Customer experience is a huge differentiator for businesses these days. And with customers increasingly preferring digital-first communications, businesses need to leverage a contact centre solution that prioritises omnichannel engagement.
According to Fortune Business Insights, the global Contact Centre as a Service (CCaaS) market is projected to grow from $4.87 billion in 2022 to $15.07 billion by 2029. And for those businesses which opt for a CCaaS solutions, access to powerful Artificial Intelligence (AI) and automation tools can not only support conversations across all channels of engagement, but it can also help drive huge improvements in experience for both customers and employees.
The new AI frontier
We’re entering a new era in AI technologies, with capabilities advancing, AI applications becoming easier to develop, and businesses seeing tangible benefits in areas where AI has already become entrenched. It’s being deployed across a range of industries to solve a huge array of business problems, although few businesses have begun exploring it fully when it comes to serving and engaging customers.
The statistics all point to customers wanting a more personalised experience whilst simultaneously being able to resolve their own queries. This is where AI steps in, offering a multitude of tools that enable this juxtaposition.
In this blog we highlight just a few examples of how businesses that adopt AI within a contact centre environment can improve customer experience…
7 ways AI influences the contact centre to deliver heightened customer experience
1. Chatbots
Chatbots are the first port of call for a growing number of customers and are one of the most common uses of AI in customer services. With chatbots using AI to answer questions based on data from internal systems, customers are able to self-solve queries about things like delivery updates, payment balances, order statuses and returns. Using AI in this way means customer service teams are freed up from answering common queries to address more complex issues, thereby improving the experience for both customers and agents.
2. Self-service
When given the option more than 60% of customers choose to solve issues directly rather than call a contact centre. And when the main function of a contact centre is to ensure a business’s customers are happy and having their queries handled, it makes sense to enable self-service with the help of AI. By building tools like website search, FAQs and live chat functions that use rich data from internal systems, repetitive and low-value interactions can be handled by tech instead of being directed to an agent. This empowers customers to solve their own problems on their own schedules and frees up agent resource for more complex queries.
3. Agent assist
Research* suggests agents spend as much as 25% of their contact time trying to find the relevant customer information in the business database. Agent assist tools that use AI can ‘listen’ to what a customer is saying or asking, then search internal systems for the relevant data, articles and knowledge. Results from the search are automatically presented on-screen to the agent handling the call, giving them all the information, they need to answer the customer’s query quickly and fully; no more digging around the various CRM, accounting or sales systems. This saves times for the agent and the customer, and results in vastly improved customer experiences.
4. Natural language processing
AI natural language processing (NLP) tools work by analysing transcriptions of customer interactions over phone, email, chat and messaging to spot themes and trends that can be leveraged to resolve issues more quickly. Using NLP to analyse data from across platforms allows businesses to personalise interactions at various touchpoints to create better customer experiences and support more efficient contacts, as well as spot opportunities for efficiencies and improvements across the business.
5. Intelligent IVR
Interactive Voice Response (IVR) systems have been a mainstay in the contact centre for decades, traditionally being used to automatically route calls when this was the only method of contact. The new generation of conversational IVR uses AI to automate a huge range of additional tasks, from verifying users with voice biometrics to directing the IVR to complete a specific action with the help of NLP. For example, routing calls to the most appropriate agent, not just the next available one. IVR can also be used with AI functionality to streamline customer actions within mobile apps, further simplifying and improving the customer experience.
6. Sentiment analysis
Customers losing their temper with contact centre agents is all too common. More than a third of British consumers (38.6%) admit to having lost their temper while on the phone to customer services at some point. More than 44% say they have hung up in frustration, and 53.9% have asked for their call to be escalated to a manager. These are all situations that nobody enjoys, and AI helps businesses minimise these kinds of interactions through sentiment analysis.
By using tools that can identify when a customer is becoming upset or frustrated and automatically notify a team leader, potentially fractious conversations can be de-escalated and issues resolved before they reach a critical point.
Further, sentiment analysis can help businesses build up a ‘personality profile’ of customers, which can be used to automatically route the customer to the most appropriate agent – so those who like a no-nonsense resolution can be connected with a pragmatic agent, and those customers who value a bit more social interaction can be routed to a chattier one. This sort of personalised interaction is a key differentiator in the customer experience, and AI sentiment analysis can have a huge impact on satisfaction levels among contact centre teams, as well as customers.
7. Machine learning
Machine learning (ML) is key for helping businesses get the most out of the AI tools they use. In essence, ML is the means by which huge amounts of customer, agent and business data is processed and analysed to determine key insights in terms of contact resolution. In the contact centre, this might mean harnessing predictive analytics to identify common queries and responses, or to help chatbots adapt to evolving customer conversations based on previous results to ensure customers get the most efficient and effective self-service support. All of this goes a long way to improving the customer experience and maximising contact centre resources.
A contact centre fit for the future
With customer expectations for digital-first, omnichannel and personalised engagement increasing by the day, businesses can no longer afford to regard the contact centre as a simple tool for customer service. AI-driven CCaaS solutions are paving the way for hugely improved customer and agent experiences that can help businesses not only drive engagement, but foster increased brand loyalty, enhance productivity, reduce talent churn and drive profitability through personalised purchasing recommendations and upselling opportunities.
With the right technology partner, business of all sizes can build a contact centre that’s fit for the future – whatever it may hold. For more on how M247’s Contact Centre solution can support your business into the future, read here. Or get in touch with our team today.
