Technological advances have been an integral part of human evolution. Most of these advances have a direct impact on easing human lives’ existence. These new technologies, which may be a combination of AI & ML, are spinning out new-age solutions like never before. Likewise, there is a significant evolution happening in the cognitive technologies side that is extensively exploited in customer experience, satisfaction and engagement. The want for taking quick decisions, saving time and cost are compelling innovators to launch AI-based products that are cognizant in analyzing customer to service provider’s conversations.
Nasdaq-listed customer engagement company, Verint Systems Inc. recently launched a product called AI Blueprint – a patent-protected conversation analysis system that identifies intelligent virtual assistant (IVA) use cases and accelerates automation.
Jason du Preez, Vice President of Sales for CX Solutions – Asia Pacific, Verint, in a conversation with Voice&Data discusses how the company’s AI Blueprint can boost customer experience through conversational analysis.
AI Blueprint eco-system in conversational analytics
Bullish on Verint’s AI Blueprint (IBA) program, Jason du Preez says that the product is based on 15 years of experience and focuses on 5 key areas with conversational analytics as the crux. He says that Conversational Analytics allows one to take advantage of the data that organizations have collated and analyze all that data to identify key trends and intentions of customers to understand how most processes can be automated.
Explaining appropriately du Preez says, “AI Blueprint unlocks the power of conversational data and returns specific insights for achieving an organization’s unique business goals. The system then delivers a ‘blueprint’ of precisely how and where businesses can get started with AI or continue to grow their AI capabilities, reducing risk and leading to improved operational efficiency and faster ROI. AI Blueprint has the potential to unlock the power of conversational data and return specific insights for achieving an organization’s unique business goals.”
According to du Preez, the AI Blueprint is capable of leveraging AI and machine learning for analysis, classification, and labeling of any company’s structured and unstructured conversational data. The product, he says, can determine whether the organization using its technology could benefit from deploying AI. If the AI Blueprint identifies that there is a business need for AI, the analysis system returns comprehensive and customized recommendations. It identifies which use cases will generate the most business value, develops a range of measurable key performance indicators adapted to the business goals, and generates a roadmap for implementing and/or further developing AI-powered Intelligent Virtual Assistants (IVAs) in ways that ensure long-term success.
Clearing misnomers associated with AI implementation at enterprise level
Jason du Preez says that Verint’s AI Blueprint is vested with the ability to aid decision making when there is an ambiguity scenario on deploying AI. He says it works on two premises:
- To be able to use the existing data and where to focus in an AI engine
- To identify and then drive RoI by rolling out short and sharp initiatives at the back office.
“Our blueprint focusses on five specific business problems which we’ve been able to prove in a real-world environment. APIs that we actually track and measure to actually identify the outcome of the tracking and measuring the APIs is also part of that typical AI engine. Let me elaborate on the 5 business problems that we can resolve through AI blueprint:
Through AI Blueprint’s unique two-factor analysis approach, enterprises have seen:
- 83% deflection in live chat volume.
- 44% cost reduction in the first year.
- $1 million saved in customer service email costs in a single year.
- 50% decrease in the amount of time it takes a customer to reset a password.
- 27% reduction in live-chat costs.
The first one is the customer service component, which solves the problem around helping a customer sort out a problem on the website from a typical customer support perspective. The second component is around brand engagement and loyalty assistance and the objective here is really to ensure we’re targeting the customer and the audience that we’re dealing with in a meaningful way to help drive contextual CX so as to take actions and convert leads. The third, fourth and fifth business areas are actually internally focused. They are what we call the employee resource assistance, explains du Preez.
Leveraging IVAs to achieve specific business goals
Jason du Preez says that Verint has designed an Intelligent Virtual Assistant (IVA) that enables companies to engage at critical moments to help customers make a purchase, get more information or resolve an issue at the earliest, saving money and time. Comprehending contextual information, the Verint Intelligent Virtual Assistant provides personalized answers based on the customer’s prior purchases, location, and other factors.
“Verint’s IVA helps customers experience higher goal completion rates with a user experience that’s better, smarter and faster, and that involves less effort. Businesses benefit too, realizing greater self-service utilization across all channels, translating into higher automation and lower escalation rates. Verint’s IVA is powered by an open, modular AI engine that gives enterprises the ability to manage, extend and scale the solution. The accompanying tools, analytics and an extensive set of training data put the enterprise in control of the conversational AI that drives the Verint solution. Its modular architecture provides investment protection as AI technology advances and integration requirements evolve,” elaborates du Preez.