Say Hello to AI Assistants 👋🏻 | Conversational AI Market Map by Zenith AI
Welcome to the #1 edition of 'AI Strategy' by Zenith AI & explore an in-depth analysis of all these chatbots that could replace your customer service team (but will actually skyrocket it).
h•AI there,
In a world where AI is transforming industries at lightning speed, staying informed is your best strategy. Whether you’re just starting out with AI or you’re already a pro, this newsletter is designed with you in mind. Trust us, you won’t want to miss out.
Each issue will dive into a different aspect of AI and its impact on various industries, giving you the insights you need to make smart decisions. Rest assured, we respect your time & attention — you’ll only hear from us when we have truly exciting and valuable content to share. No spam, just the good stuff!
Expect in-depth looks at the latest AI trends and breakthroughs shaping the future. We’ll share real stories of businesses successfully integrating AI, along with their challenges and successes. Plus, get exclusive insights from industry experts you won’t find anywhere else.
With no further ado, let’s get into our first issue—Conversational AI.
In this edition, the spotlight is on Conversational AI, a simple yet groundbreaking innovation transforming business interactions and operations. It revolutionizes the way businesses engage with customers and streamline internal processes, making it an ideal starting point for our tech stack map.
The sudden success and popularity of LLMs such as GPT, Claude, LLaMa, and Gemini (regardless of generation) posed a significant challenge to many vendors active on the market long before November 30, 2022, when ChatGPT was released to the public. The market for conversational tools was no exception and is one of the markets most heavily impacted by the rise of generative AI (GenAI).
Market Map Compass:
To help you better understand the market, we've mapped key vendors in conversational AI into internal and external applications, further categorized by specific use cases. Our classification focuses on dominant use cases, highlighting UX as the primary differentiator influencing performance across areas. Note that vendors often operate in multiple use cases.
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Market Map Categories:
AI Chat Support providing text-based solutions to reduce the need for customer service staff involvement.
AI Voice Support offering voice-based solutions to minimize direct engagement of customer service personnel.
Agent Support delivering AI solutions to enhance the efficiency of customer service employees.
AI Chat Support / Internal Automation Support offering AI-driven solutions to automate conversations in departments like IT or HR.
Knowledge Search enabling efficient searches of organizational databases and knowledge sources for employees.
AI, just like our bodies, needs a strong core.
It might seem that GenAI is a technology completely different and independent from what has already been built to efficiently run so-called “flow-chart chatbots” based on simple algorithms. However, it is quite the opposite. GenAI opens a new chapter in the history of building customer service products, but it is still a chapter in the same book. While GenAI enables new features and capabilities, the core of every good conversational platform remains the same. Every effective conversational platform should include privacy, security, and compliance procedures, as well as analytics modules, back-end integrations with the client’s tech stack, dialogue management features, multimodality, and multichannel connectivity (either integrated or enabled by an external provider).
“Powered by AI” is a commodity.
All vendors on our map have either been GenAI-native companies or have recently added GenAI features to their product offerings. Most of them use prompt engineering via RAG (Retrieval Augmented Generation) to improve the performance of LLMs running in the background. Their interactions with LLMs are usually quite similar. Therefore, you should focus more on specific guardrails for validating LLM responses. These guardrails should be built on use cases or industry-specific experience and datasets. We encourage you to take a closer look at vendors highly specialized in specific industries or GenAI use cases.
Longer doesn't mean better.
Some vendors that have been active in the market for over five years claim that their experience puts them in a better position to serve customer needs. We do not see any correlation between years of experience and the quality of products in the GenAI area. Many groundbreaking innovations in this area have occurred in the last 2-3 years, so tenure in this market should not be a significant factor when benchmarking different solutions. For instance, the partnership for voice solutions between IBM Watson and McDonald's ended abruptly last month. IBM Watson, despite its years of experience in AI, was unable to successfully meet the needs of this customer.
Watch your risk/ reward ratio.
When considering possible Conversational AI use cases, remember that GenAI has its lights and shadows. Even without advanced fine-tuning, it is capable of helping employees find useful information in unstructured data, thereby streamlining their work. In this case, small inaccuracies are acceptable because employees can use their experience and expertise to verify the information received from GenAI. Generally, newly available GenAI-native solutions are more suitable for supporting employee-assistant use cases. However, for customer-facing applications, the error margin is much smaller. You should spend more time testing and improving the model before launching it to the public.
Muffintech built a specialized Generative AI solution for the insurance industry, leveraging a robust Large Language Model (LLM) to enhance customer service, sales, and operational efficiency. Key features include 24/7 client support, sales automation, claims management, and seamless CRM integration.
Muffintech’s LLM accurately interprets inquiries and provides precise information, supporting both customers and employees. Applications range from automating routine customer support to streamlining internal processes like claims management and sales. This optimization leads to faster, more accurate responses and improved customer interactions.
The product has delivered significant improvements within the insurance sector:
GOING PUBLIC! partnered with Muffintech to create an AI-powered bot designed to assist prospective insurance brokers with preparing their certifications. This AI enhances learning through practice questions and interactive modules, helping brokers prepare for the proficiency exam.
