > Used car 6+ years |
| Audiences by Oracle > Auto, Cars and Trucks > In-Market > Condition > Used > Less than 5 years old | Autos, Cars and Trucks > In Market-New/Used > Used car 0-5 years |
| Oracle BlueKai > In-Market > Auto, Cars and Trucks > Classes > Cars > Compact and Sub-Compact Cars | Autos, Cars and Trucks > In Market-Body Styles > Compact or Subcompact Cars |
Lifestyle and Interests

Experian’s Lifestyle and Interests data helps you reach and target consumers based on their predicted lifestyle and behavioral characteristics with data sourced from consumer surveys, research panels, and online behaviors, enabling more personalized and impactful marketing strategies.
Here are five of the most popular Experian audiences that align with Oracle’s lifestyle and interest audiences:
| Audience by Oracle | Experian audience |
| Audiences by Oracle > Hobbies and Interests (Affinity) > Pets > Dogs | Lifestyle and Interests (Affinity) > Pets > Dog Owners |
| Audiences by Oracle > Hobbies and Interests (Affinity) > Pets > Cats | Lifestyle and Interests (Affinity) > Pets > Cat Owners |
| Audiences by Oracle > Hobbies and Interests (Affinity) > Health and Fitness > Exercise | Lifestyle and Interests (Affinity) > Health & Fitness > Fitness Enthusiast |
| Oracle DLX (Datalogix) > DLX Finance > Investors | Lifestyle and Interests (Affinity) > Investors > Active Investor |
| Audiences by Oracle > Lifestyles > Merchant Category Audiences > Sports Lovers | Lifestyle and Interests (Affinity) > Sports and Recreation > Sports Enthusiast |
Demographics

Experian’s demographic data allows marketers to tap into the accurate data from Experian Marketing Data to refine audiences to meet a brand’s target persona. Our demographic audiences deliver insight into age, gender, income, and household attributes such as home ownership, presence of children in the household, and length of residence.
Based on customer feedback, we have expanded our range of age-based audience segments. These new segments cover various adult age groups and gender distinctions (e.g., Adult Females 18-39, Adult Males 35-54).
Here are seven of the most popular Experian audiences that align with Oracle’s demographic audiences:
| Audience by Oracle | Experian audience |
| Audiences by Oracle > Demographics > Validated Demographics > Household Income > HHI: $100,000+ | Demographics > Household Income (HHI) > $100,000+ |
| Audiences by Oracle > Real Estate and Home Property Services > Real Estate Attributes > Ownership > Home Owners | Demographics > Homeowners/Renters > Homeowner |
| Audiences by Oracle > Demographics > Age Groups > Adults 25-54 | Demographics > Ages > 25-54 |
| Audiences by Oracle > Demographics > Gender > Females | Demographics > Gender > Female |
| Audiences by Oracle > Demographics > Validated Demographics > Age Groups > Adults 25-54 > Females 25-54 | Demographics > Ages > Female 25-54 |
| Audiences by Oracle > Demographics > Age Broad > Ages 40-49 | Demographics > Ages > 40-49 |
| Audiences by Oracle > Demographics > Validated Demographics > Age Broad > Ages 65+ | Demographics > Ages > 65+ |
Quick Service Restaurants (QSR)

Here are six of the most popular Experian audiences that align with Oracle’s QSR audiences:
| Audience by Oracle | Experian audience |
| Audiences by Oracle > Restaurants > Merchant Category Audiences > In Store QSR Fast Food Frequent Spenders | Retail Shoppers: Purchase Based > Food and Drink > Restaurants: Fast Food/QSR QSR Frequent Spenders |
| Audiences by Oracle > Restaurants > Merchant Category Audiences > QSR Chicken Frequent Spenders | Retail Shoppers: Purchase Based > Food and Drink > Restaurants: Fast Food/QSR Chicken Frequent Spenders |
| Audiences by Oracle > Restaurants > Merchant Category Audiences > QSR Burgers Frequent Spenders | Retail Shoppers: Purchase Based > Food and Drink > Restaurants: Fast Food/QSR Burger Frequent Spenders |
| Audiences by Oracle > Restaurants > Cuisine Type > Sandwiches | Retail Shoppers: Purchase Based > Food and Drink > Restaurants: Fast Food/QSR Subs and Sandwich Frequent Spenders |
| Audiences by Oracle > Restaurants > Dining Type > Casual Dining | Retail Shoppers: Purchase Based > Food and Drink > Restaurants: Casual Dining Frequent Spenders |
| Audiences by Oracle > Restaurants > Dining Type > Coffee Shops and Cafes | Retail Shoppers: Purchase Based > Food and Drink > Restaurants: Coffee Frequent Spenders |
Switch from Oracle to Experian audiences with ease
Experian is here to make it easy for advertisers and agencies to find the right audience solutions after Oracle’s exit. By partnering with us, you work with a single data provider that offers access to a diverse range of audiences across multiple categories, including political and holiday shopping. Our audiences are available for activation on the leading demand, supply, social, and TV platforms.
Reach out to your account representative or our audience team for information about our comprehensive audience mapping and finding the right audiences for your campaigns.
Download our audience lookbook to discover more about Experian’s audiences.
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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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