Cognitive Search Podcast: Recent Episodes
Cognitive Search Podcast
Elevate self-service & support with AI-powered apps built on a unified cognitive search and insights platform
Chatbots have been the talk of the town for a while now. You no longer have to wait for an agent to answer the call or reply to a mail in order to get a solution to your problem. Thanks to the dramatic advancements in Machine Learning (ML) and Natural Language Processing (NLP) that has empowered software to answer your queries without involving a live agent.
Today’s chatbots are smarter, responsive and omnipresent. Perhaps a reason why a report by Research and Markets states that by 2024, the chatbot market size will be worth USD 9.4 billion. Despite the predicted ROI from chatbot investments, businesses are in a dilemma whether to incorporate one into their customer service system or not.
In today’s episode, we invite our Technical Manager, Sagar Awasthi who to the best of his abilities will try to clear up this dilemma. Tune into this podcast and hear him talk about:
- Evolution of chatbots
- Shortcomings of traditional chabots and how a search-powered chatbot helps to overcome them
- Role of chatbots in enhancing customer support services
- How actionable insights generated by search-powered chatbots enrich CX
It takes a village to provide an unforgettable user experience that drives brand loyalty and gives your customers a reason to keep coming back. But how? Only a handful of brands have recognized that the key to stellar UX is infusing AI into the business.
Investing in technologies based on AI & machine learning will help you have a leg up on the competition. They help you in leveraging neglected user data at different touchpoints for improving customer experience. And this is just the tip of the iceberg. There's a lot more where this came from.
Our guest today Bharat Sethi, has worked with a number of technical teams and assisted them with measuring and improving user experience. Tune in to this episode and hear him talk about:
Key Takeaways
- Key components that influence a user experience
- Technologies that will shape the future of CX
- Metrics to measure & improve user experience
Self-service is a win-win for businesses as well as for customers. Customers love to help themselves. According to Harvard Business Review, 81% of customers prefer self-solving their issues before reaching out to a support representative.
And businesses save support cost when they enable their customers to self-serve. That makes driving customer self-service the holy grail of customer service leaders and case deflection is an important way to achieve and measure self-service success. One of the most important questions for service leaders is “What exactly is case deflection, and how do we accurately measure it?” Is there one definite answer? Or are there more than one ways to define and measure it?
Our guest today, Sumit Aggarwal, has worked with a number of service leaders and assisted them with measuring and improving case deflection. Tune in to this episode and hear him talk about:
What is self-service and case deflection? How to define and accurately measure case deflection? How to improve case deflection? How does intelligent search improve the self-service experience?
KCS is about creating knowledge as a by-product of resolving problems. And that knowledge is then used by customers and support teams across self-service communities, support consoles, websites, etc. But when it comes to implementing KCS, only a fraction of organizations have experienced success. Why?
To dig deeper, we invited Brian Corcoran, our Regional Sales Manager in the US and a KCS-certified practitioner. He has helped a variety of organizations increase their support capacity by driving KCS. Hear him provide succinct answers to questions like:
- What does a standard KCS process look like?
- What does a successful KCS implementation require?
- How does the double loop process drive KCS?
- How can cognitive search change the KCS landscape?
“Customers remember the service a lot longer than they remember the price.” Lauren Freedman, President of the E-tailing Group
It’s no secret that the impact customer service teams can have on user experience is enormous. Key metrics like CSAT or NPS are most directly affected by the quality of your support operations. That said, the lack of innovation in customer support has always been a problem. Agents can not be expected to surpass customer expectations using the same old tools and technologies. That’s why support organizations are turning to tech like artificial intelligence (AI) to help agents work more efficiently and power proactive support.
76 percent of contact center leaders say they plan to invest in AI over the next two years, and 56 percent see opportunities for widespread adoption in their contact centers, according to a Global Contact Center Survey by Deloitte. “These technologies can enable a skilled workforce to deliver personalized, human experiences to customers,” notes the survey.
Our guest for today’s podcast episode, Divanshi Arora, Customer Success Manager, SearchUnify has witnessed the power of AI-powered applications in empowering next-gen agents and help them deliver stellar customer experiences. Listen to her as she talks about:
- How critical is customer support to good customer experience?
- How can AI empower the next-gen support agent?
- How does agent augmentation reduce agent churn?
- What are some practical use cases of AI in augmenting agent productivity and contact center quality?
Contact centers have transformed from being cost centers to revenue centers. Customer support is no longer a reactive action of pacifying an irate customer and resolving their issue. It’s now about proactively supporting a customer, enabling them to self-serve, and converting them into brand advocates. The focus has shifted from support to experience and the role of support leaders has evolved from improving CSAT and reducing churn rate to delighting customers and growing them.
Our guest today, Vishal Sharma, CTO, SearchUnify has witnessed this transformation first hand and has worked with enterprises across industries to help them scale their support operations. Tune into this episode and hear him shed light on:
- What are the major pain points of support leaders?
- How can they make the most of their AI investment?
- How can they measure the ROI of their AI investments?
- How is cognitive search the underlying technology that powers support apps?