Geo-based Predictive Spend and Geo-based Spend History are Experience OS extensions, powered by the data of Mastercard.
Geo-based predictive targeting enables you to target anonymous users who are likely to engage and spend on various preset categories (for example, Children’s Apparel, Jewelry, Beauty Products, and many more), based on proprietary predictive models and localized consumer spending data provisioned by Mastercard.
See the list of categories for targeting.
Geographical coverage
Geo-based predictive targeting is currently available for the following countries:
Australia | Austria | Belgium | Brazil |
Canada | Denmark | Finland | Germany |
Ireland | Italy | Malaysia | Netherlands |
New Zealand | Norway | Singapore | Spain |
Thailand | United Kingdom | United States |
Note that category availability is not uniform across geographies, as certain subsets of categories might only be available for a subset of countries. This is primarily true for the Predictive Spend categories, which are currently supported mostly in the United States. Additional countries will be added gradually.
See the full availability in the Predictive targeting category lists tables.
When you select a geo-based category to target in an experience, the number and list of countries where targeting is available appears.
Click the link to see the specific countries:
How it works
The extension evaluates the user’s geographical location in real time, based on the user’s IP address and the geographies it maps to. It then evaluates whether users in that geographical location are considered highly likely to spend on any of the given categories based on a propensity scores that are calculated by Mastercard predictive models and datasets. If the propensity score for the user’s location is high for the chosen category, the user is targeted and receives one of the variations in the experience; if the score is low, the user is not targeted.
Determining high and low scores
Each location is assigned a propensity score for each measured category. A high score is one in the top 20% percent. So a user in a location with a score in that range is targeted, and a user in a location with a score in the bottom 80% is not.
You don't need to specify any location to set up a targeted experience leveraging Geo-based Predictive Targeting conditions. The geo-based evaluation is done automatically, referencing all relevant data points to determine whether a user should be targeted.
Targeting conditions
The two extensions map to the two available condition types, which can be used separately or together, and work similarly to every other available targeting condition:
- Locations with high probability to spend: Targets users based on the geo-based predictive models.
- Locations with high spend history: Targets users based on the historical consumer behavior observed in their zip code.
Learn more about Targeting Conditions.
Use case examples
Targeted experiences and content personalization are especially relevant to category promotions or hero banner optimization on the homepage, for example:
- E-commerce:
Offer high-end brands for users in zip codes with high scores for luxury retail, and money-savers for users in areas with a preference for discount stores. - Financial institutions:
Promote different credit cards (travel, premium) to users in areas with high scores for respective categories (international air travel, high net worth consumers). - Other business areas:
Offer tools or decor items to high-spend areas for home improvement, beauty subscriptions to high-spend areas for cosmetics, and so on (pet care, new parents, consumer electronics, and more).
Best practices
The best use of Geo-based Predictive Targeting is to target users for whom you haven't yet collected any behavioral data. This includes anonymous or first-time visitors who would otherwise default to a non-personalized, sub-optimal experience.
In practice, this means that the best way to incorporate Geo-based Predictive Targeting into a campaign is in targeted experiences, as follows:
- The top-most experiences are aimed at known users, based on behavioral targeting conditions or audience membership.
- Next, create Geo-based Predictive Targeting experiences.
- At the bottom, place the default experience.
See this arrangement illustrated in the following screen capture, where tech enthusiasts in an audience are targeted first; next, users are targeted because they have an affinity to tech; the next tier of targeting is based on users being in a location with high tech spending, and then, finally, the default experience is served to visitors who do not match any of these criteria:
With this setup, the number of users who receive a personalized, optimal experience is maximized. Of the remaining users, the number receiving a geo-based experience is then maximized, and only users for whom there is no data at all default to a generic, non-personalized experience.
