Need to improve your contact centre’s performance? Here’s how we do it.

Your contact centre serves as the frontline for customer service and brand reputation and plays a crucial role in the delivery of customer satisfaction, driving up retention and repeat purchases. But businesses are complex; people are complex; CX technology can be complex. If customer service was easy every single organisation the world over would be boasting a NPS of 95+ (and businesses like ours probably wouldn’t exist!)

However.

Getting service delivery right every time is difficult, because contact centre operators face big challenges in areas such as staff retention, technology not delivering, and disconnected systems/processes. What’s more, large scale transformation projects are as expensive as they are challenging, so organisations today are trying to focus their effort and budget in the areas that can provide sustainable, high-impact performance improvements, on a tactical, less-intrusive level.

Simple, right? 🤣

No. But it can be simplified by taking a logical approach.

In this article we’re going to explain how Acceleraate approaches CX and contact centre improvement. We’ll talk about some of the technology – some relatively new, and some not-so-new - and the areas we’ll typically focus on to deliver performance gains, cost improvement, and higher quality experiences.

Our approach

In a nutshell, our approach is to break down the customer experience & contact handling process into phases and then identify what should be changed and, more importantly, what we can control.

Around a decade ago we learned of Sir David Brailsford’s "aggregation of marginal gains" concept. The very concept he applied to British Cycling (Team Sky) and quickly started delivering Olympic medals and Tour de France titles. Thus, turning around almost one hundred years of British Cycling mediocrity. Brailsford and his team broke down everything they could think of that goes into riding a bike and then set about finding 1 percent improvements in every controllable area. And as the improvements consolidated, the results came.

It struck us that Brailsford’s approach could be well utilised in customer service and contact centre improvement.

So, when we look at contact centres, we separate the customer experience into three core areas, and then identify where we can use modern technology, improved integration, and process re-design to deliver those compounding gains.

The three areas are as follows.

• Before contact reaches an agent (Pre Agent)

• When contact reaches an agent (With Agent)

• After contact reaches an agent (Post Agent)

In our experience, considering these elements separately is key because getting to the root of where your potential efficiency gains and CX improvements lie is not as simple as just implementing new technology with an improved feature set. As has been said many times before - technology provides the means, but people provide the answers. So we need to understand the processes and the challenges throughout the customer journey, because that is how our clients’ budgets and resources should be prioritised.

(As an aside, this is where many CCaaS and AI transformation programmes fall down – and is often why you inherit all of the same problems, just in a slightly shinier box!)

Pre Agent

This stage of the customer experience is where we look to establish simple and focused processes that are primarily designed to reduce queuing and to correctly triage customer interactions.

Mainstream Generative AI has been a “thing” for a couple of years in the world of CX and contact centre and, today, we can significantly improve customer journeys by providing intelligent, conversational agents that can handle a wide range of queries and information capture. Historically, the use of AI in contact centres was primarily focused on deflection and containment and, whilst there are multiple use cases for this approach, we can additionally use this technology to provide much more accurate and efficient support and triage for customers:

• AI-Powered Chatbots & Virtual Assistants such as Zoom Virtual Agent can generate human-like responses to customer enquiries, allowing them to handle routine tasks such as answering FAQs, guiding users through troubleshooting steps, or helping with account management. By understanding and generating natural language, these bots can offer personalised and contextually relevant support, improving the customer experience. We can also create virtual assistants that handle more complex requests by understanding context and intent, such as booking appointments, processing orders, or providing detailed product information. This reduces the need for human intervention and enables 24/7 service availability.

• Information Capture: Your agents’ time will always be the most expensive part of the customer service you provide. So, if we know that there are certain questions your agents will always need to ask, we look to automate those. This could be as simple as an automated ID&V process, or something slightly more involved like using AI to gather specific issue details or evidence. The more we can achieve up front, the more efficient the support process becomes.

• Automated Issue Categorisation: When a customer submits a query, generative AI can analyse the text to understand the problem's nature and urgency. It can then automatically categorise the issue and prioritise it based on predefined rules, ensuring that critical issues are addressed promptly and handed over to the right team and contact channel.

• Intelligent Routing: Once an issue is categorised, generative AI, or back-office integration can route it to the most suitable agent or department. This helps in reducing resolution time and improves the overall efficiency of the support system.

In our experience, using AI for effective triage and information capture saves 1-2 minutes of agent time per interaction, on average.

With Agent

This stage of the customer experience is where we look to ensure that your agents have everything that they need to resolve the customer’s issue or enquiry as quickly and as efficiently as possible.

One of the most frustrating experiences for a customer is going through an automated pre-agent process and then being forced to repeat themselves. This happens when the pre-agent processes are not integrated into the contact centre operation. With modern contact centre technology solutions like Zoom Contact Centre this no longer needs to be an issue:

• Contextual Hand-Off for Agents: The hand-off from Pre-Agent to Engagement is critical. Smart AI technologies such as Zoom AI Companion can create summaries of customer interactions, providing agents with concise and relevant information. This allows agents to quickly understand the issue without needing to review the entire conversation history or asking the customer to repeat themselves. This enables faster and more effective responses.

