Explore the ways automation can support your customer service teams to offer a better experience.
With contact centers becoming an increasingly popular way to offer a streamlined customer experience across different touchpoints, there is a push to make them as effective as possible.
In fact, according to the latest statistics, automation in contact centers, AI has increased 95%. It is becoming used to better support agents and complete tasks that might be considered mundane, repetitive, or time-consuming in order to improve workflows and boost efficiency.
Contact center AI can be applied to augment the work of human agents on phone calls and offer new pathways of communication via social media and websites. In the meantime, you’re free to assign your human agents to more complex tasks where a human touch is required and appropriate.
AI can also offer an improved self-service experience for customers who prefer to be more independent and autonomous in finding solutions for their problems. The use of chatbots, a classic example of contact center AI, is a great self-service solution that can imitate human interaction with customers and offer solutions to queries without the need for a phone call.
Applying automated solutions to your contact center opens your business up to a great selection of tools and methodologies to boost productivity and optimize your workflows.
The evolution of the customer experience
Over the last few years, customer experience (CX) has undergone significant advances. Defining every interaction a customer can have with a company, CX is generally divided into four areas, from brand and product to price and service, with the aim of creating a positive impression of your business.
One of the most important developments in this area is the combination of humans and technology to enhance the customer experience. AI offers unprecedented opportunities for streamlining and supporting customer service teams, although a careful balance is required to make sure that customers receive personalised attention and are satisfied with the quality of service that they receive.
Mobilizing the entire company to get involved in aspects of the customer experience is also a significant recent development. Customer experience is now shaped by many departments beyond traditionally outward-facing teams like customer service and sales.
For example, web development teams now must consider the end-user experience when designing websites and apps. Even marketing teams are setting up the customer experience from the very first interaction with target audiences.
Contact centers are defined by their multiple platforms for communication including social media, email, instant messaging, and web chat. The days of phone-only support in traditional call centers seem antiquated, especially for large companies that work across multiple time zones.
With AI contact centers, key features can be enhanced. Live chat and video chat options come with seamlessly integrated automatic reminders, workflows, agendas, and follow-up tasks. Meanwhile, customer-facing chatbots are powered entirely by AI.
Automation provides real-time, responsive support with an efficiency that is now considered central to the customer experience.
Benefits of an AI contact center
How can you boost your company’s productivity with the help of automation? Here are a few key benefits of contact center AI that can help you offer enhanced service for customers while supporting your customer service agents.
An increased first interaction resolution rate
Resolving customer issues on the first interaction is a key metric for measuring customer service. It suggests efficient and focused performance. AI and automation can solve basic issues directly through self-service or equip your human agents with contextual resources about their customers to help them solve issues more effectively.
Increased customer and employee satisfaction
By streamlining workflows and taking on repetitive tasks, AI can reduce the demand on customer services agents. It frees them up to focus on more complicated and personalized tasks which offer more employee satisfaction and ensure higher levels of service for customers.
24/7 customer service
No matter where you are, AI allows you to maintain 24/7 support. AI-powered chatbots can provide automated responses and immediate help around the clock, at least for basic queries. AI is also becoming more advanced, logging and sharing interaction histories so that your human agents can more easily follow up when they return to work.
Reduced operational costs
There is always a careful balance at the heart of a contact center; deciding between reducing costs and increasing inefficiency, or improving efficiency while spending more in operational costs. With better value AI solutions, you can scale up for less, improving productivity without inflating operational costs.
Increased personalization
With automation handling mundane tasks and streamlining workflows, your customer service team has more time for complex tasks that require a more personal touch. Automation also increases opportunities for personalization by providing real-time interaction histories and other important data to agents to they can support customers in a more targeted way.
Leverage revenue streams
A slack customer service means that your business loses revenue through abandoned calls, bottlenecks, long waiting times, and a damaged reputation. AI allows you to scale up your contact center capacity by taking on repetitive, mundane tasks while your human agents can address more complex ones.
