An Introduction to… Contact Centre Analytics

Our panel of experts explain everything you need to know about contact centre analytics, from its benefits and key features to its costs.

What Is Contact Centre Analytics?

Contact Centre Analytics Allows you to Gain Insights

Contact centre analytics involves analysing customer interactions, agent performance, and operational data to gain insights into customer behaviour, agent effectiveness, and overall contact centre efficiency.

This data can be used to make data-driven decisions about staffing, training, and resource allocation. Key metrics used in contact centre analytics include customer satisfaction (CSAT), first-call resolution rate (FCR), average handle time (AHT), and agent adherence to scripts or processes.

Thanks to Ben O’Reilly at MaxContact

Analytics Can Play a Crucial Role in Improving Customer Experience

Contact centre analytics can play a crucial role in improving customer experience by providing valuable insights into customer behaviour, preferences, and needs.

As more companies look to be customer obsessed, it is the quality of analytics that can be a competitive difference. After all, you can’t manage what you can’t measure.

It is the quality of analytics that can be a competitive difference. After all, you can’t manage what you can’t measure.

Analytics helps organizations to collect, analyse and interpret data from various sources within a contact centre, to gain insights and improve company performance, in new customer acquisition as well as in customer retention.

The sources can include data from all media, and whilst voice may still be king, it is clear that giving customers the choice to interact in the media that best suit them is vitally important.

From phone calls, emails, chat messages, social media interactions, the importance of collating and analysing this data has never been greater.

Contact centre analytics can be used to track KPIs such as call volume, average handle time, first call resolution, and customer satisfaction scores. It can also identify trends and patterns in customer behaviour, agent performance, and overall contact centre operations.

By analysing this data, contact centre managers can identify areas of improvement, make data-driven decisions, and optimize their operations for a better customer and employee experience, further improving the CSAT scores, reducing employee ramp and retention metrics.

Thanks to Chris Angus at 8×8

To understand how to harness unstructured VoC data to better understand customers’ needs, read our article: Are You Embracing the Potential of Unstructured VoC Data?

Analytics Takes Away Data Complexities

Today’s contact centres are fantastic but complex beasts – remote and hybrid working, multiple channels, more complicated interactions, higher expectations all round, and a deluge of data.

The amount of data can be overwhelming and get in the way of delivering an exceptional experience for customers and for agents.

Analytics takes away many of these complexities by transforming copious amounts of raw data – from within the contact centre as well as from other parts of the organization – into meaningful, valuable business intelligence using the power of artificial intelligence (AI) and machine learning (ML).

Thanks to Jennifer Docken at Calabrio

How Does Contact Centre Analytics Work?

Four Key Aspects of Contact Centre Analytics

Here’s a high-level overview of how contact centre analytics works:

Data Collection & Standardization:

Contact centre analytics typically involves collecting data from multiple sources, including call recordings, chat transcripts, and more. This data is often stored in a central repository in a standardized way, for easy access and analysis.

Data Analysis:

The data can be analysed using various techniques such as data mining, machine learning, and statistical analysis.

This analysis can help identify patterns, trends, and insights that can inform decision-making and process improvements.

Reporting:

The results of the analysis are typically presented in the form of reports or dashboards, which can provide real-time and historical visibility into contact centre performance and customer behaviour.

These reports can be customized to suit the needs of different stakeholders, such as contact centre managers, agents, and executives.

Actionable Insights:

Finally, the insights gained from contact centre analytics can be used to make data-driven decisions and improve performance.

For example, insights might lead to changes in agent training, adjustments to call-routing strategies, or improvements to self-service options.

Thanks to Chris Angus at 8×8

Measure and Analyse the Most Important Metrics

In order to effectively utilize data analytics, it’s crucial to understand how it works.

With so many different types of data and metrics available, it’s easy to get lost in a sea of information and miss the key insights that can drive business success.

To start, it’s important to identify the metrics that matter most to your business and begin tracking them through live and historical reporting.

By measuring and analysing the most important metrics, businesses can make informed decisions and quickly respond to areas that need improvement.

Live reporting can provide up-to-date insights into intra-day performance, while historical reporting can reveal trends and explain overall business performance over time.

It’s important to note that the metrics that matter may vary for different levels of the business, and a set of complementary KPIs is often more effective than measuring one thing in isolation.

Thanks to Sean McIver at MaxContact

For information on what to consider when choosing your metrics, read our article: Contact Centre Metrics: Are You Measuring the Right Things?

They Convert Data Into Useful and Actionable Information

Contact centre analytics is a set of software tools that converts data into useful and actionable information by making correlations, uncovering trends and identifying root causes.

Contact centres typically use multiple systems – order entry, CRM, ACD, IVR, quality management – to serve customers.

Analytics tools overcome the limitations of those data silos by bringing all customer interaction information together so it can be analysed holistically.

Additionally, they may handle contacts in a variety of channels, such as phone, chat and email. With the various ways customers now prefer self-service, data silos can easily get created as well.

Analytics tools overcome the limitations of those data silos by bringing all customer interaction information together so it can be analysed holistically.

With the emergence of artificial intelligence (AI), contact centres now also have the opportunity to add AI-powered analytics to their collection of analysis tools.

AI-powered analytics are capable of “listening” to calls and reviewing text, such as chat transcripts, in order to analyse customer language and intents.