Predictive targeting category lists
Category | Description | Availability |
Apparel & Accessories | ||
---|---|---|
Children's Clothing & Apparel | High spenders at retailers of children's clothing and accessories. This includes children's dresses, shirts, pants, skirts, outerwear, and other clothing. |
Australia, Austria, Belgium, Canada, Denmark, Finland, Germany, Ireland, Italy, Netherlands, New Zealand, Norway, Spain, UK, US |
Men's Clothing & Apparel | High spenders at retailers of men's casual, professional, and formal wear. | All supported countries |
Luxury Retail | High spenders at retailers of luxury products or jewelry across all categories. | Australia, Germany, UK, US |
Luxury Men's Clothing & Apparel | High spenders at luxury men's retailers of clothing, casual, professional, and formal wear | Australia, Brazil, Germany, UK, US |
Luxury Women's Clothing & Apparel | High spenders at luxury women's retailers of clothing, casual, professional, and formal wear. | Australia, Brazil, Germany, UK, US |
Women's Clothing & Apparel (Online) | High spenders in women's apparel retailers, purchased online (excludes in-store brick-and-mortar sales). | Austria, Belgium, Denmark, Finland Germany, Ireland, Italy, Netherlands, Norway, Spain, UK, US |
Women's Clothing & Apparel (In-Store) | High spenders in brick-and-mortar women's apparel retailers (excludes online purchases). | |
Men's Clothing & Apparel (Online) | High spenders in men's apparel retailers, purchased online (excludes in-store brick-and-mortar sales). | Australia, Austria, Brazil, Canada, Italy, Belgium, Germany, Ireland, Denmark, Finland, Netherlands, Norway, Spain, UK, US |
Men's Clothing & Apparel (In-Store) | High spenders in brick-and-mortar men's apparel retailers (excludes online purchases). | Australia, Austria, Canada, Italy, Belgium, Germany, Ireland, Denmark, Finland, Netherlands, Norway, Spain, US |
Department & Discount Stores (Online) | High spenders in online department stores (excludes in-store brick-and-mortar sales). | Australia, Austria, Belgium, Canada, Denmark, Finland, Germany, Ireland, Italy, Netherlands, Norway, Spain, UK, US |
Department & Discount Stores (In-Store) | High spenders in brick-and-mortar department stores (excludes online purchases). | Australia, Austria, Belgium, Canada, Denmark, Finland, Germany, Ireland, Italy, Netherlands, Norway, Spain, UK, US |
Ultra Luxury Stores and Services | High spenders on extremely luxurious items or services. | Australia, Germany, UK, US |
Shoe Stores | Highly spenders at shoe stores. | Austria, Belgium, Brazil, Canada, Denmark, Finland, Germany, Ireland, Italy, Netherlands, Norway, Spain, UK, US |
Dollar Stores | High spenders at dollar stores. | US |
Athleisure Apparel | High spenders on athleisure. | US |
Department Stores | High spenders at department or super stores, mostly comprised of large chain stores. | Austria, Belgium, Canada, Denmark, Finland, Germany, Ireland, Italy, Netherlands, New Zealand, Norway, Spain, US |
Sporting Goods | High spenders at retailers that sell athletic equipment and sporting apparel. | All supported countries |
Luggage / Suitcases / Carry-Ons & Leather Stores | Highly spenders at luggage and leather stores. | US |
High-end Retail Establishments | High spenders at high-end retail establishments | Australia, Brazil, US |
Items for New Parents & Growing Families | High spenders at retailers that sell infant / young children's apparel and baby products | US |
Golf Equipment | Frequent buyers of golf equipment or clubs | US |
Jewelry & Gifts | High spenders at retailers of jewelry and gifts | Austria, Belgium, Brazil, Canada, Denmark, Germany, Ireland, Italy, Netherlands, Spain, UK |
Family Clothing & Apparel | High spenders at family clothing retailers | Australia, Austria, Belgium, Canada, Denmark, Germany, Ireland, Italy, Netherlands, New Zealand, Spain, UK |
Luxury Department Stores | High spenders at luxury department stores | Australia, Germany, UK |
Discount & Outlet Stores | High spenders at lower-cost department or dollar stores | Australia, Brazil, Canada, UK |
Wholesale Clubs | High spenders at wholesale clubs | Austria, Belgium, Canada, Denmark, Germany, Netherlands, Spain |
Discount Department Stores | High spenders at discount department stores | Austria, Belgium, Denmark, Germany, Ireland, Italy, Netherlands, Spain |
Sustainability / Green Services | High spenders on energy-friendly services including solar panels, hybrid cars, bike rentals, and eco-friendly products | UK, US |
Holiday Shopping - Luxury Retail | High spenders at top Fortune 500 retailers of luxury products and jewelry across all categories between November 15 – December 31 | US |
