Customer 720

Customer Hyper-personalization Leveraging Knowledge Graphs

Industry Problem

Today's customers are very demanding, and technological disruptions make them wanting more. Organizations are struggling to define their buyer personas more than ever to create the best customer experience across the channels and find more cross-selling opportunities with their buyers. These industry trends in the customer experience warranted advanced solutions to offer a personalized experience for each unique customer - ultimately creating a 'segment of one' buyer experience. Financial institutions have made some inroads with the KYC initiatives because of the regulatory demands. Still, most industries struggle to view their comprehensive customer information by connecting the dots across business lines, which we all Internal-360 view of the customer. To offer a hyper-personalized experience to their customers, organizations need not only the internal customer data, but they also need to understand their customer's trigger points such as life events, social dynamics, and more, which we call External-360.

Today's organizations strive to read their customers' minds and stay proactive, addressing their needs before they even express. A highly successful organization differentiates itself by offering a unique but consistent across all the channels and touchpoints.

Fusing the customer information from Internal-360 and External-360 results is the ultimate nirvana, which we call Customer-720, enabling the organizations to transform to customer-centric from product-centric.

How it Works

This product leverages Graph Technology to bring the customer data from internal (Internal-360) and external sources (Extern-360) together from structured and unstructured data sources in real-time and in batch.

Many beacons/integrations in the product start to listen for the triggers and associated life events such as a new child in the family, education events, change in hobbies, marriages, deaths, career events, change in interests, and more. At this point, the product's AI-based engine starts generating insights, associated actions, and next-best-action for the organization to act, resulting in improved customer satisfaction and cross-selling the additional products.

Sample Use Cases

A mortgage company retaining its customer by proactively offering a refinance on an existing loan - an external trigger that the customer read and followed 'low interest rates' news feed.

A Bank sold a new auto loan for a mini-van to its customer - an external trigger that customer posted a life event that they got a new addition to the family.

A doctor in a hospital system reduced blood-pressure medication dosage - an internal trigger combined with external stimuli. The patient's exercise and diet routines and medications significantly altered the conditions. ​​

An insurance company upgraded its customer from rental insurance to home insurance - an external trigger that customer applied for a new mortgage.

Impactful Outcomes

Higher Personalized Customer Experience

Higher Revenue Growth

Reduced Cost of Operations

Higher Customer Retention

Higher Customer Acquisition

Higher Input on Product Design and Campaigns

Features

Enriched Customer View

Collate data from structured and unstructured data from internal and external data sources, including business, social, contact center data to enrich the base customer view

Hobbies and Interests

Identifying customer hobbies and interests based on the repetitive events happening in a customer’s life

Contextual Knowledge and Insights

Develop contextual knowledge and insights to provide the right offers and action to boost the customer experience

Event Timelines

Keeping track of critical events happening in a customer’s life can provide a clear view of why the customer has taken a particular decision?

Spending Pattern

Based on the Customer’s spending pattern, compare the average spending pattern of a similar segment of customers.

Brand Affinity

Understand the customer affinity towards Brands based on the internal and external transactions to administer the right offers to improve the customer experience

Location Intelligence

Identify where the customer is right now or last seen to develop location-based contextual knowledge to provide the right contextual offers to boost the customer experience

CUSTOMER SPEAK

“We have not see something like this before, it’s a great step towards developing a real good customer experience”

SVP, Consumer Lending, A Medium Size Bank in US

“This is a game changer and it helps us to bring the data together which is Data Lake, MDM and other platform. I Love this.”

Chief Data Officer, A Regional Bank in US

“We want to use this as growth stimulus platform to boost the revenue through generating demand and being Proactive to understand customers needs rather than being reactive.”

SVP, Mortgage Head of Operations, A Medium Size Bank in US

Request a Demo

We are excited to Demonstrate the capabilities of the product.