Key ways AI can enhance experience
There are several key areas that represent great opportunities for automated solutions powered by AI. These areas address pain points for customers and help companies offer the best service at the most affordable price.
Conversational AI
With the ability to simulate human conversation, conversational AI brings opportunities for customers to resolve their own basic issues through self-service, or the chance to initiate interactions with your business or brand without human agents initially needing to get involved. These advanced AI-powered chatbots work seamlessly, with endless patience and 24/7 service.
Big data management
Your contact center might collect an overwhelming and impractical amount of data for analysis, consuming time and expense. Instead, you can apply AI solutions to manage and generate accurate insights thanks to machine learning, working through collected data with far greater speed than the human eye.
Identifying errors
When filtering through huge volumes of data, contact center AI can apply predictive analysis to detect any issues or deviations with ease. You will receive a real-time alert to inform you of any identifiable issues with your data collection, meaning that they can be quickly resolved.
Sentiment analysis
AI can use natural language understanding to monitor and understand the overall sentiment a customer has towards a product, service or an overall brand. In customer service, it can be used to help route support requests and prioritize them, as well as monitoring interactions between customers and human agents to better support them.
Voice call automation
You can revolutionize your phone support with a voice bot. Today’s technology is much more advanced and can recognize elements such as intent and context. They respond to voice commands intuitively and can be used for services ranging from outbound calling and telemarketing through to conducting surveys and promoting offers.
Large language models
A game-changer for AI communication, large language models are advanced language models that provide seamless integration for AI and human agents. They analyze customer messages, fine-tune agent responses, and provide personalized pre-written text with faster and more efficient processing speed.
How to measure success
When implementing automation in your contact center, you will need to consider how to monitor your key performance indicators (KPIs) to ensure you’re getting the best from your solutions. There are a variety of metrics to choose from, helping you to evaluate agent performance and identify ways to enhance your customer service.
It is wise to focus less on traditional, operational metrics like average handle time, but rather a new culture of metrics based on achievable outcomes, that measure customer experience and potential customer loyalty.
Customer satisfaction
Customer satisfaction, or CSAT, is a key customer service metric that is collected from direct customer feedback after each interaction. The type of feedback can vary in complexity, from customers providing a score based on the service they’ve received, to lengthier responses collated by an interactive voice response system (IVR). You can now even hand CSAT over to AI, using solutions to infer customer satisfaction from interactions rather than asking them to complete surveys.
Speed
The manner in which your team resolves issues is also open to assessment, via metrics such as first contact resolution. This counts how many issues are resolved in the first interaction a customer makes with your business.
The customer is likely to look more favorably on issues that are solved quickly, leading to a higher resolution rate. AI can assist with this, providing conversational AI solutions like chatbots that can address basic issues with ease, leaving human agents free to work on more complex resolutions.
Resolution success
Remember that while a great first resolution rate is desirable, it’s also important that agents work to resolve issues effectively first, rather than prioritizing speed. Average resolution time is a metric that can provide the bigger picture, and inform you how long it generally takes for all types of issues to be resolved, regardless of communication channel.
You can boost your average resolution time by equipping human agents with resources such as large language models to predict customer behavior and provide agents with predictive or pre-written text to fine-tune responses.
Response times
You can also assess how long customers are left waiting to speak to a human agent by checking average response times. With the wealth of live chat and instant messaging options that automation provides, many customers now expect a real-time response.
Average wait time per channel will also help with this, as it breaks down the type of communication that leaves customers waiting the longest. Abandonment rate is also useful to combine with waiting time metrics, as it lets you know the proportion of customers who decide to abandon a call or other means of communication after waiting for a certain amount of time.
You can improve waiting times and abandonment rates with AI resources like intelligent call routing, ensuring that customers quickly speak to the agents they need.
Interactions
It’s possible to evaluate workflow with other metrics too, by checking the number of interactions each platform or form of communication receives. If one area receives more interactions than another, you can assign agents to handle the stronger workflow and cut wait times.
