By Michael J. Martin
Not long ago, chatbots were fairly basic. They were programmed to perform specific tasks, responding to straightforward command scenarios where information revolved around single turns. Many chatbots were used as online or search pop ups and could send only simple messages like “How can I help you,” to online users.
Today, chatbots have evolved to be able to discern the meaning of queries by analyzing and comparing different elements. Innovative technologies like artificial intelligence (AI) are making this transformation possible, thereby transforming how businesses and marketers use chatbots to interact with consumers.
Science has made leaps and bounds in AI and natural language processing (NLP) to allow individuals to interact and converse with computers much more naturally.
As a result, chatbots have become more than greeting tools. They now play significant roles within marketing and customer service for organizations across every industry, including retail, e-commerce, banking and healthcare. Chatbots are helping customers with almost any function, from ordering pizza to online shopping.
For marketers, some of the key benefits of AI-powered chatbots include:
- Instant communication with customers that avoid long wait times and complicated explanations;
- Driving more personalized customer experiences by understanding specific customer needs, wants and concerns to ultimately boost brand advocacy and increases business revenue; and
- Better engagement and open rates when compared to methods of old, like direct email or mail-ins, which audiences typically (and easily) ignore.
In industries like retail companies can use chatbots for personalized marketing systems. For instance, a floral retailer can use the system to help detect user tone. With an AI-powered gift concierge to interact with online customers, the chatbot can be designed to use NLP and ask users questions about the specific occasions for their purchases. With this information, the chatbot can then suggest personalized gift options.
More companies are realizing the competitive advantage of chatbots. According to an IBM report, chatbots could bring cost savings of USD $8 billion annually by 2022, up from USD $20 million in 20171. A recent Gartner study 2 states that by 2018, 30% of our interactions with new technologies will be through conversations with smart machines.
IBM believes organizations can use AI platforms to build chatbots that assist customers at a higher level of understanding and intelligence and with a wide range of tasks than ever before. Here are several ways companies can use chatbots to boost the customer experience:
Man and machine working together.
Many companies are tapping virtual assistants to help human customer service agents provide more personalized guidance. Incorporating a chatbot into a customer service program is an opportunity for human and machine to work together to give the best outcome for a customer.
For example, an e-commerce site could use virtual customer service to reach out to customers (subject to the Canada Anti-Spam Law), and help marketers better and more quickly understand customer queries. After a few months of training, the chatbot can respond to questions with 80% more accuracy, leading to more satisﬁed customers.
AI makes chatbots customizable. AI-enabled chatbots are built on many different technologies, such as cloud, that equip them to accomplish various tasks like analyzing huge amounts of data and NLP to understand customers’ tones and sentiment. Chatbots can be built to suit the specific needs of their organizations rather than fit into standard models. As a result, businesses and marketers can provide personalized experiences, advertising and promotion items that are tailored to specific end-customers.
Building emotional intelligence into chatbots. Advances in AI will progress and allow businesses to add emotional intelligence to their chatbots. Cognitive computing capabilities can gather data about users’ preferences and intentions through the words they use. The primary purpose of every conversation with a chatbot should be to certify that the customer feels understood.
The future of customer service
The progression of AI means that chatbots will continue to become more skilled in natural communication, emotional intelligence and data analysis. To better serve customers, automated conversational agent systems have to be trained
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. Chatbots cannot just be programmed to perform specific tasks. They have to learn. They have to fundamentally interact with us like humans and know that we have emotions that can vary throughout the course of a conversation.
That said, as more AI conversation agents have a deeper level of understanding of people and become more skilled at mimicking human behaviour, it will be critical that businesses become transparent about whether the system interacting with the end user is human or AI. To maintain customer loyalty, users should never be misled into thinking that the agent they are interacting with is a real person if it is not.
Companies must also take responsibility for protecting customer data that is presented in a conversation and maintain strict privacy of the individual to ensure that they are not unnecessarily revealing information that is irrelevant to specific issues, and in compliance with applicable regulations.
The future of the customer service experience will ultimately be fueled by AI through learning, reasoning and understanding customers’ intentions. AI will help businesses and marketers make smarter, responsible decisions that will benefit customers by providing them with respectful loyalty-building service.
Michael J. Martin is senior executive, of Internet of Things Lead, Broadband Networks and Network Services, IBM Canada
Qoints enables micro influencer campaigns with IBM Watson AI
Qoints is a Cobourg, Ontario-based company that provides access to live digital marketing data from the campaigns of many leading brands. Its customers use this data to create benchmarks that tell them how their marketing campaigns are performing against their own internal targets, and against industry benchmarks.
Qoints has been focusing on micro influencer and micro-targeting programmes for its customers. The company says influencer marketing is shifting away from celebrity influencers to micro influencers as the latter are more relatable, genuine, trustworthy and authentic.
Micro influencers have been especially popular as they generate an average engagement rate that is almost five times higher than what macro and celebrity influencers get on their sponsored posts, according to Qoints. But a major issue that marketers face is actually finding the right micro influencers, which today is a largely manual process.
To help its customers find micro influencers quickly and affordably Qoints offers AI Social Discovery, powered by IBM Watson. It is an app that taps Watson AI and psychographics (personality profiling) to identify highly engaging micro influencers for influencer marketing campaigns based on their social activity.
Qoints AI Social Discovery dramatically reduces the cost of finding micro influencers for brands that want to run their influencer marketing campaigns internally, as well as for brands that use marketing agencies to execute their influencer marketing initiatives.
Qoints AI Social Discovery creates social language profiles by pulling the last six months of tweets from each prospect that meets the customer’s parameters. These profiles are processed through IBM Watson to determine popular themes from each potential influencer and to create the psychographic profiles that inform the results that are reported. These profiles, along with available social engagement metrics, are analyzed by a machine learning algorithm that is trained by Qoints’ growing database of past influencer campaigns.
“IBM supports Qoints with commercialization, so we can scale as fast as we need without worrying about infrastructure,” said Cory Rosenfield, Qoints co-founded and CEO. “We know the AI tools we use will be of high performance quality and so do our customers. It helps us bolster our company profile and even lends credibility to our recruitment process.”
1 IBM, “Chatbots worth talking to”, study, October, 2017.
2 Gartner, “Gartner Says Smart Machines Will Enter Mainstream Adoption By 2021”, news release. December, 15 2016.