Loyalty Card Data

Loyalty card data is the data about sales and purchases made using various loyalty cards. It's used by retailers and supermarkets for consumer purchase analytics to know which products are their biggest income drivers and which make the most profit. Learn more →
Find the right data, effortlessly.
Discover, compare, and request the best loyalty card datasets and APIs.
Our Data Partners
Multimedia List - Transactional Retail & Bank Card Holder Data USA (24 Million records) 24M transaction retail and bank card holders icon
24M transaction retail and bank card holders
Multimedia List - Transactional Retail & Bank Card Holder Data USA (24 Million records) USA covered icon
USA covered
24+ Million transactional retail and bank card holders of US individuals provided by Multimedia Lists.
Show all →
datarade.ai - Multimedia Lists profile banner
Multimedia Lists
Based in USA
Multimedia Lists
Data and lists are our business. We compile them, clean them up, merge/purge them, manage them for other companies and we find YOU lists that can target any ...
+245M
US Consumers
Regular
Updates
+90%
Consumer Compiled
Cardlytics
Based in USA
Cardlytics
Cardlytics is a data provider offering Alternative Data, Bank Transaction Data, Credit Card Transaction Data, Demographic Data, and Loyalty Card Data. They a...
datarade.ai - Affinity Solutions profile banner
Affinity Solutions
Based in USA
Affinity Solutions
Affinity Solutions was founded 15 years ago based on innovating solutions that help financial institutions and retailers craft precision marketing programs t...
Show all →

The Ultimate Guide to Loyalty Card Data 2021

Learn about loyalty card data analytics, sources, and collection.

What is Loyalty Card Data?

Loyalty card data is information regarding sales and purchases made using different loyalty cards for supermarkets and retailers. It also provides information about the loyalty card owner. The data covers information related to product discounts offered to customers, coupons, rewards coins towards stock or some other reward in exchange for their willful participation in the loyalty card program. Loyalty card data helps retailers know customer’s behavior and then develop strategies by targeting advertising and organising products to encourage sale.

How is Loyalty Card Data collected?

Retailers can collect loyalty card data by purchasing customer data from third-party POS (point of sale) data providers. These third-party firms amass information from a variety of specialists to create “profiles” of people with information about purchase habits, patterns and personality. This helps retailers to know all the information about purchases made by customers, which products are the bestselling and trendy in the market, which type of offer/sales schemes will attract new customers.

What are the attributes of Loyalty Card Data?

Here are the two major attributes of loyalty card data:

  1. Customer loyalty card data: Customer loyalty data tells information about customers who make regular purchases with a store, the physical gifts and gift vouchers that are given to customers, the tangible and non-tangible gifts offered to customers as incentive to shop with the business again.

  2. Referral loyalty card data: This data tells information about the purchases made from loyalty cards by new customers through referrals from the existing customer base.

What is Loyalty Card Data used for?

As a form of POS data, loyalty card data is used by anyone who wants to analyze consumer spending. Loyalty card data is used to:

  1. Grow the business, draw new customers and re-engage and preserve current customers.
  2. Plan schemes and offers for loyalty card holders.
  3. To create a competitive advantage for the company against its competitors.
  4. To provide a better, more relevant experience to the user every purchase.
  5. To forms a true spirit of partnership between the business and the customer.

How can a user assess the quality of Loyalty Card Data?

Here are some ways in which you can measure the quality of loyalty card data:

  • Completeness: Completeness relates to how well a loyalty card dataset is populated. Datasets with missing data points are lower quality.
  • Timeliness: Timeliness refers to the historical coverage and recency of your loyalty card data. Some users will need loyalty card with years of data points, other users will only need the most up-to-data intelligence, so would find a real-time loyalty card data feed most useful.

    Who are the best Loyalty Card Data providers?

    Finding the right Loyalty Card Data provider for you really depends on your unique use case and data requirements, including budget and geographical coverage. Popular Loyalty Card Data providers that you might want to buy Loyalty Card Data from are Multimedia Lists, Cardlytics, Affinity Solutions, Caddle, and Fidall.

    Where can I buy Loyalty Card Data?

    Data providers and vendors listed on Datarade sell Loyalty Card Data products and samples. Popular Loyalty Card Data products and datasets available on our platform are Multimedia List - Transactional Retail & Bank Card Holder Data USA (24 Million records) by Multimedia Lists.

    How can I get Loyalty Card Data?

    You can get Loyalty Card Data via a range of delivery methods - the right one for you depends on your use case. For example, historical Loyalty Card Data is usually available to download in bulk and delivered using an S3 bucket. On the other hand, if your use case is time-critical, you can buy real-time Loyalty Card Data APIs, feeds and streams to download the most up-to-date intelligence.

    What are similar data types to Loyalty Card Data?

    Loyalty Card Data is similar to Credit Card Transaction Data, Point-of-Sale (POS) Data, Consumer Transaction Data, Debit Card Transaction Data, and Bank Transaction Data. These data categories are commonly used for Marketing and Loyalty Card Data analytics.

    What are the most common use cases for Loyalty Card Data?

    The top use cases for Loyalty Card Data are Marketing, Purchase Intelligence, and purchase behavior analytics.