Call us: 0800 3167566
THOUGHT LEADERSHIP GUIDE
USING AI TO IMPROVE CUSTOMER EXPERIENCE (CX)
ASK AI – WHY OPUS?
12 minute read
Author: Stuart Green – Account Director Contact Centre
Using AI to improve customer experience in a contact centre
Every stakeholder in a contact centre is under tremendous pressure every single day. From training your junior agents to overhauling your customers’ experience and deploying the necessary technology to achieve that goal, converting a contact centre into a profit-generating hub is a significant challenge.
In the current competitive landscape of business, delivering outstanding customer experiences is essential. Many find it challenging to meet even minimum standards. The traditional “three strikes and you’re out” policy is no longer relevant. In fact, research shows that 92% of customers are inclined to leave a company after encountering a second negative customer experience.
Moreover, 79% of customers anticipate faster response times from businesses with whom they’ve had positive or neutral experiences. The encouraging aspect for modern technology is that, despite the current negativity surrounding customer experience and contact centres, 67% of customers are more than happy to seek out faster and more satisfying experiences independently. They will willingly choose the self-service route if it effectively accomplishes the task at hand.
Among the 67% of individuals who anticipate a self-service delivery, each one expects it to be flawless. Their expectation is straightforward: when they require something from your business, they anticipate it being readily available without having to wait in a call queue.
That’s precisely where Artificial Intelligence (AI) is making its biggest impact in improving customer experience. By removing the burden on agents, shortening customer wait times, and giving customers access to what they need when they need it, AI is fast becoming the difference between a mediocre contact centre and a high-performing one.
The benefits of deploying AI to improve customer experience (CX)
When customers insist on faster and superior experiences, attention must be directed towards enhancing both efficiency and quality. However, with calls accumulating and agents contending with irate customers and time constraints, it becomes challenging to resolve.
The obvious solution is to hire more agents to handle higher call volumes.
However, that comes with additional costs:
- More salaries
- More hardware costs
- More software costs
- A gap between time to train and agent autonomy
What’s required is a method to ease the pressure on agents and a way for customers to retrieve information without the need for human input.
Note: This won’t apply to every enquiry, quite the opposite. However, if customers are already aware that they can independently access services from other businesses, they rightfully expect the same from you.
We’re discussing the empowerment of humans through the utilisation of technology, plain and simple. This principle mirrors our approach to purchasing or utilising any technological tool.
There should always be an incentive prompting us to consider trying, purchasing, and integrating any product we invest in. It could be an AI-driven contact centre solution promising to reduce average handling times by 50% while boosting your Net Promoter Score (NPS) by a few points. Conversely, it might also be something as simple as a bicycle. Perhaps you aim to improve your fitness, dislike the gym environment, and realise cycling could expedite your commute to the office. The benefits are clearly evident.
Using AI to improve customer experience enables efficiency benefits such as:
- Offloading repetitive tasks
- Lowering average hold time
- Reducing risk of manual error
- Faster information retrieval
- Automated identity and verification
- Fewer customer transfers between agents
With these efficiencies, you get happier customers and more productive agents. When customers are happy, they stay for longer, churn decreases and the likelihood of referral increases. When agents are more productive, they can spend time on more value-adding activities. By integrating AI efficiency into your contact centre, you will also improve your bottom line.
Your contact centre before and after AI
What not to expect when implementing AI in your contact centre
When you take your first journey into AI to improve customer experience, it can sound futuristic and we often paint a picture of robots and drones. In reality, all you’re doing is using Artificial Intelligence to improve existing processes.
Customers will continue to reach out when they require assistance, and your business will continue to strive to meet their needs. Integrating AI doesn’t necessarily imply replacing human interactions with virtual reality meetings or eliminating the possibility of speaking to a human representative (although it could, depending on your audience preferences).