Holiday Shopping - Jewelry & Gifts | High spenders at retailers of jewelry or giftware between November 15 – December 31 | Canada, US |
Mother's Day - Jewelry | High spenders at jewelry stores in the two weeks prior to Mother's Day | Brazil, Canada, UK, US |
Valentine's Day Shoppers - Jewelry | High spenders at jewelry stores in the two weeks prior to Valentine's Day | Brazil, Canada, UK, US |
Automotive | ||
Automotive Parts & Accessories | High spenders at retailers of auto parts or non-essential automotive products | Austria, Belgium, Denmark, Finland, Germany, Ireland, Italy, Netherlands, Norway, Spain, US |
New / Pre-owned Cars | High spenders at retailers of new and pre-owned automobiles | Australia, Belgium, Canada, Denmark, Germany, Ireland, Italy, Netherlands, New Zealand, Spain, UK |
Beauty & Personal Care | ||
Clothing & Beauty Subscription Services | High spenders on subscriptions for monthly apparel, beauty, or clothing rental services | US |
Cosmetic Products and Beauty Services | High spenders on cosmetics and beauty products, including makeup, hair care products, and services | Austria, Brazil, Canada, Denmark, Finland, Germany, Ireland, Italy, Netherlands, Norway, Spain, UK |
Beauty and Cosmetic Products (Online) | High spenders at retailers of beauty products purchased online (excludes in-store brick-and-mortar sales) | US |
Beauty and Cosmetic Products (In-Store) | High spenders at brick-and-mortar retailers of beauty products (excludes online purchases) | US |
Books & Education | ||
College & University Education | High spenders at colleges or universities, including tuition, books, supplies, etc. | Australia, Austria, Belgium, Brazil, Canada, Denmark, Finland, Germany, Italy, Netherlands, New Zealand, Norway, Spain, UK, US |
Newspaper & Magazine | High spenders on newspaper and magazine subscriptions | Austria, Belgium, Canada, Denmark, Germany, Ireland, Netherlands, Spain |
Books | High spenders at bookstores | Austria, Belgium, Canada, Denmark, Germany, Ireland, Italy, Netherlands, Spain, UK |
Consumer Electronics | ||
Consumer Electronics / Devices (In-Store) | High spenders in brick-and-mortar consumer electronics stores (excludes online purchases). | Australia, Austria, Belgium, Canada, Denmark, Finland, Germany, Ireland, Italy, Netherlands, Norway, Spain, US |
Cameras & Photography | High spenders at retailers of camera & photography supplies, printing services, or photo editing services. | Australia, Austria, Belgium, Canada, Denmark, Finland, Germany, Ireland, Italy, Netherlands, Norway, Spain, UK, US |
Consumer Electronics, Appliances & Accessories | High spenders at retailers of consumer electronics, accessories, appliances, and gadgets. | Austria, Belgium, Brazil, Canada, Denmark, Finland, Germany, Ireland, Italy, Netherlands, New Zealand, Norway, Spain, UK, US |
Consumer Electronics / Devices (Online) | High spenders in consumer electronic retailers purchased online (excludes in-store brick-and-mortar sales). | Australia, Austria, Belgium, Canada, Denmark, Finland, Germany, Ireland, Italy, Netherlands, Norway, Spain, UK, US |
Computer & Software Sales | High spenders at retailers of desktop computers, laptops, software and accessories | Australia, Austria, Belgium, Canada, Denmark, Germany, Ireland, Italy, Netherlands, Spain, UK |
Consumer Packaged Goods | ||
Organic/Natural Grocery Stores | High spenders at natural or organic grocers | US |
Grocery & Food Stores | High spenders at retailers of fresh, specialty, frozen, and big box foodstuffs, including grocery stores | All supported countries |
Drug Store Chains | High spenders at drug stores for items including over-the-counter medication, prescriptions, and supplies | Australia, Brazil, Canada, US |
Online Food & Meal Delivery | High spenders at online food or meal delivery providers, including meal kit delivery services (excludes in-store brick and mortar sales) | UK, US |
Online Grocery Stores | High spenders on online grocery stores, including grocery store chains that have an online website or app that allows grocery purchases (excludes in-store brick and mortar sales) | Belgium, Ireland, UK, US |
Meal Kits | High spenders on meal kit delivery services | Belgium, Germany, Ireland, UK |
Entertainment | ||
Live Performances, Events and Exhibits | High spenders on live performances, events, and exhibits | Australia, Austria, Belgium, Canada, Denmark, Germany, Ireland, Italy, Netherlands, Spain |
Financial Services | ||
Tax Preparation Services | High spenders on tax preparation services between March 1 and April 20 | US |
Premium Credit Cards | High spenders on a premium credit card (cards with high premiums) | US |
