Virtual assistants are a white-hot topic nowadays. Vendor marketing drumbeat is loud, and they promise nothing short of eradicating world hunger with their chatbots! However, if you look beyond the hype, success stories are few and far between.
54% of online US consumers think that interactions with customer service chatbots will negatively impact the quality of their lives, per Forrester’s latest research, who predicts a chatbot backlash this year. A customer called the virtual assistant of a business he was dealing with a "virtual idiot"!
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How do you prevent your virtual assistant from suffering such ignominy? This article lists 12 mistakes to avoid.
While a chatbot can become smarter over time, trying to do too much with it at the outset often leads to failure. It is best to limit its scope to a narrow set of use-cases and intents to get a quick win and then gain momentum.
When customers have a specific question, many chatbots just push back web pages or FAQs or documents instead of answering the question. It is like giving the entire haystack rather than finding and handing over the needle, which is what was demanded from a chatbot.
It is important to first understand the intent of the customer for fast time to answer. Except for the lonely soul or two out there, consumers are not looking to socialize with chatbots—they want quick answers. A good practice is to use human chat conversations, label the intent, and use machine learning to match the customer utterances to intents.
Many chatbots, even those touted as success stories, ask users repeatedly to rephrase the question even after they unload all the synonyms from a thesaurus! Step #3, combined with robust Natural Language Processing capability can help understand intent better.
Understanding intent is a good first step. Next, the chatbot needs to be able to converse and guide the customer to an answer, especially for the more complex queries. Look for a chatbot solution that is backed by AI reasoning to provide such guided, conversational assistance.
One of our major telco clients uses our agent-facing bot, backed by reasoning and knowledge, to guide 10,000 agents in the contact center and associates in 600 retail stores to answers. The company has since seen a 37% improvement in FCR (First-Contact Resolution), 30-point improvement in Net Promoter Score (NPS), and 50% improvement in agent speed to competency.
Some businesses are looking at creating a concierge bot and a set of specialist bots, where the concierge passes the baton to specialist bots if it is unable to answer a question. Bot-switching can be as painful as channel switching and can lead to poor customer experiences, especially if the specialist bots cannot resolve the customer query.
The answer is in implementing a smart chatbot, powered by a robust knowledge base and reasoning capabilities, that can escalate to human chat agents with full context ensuring the best possible customer experience. Another approach is to make the bot switch invisible to the customer. In either case, the customer experience should be at the front and center of the approach.
Chatbots should be able to escalate to human agents, based on customer sentiment, customer value, customer situation, its own inability to resolve the issue, or a combination of these factors. And, it should do so with all the context intact so that the conversation with the human agent moves the conversation forward instead of starting over.
Some queries may need long-lived, multi-step resolutions. In such cases, the chatbot should be able to pause a conversation and pick it up where it left off without asking the customer to repeat information or steps that had already been completed. You need a unified, omnichannel customer engagement system, backed by knowledge management and AI reasoning, to ensure these capabilities.
One of our premier clients uses our chatbot to answer DIY tax-payer questions. Where needed, the customer is given the option to escalate to a human advisor with all the context intact. The advisor then chats and cobrowses with the consumer to answer questions and help fill out forms in real-time, a novel experience for the consumer and a win-win for both the consumer and the tax preparation giant!
While it is OK to start small, the business should make the chatbot smarter over time in both breadth and depth of knowledge and knowhow. Moreover, the knowledge base and AI reasoning paths need to be updated and optimized with analytics on an ongoing basis.
Chatbots can go beyond reactive customer service to proactive engagement. It is important that you make it visible on your website. Feature the chatbot at least on the top 10 most visited web pages, in addition to the support section.
When consumers look to get customer support, the last thing they want to do is stare at the wait cursor, whether it is the wheel or the hour glass! If your chatbot is not fast, they will defect. Make sure it can scale.
Your chatbot needs to be aligned with the brand in both style and substance. If it is fronted by an avatar, make sure it is aligned with the personality of your brand and the target customer. So should the bot’s conversational tone mirror your brand style. If it is a high-touch brand, you may want to escalate more quickly to a human if the chatbot is unable to answer the customer’s question.
With many vendors promising omniscience from their chatbots, you are faced with the unenviable task of picking one. Technology capabilities are important and so is best-practice domain expertise. How long has the vendor been in the space? Do they put skin in the game by offering risk-free pilots with best-practice guidance, all free of charge? Get answers to these questions.
By avoiding these mistakes, you can make your virtual assistant a virtuoso assistant!
About eGain Corporation:
eGain customer engagement platform automates digital-first, omnichannel experiences across all touch points. Powered by AI, machine learning, knowledge, and analytics, our top-rated software optimizes customer journeys with virtual assistance, messaging hub, and desktop to serve customers, reduce cost, and improve compliance.
Published: Wednesday, September 2, 2020
VoiSentry is a voice biometric engine for speaker verification / identification. It is delivered as a virtual instance to be controlled by an application via APIs and can be deployed in whatever is the most appropriate environment i.e. public cloud, private cloud or on-premise. It is generally deployed as a white-label or OEM product, whereby Aculab’s partner integrates it into their own solution/platform and offers it as an integral part of their service. Unless they go public with it, none of their clients would even know that it was Aculab’s VoiSentry engine under the hood. As with any biometric speaker verification system, VoiSentry is language and dialect independent.
Agara is an autonomous virtual voice agent powered by Real-time Voice AI. It is designed to have intelligent conversations with your customers, vendors, and partners without any assistance from human agents. It can handle a wide variety of calls including inbound customer care calls, outbound lead generation calls, appointment scheduling calls, and overdue payment recovery calls.
Agara is available for several industries including banking, insurance, retail, e-commerce, airlines, and telecom. Powered by advanced Real-time Voice AI that understands speech in real-time, automatically determines the right process to follow and guides the caller along in the process with natural conversation.
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Execute automated actions based on words spoken by your customer.
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Daisee builds technology that empowers people to solve problems by making interactions simple and smart so they can have a more significant impact, be more productive and be better at what they do. We believe incremental improvements carry huge potency and provide exponentially greater change for the better.
Genesys customers can now automate risk and quality management using Daisee’s speech and sentiment analytics and remediation workflow software. Daisee helps improve customer experience, ensure regulatory compliance, identify missed commercial opportunities & training requirements as well as provide valuable insights back to the business directly from the frontline – the true voice-of-...
Advanced speech recognition and natural language expertise that routes callers by simply asking ‘how can I help you?’. It allows customers to use their own words to ask for what they want and steers them to the right place.
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An all-inclusive speech analytics application that enables you to visualize your audio using state-of-the-art speech recognition, transcription, and text analytics technologies.
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|9.)||Voci Technologies Incorporated|
V-Blaze Speech to Text
Our GPU-accelerated, AI-based technology enables you to deliver greater insights to the contact center by transcribing audio into analyzable text.
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