The analytics advantage

Contact centre analytics improve service quality keeping the bottom line in mind
Shaheen Haque is the territory manager for Middle East and Turkey for Interactive Intelligence.
Shaheen Haque is the territory manager for Middle East and Turkey for Interactive Intelligence.


By Shaheen Haque

Customer service has always been an integral business function for any organisation, but between technological advances, new channels for engagement, and the general economic conditions that have prevailed in the Middle East for over a year, delivering a level of service that can attract and retain customers is now more important than ever.

The contact centre remains at the heart of most organisations’ customer service strategies and companies have now begun to explore analytics to turn these traditional ‘call centres’ into ‘insight centres’. With the right solutions, businesses can monitor and improve a wide range of KPIs including call times, agent efficiency, time to resolution, and of course, customer satisfaction. It’s no wonder then that a recent report indicates that the speech analytics market alone will be worth $1.6 billion by 2020 due to the rising demand for finding hidden insights from customer interactions.

But the wide scope of contact centre analytics presents a challenge - which analytics should you prioritise and how can these improve contact centre performance? While the ideal combination will vary from business to business, here are five types of analytics you should consider:

Speech and real-time analytics

With the advent of natural language processing (NLP) technologies and the ability to understand more unstructured data, like phone call recordings, companies can start to extract a wealth of information from every recorded call. This can then be used to improve efficiency and customer experience in several ways, including:

• Alerts: Either through word, phrase, or sentiment spotting, the system can notify a supervisor about some specific content in a call between an agent and a customer that may need to be reviewed and/or actioned.

• Agent guidance: Real-time analytics, paired with guidance engines, can prompt agents on the best sales offer to make and when.

• Automation: If the system detects that the customer has provided his/her address at a point in the interaction, it could paste that address into the field automatically.

Interactive Voice Response (IVR) analytics

IVR systems are an integral element of this engagement – but often, much to the frustration of customers who are eager to connect to an agent in as few steps as possible.IVR analytics can not only optimise IVR workflows and provide routing to the appropriate support agent, but if integrated with the CRM system, can also provide agents with relevant and up-to-date customer information, thereby further enhancing the customer experience.

Self-service analytics

There are plenty of areas where self-service can be more efficient for both the customer and the business. For example, when updating personal information, is it not easier for a customer to do so online rather than on a call with a contact centre agent? Monitoring and reporting on these channels, however, is critical to ensuring a consistent and positive experience.

Predictive analytics

An in-depth review of past performance against key metrics such as call volume, service level, handle time, and customer satisfaction provided by predictive analysis enables the business to make more informed decisions. Through analysis of transactional and other types of data, companies can identify information about their customers’preferences, enabling them to provide more proactive and personalised service.

Cross-channel analytics

Providing multiple channels for customer engagement is by no means an easy feat. It is critical to leverage cross-channel analytics to help shape customer interactions in real-time.

When contact centres get this real-time data, they can categorise interactions and identify trends in customer interests and behaviour. This data can also be used to drive critical business decisions, such as which channels need to be improved or focused on based on their usage, effectiveness and popularity.

By implementing these analytics, contact centres can save precious time, provide comprehensive omnichannel support, and gain the insights they need to make more informed business decisions. Forward-thinking organisations that adopt these methods will see an improvement in customer satisfaction, giving them a critical competitive advantage.

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