Rewards Credit Cards | High spenders on a reward credit card (cards with high reward points) | Brazil, US |
General Insurance Services | High spenders on any type of insurance, including travel, identity theft, disability, accidental, life, and auto insurance | All supported countries |
Mobile / Smartphone & Digital Payments | High spenders using mobile payment methods or apps that include mobile payments, mobile wallets, mobile investments, and/or cryptocurrencies | US |
Accounting and Legal Services | High spenders on accounting and legal services | Australia, Austria, Canada, Denmark, Germany, Netherlands, New Zealand, Spain, UK |
Gifts, Toys, & Office | ||
Office Supplies | High spenders at office supply stores or home office specialty stores | Australia, Austria, Belgium, Canada, Denmark, Finland, Germany, Ireland, Italy, Netherlands, New Zealand, Norway, UK, US |
Gifts, Cards & Stationary Stores | High spenders at gift and/or card stores | UK, US |
Toy Stores | High spenders at toy stores | Austria, Belgium, Canada, Denmark, Finland, Germany, Ireland, Italy, Netherlands, UK |
Home & Furniture | ||
Home Furniture and Furnishing | High spenders at retailers of home furnishings, home decor, bedding, and accessories | All supported countries |
Home Furniture and Furnishing (Online) | High spenders at online retailers of home furniture, home décor, and accessories (excludes in-store brick-and-mortar sales) | US |
Home Furniture and Furnishing (In-Store) | High spenders at brick-and-mortar retailers of home furniture, home décor, and accessories (excludes online purchases) | US |
Home Improvement | High spenders on home improvement supplies, furnishings, services, etc. | Australia, Austria, Belgium, Canada, Denmark, Finland, Germany, Ireland, Italy, Netherlands, New Zealand, Norway, UK, US |
Pets | ||
Pet Care & Veterinary Services | High spenders at pet care or veterinary services, including boarding and grooming. | All supported countries |
Restaurants | ||
Quick Serve Restaurants | High spenders at restaurants with no wait staff or server, including fast food restaurants | Australia, Belgium, Ireland, New Zealand, UK |
Quick Serve Restaurants - Asian | High spenders at restaurants with no wait staff or server, including fast food restaurants, that specialize in Asian cuisine | US |
Quick Serve Restaurants - Ice Cream | High spenders at restaurants with no wait staff or server, including fast food restaurants, that specialize in serving ice cream and/or yogurt items | US |
Quick Serve Restaurants - Mexican | High spenders at restaurants with no wait staff or server, including fast food restaurants, that specialize in Mexican cuisine | US |
International Cuisine | High spenders at international or foreign cuisine restaurants | US |
Fine Dining | High spenders at luxury dining establishments | UK, US |
Mid-Range Restaurants & Non-Quick Serve | High spenders at mid-range restaurants | UK |
Eating Places | High spenders at restaurants, quick service restaurants, and other eating places | Australia, Austria, Belgium, Brazil, Canada, Denmark, Germany, Ireland, Italy, Netherlands, New Zealand, Spain |
Travel | ||
Luxury Travel & Tourism | High spenders on luxury travel, including first-class tickets, travel bookings, lodging, and activities | UK, US |
Luxury Hotels / Resorts | High spenders at any Fortune 500 luxury hotel | Brazil, UK, US |
International Air Business / Work Travel | High spenders on international air travel for business | US |
Domestic Budget Flights | High spenders on domestic budget airlines, hotels, and car rentals | US |
Budget Travel | Frequent buyers on domestic budget airlines, hotels, and car rentals | US |
Domestic Air Travel | High spenders on domestic airline travel (anywhere in the United States) | Australia, New Zealand, UK, US |
International Air Travel | High spenders on international airline travel (anywhere outside of the United States) | Australia, New Zealand, UK, US |
Upscale Hotels / Resorts | High spenders who visit Fortune 500 or nationally recognized upscale hotels | UK, US |
Midscale Hotels & Resorts | High spenders at midscale hotels | US |
Affluent Leisure Travel | High spenders on high-end travel, including first-class tickets | US |
Airline Travelers | High spenders on airline travel | Australia, Austria, Belgium, Brazil, Canada, Denmark, Germany, Ireland, Italy, Netherlands, Spain |
Cruise Travelers | High spenders on leisure trips through cruise lines | Australia, Austria, Belgium, Canada, Denmark, Germany, Italy, Netherlands, New Zealand, Spain, UK |
