In the past few years, advances in artificial intelligence led to the widespread use of Conversational AI. The rise of the technology continues thanks to its successful use cases in both consumer and enterprise applications. According to Research & Markets, the Conversational AI market generated $3 billion and is predicted to reach $15 billion in 2024, advancing at a 30% CAGR.
The Rise of Conversational AI
The rising demand for AI-powered customer support services, positive return on investment (ROI) for companies deploying Conversational AI solutions, and an increasing number of solution providers in the market are effective in this growth. So, the adoption of AI in the enterprise sector is increasing. According to Gartner, 31% of CIOs have already deployed conversational platforms, representing a 48% year-over-year growth in interest. Conversational AI is implemented across various use cases, including customer service, sales support, human relations, employee engagement, customer engagement, retention, and more.
What does Conversational AI Offer?
Today’s customers expect smooth journeys. They want to interact with brands easily, at any time, at any channel; contact centers, chatbots, messaging apps, smart assistants. And while doing this, they expect to be understood fast. They want to be understood before they open their mouth. They want to be understood not only by humans (customer reps) but also by machines. The answer to this expectation is Conversational AI.
Natural Human-Machine Interaction
Combining technologies like natural language processing (NLP), speech recognition, and text-to-speech, Conversational AI enables smooth interaction between customers and machines. The technology allows customers to naturally interact with systems in their own words via speech or writing. Conversational AI provides a personalized and enhanced experience for customers. Customers can complete various tasks simply by speaking to systems as if they are speaking to a human.
Reducing Costs and Enhancing Experience
Keeping costs minimum while offering high-quality customer service is among the biggest challenges that businesses face. Conversational AI automates routine customer service tasks by allowing customers to self-serve. This helps companies reduce operational costs while increasing efficiency. Offering enhanced customer service also provides an effective differentiation tool for businesses. Conversational AI leads to higher customer satisfaction and greater customer loyalty. This means a sustainable competitive advantage and a positive brand perception from customers.
3 Steps of Conversational AI Deployment
Deploying Conversational AI for the sake of “everybody else is doing it” might be the worst thing you can do for your business. Boston Consulting Group’s latest study shows approximately 70% of organizations fail in their attempts for digital transformation. You will need a well-thought strategy before you take any action. Following the steps below might help you build and implement a result-oriented conversational AI strategy.
Step 1: Set your end goal
So, you are not implementing Conversational AI to jump on the bandwagon. Then, try to discuss within your company (within your team) the following questions:
⦁ What do we want to achieve with implementing AI? What is our end goal?
⦁ How can AI serve our business objectives?
⦁ What are the main pain points of our customers that we think AI can help solve?
⦁ How will this solution help them?
⦁ How can we set up KPIs to monitor progress?
Step 2: Select the right vendor.
Developing AI solutions within your company will take a serious amount of time and effort. When there are AI vendors working on these solutions for more than decades, it would be wise to get some outside help.
But choosing the right vendor is important. While deciding on the technology provider, make sure that they have the following capabilities:
⦁ Technology and industry-specific expertise
⦁ UX-oriented approach
⦁ Competence in professional services
Step 3: Phase the plan
⦁ Bringing together your team with your technology provider’s team to determine requirements.
⦁ Prepare checklists on specifications, installation requirements, and KPIs beforehand.
⦁ Testing technology specifications to see if specifications are implementable in practice.
⦁ Launch internally before offering it to your customers to complete user and security testing and apply necessary fixes on time.
⦁ Now your project is live, and your customers can start interacting with your solution.
⦁ Monitor customer behavior and get as much feedback as possible to detect improvement needs.
⦁ The success of any project depends on objective performance evaluation.
⦁ Continuously monitor and analyze your efforts to measure the effectiveness of the solution and define your next steps for improvement.
⦁ You can use Conversational Analytics tools such as Speech, IVR, and Bot Analytics for an in-depth evaluation.
To learn more about leveraging self-service automation and enhancing the customer experience with Conversational AI technologies, download our “The Conversational AI Playbook” by filling the form below.