Additionally, muffintech’s products serve as a personal assistant, offering real-time support for industry-specific queries and promoting ongoing professional development with up-to-date information and resources:
Bastian Kunkel from Versicherung mit Kopf noted enhanced efficiency by addressing bottlenecks and streamlining processes.
Hava Misimi from Femance Finance praised muffintech for its exceptional performance and deep industry understanding, positively impacting operational processes and customer interactions.
Armin Christofori from SDV AG highlighted the significant value muffintech's customized solutions and AI expertise bring, showcasing a deep commitment to meeting the unique needs of the insurance industry.
Zenith’s comment:
Muffintech is a perfect example of a vendor that enterprises can onboard to enhance their operations with tailored AI solutions for the insurance industry. Unlike generic solutions or building your own LLM, Muffintech offers tailored features for quick implementation and ongoing support. Its advanced AI, AION, handles complex queries with high accuracy, while customizable tools enhance operational efficiency.
Zowie provides a generative AI-powered platform designed to enhance ecommerce customer service, increase revenue, and reduce costs. It automates customer conversations and provides data-driven insights, boosting conversion rates by up to 18%.
The product proactively engages customers, helping them make informed decisions. It features auto-ticket assignment and buyer intent recognition to streamline efficiency and turn customer support into a revenue generator.
Zowie has delivered impressive outcomes across various clients:
When True Classic switched to Zowie, the AI efficiently handled the workload of eight customer service agents, enabling the company to manage high interaction volumes without extra staffing. This resulted in a $3 million revenue boost and streamlined operations, with features like auto-ticket assignment improving agent efficiency and allowing the support team to focus on complex inquiries.
Calendars.com implemented Zowie’s solution in just two weeks, achieving automation goals quickly and minimizing disruption. This led to an 81% drop in chat wait times, significantly enhancing customer service. Overall, Zowie improved metrics with a 57% reduction in wait times, a cut of 17 seasonal agents, an 84% automation rate, and a 40% rejection rate, showcasing its impact on efficiency and satisfaction.
Zenith’s comment:
In our view, selecting Zowie provides a significant advantage in enhancing customer engagement and driving revenue growth, all while simplifying implementation compared to building a custom solution. This platform is particularly well-suited for ecommerce businesses, as it leverages innovative AI capabilities to automate conversations and recognize emotional sentiment, ensuring a seamless customer experience.
Why Your Failed Chatbot Experience Doesn't Mean AI isn't the Future
Misleading tips. Same answers to different questions. Irrelevant insights and relevant mistakes. Dead ends. Conversations as natural as C-3PO. When was the last time, when you felt frustrated with chatbot interactions?
Until recently, at least, some of them gave you a soothing voice of Samuel L. Jackson. But even this is not true anymore.
We know, for some time chatbots were not that great. Over 60% of customers felt that they are unable to solve complex issues. More than 50% felt chatbots do not understand their needs.
This is all true. For enterprise - big or small, automatic customer support has to make measurable difference. For clients, they have to make the experience.
But the world is changing and it is changing fast. Pre-trained vertical solutions, data pools extracted from Reddit and WhatsApp conversations, gen AI that give real person experience and can talk gaelic, flamand or silesian. Right now those conversational AI solutions can sound frightfully more true than the actors they are impersonating.
The questions anymore is not whether they make sense.
The questions are:
what do you really need?
do you have data?
can you use your data?
If you do - then you are ready for the next big thing. If you don't - no worries, we will tell you how to handle this.
If you're looking to adopt AI in your company, you're in the right hands with Zenith AI! Message us, and let's make it happen:
But anyway - do not spend any time thinking about old pre-defined chatbots. It is as smart as thinking about shortcomings of Ford T on Tesla release date.
Stay tuned and try to figure out how to make sure your client does not have to wait any more to solve his problems.
Chatbots vs. Voice Agents: Differences and Synergies
Chatbots and voice agents revolutionize customer interactions, each excelling in different areas and industries.
In eCommerce, chatbots integrate seamlessly, providing quick support, product recommendations, and facilitating purchases, handling multiple queries simultaneously, enhancing customer service and engagement. Their flexibility allows them to manage a wide range of tasks, from simple questions to complex issues.
In healthcare, where online patient interactions are less frequent, voice agents improve processes and patient experiences. They excel at specific tasks like appointment scheduling, visit confirmations, and handling complaints. Voice agents offer a human touch, comforting patients who prefer speaking over typing or simply are not tech literate, as well as serve visually impaired customers.
Though they serve different functions, chatbots and voice agents complement each other well. Advanced conversational AI is blurring the lines between them, enabling more open-ended interactions.
Together, chatbots and voice agents significantly enhance customer experience and business outcomes. For instance, a chatbot can handle initial inquiries while a voice agent manages more detailed or sensitive matters. This teamwork reduces costs and boosts revenue by improving customer engagement and loyalty.
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Until next time, stay AI-some!
Zenith AI