• Access to Information: When back-office tools and systems like CRM, ERP, and knowledge base are integrated with the contact centre, agents gain immediate access to in-the-moment intelligence and answers, and comprehensive customer data, including past interactions, purchase history, and preferences. This allows agents to provide a more personalised and informed service, reducing the time spent searching for information and improving the quality of interactions. Acceleraate is a system integration specialist – we’ve even built our own integration acceleration platform for Zoom – so no matter which systems our clients are using, we can usually find a way to integrate them.

• Scripting & Best Action: Whilst not a new concept by any stretch it’s often surprising to see how few contact centres have built their scripting and best actions into the agent workspace. In fact, most of the time it’s in a separate browser tab, or a word document. Toggle tax is inefficient by nature (I guess that’s why we call it a tax?) and scripts/actions/intelligence are difficult to maintain effectively. With solutions like Zoom Contact Centre we can generate both standalone agent guides, alongside instant access to dynamic knowledge base content directly from the agent workspace.

We also look at how we can empower agents to complete their post-interaction tasks and administration quickly, efficiently, and accurately; whilst ensuring that any agreed follow-up actions are documented and escalated appropriately. Post interaction wrap-up is often the most inefficient and open-ended part of a contact centre process. We’ve worked with contact centres where wrap-up takes 15 minutes or longer. Ironically, this is often the forgotten part of the CX improvement process. It’s almost because it comes last in the interaction handling process, so it gets considered last. But in many cases, it’s actually where the largest efficiency and time-saving gains can be found:

• Automated Summarisation: Generative AI can take a conversation - whether voice, chat, email, social etc. – no matter how long, and summarise it into a couple of paragraphs. This significantly reduces the length of time it takes for agents to type up their after-contact notes and assures the accuracy of the information being captured.

• Automated Follow-up Actions: The same technology can be used to identify the follow up actions that have been agreed – and make them available to the agent and/or supervisor in simple bullet point format. Actions and escalations can also be fully automated, ensuring that nothing is missed, and service issues can be closed as quickly as possible.

• Automated Disposition: In some products such as Zoom Contact Centre, the generative AI can also recommend a disposition based on the context and content of the interaction. This improves reporting accuracy and removes the need for the agent to scroll through tens (sometimes hundreds) of disposition sets to find the right one.

For a typical 8-10 minute customer service call, a streamlined, single pane agent workspace, supported by generative AI solutions like Zoom AI Companion & Expert Assist can save 2-5 minutes of agent time per interaction, on average.

Post-Agent

For many, the CX journey & process ends when the agent clicks "Finish Wrap-Up". But, for us, it's actually where it starts. This is the stage where we can generate the insights that inform and advise the next steps for improvement. Our clients need to focus their time and budget on the right things, and those right things are primarily identified by data and intelligence. So we focus on making sure the data and insights that are being generated are not only useful, but actionable:

• Meaningful Insight: Once an agent finishes an interaction, the raw data generated from that engagement becomes invaluable. By examining metrics like handle time, customer sentiment, first contact resolution, and escalations, you can identify patterns and areas that need attention. For example, if call durations are consistently longer on a particular product issue, this might highlight the need for improved agent training or clearer product documentation. Or, if customers are persistently dropping out of a self-service journey or IVR flow at certain points, it highlights the need to investigate and re-think the process. These insights enable targeted improvements rather than broad-brush strategies, ensuring resources are used effectively.

• Customer Feedback Integration: Beyond just focusing on agent performance metrics, we integrate post-interaction customer feedback - whether through CSAT, NPS, or follow-up surveys - to triangulate data. For example, if the analytics show that an agent resolved an issue within the expected handle time, but the customer still rated the experience poorly, we can deep-dive into what caused the disconnect. Was it a lack of empathy? Was the issue unresolved from the customer’s perspective? With this insight, businesses can fine-tune their agent training programs to improve the soft skills or technical knowledge that are truly impacting customer satisfaction.

• Quality Assessment for Continuous Improvement: After each interaction, management teams can conduct quality reviews that are more than simple scorecards. With solutions like Zoom Quality Management, these reviews can include customer sentiment analysis, key interaction moments, and follow-up actions. By correlating these metrics with KPIs such as first contact resolution and customer effort scores, organisations can pinpoint exactly where quality falls short. For example, an audit might reveal that while the agent handled the technical issue well, they missed opportunities to upsell a service - giving the business a clear direction for improvement initiatives.

• Predicting Future Trends: By leveraging machine learning and predictive analytics, post-interaction data can not only highlight what went wrong but also forecast future challenges. For example, a spike in customer complaints about a certain product feature could indicate an emerging problem that hasn’t been fully realised yet. With this foresight, companies can proactively adjust their support strategies, ramp up agent training, or issue product updates before the situation escalates, ultimately improving customer experience and loyalty.

In Summary

Every contact centre and customer service operation is different, and - sadly - there's no such thing as a one-size-fits all strategy. Modern CCaaS and AI technologies are providing more and more capability with every passing week, but the adoption of that technology needs planning and designing, especially where your customer experience and brand reputation is concerned.

Acceleraate brings two decades of experience to the table, helping our clients to identify what needs to change, and what the outcomes are going to be. We break the process down and then identify and deliver change that significantly moves the needle.

So, if you're considering re-platforming your contact centre or AI tech in the near future and would like to know more about the technologies and the approach we've shared, don't hesitate to get in touch with us for a friendly chat.