Inefficient communication while dealing with a business can be quite inconveniencing. We have all at one point or another experienced it. Say you wanted to cancel or change an airline reservation for instance. You were likely put on hold for prolonged periods of time, switched from one agent to another, and had to start afresh with every new agent. You probably even ended up getting disconnected without a resolution. The thought of having to go through all that again is just dreadful.
This is just but one scenario is taken from a customer’s point of view. For a business, such examples represent missed opportunities in conversations as a result of inefficient communication methods. But all this can change with conversational intelligence. By mimicking human conversational capabilities, machines (bots or AI) can make a big difference in:
- Your capacity to build relationships with your customers
- Personalization of conversations, because AI is scalable and can handle multiple issues at a go.
- Employee empowerment and their ability to be responsive and proactive. Conversational is a tool that can be instrumental in helping employees to be their best.
Be it in chat messaging, or voice, a lot of companies are already implementing conversational AI, with the significant operational and bottom-line gains.
What is Conversational Intelligence? Why is Conversational AI important?
Conversational AI involves the use of machine learning to mimic human communication in:
A machine can take voice content or text and using algorithms, attempt to decipher:
- If natural language is used
- The language used
- Names of people or places
- Inflection, such as in questions
Machines such as chatbots, gain this understanding based on repetitive training using varied data sets. Based on statistical patterns from that training, conversational AI can, at a future date, formulate speech like a human.
This involves a machine’s capacity to
- Generate/ simulate natural language
- Convert text to speech
Again, this process uses large amounts of data, from which machines learn human communication and its nuances. Some aspects of reproducing natural language can be simple. For instance, chatbot responses can be generated using templates but a task like generating analysis reports is difficult.
Converting text to speech involves the use of technology to generate audio messages. In other words, conversational AI can read text out loud in place of a human.
Other experts define AI as falling into 2 categories:
Conversational agents: which is basically AI that can have a conversation with users in a natural language .text to speech converters also fall on this category.
Conversational enhancements: which is A1 that Improves or enhances conversations between people. Such AI can, for instance, make email communication More efficient by suggesting appropriate responses or track changes to a document, etc.
Top 10 facts of conversational intelligence
Users and critics maintain that some conversational AI performs just as good, if not better than humans. As reliance on machine intelligence continues to grow, so will conversational AI. Below are 10 things you must know about the development of conversational AI:
1. People don’t mind handling business through chatbots
Reports show that people are okay dealing with chatbots as long as they get the answers they need.
When making a purchase decision, 29% of customers prefer to use chat to contact sellers when weighing a purchase decision. (Source: 7.ai)
27% of people would more readily use a chatbot than email. (Source: 7.ai)
37% of Americans say they can make chatbot assisted purchases even for items as high as $55 or more. according to Digitas.
2. Consumers expect a good experience when using chatbots
A good chatbot strategy is essential for customer retention. Over 73% of people would not transact with a company after a bad experience with a chatbot. (Martechtoday) Generally, people are more forgiving of human mistakes than they are tolerant of a frustrating chatbot experience. According to MindShare’s report, more than 60% of people would be frustrated after a bad experience with a chatbot.
3. Conversational intelligence can be a great marketing tool
37% percent of American consumers are open to receiving recommendations or advice from chatbots, according to Digitas. Breaking this down further, consumers are interested in recommendations for products from retail stores (22 percent); hotels/accommodations (20 percent); travel (18 percent); products from a pharmacy (12 percent); and fashion/style (9 percent).
Consumers of all ages are okay receiving product recommendations from brands they deal with. For instance, 48% of millennials say they don’t mind product recommendations on chat.
4. People are looking for an authentic and transparent chatbot experience
Consumers insist on knowing whether they are dealing with a human being or a machine. Some companies are already responding to this expectation by alerting consumers when they are being served by AI.
5. AI is enabling more communication on social media
Messaging apps rival social media in popularity.
By 2019, global users of messaging apps reached 2.5 billion. (emarketer)
In 2018, over 8 billion messages were exchanged on messenger (Venture Beat)
By 2020, it is predicted that 80% of businesses will make use of chatbots. (smallbizgenius)
6. Humans and robots may be indistinguishable by 2029
Ray Kurzweil, a goggle engineer predicts that by 2029, Language ability of chatbots will have evolved to human level. He said in an interview, “If you think you can have a meaningful conversation with a human, you’ll be able to have a meaningful conversation with an AI in 2029. But you’ll be able to have interesting conversations before that.” (Ray Kurzweil via The verge)
7. Conversational intelligence results in Cost Efficiency
Executing AI can result in cost efficiency across your whole organization.
Research shows that by 2022, use of conversational AI will result in cost savings of up to $8 billion per year.
Close to 30% of customer service jobs can be replaced by bots, resulting in lower cost of labor and operational expenditure. McKinsey
8. Speech to text services are becoming a critical part of respondents’ workflows
Speech to text serves many functions in the day to day lives of individuals and businesses. Some of these include:
- Sorting through video or audio content
- Voice recognition
- Availing content such as reports, or meeting minutes on demand
Below are some useful statistics on how speech to text affects workflow:
9. Text to speech conversion is also a way of fulfilling your customers’ content demands
The demand for content is ever-growing. One of the main challenges that companies face in meeting content demands is that they cannot come up with enough fresh content. But, what if, from your meetings, you could spark fresh ideas for content?
Take a CSR meeting for instance. Transcriptions from such a meeting can be shared with internal and external customers as needed. Another example is product meetings. If you are launching a new product, transcriptions of meeting minutes can become the basis for your press release.
10. Conversational intelligence has the capacity to improve team dynamics
Bots not only help individual teams to succeed, but they are also instrumental in tying teams together. what that means, according to Andy Payne of Cisco Emerge, is that AI can coordinate different meetings at once. Every meeting can be AI-led.
At a higher level, and as AI continues to advance, AI will and can:
- Identify meeting overlaps
- Check meetings by topic to avoid redundancy and wastage of effort or resources. This well also boost collaboration among teams with common interests
- Identify employees’ strengths and skillsets
- Find out which projects people are working on and the status of those projects
ALL these tasks can be accomplished by AI. When you have bots that are intelligent enough to understand overarching business goals and then suggest team pairings for those goals, then we can conclude that we are looking at a future in which we run very smart companies.
Conversational intelligence is a topic that has been awash with discussions. Not only is it exciting to think that a machine can talk, but from an economic viewpoint, the ROI of such an investment will be huge. When machines understand what people say and how they say it, then it becomes easier to redirect human capital to other tasks that can’t do without the human touch. At the same time, having bots introduces a more efficient way for customer handling.
With that said, great customer experience is dependent on having conversational Al that is advanced enough to deliver over and above beyond what a human can.