April 8, 2020
Consumer data used to be important because it helped businesses understand what products consumers were purchasing. Today, not only is it still important to understand purchase data, the data is important because it helps business tailor experiences to their customers.
Consumers prefer to see products on shopping pages that intrigue them or that are wish-list items. A personalized digital experience informed by data regarding individual preferences is important as consumers choose the brands that cater to their interests and buying needs.
Data is an essential foundation that helps businesses gain a better understanding of the way their consumers behave online. It uncovers customer demographics by product or region to reveal ways to improve the overall customer experience. Data gives businesses the keys to deliver a targeted customer experience.
In order to accomplish these goals, businesses need to rely on a tool that gives them a comprehensive breadth of data presented in a reporting structure that is easy to interpret and is actionable.
What Is Data on Demand?
What Is the Value of This Data-Driven Information?
The augmented data can be valuable for many different departments across a company for deep analysis, reporting, and the creation of custom Machine Learning (ML) models to address specific business needs.
Analysis of this data can not only uncover insights into fraud anomalies, it also reveals business insights outside of the fraud space such as buying behaviors, and the value or risk associated with each customer, business, or partner. Further, analytics can reveal opportunities to improve business operations and to surface customer and market insights for product improvements.
The augmented data provides a 360-degree view of customers across channels to uncover true omnichannel customer behavior and experience, providing insights for enhanced customer targeting. Businesses gain a more complete view of their customers by augmenting existing data with new information such as age, gender, and residential distance to a retail location. Augmented data can inform product and market-related decisions, including whether to launch in a new country or
retail location or how to personalize marketing campaigns by location or demographic.
By adding more relevant data to a single transaction and analyzing data based on purchase behavior, location, device data, or demographics, businesses can make better decisions about new products or features, new store locations, new markets, or targeted marketing campaigns.
How Does Data on Demand Work?
Kount Data on Demand is built on Snowflake’s cloud architecture. This secure, single, near-zero maintenance platform-as-a-service provides logically integrated compute, storage, and cloud services layers. The layers are scale-independent to support high workloads, enabling quick data manipulation without performance, concurrency or scale limitations. Snowflake runs on the AWS cloud, providing uninterrupted access to data.
Snowflake’s cloud architecture means businesses can:
- Access data any time to view, analyze, or report on metrics
- Access customer events including purchase and sign-up details, to use in detailed analysis and reporting
- Extract data quickly for modeling and offline evaluation
- Share data instantly and securely across the organization and beyond, without having to copy or move data
- Create custom AI models with all collected Kount and non-Kount data to anticipate specialized fraud or business problems
What Type of Data Is Available?
The data warehouse is organized with rows that contain individual transactions and with columns and semi-structured JSON containing all collected, provided, and augmented data.
This data includes:
- Customer-collected payment details
- Data from Kount’s User Defined Fields (UDFs)
- Data from triggered rules, reviews, and outcomes
Other valuable data that can be imported and augmented includes device and location data such as:
- Geographic lookup data from IP and mobile location services
- Address lookup data from mailing address, phone number, and name
- Email First Seen
- Kount’s AI-driven Omniscore and persona ML features
Data is available within minutes of the transaction or status update, and multiple departments in a business can access or analyze the information.
With Data on Demand, any combination of Kount-collected or company-collected data can be retrieved and displayed through a SQL-based reporting tool of choice as opposed to an API integration update, which can take hours or even days to update.
How Does Kount’s Data on Demand Solution Solve Specific Business Challenges?
Here are a few examples of how Data on Demand addresses business challenges:
- View data in a single platform including transaction-level payments data and company data sources, for a deeper view of transactions, customers, business, and partners across channels.
- Find insights that are difficult to view on a transaction level or in real time by viewing aggregated data from multiple sources.
- Build and automate detailed reports to analyze and track fraud or business KPIs with data that isn’t typically available on a payment transaction.
- Increase revenue with data-driven insights from aggregated Kount data such as payments data, digital identifiers, devices, locations, emails, and decision data from Kount’s Identity Trust Global Network.
How Can Data on Demand Deliver a Positive Customer Experience?
With comprehensive data, business can discover true omnichannel customer behaviors, such as the average dollar value of sales cart purchases, product popularity by time, location, device or demographics, or sales by location. This information can lead to opportunities to cross-sell, upsell, or create new leads and make valuable data-driven decisions.
The bottom line? More information can lead to more informed decisions that can translate into revenue.