
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
- 2,400+ syndicated audiences powered by marketing data ranked #1 in accuracy by Truthset offers advertisers the ability to reach people based on demographic, geographic, and behavioral attributes
- Our audiences span 15 data categories including demographics, auto, retail purchases, lifestyles and interests, financial, and travel
- Audiences are available on-the-shelf on 30+ major ad platforms, including TV, social, and programmatic, or distribute them to 200+ media platforms
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.
Latest posts

On some level, collecting data and analyzing it to find meaningful conclusions has always been part of how marketers go about connecting with consumers. Their strategies have improved dramatically over time, though. Perhaps in a previous era, marketing executives were only able to make sweeping generalizations about large swathes of the population. But, as marketers have gathered more data on individual consumers, they’ve found ways to fine-tune their searches. They’re no longer messaging to groups in vague terms. Smart Data Collective recently examined the marketing world’s transition away from broad stereotyping toward better targeted forms of data mining. Josh Brown, a member of the marketing team at business and IT consulting company Iconic Mind, argues that this era of overgeneralization is coming to an end. We now have the capability to zoom in on the specific customer. “Big data is how successful companies are building more detailed models of consumer behavior,” Brown wrote. “Instead of relying on the traditional demographic models that marketers used when we were operating in a mass consumption environment and had nothing better, big data capitalizes on developing market trends to allow businesses to become far more specific when segmenting their customers.” Brown cited Amazon.com as an example. The online superstore is notable for its targeted recommendations of products that shoppers see every time they log on to the site – the advisements are impressive because they’re usually right up the customer’s alley. Amazon doesn’t generate these ideas by making guesses based on whether the consumer is old or young, male or female – instead, the site takes in specific information about people’s buying histories and looks for similar products. This approach is quickly becoming mainstream. It’s not hard to understand why – people don’t like being reduced to profiles of their demographic characteristics. Consumers are expecting more from the companies they do business with. Thanks to the rapidly improving technologies that companies use for data collection, marketers can be more targeted and make more intelligent interactions. However, to take advantage of these new technologies, marketers need to maintain high quality data. Without a data quality strategy, customer information will be spread out across the organization, making it difficult to make intelligent marketing offers. To learn more about improving your understanding of consumers, check-out our infographic on building a single customer view.

Adam Garone is the CEO & co-founder of Movember, the annual world-wide charity movement dedicated to changing the face of men's health – all through the power of the moustache. To date, over 3 million moustaches have been grown and supported for Movember, raising more than $440 million to change the face of men's health. Adam kicked off day two of the EMS Client Summit by saying he’s a lucky guy because he gets “to wear a 1993 porn stash year-round.” That line got a laugh, but Adam’s storytelling around Movember really caught the attention of Summit attendees. Adam had learned that prostate cancer affects as many men as breast cancer does women, and while discussing this fact over beers with his brother in Australia, the idea for Movember was born. They took the Aussie slang for moustache (“mo”) and combined it with “November” (a good month for men to grow them) to create the name. That was in 2003 and over the last decade, Movember has become a global movement around prostate and testicular cancer awareness, as well as men’s mental health issues. Watch his full presentation below: [Watch video on YouTube] Here are some cool facts cited by Adam: Everyone who grows a moustache for Movember is a “celebrity ambassador.” Last year, 2.7 billion conversations about Movember and men’s health issues were generated during the month of November. Most foundations go out with a “fear-based message” (x number of men die from cancer each year, for example). Movember has never done that. They encourage nicknames (i.e., participants are called “mo-bros”) and want people to have fun with it. Adam’s message: don’t be part of it because you’re scared, but because you will be fine and you get to help others. Each year they totally revamp their brand, changing the look, feel and tone. A few years ago their theme was “The Modern Gentleman” and last year it was “Movember and Sons,” and played off the relationship between father and son. Movember raised $145 million last year. They put 10% of the funds into a pool that goes towards research around other diseases. Adam says this kind of collaboration is to help reduce the heaving competition amongst charities that typically compete for donations. Key takeaways when it comes to growing a foundation (or business) from the ground up: Start with a great idea – naivety is good Rely on strong leadership –have a clear vision and detailed plan and work really, really hard Recruit amazing people – preserve culture and values During rapid growth, keep it simple—stay true to your core Brand management is key – sometimes you have to say no to potential partners because they don’t fit with your brand (in a humble way, of course) Know your customers – inspire them to become your ambassadors Partnerships are key Never underestimate a room full of people

These days, there are a number of buzzwords being thrown around the marketing industry and the data management space. One of the biggest? Say it with me: Big Data. NPR argued last December that ‘big data’ should’ve been the “word of the year,” in part due to the re-election of President Barack Obama. Obama’s campaign managers didn’t let the Republicans’ monetary advantage discourage them. Instead, they gathered information on their voters and compiled important analytics based on that information. By handling this mass of data in an organized and well thought out process, they were able to more effectively appeal to voters and ultimately win the re-election. Marketers and corporations across the country were inspired by the campaign’s success, and have turned to big data to solve their problems as well. Anyone who catches the news on a regular basis, shops online, or owns a smartphone can see this evolution firsthand. However, it’s worth mentioning that this progression doesn’t necessarily mean “big understanding” or “big information.” Many companies are faltering in their efforts to harness big data and make real use of it. The pool of information is constantly changing, and as so many businesses rush to gather the data in real-time, it becomes even more challenging to keep pace and actively comprehend information as it becomes available. And the challenges go beyond the initial harnessing of the data. As big data continues to grow, companies are running into issues of incorrect and duplicate data in their systems. This erroneous data is a result of poor processes that companies have in place, and oftentimes begins at the point of data input. For a number of companies, data input is performed on a daily basis via their call centers. When incorrect data is recorded, it prevents sales representatives from getting leads in a timely manner, and hampers them further when they try to contact the correct individuals seeking assistance. The resulting slower response time then goes on to impact a company’s SLA and credibility to the population they serve. There is no doubt that when processed correctly, big data can be integral to a company looking to improve their understanding of the customer’s needs and wants. But data quality is an important consideration during the transition, and one that must be confronted before big data can reveal all it has to offer. To learn more about big data and how it relates to the data quality initiatives that may be taking place within your organization, watch Experian QAS’ webinar, “Ensuring Data Quality in your Big Data Initiative.” Learn more about the author, Erin Haselkorn