How Data on Demand enhances business growth, customer journey insights

Benefits of Data on Demand: Get access to multiple data sources, get a complete view of customer behavior, anticipate unique fraud problems quickly

In the past, consumer data was limited to helping businesses understand what products consumers were purchasing. Today, it does that and more. Data can help businesses understand purchasing trends, gain a better understanding of how customers behave online, and uncover demographics by product or region.

Together, these data points can reveal how businesses can improve their overall customer experience. But first, they’ll need a solution that gives them a comprehensive, actionable breadth of data. Enter Kount’s Data on Demand, a solution that collects thousands of additional data points from Kount’s global network and AI-driven platform. Data on Demand insights turn customer data into revenue growth in three ways.

It grants access to multiple data sources that can uncover upsell, cross-sell opportunities

From any one customer event — new account creation, login, payment, etc. — comes countless data points that businesses can use to improve their operations. Data on Demand grants unprecedented access to those countless data points from multiple data sources in one place.

The first source is Kount-collected data, which Kount has gained from over a decade of fraud prevention best practices. The second source is a business’s company-collected data. The third source is data from the Identity Trust Global NetworkTM.

Kount’s global network contains data from billions of annual interactions from across countries and industries that all help establish trust and risk levels behind every customer event. Kount’s data can give businesses access to four types of data.

  1. Payments data: Payment type, payment token, bank name, country, transaction amounts, currency used, etc.
  2. Location ID data: Physical location, billing address, shipping address, address verification, time zone, local time of day, etc.
  3. Digital identifier data: Device ID, device type/information, IP address, billing and shipping email addresses, phone number, logins and sites visited, etc.
  4. Unique customer data: Unique customer data, coupon codes used, loyalty number, etc.

Essentially, these combined data points can inform a business on everything from a customer’s lifetime value to how old an email address is when someone uses it to create an account. And from them come actionable customer insights that can reveal opportunities to reduce friction and false declines and increase revenue through data-informed upsell and cross-sell initiatives.

With Data on Demand, any combination of Kount-collected or company-collected data can be retrieved and displayed through a business’s SQL-based reporting tool of choice. Unlike an API integration update, an SQL-based reporting tool doesn’t take hours (or even days) to update. Data is available within minutes of an event, transaction, or status update, and it’s accessible to departments across a business.

How Data on Demand works: A transaction or event can reveal thousands of data points that inform Kount-collected data, company-collected data, and global network data.

It gives businesses a complete view of customer behavior across channels

Additional customer data can be valuable across a company for deep analysis, reporting, and to create machine learning models that can address specific business needs. Analyzing the data can uncover fraud anomalies, customer buying behaviors, and the trust or risk associated with each customer, business, or partner. Analytics can reveal opportunities to improve business operations and surface customer and market insights for product improvements.

Combined data provides a complete view of customers across channels. And it allows businesses to better target trends based on new information such as customer’s age and residential distance from a retail location. This additional data can inform product and market-related

decisions, including whether to adopt new buying channels and payment methods or expand brick-and-mortar locations.

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.

It can help businesses anticipate and address unique fraud and business problems quickly

A diagram to represent Data on Demand's aggregated data, hosted by Snowflake.

Data on Demand is built on Snowflake’s cloud architecture. This secure, single, near-zero maintenance platform provides logically integrated compute, storage, and cloud services layers. Each layer is scale-independent, so it can support high workloads and allow for quick data manipulation without performance, concurrency, or scale limitations.

The more time businesses can save on reporting and analytics, the better they can anticipate fraud and other anomalies. And the faster they can get back to serving their customers. Essentially, accessing Data on Demand through Snowflake’s cloud architecture means businesses can:

  • View data in a single platform for a deeper view of transactions, customers, and partners across channels.
  • Analyze and report on events like customer purchases and signups.
  • Find insights that are difficult to view on a transaction level.
  • Automate detailed reports to analyze and track fraud or business KPIs.
  • Share data across the organization and beyond instantly and securely.
  • Customize AI models to solve specialized fraud or business problems.

