The Good, The Bad And The Bot: How Chatbot Experiences Can Make Or Break Your Business

How trusted generative AI can improve the connected customer experience

How to Improve Customer Experiences with AI Voice Chatbot?

Conversation-driven experiences will transform how people interact with companies. In fact, 63% of customers would prefer messaging with an online chatbot (Mindshare), while 33% of companies that use virtual agents report an increase in customer satisfaction, plus save 33% per voice engagement (Gartner). Despite their versatility, many first-gen chatbots struggle to understand complex requests or questions and are limited in maintaining context throughout an interaction.

Generative AI on its own will not improve the customer experience

How to Improve Customer Experiences with AI Voice Chatbot?

Customer experience (CX) will be the big winner of the current voice tech bonanza. The faster and more completely customers’ needs are solved, the more positive the experience. Conversational AI is the bridging innovation to make it easiest for customers and businesses to communicate.

How to Improve Customer Experiences with AI Voice Chatbot?

Agent Workspace brings UCaaS and CCaaS together

Maxie Schmidt-Subramanian of Forrester Research tells us AI will help us get closer to understanding customer emotions by using speech analysis and facial recognition. Looking at purchase data, they would find that people who return things are more inclined to purchase more, so helping expedite this process would lead to more sales. With all these data points, the AI would spit out a suggested action that there should be a separate process for returns than other purchase activities. “LLMs are fundamentally changing the way search algorithms work,” Sean Mullaney, CTO of search engine SaaS platform Algolia, told VentureBeat. Traditional search engines match individual words from a query with the words in a large index of content, he said, but LLMs effectively understand the meaning of words, and can retrieve more relevant content. For instance, AI might recommend what to do for a customer case based on the information it has.

How to Improve Customer Experiences with AI Voice Chatbot?

These images and text are sufficiently advanced to convince a human that people and not computers create them. Voice biometrics is emerging as a solution for AI-based behavior tracking and composite risk-based authentication. Unlike just a match on whether something is “true” or “false,” which is a binary result from other biometrics systems, a “confidence score” is the output of the voice biometrics system, so one can do RB-MFA with voice with ease. According to Maxie, there are some current challenges to be overcome until AI and machine learning can fully work their way into VoC product development efforts. Explore the future of AI on August 5 in San Francisco—join Block, GSK, and SAP at Autonomous Workforces to discover how enterprises are scaling multi-agent systems with real-world results.

This has resulted at times in a stilted or rigid customer experience, as the chatbots are often restricted to a limited set of interactions. At Verizon, for example, AI gave customer service representatives instant access to information about the customer, the interaction and the context. Now, more than 40,000 Verizon reps use AI-driven tools to support customers and make sure everyone is on the same page. After all, your customers shouldn’t have to repeat themselves or reexplain their preferences every time they interact with your company. These days, customer experience is “a seamless digital and physical interaction,” said Vivek Gurumurthy, the senior VP and CIO of Verizon Consumer and Business Group.

Mostly spending more of their time assigned complex tasks that require higher-order analysis of situations that have no clear resolution. Similarly, whether you want to know your latest account balance or you want assistance transferring $100,000 from your savings to a checking account, the set of questions or verification process could be the same. All this can lead to frustration and even compromise security, as personal information is often easily available on social media or through social engineering methods imposters follow. Another advance to look out for, according to Maxie, is a chat-bot interface for the business data user.

At Salesforce where I work, we have changed all of that with the advent of Salesforce Genie Customer Data Cloud. We have connected the customer data, harmonized it into a customer graph, and made it available to all departments in the organization. You might also ask if the agent answered your caller’s questions or met their needs. The data collected and analyzed can help determine if your automated interactions are achieving the desired result of improving the customer experience.

  • Conversation IQ can be utilized by any person performing any role within an organization, whether it’s the contact center, front desk, or back office.
  • But perhaps the biggest barrier to AI adoption is a mix of data silos and systems fragility holding companies back.
  • Krish tells us that you want to apply machine learning on top of all the direct and unsolicited data you collect and sort it to see if it data points are one-off event or more systemic.
  • Chatbots are a great way to offer users real-time, round-the-clock support that moves customers through the sales funnel.

Start with the most boring, repetitive tasks

AI-driven chatbots are commonly used on websites as a way for customers to instantly locate the goods or services they are searching for, as well as for customer service needs. “The challenging part is fine-tuning the models to solve specific customer problems, such as in ecommerce or customer support where the answers are unavailable from the base training. In addition, these use cases need proprietary company data to fine-tune them to meet domain-specific use cases like product catalogs or help center articles,” said Algolia’s Mullaney. Traditional chatbots allow interaction in a seemingly intelligent conversational manner, while the GPT-3’s NLP architecture produces an output that makes it seem like it “understands” the question, content and context. However, the current version of ChatGPT also has its drawbacks, such as generating potentially false information and even politically incorrect responses. The OpenAI team has even advised against relying on ChatGPT for factual queries.

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