Krisp’s Post

7 out of 10 people are either frustrated or annoyed with today’s AI voice agents 😱 Respondents say their biggest complaints for human agents are long wait times (39%) and the agent having difficulty understanding accents or speech clarity (39%). In this interview, John Robb, Head of Customer Success at Tenyx and I do a deep dive into how customers perceive AI voice agents today. Here’s what stood out to me most 👇 1) AI systems must focus on more than speed, including understanding pauses, interruptions, and background noise. 2) Latency improvements in AI are important, but sometimes systems may need to slow down for better interaction quality. 3) People are disappointed with the current state of automation, presenting both a problem and creating an opportunity for innovation. 4) Many current automated systems are based on outdated, 10+ year-old technology and customers expect more. 5) Automated solutions and deployment should deliver immediate benefits to both businesses and customers. 6) Technologists must avoid trying to do too much, too soon in AI development. 7) AI deployment should start small and gradually expand to be successful. 8) Striking a balance between innovation and practical application is crucial for successful AI deployment. 9) Consumer frustration likely lies more with outdated, inadequate tech than lack of human touch. 10) Consumers prefer human agents but are frustrated by long wait times and agents’ inability to understand accents. 11) Perfectly functioning automation should connect users to human agents as quickly as possible, and enable humans to be super agents once connected. 12) Effective AI agents should quickly address the top 10 customer queries and deliver needed information fast. 13) Over the next five years, AI will increasingly remember preferences, leading to smoother and more personalized interactions. 14) Fully conversational AI agents will reduce or eliminate wait times, massively improving customer experience. John, thanks for your time and insights 🙏 Full interview here 👉 https://lnkd.in/eGm8xRH3

85% of call centers will employ generative AI over the next 5 years. Accenture recently predicted that more than $10.3 trillion in additional economic value can be unlocked by 2038 if organizations adopt generative AI responsibly and at scale. Gartner just predicted that "2024 will be the year when organizations actually invest in planning for how to use GenAI." None of this is surprising. Here at ASAPP, we have been seeing how transformative AI + automation is for many of our Fortune 500 customers. The key to unlocking the real power of Generative AI is to *focus on business outcomes* and highly refined experiences.   ASAPP recently launched GenerativeAgent, the industry's first fully operational Generative AI agent, built exclusively for CX. It's wild how transformative this is from a cost savings perspective. If you'd like to see it in action, let's talk! https://lnkd.in/dkiZy5c8

The path to effective AI adoption is inherently complex, necessitating a strategic and deliberate approach. By launching targeted pilot initiatives, organizations can gain valuable insights into the technology’s capabilities and constraints, thereby establishing a robust foundation for future scaling. To navigate the intricate landscape of generative AI implementation in customer experience, it is essential to examine the six key challenges and explore actionable strategies for overcoming them.   #GenerativeAI #PowerofConcentrix   https://shorturl.at/D9uRk

“The technology speeds up the whole process,” he says. “An email that would normally take an agent 12 minutes to answer now takes about a minute and a half, so you can see the value of having 10 spare minutes to do complex value-adding work within our business.” Take a look at CIO Online's recent post about How CIOs Use AI to elevate CX services! #ConsultisExcellence #CIO #AI #GenerativeAI

The average return on investment for implementing conversational AI in contact centers is huge, with numerous benefits contributing towards this. On average, businesses see an ROI increase ranging from 30% to 40% of current function costs when they deploy conversational AI technologies such as virtual assistants and chatbots by enhancing productivity through automating routine customer interactions which in turn reduces labor costs and operational expenses. McKinsey & Company found that companies using generative AI for customer service functions experienced a 14% increase in issue resolution per hour and a 9% reduction in handle time. This translates into lower overall costs and higher efficiency, contributing to the afformentioned substantial ROI improvement. Additionally, these AI solutions help decrease the cost per call below the industry benchmark of $4.50, further boosting ROI. For comparison a bot handled interaction can cost as little as $0.10. Moreover, conversational AI implementations done correctly, result in increased customer satisfaction and retention rates. Companies report up to a 50% increase in customer satisfaction scores and a 40% improvement in customer retention rates. More loyalty, more customer lifetime value! If you would like us to put together a free, no obligation, ROI Calculation based on your contact center then please reach out to us at the link in the comments

