By AI Trends Staff
Conversational AI refers to the use of chatbots, messaging apps, and voice-based assistants to automate customer communications with a brand.
Software that combines these features to carry on a human-like conversation might be called a “bot.” The term “chatbot” might refer to text-only bots. Amazon Alexa or Google Home virtual assistants use conversational AI; they learn about the customer and the customer learns about them. With deep learning underlying the interaction, the conversation experience should improve over time.
The advantages of conversational AI in marketing include an instant response, which leads to higher conversion rates of queries to sales.
The adoption of conversational AI is being fueled by the rise in use of messaging apps and voice-based assistants, according to an account from the site of Shane Barker, a digital marketing consultant and cofounder of Attrock, a digital marketing agency.
The most popular messaging app, according to Statista, is WhatsApp, from a US startup now owned by Facebook, with over 1.6 billion users. That is followed by: Facebook Messenger with 1.3 billion users; WeChat, developed by TenCent of China, with 1.1 billion users; QQMobile, also from Tencent, with 800 million users; Snapchat from Snap, Inc. of the US, with 314 million users; and Telegram from Telegram Messenger, founded in Russia in 2013 on the macOS and released on Android in May of this year, with 200 million users.
“If you are not using conversational AI platforms yet, you should start now,” advised Barker.
The conversations could be text-based or audio-based, and can be done on any messaging or voice-based communication platform. While conversational AI is the technology behind chatbots and voice-based assistants, it is not synonymous with either. You can use a messaging service, a website chatbot or a voice-based assistant, and use conversational AI to automate conversations on it, Barker advises.
How Conversational AI Can Help Your Business
Some conversational AI technologies are advanced enough to understand the context and personalize the conversations. User-friendly chatbots can generate leads and help drive sales. The first and most common use of conversational AI is to provide around-the-clock customer service. The bot can answer commonly-asked customer questions, resolve problems and point to solutions. The user company can build a customized database of information that can feed the conversational AI platform to make it more accurate.
A website chatbot can interact with users and direct them to the right pages, products, or services — basically leading them down the sales funnel. The bot can also drive conversions by cross-selling or up-selling products. The bot can be trained to suggest complementary or higher-value products. The platform can also deliver offers and promotions to customers.
As far as lead generation is concerned, conversational AI-based chatbots can schedule appointments and collect email addresses during non-working hours. You can then pass that information on to your sales team, who can then nurture those leads.
Among the conversational AI platforms recommended by Barker are:
- LivePerson from LivePerson of New York City, with an AI offering released in 2018 from the company founded in 1998;
- SAP Conversational AI from SAP, the German multinational software company;
- KAI from Kasisto of New York City, founded in 2013;
- MindMeld now from Cisco Systems, founded in 2011 and acquired in 2017;
- Mindsay from Mindsay, headquartered in Paris; founded in 2016.
iAdvize Taps Network of Freelance Experts for Customer Service
Another player is iAdvize, founded in France in 2010, offering a chat tool focused on customer service. Today iAdvize is a leading conversational platform in Europe and is now expanding in the US. The company says the tool is currently being used by over 2,000 e-commerce websites worldwide including Samsung, Disney and Lowe’s.
The platform uses AI to identify each customer’s needs and connects them to a mix of in-store associates, in-house agents, chatbots and on-demand product experts from ibbu. Founded by iAdvize in 2016, ibbu today uses over 20,000 knowledgeable product experts from around the world who chat with customers and are paid for the advice.
The freelancers are vetted to be experts in electronics, home improvement, sporting goods, hobbies, and other product segments. They get paid a percentage of sales they generate. Ibbu experts the company says have conducted over 1 million conversations with iAdvize’s e-commerce customers.
Customers using iAdvize have seen an increase in online sales of 5% to 15%, according to the company. iAdvize was co-founded by Julien Hervouet, now the CEO. He stated in a press release on the announcement of ibbu in the UK in 2016, “We believe the future of marketing is conversational commerce, where brands use genuine fans to improve the customer’s experience of the brand.”
How Adobe Used an AI Chatbot to Support 22,000 Remote Workers
When the COVID-19 virus hit in March throughout the US, Adobe like many companies sent their workers home and shifted into remote work over a single weekend. “Not surprisingly, our existing processes and workflows weren’t equipped for this abrupt change,” stated Cynthia Stoddard, Senior VP and CIO at Adobe, in a written account published in VentureBeat. “Customers, employees, and partners — many also working at home — couldn’t wait days to receive answers to urgent questions.”
The first step was to launch an organization-wide channel using Slack, a business communications platform from Slack Technologies, launched in 2013 in San Francisco. The 24×7 global IT help desk would support the channel, with the rest of IT available for rapid event escalation.
The same questions and issues came up frequently. “We decided to optimize our support for frequently asked questions and issues,” Stoddard stated. They combined AI, machine learning and natural language processing to build a chatbot. Its answers could be as simple as directing employees to an existing knowledge base or FAQ, or walking them through steps to solve a problem. The team focused on the eight most frequently-reported topics, then continued to add capabilities based on what delivers the biggest benefits.
“The results have been remarkable,” she wrote. Since going live on April 14, the system has responded to more than 3,000 queries and has noticed improvement in some critical issues. For example, more employees are seeking IT support through email. It was important to speed the turnaround time on these queries.
“With the help of a deep learning and NLP based routing mechanism, 38% of email tickets are now automatically routed to the correct support queue within six minutes,” she stated. “The AI routing bot uses a neural network-based classification technique to sort email tickets into classes, or support queues. Based on the predicted classification, the ticket is automatically assigned to the correct support queue.”
The average time required to dispatch and route email tickets has been reduced by the AI chatbot from about 10 hours to less than 20 minutes. Continuous supervised training on the bot has helped Adobe achieve 97% accuracy, nearly on a par with a human expert. Call volumes for internal support have dropped by 35% as a result.
The neural network model is retrained every two weeks by adding new data from resolved tickets to the training set. They leveraged the work done for a company chatbot for finance. Adobe continues to look at robotic process automation, to explore business improvements through the combination of autonomous software robots and AI.
Keeping employees in the loop about the AI and chatbot technology being employed is critical. “When introducing a new/unknown technology tool, it’s critical to keep employee experience at the core of the training and integration process – to ensure they feel comfortable and confident with the change,” Stoddard wrote.