Conversational AI is changing the way companies service and engage with their customers. Here’s what you need to know about conversational AI and how it can benefit your customers and contact center.
What is conversational AI?
Conversational artificial intelligence (AI) uses natural language processing, machine learning, and big data to enable computers and humans to converse in a human-like way. Instead of having humans conform to robotic-like ways in order to engage with computers, conversational AI makes talking with machines feel human and natural. By enabling computers to recognize words and understand intent, conversational AI lets machines and humans easily understand and interact with each other.
How does conversational AI work?
How conversational AI works is by using natural language processing (NLP) and machine learning (ML) to understand human speech or text and derive intent. Then, respond naturally over voice or text.
What is natural language processing?
Natural language processing is a branch of AI that enables computers to understand text and speech similarly to how humans do. It “combines computational linguistics — rule-based modeling of human language — with statistical, machine learning, and deep learning models.” NLP empowers computers to recognize words, derive intent, and respond in a way that’s understood by humans.
NLP is made up of four processes:
- Input: Humans engage with the computer via text or voice. This is often through a website, app, or smart home device.
- Analysis: For text-based input, the computer uses natural language understanding (NLU) to identify intent. NLU uses computer software to understand text or speech inputs. For voice-based input, the computer uses NLU and automatic speech recognition (ASR). ASR converts spoken words into text, which enables the computer to process speech.
- Dialogue: The computer forms a response using natural language generation (NLG). NLG is a subset of NLP and converts computer data into natural language.
- Learning: The computer uses machine learning algorithms to continually improve its understanding and accuracy over time.
NLP has a wide range of applications, including customer service. For example, when a virtual agent asks, “How may I help you today?” and the customer says, “I’m looking for pink cowboy boots in a women’s size 9.5 wide,” the virtual agent will use NLP to identify the words “looking for” as intent. It then identifies “pink,” “cowboy boots,” “women’s,” and “size 9.5 wide” as search criteria. It’ll look in the company’s inventory and respond to the customer with options that meet those requirements. Other common applications of NLP are GPS systems, voice assistants, and chatbots.
What is machine learning?
Machine learning is another branch of AI that enables computers to automatically learn and improve through the use of data and algorithms. The goal is to continually expand the computer’s understanding and knowledge so it can be more accurate or provide better results. Data scientists write algorithms that are trained to classify and mine data for key insights, which are then used to make predictions or provide a response.
In conversational AI, machine learning is essential to the computer’s ability to improve its understanding of language and intent and its response accuracy.
Conversational design: The art of creating effective, efficient, and cooperative conversations
With text and speech becoming the way users interface with companies and their products or services, the user experience now relies on how well the conversation is crafted. Conversational design (CxD) is the art of designing two-way interactions between computers and humans, based on how humans communicate. It is a subset of user experience (UX) design. The result of good conversational design is efficient and cooperative conversations that feel natural and flow smoothly.
Conversational design is incredibly important because customers have high expectations for every brand interaction they have. They expect fast and accurate answers to their questions, resolutions for their issues, and guidance for purchasing decisions. They don’t want to repeat information or have slow, cumbersome conversations. A poorly designed conversation causes frustration and motivates customers to either abandon the conversation or ask for a human agent.
The best conversational design makes interactions with computers feel so human that people can hardly distinguish whether they’re conversing with a machine or not. On the other hand, poor conversation is extremely apparent. There’s repetition, the conversation is confusing and difficult to follow, and the language doesn’t feel natural to humans.
Benefits of conversational AI for customers
Contact centers that use conversational AI provide numerous benefits to their customers that ultimately improve customer experience and customer satisfaction. These benefits include:
- No hold times: Conversational AI answers every call and responds to messages immediately, which means customers no longer have to wait on hold.
- Faster, accurate resolution: Transactional requests and issues can be resolved quickly and accurately, as conversational AI draws data from your systems and makes updates in milliseconds. With continuous learning, conversational AI also constantly increases its ability to resolve issues and correctly understand customers.
- 24/7 customer service: For global businesses and those catering to expanded customer service hours, conversational AI provides customers with 24/7 access to service — no matter where they are located in the world.
- Easy self-service: Customers can conveniently access self-service through a voice or text conversation.
Benefits of conversational AI for businesses
The benefits of conversational AI for businesses include reduced costs, elasticity, and a better customer experience.