Car Rental & Car Sharing Services | High spenders on car rentals | Australia, Austria, Belgium, Brazil, Canada, Denmark, Germany, Ireland Italy, Netherlands, Spain, UK |
Hotel & Motel | High spenders at hotels for business or leisure travel | Australia, Austria, Belgium, Brazil, Canada, Denmark, Germany, Ireland, Italy, Netherlands, New Zealand, Spain, UK |
Spending Behavior | ||
Black Friday / Cyber Monday - Brick & Mortar Shoppers | High spenders at brick-and-mortar retail stores on Black Friday through Cyber Monday | Brazil, Canada, UK, US |
Big Ticket Shoppers (Online) | High spenders on "big ticket" items online or through e-commerce | UK, US |
Black Friday / Cyber Monday - Online Shoppers | High spenders at online retail stores on Black Friday through Cyber Monday (excludes in-store sales) | Brazil, Canada, UK, US |
Brick & Mortar Shoppers | High spenders in brick-and-mortar stores of any industry | US |
Online Shoppers | High spenders on online stores | Australia, Austria, Belgium, Brazil, Canada, Denmark, Finland, Germany, Ireland, Italy, Netherlands, Norway, Spain, UK, US |
Big Ticket Shoppers | High spenders on "big ticket" items | US |
Category | Description | Availability |
Apparel & Accessories | ||
---|---|---|
Department Stores | Highly likely to spend at department or super stores, mostly comprised of large chain stores, in the next 30 days based on a propensity model | US |
Value & Discount Stores | Highly likely to spend at lower cost department, off-price, discount, or dollar stores in the next 30 days based on a propensity model | US |
Sporting Goods | Highly likely to spend at retailers of athletic equipment and sporting apparel in the next 30 days based on a propensity model | US |
Children's Clothing & Apparel | Highly likely to spend at retailers of children's clothing and accessories in the next 30 days based on a propensity model. This includes children's dresses, shirts, pants, skirts, outerwear and other clothing | US |
Family Clothing & Apparel | Highly likely to spend at retailers of clothing for the whole family in the next 30 days based on a propensity model | US |
Men's Clothing & Apparel | Highly likely to spend at retailers of men's casual, professional, and formal wear in the next 30 days based on a propensity model | US |
Women's Clothing & Apparel | Highly likely to spend at retailers of women's casual, professional, and formal wear in the next 30 days based on a propensity model | US |
Luxury Men's Clothing & Apparel | Highly likely to spend at luxury men's retailers of clothing, casual, professional, and formal wear in the next 30 days based on a propensity model | US |
Luxury Women's Clothing & Apparel | Highly likely to spend at luxury women's retailers of clothing, casual, professional, and formal wear in the next 30 days based on a propensity model | US |
Luxury Retail | Highly likely to spend at retailers of luxury products or jewelry across all categories in the next 30 days based on a propensity model | US |
Jewelry & Gifts | Highly likely to spend on jewelry, giftware, or accessories in the next 30 days based on a propensity model | US |
Valentine's Day Shoppers - Jewelry | Highly likely to spend at jewelry stores in the two weeks prior to Valentine's Day based on a propensity model | US |
Automotive | ||
Automotive Parts & Accessories | High likelihood to spend at retailers of auto parts or non-essential automotive products within the next 30 days based on modeled spend behavior | Brazil, US |
Foreign Cars | Highly likely to spend on a foreign brand car within the next 30 days based on a propensity model | US |
Domestic Car Buyers | Highly likely to spend on a domestic brand car within the next 30 days based on a propensity model | US |
New / Pre-Owned Cars | Highly likely to spend on a new or pre-owned car within the next 30 days based on a propensity model | Brazil, US |
Luxury Cars | Highly likely to spend on high end luxury car within the next 30 days based on a propensity model | US |
New / Pre-Owned Cars (New Buyers) | Highly likely to purchase a new or pre-owned car, without previous evidence of similar spend, within the next 30 days based on modeled spend behavior | US |
Beauty & Personal Care | ||
Hair Care / Styling & Beauty Salons | Highly likely to spend at hair care, beauty salons, hair salons and barber shops in the next 30 days based on a propensity model. This includes services such as haircuts, nail care, manicures, and pedicures | US |
Books & Education | ||
Books | Highly likely to spend at book or magazine stores in the next 30 days based on a propensity model | US |
Newspaper & Magazine | Highly likely to spend on newspapers or magazines in the next 30 days based on a propensity model | US |
Consumer Electronics | ||
