Although many people might not realise it, the vast majority of us interact with conversational AI on a daily basis. Tools such as virtual assistants and chatbots leverage conversational AI to deliver a human-like experience, bringing together several digital components including Natural Language Processing (NLP), machine learning, big data analytics and dynamic text to speech.
It’s a rapidly expanding market, which is expected to grow from $4.8 billion in 2020 to $13.9 billion by 2025. This growth has accelerated in recent months as a result of the Covid-19 pandemic, with government lockdowns and staffing issues forcing businesses to deploy virtual assistants in order to handle an influx of customer calls.
For example, IBM saw a 40% increase in traffic to its Watson Assistant from February to April last year, highlighting the need for businesses – particularly call centres – to deploy digital tools to streamline processes and meet customer needs.
The technology itself is also developing fast. Recent advances in NLP have dramatically improved on the clunky automated systems of the past, making today’s generation of chatbots and virtual assistants more responsive to user inquiries. This is presenting new opportunities for businesses and building trust among customers.
With all this in mind, it’s clear that conversational AI can be an extremely valuable differentiator for enterprises, enabling them to engage customers and deliver services with increased efficiency.
Conversational AI in action
The most popular use case for conversational AI is online customer support, where chatbots can answer FAQs around topics such as shipping and returns, provide personalised suggestions and cross-sell products. Having such tools in place can provide businesses with several benefits, such as improving the customer experience and driving customer retention. This is particularly true in times of upheaval and uncertainty.
Perhaps most importantly, they can provide a valuable differentiator to help businesses stand out from their competitors. Customers will be able to get their queries answered faster, at any time of day and in a user-friendly way – all of which will go a long way to fostering long-term loyalty.
And there are many other ways that conversational AI, through chatbots and virtual assistants, can be used to gain an all-important competitive edge. Here are just a few:
- Cost-efficiency: chatbots can interact with thousands of customers simultaneously, significantly cutting costs compared to humans and providing much greater value for money.
- Increased productivity: chatbots can be used to streamline internal processes and support employees in complex tasks, empowering them to be more productive and efficient.
- Actionable customer insights: AI-powered tools can capture and interpret conversational data, providing insights that businesses can use to better understand their customers and meet their needs.
- Improved employee experience: with AI tools taking some of the load, employees will be free to focus on adding value to the business, making them more likely to stay long-term.
Of course, with conversational AI in its relative infancy, there are still come challenges to consider. For example, language variables such as dialects, accents and slang can impact its understanding of the raw input. Tone and sarcasm can make it difficult for the AI to correctly interpret user meaning and respond appropriately, while some users may simply be apprehensive about sharing personal information with a machine.
But these issues are quickly becoming less apparent as the technology continues to evolve. The bottom line is that conversational AI has the potential to transform many areas of business across multiple sectors, equipping businesses with everything they need to get an edge over the competition. The big question is, how can you get started?
Adding a competitive edge
For any enterprise, the first step must always be to scope out and validate key hypotheses before AI delivery. This typically involves a combination of journey mapping, technical feasibility, content analysis, channel strategy and user testing to define the most effective implementation approach.
This is an important step, as conversational AI must be integrated into an overall digital strategy. Taking the time to build and test the business case up front with your chosen vendor and key internal stakeholders will save a lot of time and effort in the long run.
Once your strategy is in place, you can move on to the design and development phase. Start training your system and testing its natural language capabilities in multiple conversations across your key channels. This will help you work out any kinks and ensure that the system is able to address both your customers’ needs and your company’s goals.
Next, it’s time to start implementing. Roll out the system in the way that best works for your business and that most effectively connects with your existing infrastructure. Work with your vendor to integrate any third-party applications – while always remembering to keep the business goals front of mind.
Once the system is up and running, the focus moves to ongoing evaluation, maintenance and development. Monitor the chatbot’s performance related to your business goals, experiment with new channels and add new capabilities over time to deliver the most value from your chatbot or virtual assistant.
Ultimately, it’s becoming increasingly evident that virtual assistants and chatbots can give enterprises the competitive edge that is so valuable in today’s business landscape. The time to start building conversational AI into your operations, in turn empowering your staff and customers to make the most of the technology, is now.