More data helps businesses deliver better customer experiences

With comprehensive data, businesses can discover true omnichannel customer behaviors. Such behaviors include the average dollar value of sales cart purchases, sales by location, and product popularity by time, location, device, or demographic.

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.

Let us show you how Data on Demand can help your business grow

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How Data on Demand enhances business growth, customer journey insights
In the past, consumer data was limited to helping businesses understand what products consumers were purchasing. Today, it does that and more. Data can help businesses understand purchasing trends, gain a better understanding of how customers behave online, and uncover demographics by product or region. Together, these data points can reveal how businesses can improve their overall customer experience. But first, they’ll need a solution that gives them a comprehensive, actionable breadth of data. Enter Kount’s Data on Demand, a solution that collects thousands of additional data points from Kount’s global network and AI-driven platform. Data on Demand insights turn customer data into revenue growth in three ways. It grants access to multiple data sources that can uncover upsell, cross-sell opportunities From any one customer event — new account creation, login, payment, etc. — comes countless data points that businesses can use to improve their operations. Data on Demand grants unprecedented access to those countless data points from multiple data sources in one place. The first source is Kount-collected data, which Kount has gained from over a decade of fraud prevention best practices. The second source is a business’s company-collected data. The third source is data from the Identity Trust Global NetworkTM. Kount’s global network contains data from billions of annual interactions from across countries and industries that all help establish trust and risk levels behind every customer event. Kount’s data can give businesses access to four types of data. Payments data: Payment type, payment token, bank name, country, transaction amounts, currency used, etc. Location ID data: Physical location, billing address, shipping address, address verification, time zone, local time of day, etc. Digital identifier data: Device ID, device type/information, IP address, billing and shipping email addresses, phone number, logins and sites visited, etc. Unique customer data: Unique customer data, coupon codes used, loyalty number, etc. Essentially, these combined data points can inform a business on everything from a customer’s lifetime value to how old an email address is when someone uses it to create an account. And from them come actionable customer insights that can reveal opportunities to reduce friction and false declines and increase revenue through data-informed upsell and cross-sell initiatives. With Data on Demand, any combination of Kount-collected or company-collected data can be retrieved and displayed through a business’s SQL-based reporting tool of choice. Unlike an API integration update, an SQL-based reporting tool doesn’t take hours (or even days) to update. Data is available within minutes of an event, transaction, or status update, and it’s accessible to departments across a business. It gives businesses a complete view of customer behavior across channels Additional customer data can be valuable across a company for deep analysis, reporting, and to create machine learning models that can address specific business needs. Analyzing the data can uncover fraud anomalies, customer buying behaviors, and the trust or risk associated with each customer, business, or partner. Analytics can reveal opportunities to improve business operations and surface customer and market insights for product improvements. Combined data provides a complete view of customers across channels. And it allows businesses to better target trends based on new information such as customer’s age and residential distance from a retail location. This additional data can inform product and market-related decisions, including whether to adopt new buying channels and payment methods or expand brick-and-mortar locations. 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. It can help businesses anticipate and address unique fraud and business problems quickly Data on Demand is built on Snowflake’s cloud architecture. This secure, single, near-zero maintenance platform provides logically integrated compute, storage, and cloud services layers. Each layer is scale-independent, so it can support high workloads and allow for quick data manipulation without performance, concurrency, or scale limitations. The more time businesses can save on reporting and analytics, the better they can anticipate fraud and other anomalies. And the faster they can get back to serving their customers. Essentially, accessing Data on Demand through Snowflake’s cloud architecture means businesses can: View data in a single platform for a deeper view of transactions, customers, and partners across channels. Analyze and report on events like customer purchases and signups. Find insights that are difficult to view on a transaction level. Automate detailed reports to analyze and track fraud or business KPIs. Share data across the organization and beyond instantly and securely. Customize AI models to solve specialized fraud or business problems. More data helps businesses deliver better customer experiences With comprehensive data, businesses can discover true omnichannel customer behaviors. Such behaviors include the average dollar value of sales cart purchases, sales by location, and product popularity by time, location, device, or demographic. 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.
https://kount.com/blog/how-data-on-demand-improves-the-customer-journey/
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