Seamless integration between communication channels can be better analyzed by the transfer rate. This metric helps you to identify how many customers are transferred to another team member, department or communication channel after their initial interaction.
AI tools such as real-time call transcription and call summaries can assist smooth integration between channels, as contextual information about each customer is easily shared.
The sheer number of metrics available to assess customer experience can be intimidating, and it’s wise not to overburden yourself. Different businesses in different industries or sectors will require different metrics to identify areas for improvement. It’s key that before you begin tracking metrics, you first identify which areas are most important for you to look at.
5 contact center AI trends to look out for in 2023
Self-service options and chatbots
In recent years, customers have expressed a wish to save time and find solutions for their issues independently. This might mean that companies provide a knowledge base for customers to research ways to resolve their problems through an information hub online, empowering them to find their own support.
In the field of artificial intelligence, there are plenty of opportunities for self-service. AI-powered chatbots are capable of simulating human interactions, offering solutions to more basic customer issues.
If a human agent is needed for a more complex level of interaction, the chatbot can hand over control of the conversation along with contextual information and a history of the interaction, so the human agent remains fully informed. This reduces the burden on your human agents and meets your customer expectations for more independent, personalized service.
AI-powered hyper-personalization
It’s believed that around 71% of customers now expect a degree of personalization in their interactions with companies. With automated solutions, you can bring personalization to your customer journey. There is a variety of exciting technologies making advancements in this field. One key tool for this area is sentiment analysis.
Sentiment analysis will allow you to use AI to monitor real-time emotions and intentions of a customer by identifying specific traits. This includes keywords and phrases in messages, and even voice recognition on phone calls. Information will then be fed back to your human agent, allowing them to respond appropriately to the customer’s needs.
This contextualization of the customer experience is worth getting right. Research indicates that companies that are exceptional at offering personalized services generate 40% more revenue than companies that underperform in doing so.
Omnichannel approach through automation
The option for customers to communicate with brands and businesses through multiple channels is fast becoming the acceptable norm. While the omnichannel approach has a lot of exciting potential for scaling up capacity and broadening the options available to your customers, it’s important to remember that integration across multiple platforms is key for a consistent experience.
There are different approaches that can support this. Contact center as a service (CCaaS) software will help connect customers smoothly with sales and support staff. Unified communications as a service (UCaaS) will support the integration of team members within an organization or department. And experience communications as a service (XCaaS) combines CCaaS and UCaaS approaches, meaning that your internal and external communications are brought into one centralized framework.
By using AI, your customer service agents will be able to easily access the history of customer interactions and gain context on every conversation with a customer. This can be done with real-time call transcription, call summaries, real-time coaching and knowledge base integration. All of these AI solutions enable smoother support across different touchpoints.
The rise of large language models
In the past, AI often struggled to generate organic, human-sounding responses. The development of large language models shows great promise in overcoming this obstacle. A large language model provides a huge dataset of human-like responses with the context, sophistication and resources to generate replies coherently and helpfully.
Large language models have a number of benefits for contact center productivity. The real-time guidance that AI provides agents can boost their efficiency, cutting time spent searching for information and leading to shorter calls. Potentially faster resolution rates will also improve general customer satisfaction.
The ability of large language models to simulate customer-based scenarios and provide feedback can strengthen your onboarding and training processes, making them more cost-effective. Companies that embrace large language models will be giving greater support and resources than ever to their employees, allowing your customer service teams to carry out their work to the best of their abilities.
The influence of AI on productivity
With the rapid technological advances of the digital era, automation is becoming the norm in many sectors and industries, and there is great potential to enhance the customer experience through contact center AI.
Customers are responding positively to these new developments. An average of 57% of customers of all ages prefer to engage with companies via digital channels. It’s believed that around 52 per cent of contact centers have strategies built around the application of AI.
With greater expectations of efficient customer service, and more value placed on the importance of a positive customer experience, achieving high productivity in your contact center is rapidly becoming only possible with the smart application of AI to cut wait times, speed up resolutions and provide tangible support for your employees.