It also doesn’t mean:
- A new, confusing experience for customers
- Total overhaul of procedures
- Loss of control of your data
- Redundant agents
Instead, you should expect:
- In-call agent coaching
- Accurate staff forecasting
- Rapid response times via self-service
- Predictive responses based on data and trend analysis
- Less focus on call metrics and more focus on value-based metrics
- Empowered agents spending more time on training and escalations
- Hyper personalised customer journeys based on buyer and support data
7 features you can implement within your contact centre now
Turning on AI features is just as simple as turning on any other contact centre feature. Thanks to the flexibility of the cloud, your existing contact centre may already have built-in AI features you could be taking advantage of.
Smart IVR uses AI to improve customer experience
We’re talking smart responses to customer inputs. Instead of your agents fielding basic queries (like opening times), use an AI-assisted Intelligent Voice Response (IVR) system to understand and process queries based on numeric or voice input.
Think about how your current menu asks people to press 1 for sales and 2 for support. Once a customer has made their selection, they still need to queue for an available agent. When you load this IVR technology with AI, you remove the need (in many cases) for an agent to be involved and free up call queues for those who need it most.
What we’re doing here is creating “digital offload”. Your call centre queues are dissipating and being filtered into self-service channels like live chat and knowledge bases.
We know that 91% of customers are happy to use a self-service knowledge base if one exists, so making them aware of such a service is crucial here. Not only will this remedy their current enquiry, but it will also become their first port of call for support next time.
Interactive Virtual Agents (IVA)
The same applies to chatbots on your website. Instead of asking agents to go through the basic greeting and verification processes, outsource this to an Interactive Virtual Agent (IVA). This second-generation chatbot uses natural language understanding technology to appreciate the context and handle first-line enquiries into your helpdesk and sales teams.
This is a basic example showing what’s possible by simply connecting an IVA to your ticketing, billing, or sales systems. What’s more impressive is when less data-based queries arise. Let’s assume the customer isn’t happy with the five-day turnaround for their refund.
As this interaction concludes and a human takes over, your IVA has also done the following:
- Triggered a follow-up call from a human to ensure the issue is resolved
- Flagged the chat transcript for quality management
- Attached the transcript to your CRM record
- Highlighted key timestamps and summary of the call
Agent Assist
When agents are under pressure to resolve calls in a timely manner, several things happen:
- Agents rush, focusing on their average handle time metrics
- First contact resolution decreases as the whole problem hasn’t been remedied
- Customers become unhappy and are more likely to churn
- Opportunities to up-sell and cross-sell get missed
If you implement Agent Assist technology, an in-app prompt is triggered whenever keywords, phrases, or emotions are detected. For example, if a customer asks for the shipping time for the product they have just bought, agents get an AI prompt with the answer for that particular product. This saves both the agent and customer time during the call and delivers a productive experience.
Similarly, in cases where a customer experiences a technical issue that your premium product can resolve, agents might not always be informed about new features or may perceive sales-related tasks as beyond their responsibilities.
That’s where Agent Assist comes in handy once again. Recognising a common issue and cross-referencing with other products in your portfolio, agents get a prompt to say there’s a new product available for them to upgrade to. Instead of logging a fault, and waiting hours to get their problem resolved, you get a sale.
Caller Insights
Caller Insights is a brand new and exclusive integration developed by Opus that enables real-time caller insights to be made visible to agents as the call comes in to the contact centre.
Agents can preview website activity that the caller has undertaken prior to making the call to use as valuable intelligence, helping them to understand why a customer or prospective customer has got in touch.
Some example scenarios for Caller Insights:
Car Dealer
A nationwide car dealership advertising cars on their website. A call comes in and the agent is able to see which cars have been viewed prior to the enquiry, the agent can then use this information to steer the conversation and book a test drive.
Travel Agent
A call comes into a large travel agent group from a prospect looking to book a holiday. The agent can see the destinations and previous accommodations the prospect has already viewed and make recommendations based on that information to convert the sale.
Sentiment Analysis
Inside calls, web chats, emails, and SMS, AI can detect negative or highly-emotional sentiment.
- Upon recognition, several things can happen:
- Calls get flagged for quality management
- Supervisors get informed they need to take over
- Customer sentiment gets scored and tracked over time
- Internal benchmarks for customer experience start to form
You no longer have to rely on agent discretion to identify real-time calls requiring assistance. There’s no justification for allowing calls to escalate to the extent that supervisors are required. Sentiment analysis can detect if a call is becoming contentious and can take the necessary action.