Cameras & Photography | Highly likely to spend at retailers of camera & photography supplies, printing services, or photo editing services in the next 30 days based on a propensity model | US |
Consumer Electronics, Appliances & Accessories | Highly likely to spend at retailers of consumer electronics, accessories, appliances, and gadgets in the next 30 days based on a propensity model | US |
Financial Services | ||
Tax Preparation Services | Highly likely to spend on tax preparation services based on a propensity model | US |
Accounting and Legal Services | Highly likely to spend on accounting and/or legal services in the next 30 days based on a propensity model | US |
Real Estate & Realtor Services | Highly likely to spend on real estate services, including those who plan on purchasing or renting real estate/property, in the next 30 days based on a propensity model | US |
Small Businesses | Card holders which are likely small businesses based on a propensity model, and are in the market to spend on business-related products and services | US |
Gifts, Toys, & Office | ||
Arts & Crafts Stores | Highly likely to spend at arts and craft stores in the next 30 days based on a propensity model | US |
Gifts, Cards & Stationary Stores | Highly likely to spend at retailers of gift and/or card stores in the next 30 days based on a propensity model | US |
Office Supplies | Highly likely to spend at office supply store or home office specialty store in the next 30 days based on a propensity model | US |
Toy Stores | Highly likely to spend at toy stores in the next 30 days based on a propensity model | US |
Home & Furniture | ||
Home Furniture and Furnishing | Highly likely to spend at retailers of home furnishings, home decor, bedding, and accessories in the next 30 days based on a propensity model | US |
Home Improvement | Highly likely to spend at retailers of home improvement supplies and home furnishings, including services in home improvement, renovations, and interior design, in the next 30 days based on a propensity model | US |
Restaurants | ||
Valentine's Day Shoppers - Valentine's Day Dining | Highly likely to spend at restaurants on Valentine's Day based on a propensity model | US |
High-end Dining | Highly likely to spend at high-end restaurants within the next 30 days based on a propensity model | US |
Mid-Range & Non-Chain Restaurants | Highly likely to spend at mid-range restaurants within the next 30 days based on a propensity model | US |
Spending Behavior | ||
High Net Worth Consumers | Highly likely to spend with a high degree of discretionary spending available within the next 30 days based on a propensity model | US |
Online Shoppers | Highly likely to spend at online stores in the next 30 days based on a propensity model (excludes in-store sales) | Brazil, US |
Travel | ||
Economy Hotels & Motels | Highly likely to spend at economy hotels and/or motels in the next 30 days based on a propensity model | Brazil, US |
Luxury Travel & Tourism | Highly likely to spend on luxury travel, including first-class tickets, travel bookings, lodging, and activities, in the next 30 days based on a propensity model | US |
Upscale Hotels / Resorts | Highly likely to spend at Fortune 500 upscale hotels in the next 30 days based on a propensity model | US |
Domestic Air Travel | Highly likely to spend at United States based airlines within the next 30 days based on a propensity model | US |
International Air Travel | Highly likely to spend at airlines based outside of the United States within the next 30 days based on a propensity model | US |
Big-Ticket Cruisers | Highly likely to spend on leisure trips or vacations through major cruise lines within the next 30 days based on a propensity model | US |
Luxury Hotels & Resorts | Highly likely to spend at any Fortune 500 luxury hotel in the next 30 days based on a propensity model | US |
Midscale Hotels & Resorts | Highly likely to spend at midscale hotels in the next 30 days based on a propensity model | Brazil, US |
Prerequisites and limitations
- To get Geo-based Predictive Spend and Geo-based Spend History, contact your account manager.
- The list of available categories might vary between accounts, based on the account’s vertical classification (E-commerce, Financial Institutions, Quick Service Restaurants, or Consumer Packaged Goods).
- Geo-based predictive targeting currently works only for select geographies throughout the United States, Europe, Latin America, and APAC. In the near future, availability will be expanded to support additional countries, including:
-
- Argentina
- Japan
- Malaysia
-
- Portugal
- Singapore
-
- Thailand
- Vietnam