Cognitive Agents and Reinforcement of User Experience
In a world where more than 2.5 billion bytes of data are created every day, it is essential to deliver information to users effectively. Cognitive agents’.
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Key takeaways
- In a world where more than 2.5 billion bytes of data are created every day, it is essential to deliver information to users effectively.
- And less time searching for information means shorter resolution times, which equates to lower costs.
- We are at the crossroads of three momentum, application modernization, innovation through AI, and DevOps that will elevate the value of services for us and our customers.
In a world where more than 2.5 billion bytes of data are created every day, it is essential to deliver information to users effectively. Cognitive agents’ technology can understand human language to provide accurate information and quickly direct users to the optimal next step. Allowing cognitive agents to do the heavy lifting frees up human resources to tackle more extensive and more complex problems. This combination of technology helps humans produce a better user experience for everyone. As a result, advisors get the information they need to help clients resolve their inquiries faster.
How Does This Technology Work, And Who Makes It So Valuable? #
Cognitive Computing #
Cognitive agents are born from one of the main building blocks of artificial intelligence: cognitive computing. It is basically simulation of human thought processes in a computerized model. And it includes self-learning systems that harness data mining, pattern recognition, and natural language processing (NLP) to mimic patterns of the human brain. These applications are:
ADAPTIVE Cognitive solutions adapt to changing information, objectives, and requirements, thus making it possible to plan and resolve ambiguities. Most of the time, cognitive computing solutions can also process data in near real-time.
ITERATIVE AND STATEFULCognitive solutions help define a problem or find additional sources if a problem statement seems ambiguous or incomplete. Previous interactions may also be involved in determining or completing problem statements.
CONTEXTUAL Cognitive solutions can understand, identify, and extract contextual elements, including syntax, meaning, time, location, domain, regulation, user profile, process, task, and purpose. In some cases, they can also extract structured and unstructured information as well as sensory input.
While cognitive computer applications (like cognitive agents) can mimic the human brain, that doesn’t mean they are meant to replace human advisers. Instead, this technology can be seen as a powerful assistant capable of handling tedious tasks and freeing up human resources to tackle complex problems. And less time searching for information means shorter resolution times, which equates to lower costs.
Benefits Beyond Cost Savings #
Cognitive agents are an excellent money saver but they also have other benefits. For example, this technology can also improve data security, customer and employee experience, and visibility into business processes. At the same time, many organizations see benefits in simply using cognitive agents as “helpers” to living agents. à help provides information and recommends personalized offers to the customer more quickly; some use this technology to eliminate possible phishing before the interaction of natural agents to reduce the average processing time. Others have also benefited from combining cognitive agents with internal processes to speed up the onboarding process and reduce security issues and errors.
Success With Cognitive Agents #
Cognitive agents can be part of your digital transformation in many ways. Browse the stories below from real organizations to see how they implemented cognitive agent solutions to deliver valuable insights and a better user experience for clients and advisors.
Health insurance company #
Interactive cognitive agent, allowing providers to access member information quickly
CHALLENGE
A health insurance company with 13 million customers in the United States needed a better way to handle member inquiries from providers. Calls were driven by an outdated interactive voice response (IVR) system, and volumes exceeded 700,000 calls per month, with most callers opting out of the IVR system for expensive outsourced call centers.
STRONG POINTS #
- Development of a cognitive agent to converse naturally with suppliers and return correct information in good time and efficiently
- Performed IBM Watson Dialogue, Watson Natural Language Classification, Watson Speech to Text, and Watson Text to Speech
MAIN ADVANTAGES #
- Substantial reduction in the number of real agent requests, resulting in substantial savings.
- Reduced average call duration from eight minutes to three minutes
Multinational Software Company #
Reshaping the Customer Service Infrastructure with the Cognitive Agent IBM Watson
CHALLENGE
A software company specializing in architecture, engineering, construction, manufacturing, media, and entertainment struggled with an unfriendly and inefficient user experience for customers calling with service requests and questions. The company intended to improve this crucial customer experience and reduce its time to resolve issues and requests.
HIGHLIGHTS OF THE SOLUTION #
Implementation of IBM Watson Dialog and Natural Language Classifier. transform, automate and improve interactions
Understands the intention of conversations and can act as a digital concierge
KEY BENEFITS #
- Assisted management of around 60% of Group 1 requests from start to finish
- 90% decrease in support costs
- 99% reduction in resolution time
Multinational Conglomerate Company #
New cognitive shopping experience improves customer service and conversion rates
CHALLENGE
A Japanese and Korean conglomerate with functions such as retail, financial services, hotels, etc., seeks to optimize the shopping experience within their retail subsidiaries using cognitive technology to use their data better.
HIGHLIGHTS OF THE SOLUTION #
- Creation of a virtual advisor for purchases with a recommendation engine to analyze structured and unstructured data
- Text recognition, text-to-speech, and visual recognition capabilities
- Creation of a “customer DNA” with personalized recommendations based on purchase history
- Trend recommendations provided with social media keywords analyzed by AI
KEY ADVANTAGES #
- New services concerning in-store purchases and advice via a cognitive chatbot
- Personalized recommendations in real-time
- Improved customer experience with higher conversion rates
- Consolidation of disparate data sources into a unified “customer DNA.”
We all have scenarios in mind that use, for example, machine learning techniques that can automatically process ever-increasing volumes of data. This field has grown exponentially in terms of innovation in recent years. As a result, human-machine parity is getting closer to detecting and recognizing objects, speech, text comprehension, or translation.
The design of innovative services based on cognitive benefits allows companies to tell the right story by drawing on the user’s context as a differentiator. For example, it is possible to locate a user to generate engagement in a public place, manage employees’ safety on industrial sites, or imagine new residential uses of our daily lives. The field of possibilities is vast!
We are at the crossroads of three momentum, application modernization, innovation through AI, and DevOps that will elevate the value of services for us and our customers.
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