What is a call centre solution?

A contact centre solution enables businesses to manage large volumes of incoming and outgoing customer calls. It is a centralised system that includes various tools, technologies, and processes for handling customer interactions, such as voice calls, emails, chat, SMS, and social media messages.

What are the five pillars of a contact centre?

People – The recruitment, training, and management of agents and other staff members in the contact centre.Process – The procedures and workflows that are in place to handle customer inquiries and requests.Technology – The hardware and software systems that are used to manage customer interactions, such as telephony, CRM, workforce management, and reporting tools. Data – The collection, analysis, and utilisation of customer data and feedback to improve the customer experience and optimise contact centre operations.Strategy – The overall vision and direction of the contact centre, including its goals, objectives, and performance metrics.

What are the different types of contact centres?

There are five main types of contact centre.Inbound – Incoming customer calls and enquiriesOutbound – outbound calls such as telemarketingBlended – Handles both inbound and outboundVirtual – staff work remotelyMultichannel – across all channelsOmnichannel – across all channels and can switch between channelsCloud – hosted in the cloud

How many calls can a call centre handle?

The number of calls a call centre can handle varies depending on a number of factors, such as the size of the call centre, the number of agents available, and the complexity of the calls.

Who are the leading contact centre vendors in the UK?

The leading contact centre vendors in the UK are Mitel, 8×8, Cirrus, Gamma and Five 9, all of which Opus Technology are platinum partners with.

Customer Journey Analytics for Contact Centre

Understand your customers better along every stage of their journey

From initial awareness to post-purchase support and beyond, Customer journey analytics enable you to collect data from various sources, including website visits, social media, email and phone calls to gain insights into customer behaviour patterns and preferences. This data then enables you to build a comprehensive view of every step customers take with your businesses across different channels.

Using customer journey analytics to understand customer behaviour patterns

By mapping out the customer journey and analysing the data at each stage, businesses can better understand their customers’ needs, preferences, and behaviours. This enables them to make data-driven decisions to enhance the customer experience, increase customer loyalty, and ultimately drive revenue and growth.

By streamlining processes and reducing response times, Conversational AI tools can identify and overcome operational efficiency improvements and ensure consistent service is delivered.

Visualise the customer journey and monitor their demands

Customer Journey Visualisation

Customer Journey Visualisation involves mapping out the entire customer journey to visually represent each touchpoint, helping to identify key stages, channels and potential areas for improvement.

Demand Tracking and Benchmarking

Demand tracking and benchmarking monitor the fluctuations in customer demand for your products or services over time. Benchmarking compares your performance against industry standards or competitors. This helps you to adjust your strategies to meet changing customer needs.

Understand customer intent and analyse sentiment

Sentiment and intent analysis help you to understand the attitudes and motivations that drive customer actions. Sentiment analysis analyses customer feedback, reviews and interactions to gauge attitudes towards your business, products and services. Whereas Intent analysis looks at underlying motivations and goals that drive customer actions. This is particularly beneficial to help identify ways to improve CX.

Use customer journey analytics to uncover deep insights to improve the customer journey

Customer journey analytics use advanced data to build different kinds of predictive models that provide deeper insights into the customer journey. This can help to uncover and resolve complex issues or improve self-service.

By analysing customer interactions and feedback, they update their models with new data to improve accuracy and effectiveness in responding to future queries.

Assess customer effort and sentiment to gauge the barriers to communication

Customer journey analytics help you to see what is preventing your customers from getting a great experience and give you the information you need to make improvements. They proactively identify and address potential issues in the customer journey to enable you to improve customer satisfaction, retention, and loyalty. With deeper insights into customer behaviour, preferences, and pain points across various touchpoints, you can personalise marketing messages, optimise sales efforts, and enhance operational efficiency.