Reduced costs and increased revenue
Conversational AI gives businesses the ability to serve more customers without having to hire additional agents. Conversational AI solutions cost significantly less than adding more agents or outsourcing. In fact, conversational AI can cost just 50% of a highly optimized business process outsourcing (BPO) provider.
Businesses can also generate revenue by using conversational AI to upsell or cross-sell products. Conversational AI can automatically surface personalized offers or make product recommendations so companies can capture more revenue.
Repurpose human agents to deliver higher-value customer engagements
Conversational AI relieves humans of rote, routine work and frees them to concentrate on customer issues that require empathy and advanced problem-solving. Freeing up human agents from the bulk of routine customer service issues enables brands to refocus employees on work that delivers higher value to the business.
For example, agents can be trained to deliver proactive customer service — reaching out to customers to address issues before they become a problem, informing customers of discounts, or recommending relevant products or services. This adds an unexpected human touch to the customer experience, increases customer satisfaction, and gives brands more opportunities to generate revenue and retain customers.
Elastic capacity and cost
Even with the most advanced forecasting models, it’s impossible for contact centers to accurately predict when and to what degree customers will engage with them. Traditionally, brands have scaled their customer service by adding more staff, increasing overtime, or outsourcing, which are all costly options. Scaling through these methods have drawbacks though. Overestimating results in wasted agent capacity that you still have to pay for. Underestimating results in long hold times and annoyed customers.
Conversational AI creates elasticity, which gives brands the ability to automatically scale customer service capacity up and down. When your capacity always matches demand, customers never experience hold times and unexpected call spikes no longer overwhelm your agents.
Additionally, brands achieve elasticity in their costs, since they only pay for the capacity used. This allows them to avoid the cost of adding staff or outsourcing and the wasted expense of being overstaffed when lulls happen.
Improved customer experience
Brands that strategically deploy conversational AI set themselves apart by creating a superior customer experience. Two-thirds of brands compete on customer experience, and 80% of contact center leaders say “improving customer experience is the most important strategic objective and driver of investment for contact centers.” Any improvement in how fast, accurate, and easy brands can make customer engagements, the better. Improved customer experience increases customer loyalty, which in turn, boosts lifetime customer value.
Different types of conversational AI
Conversational AI is applied through a variety of channels, including voice, chat, and SMS.
- Voice AI: Voice AI enables contact centers to provide the premium experience of voice interactions at a much lower cost than engaging with human agents. Voice AI acts as an additional AI workforce that helps carry the load for human agents and gives customers a convenient self-service option that’s available 24/7/365. Conversational AI is applied to voice in the form of voicebots and voice assistants.
- Chat: Chatbots that are built with conversational AI provide a flexible experience to customers who prefer messaging back-and-forth. Unlike scripted chatbots that can only provide canned responses to certain keywords or phrases, conversational AI-powered chatbots offer dynamic interactions — to the point where humans often can’t tell if they’re engaging with a machine.
- SMS: Conversational AI for SMS allows customers to engage on their phone without being on a company’s website and experience a written conversation that feels natural.
Brands often deploy all three types of conversational AI for customer support, as it gives customers multiple self-service options.
How to choose a conversational AI solution
There are multiple conversational AI solutions available. When evaluating potential vendors, here are some criteria to consider:
- Does the solution provide a humanlike experience with fast response times? Remember, conversational AI that doesn’t provide a great experience will harm the customer experience. If the AI isn’t able to respond in less than one second and doesn’t understand intent, the conversation will feel painfully slow and aggravating to customers.
- What percentage of Tier-1 issues can the conversational AI resolve successfully? Effective conversational AI is capable of resolving issues and not just deflecting them. The best solutions can resolve 90% or more of Tier-1 issues, taking a significant amount of work off of agents’ plates.
- How fast can the conversational AI be deployed? You can either build or buy conversational AI. If you want to get up and running fast, buying a solution is the way to go. Conversational AI vendors offer pre-built use-cases that can be customized to fit your unique needs and brand. They’ll also provide a team of AI experts and conversational designers to guide you through the process, build conversations, test and QA, and deploy your AI in just a few months. Building your own conversational AI takes months or years, and many companies end up never putting the AI into production.
Bring conversational AI to your customer service experience and delight customers with fast, accurate self-service when they call. Learn how Replicant Voice can make your phone conversations with customers a strategic differentiator for your business.