The outcome? Reduced escalations and dissatisfied customers, along with increased learning opportunities and higher-quality call recordings for agent training.
Predictive Analysis
With all the data collected in contact centres (call times, repeat callers, sentiment, transaction history, etc.), it’s right to question whether you’re doing enough with what you have at hand.
The answer is, often, no. But that’s not your fault. AI can automate data processing and content creation so your data gets turned into presentable and understandable graphs and business suggestions.
The alternative, spending hours creating pivot tables in an Excel sheet saved on someone’s desktop, only to have new data the next week, seems inconceivable when you have an automatic, self-updating report accessible in the same interface as your supervisor module.
Predictive analytics use genuine data to inform all parts of your contact centre. With AI implementation, guesswork is no longer needed in your workforce management, whether it’s staff forecasting, staying ahead of high call volumes during seasonal peaks, or understanding potential outages.
AI Insights
If you know where your teams are losing time, you can start to do something about it. AI Insights introduces a dashboard that breaks down key metrics per topic. This way, you can start to understand the types of queries that take the most agent time. Using ChatGPT, technology alongside real-time transcription, AI Insights automatically detects the topic of customer conversations and sorts them into clusters.
For every topic, you can view:
- Number of interactions
- Average handle time
- Average hold time
- Average queue time
- Impact score
When, for example, the majority of your time-consuming queries are about new device activation, you can see this in a clear data-backed view and take action to reduce the number of calls into your contact centre for this type of query, directing them to a knowledge base article instead.
Barriers to AI adoption in contact centres
Operational cost is the main barrier to any new technology adoption; in fact, 54% of contact centres suggest this is their top concern.
This partly stems from the conventional cost/benefit analysis modelling we’re accustomed to. Indeed, introducing a new expense will invariably result in a new entry on your balance sheet and costs may deviate from the usual. However, when adopting any new, innovative technology several things need to be taken into consideration.
Questions to ask are:
- How much time will we save in agent productivity?
- Can we quantify cost reduction through decreased call handling times?
- What do improved first call resolution rates mean for operational costs?
- What’s the cost-benefit of retaining happy customers versus finding new ones?
- How will AI impact our NPS and CSAT ratings?
- How much revenue will be gained through upsell opportunities currently unrealised?
- What happens if we don’t adopt AI, but our competitors do?
- Which customer segments will AI serve best?
Further barriers to AI adoption include things like resistance to change, data quality, and integration complexity. These issues can all be quelled by quality planning.
Agent concerns? If agents are resistant to new processes, ensure clear communication well in advance regarding the reasons behind the changes and the benefits and training they’ll receive, once deployed.
Concerned about feeding inaccurate data into AI systems? Refrain from taking the leap until you’ve thoroughly sanitised existing data—or begin collecting new data right from the outset of your AI implementation.
If you require all your other systems to be integrated with AI as well, rely on your contact centre partner to assist you with any integration and migration requirements
Delight your customers whilst making more money
Operating at a loss while delivering good customer service is not viable. Though it may seem stringent, it’s the reality of the business. Contact centres must fulfil both objectives: ensuring customer satisfaction while also generating profit.
If you’re ready to reduce costs on human resources while increasing revenue through retention and up-selling, the technology to assist you is now readily available.
Whether you’re fully committed to deploying AI to improve customer experience or just beginning the journey, there are productivity and customer satisfaction improvements waiting for you.
If you are interested in exploring the benefits of Smart IVR, Interactive Virtual Agents, Agent Assist, Sentiment Analysis, Predictive Analytics, AI Insights and Caller Insights, please get in touch.
Need help with your AI contact centre implementation? Contact us to book a call with one of our contact centre consultants now.
Download this useful guide now as a pdf
When customers insist on faster and superior experiences, attention must be directed towards enhancing both efficiency and quality. This handy guide explains how you can deliver these experiences using AI and innovative technology within your contact centre.