👏👏 And now, the Standing Ovation + Slow Clap Award for Best AI Quote of the Day goes to... Dan Eddie, director of customer service at Simplyhealth... “I don’t think AI is the future; I think it plays a part in the future. Success still comes down to having the human involved in understanding the complexity of the customer requirement. We’ll continue to test and learn, and we’ll evolve the capability we have. But human expertise is always at the heart of all the great stuff we do." https://hubs.la/Q02ns10v0 #Healthcare #AI #DigitalTransformation #Innovation #CX

There’s a big gap between businesses' desire to implement AI chatbots and consumers’ desire to interact with them over a human according to Forrester research. It’s not the consumer’s fault – there’s a lot of bad chatbot implementations, and a lot of tools that make bad implementation easy. How and why a business deploys AI to their customer support operations dictates the outcome. The Wall Street Journal published an article outlining where AI powered customer service fails consumers. It’s a great look at areas we focused on when building Lyro, our AI support solution for businesses: Over promising and under delivering: Lyro solves up to 70% of your customers’ conversations automatically, and that’s a claim we stand by. We see it with our customers every day, and we build best-in-class training tools – and support from our team – to get them there. They can serve up inaccurate answers: We pride ourselves on being the most accurate AI on the market. By always using the latest models like Claude 3 and setting a high confidence threshold, we’ve achieved the highest possible levels of accuracy. If the model detects any chance of inaccuracy, we bring humans in to the loop. They don’t let you multitask: Lyro persists across your entire website and even across sessions, meaning customers can pick up conversations later in their session, or even days later if they don’t buy right away. That one conversation can contain all of the questions a customer might have throughout their journey. They aren’t human enough – or they’re too human: Life as an AI is tough – it’s hard to be all things to all people. Between Personalization and Tasks, businesses can configure how Lyro should behave in general, and in specific situations that might benefit from a specific tone. Building Lyro, we wanted to make sure that we built a product that solved business needs, but was also something customers looked forward to using. We’re going to keep closing that gap, because instant responses aren’t helpful if they’re instantly frustrating.

Webinar in the morning, blog post in the afternoon with Ewan MacLeod. We didn't get a chance to get to all the questions, and one stood out with importance that needed to be addressed. https://lnkd.in/gc6qd82x is a full briefing on the benefits of Conversational AI. Now, I don't normally attest to the "if your friend jumped off a bridge, would you" but that does (maybe) apply here. If others are seeing, seemingly, insane results, don't you want to see some of that in your own organization too? 200% increase in collaboration efficiency. 400% faster time-to-insight. 96% time reduction. Just naming a few that are more quantitative in their ROI. But also seeing people report results like increase employee satisfaction. What are two use cases that are seeing "low hanging fruit" adoption? Knowledge management and Service management. -KM: The problem - I know a doc/file/paragraph of text/etc. exists somewhere, but don't know who or where to go to get this answer. We all have this challenge. Even at Squirro. At Squirro, we use our own platform internally for just this. -Service Management: We all hate chatbots. That is the old 'conversational.ai' but with #tailoredAI, which is our way of delivering Squirro, we ensure AI accuracy and precision that employees and customers can trust. Leveraging #graphRAG increases that accuracy of #Conversational.ai for customer interaction. #AIGuardrails ensure it stays on brand and can be trusted externally. #Agents gain access to #operationaldata across systems to deliver answers to customers. Why? Get customers the answers they need faster with a better experience and allow customer-facing employees better focus on high ROI elements (solve problems, white-glove service, etc.).

Let's be real for a second - AI chatbots have a 💩 press. And why wouldn't they? They’ve been known to sell cars for $1, offer returns where they shouldn't, and make things up without a second thought. For humans, that's unthinkable; for AI, it's no-brainer 🤭 I’m a dreamer and designer at heart who loves to inspire people. I’ll admit, I sometimes get carried away by what I wish AI could do 🤷♂️ That’s why having a cautiously optimistic team is crucial. They keep us grounded and ensure we deliver on our promises. I can't count how many times I've been told by my Tidio colleagues not to oversell or overpromise what Tidio AI can do 👏 That’s why I’m confident that Lyro AI Chatbot is a game-changer. Despite the bad press, thanks to the balance in our team, we know Lyro isn’t just another AI chatbot. It's the future 🚀

Generative AI can help staff answer customer queries efficiently and effectively. But that’s the least it can do, or what IT leaders expect of it. My latest feature for CIO Online shows that the key to unlocking generative AI's real power is to focus on business outcomes and highly refined experiences.