With this, AI-powered analytics tools can determine common reasons for contacts, assess the quality of the interaction, identify training opportunities and alert managers to compliance violations.

Thanks to Andy Traba at NICE

Benefits All Parts of the Contact Centre

Sophisticated AI and ML tools benefit all parts of the contact centre.

At a glance, agents can understand their customers’ needs and wants every step of the customer journey and can even pre-empt how they want to interact or what they might wish to buy based on previous interactions.

Supervisors can see exactly how their staff are feeling to quickly identify those who might need extra support and training.

Analytics makes it easy to highlight IT systems bottlenecks that hinder overall contact centre performance.

Meanwhile, analytics makes it easy to highlight IT systems bottlenecks that hinder overall contact centre performance.

Thanks to Jennifer Docken at Calabrio

What Are the Key Features of Contact Centre Analytics?

Eight Most Important Features

Generally, the key features of contact centre analytics should provide a comprehensive view of all customer interactions and contact centre operations. Some of the most important features include:

1. Multichannel Analytics:

Contact centre analytics should be able to collect and analyse data from various channels, such as voice, email, chat, social media, and more, to provide a comprehensive view of customer interactions across all channels.

2. Speech and Text Analytics:

Speech & text analytics can analyse voice recordings or written interactions (such as chat transcripts, or email messages) to identify sentiment and patterns, such as keywords or phrases that are often mentioned by customers, which can help agents respond more effectively.

3. Real-Time Monitoring:

The ability to monitor contact centre activity in real time can help team leads to quickly identify issues and take action to improve performance and customer experience.

4. Real-Time Alerting and Notifications:

The ability to set up alerts based on specific metrics’ values can help managers to quickly react to their contact centre’s activity in real time.

5. Historical Analysis:

Historical data analysis can help identify long-term trends and patterns, allowing contact centres to make data-driven decisions based on past performance.

6. Predictive Analytics:

Predictive analytics can be used to forecast future trends and patterns, such as call volume, wait times, and customer satisfaction scores, allowing contact centres to be proactive in their response.

7. Fully Customizable Reporting:

Customizable reporting enables managers to create reports and dashboards that align with specific business objectives and KPIs, providing actionable insights to different stakeholders.

8. Schedulable Reports:

Schedulable reports enable managers to automatically generate a custom report and receive the relevant KPIs directly in an email, at any moment during the day, week, or month.

Thanks to Chris Angus at 8×8

Encompass an Integrated Range of AI- and ML-Driven Solutions

The best analytics platforms encompass an integrated range of AI- and ML-driven solutions that unlock the true power of data to create high-performing customer-centric contact centres.

These solutions include:

Speech and Text Analytics

Speech and text analytics capture and analyse 100% of customer interactions, turning raw data from complex omnichannel conversations into valuable intelligence insights that agents can apply to improve the customer experience in a highly proactive way.

Desktop Analytics

Desktop analytics can be used to understand agent effectiveness by determining which IT resources they use to increase performance or what existing systems or processes are slowing them down.

For example, are agents making the most of your internal knowledge base? Which applications and websites do your highest-performing agents use and how can you transfer that knowledge and learning to other agents?

Sentiment Analysis

It is not enough to analyse and understand what your customers are saying, you also need to understand how they feel.

Sentiment analysis automatically detects, extracts, and classifies the actual mood expressed during all contact centre customer conversations and automatically delivers a sentiment score for every interaction – whether positive, negative, or neutral.

No more need to manually monitor calls or study call transcripts to learn how customers feel during and after interactions.

Predictive Evaluations

Predictive evaluations let analytics do the talking to transform the way you evaluate every customer conversation. They provide the near-real-time data needed to re-engineer complete customer journeys quickly and efficiently.

Giving a complete view of customer interactions, they can identify the one word that crops up in every conversation, or highlight when 90% of customers are asking the same question to focus on what really matters for improved customer service.

Why not utilize predictive analytics to anticipate a customer’s future needs? When linked to customer survey platforms, they capture and analyse the results – valuable intelligence that can be applied to improve NPS or CSAT scores.

Customized Dashboards

Customized dashboards disseminate intelligent, analytics-driven insights from the contact centre and focus on metrics that matter to other parts of the business.

These types of dashboards help marketing teams understand areas such as brand awareness, competitor influence and campaign effectiveness.

Customized dashboards disseminate intelligent, analytics-driven insights from the contact centre and focus on metrics that matter to other parts of the business.

Finance departments benefit from insights into billing issues, refunds, and credits. Meanwhile, dashboards highlight customer effort and opportunities for process improvements.

Performance Coaching

Performance coaching enhances the ability for contact centre managers to record and track agent performance metrics, monitor agent interactions for potential skill and behaviour gaps, improve training, identify their best team coaches, automatically schedule training and link with gamification tools to reward improvement and success.

When linked to the latest workforce management (WFM) solutions, agents also benefit, with the ability to self-serve their coaching requirements by making time in their busy schedules for new learning at a time and place to suit them.

Thanks to Jennifer Docken at Calabrio

Needs to Be Data-Relevant, Brand-Specific, Easy to Digest and Actionable

To truly work, contact centre analytics needs to be data-relevant, brand-specific, easy to digest and actionable to drive measurable improvements. This allows businesses to monitor the entire customer journey across all channels.

Analytics understands customer sentiment, giving brands a clear picture of their customers’ needs and how they are being met.

Analytics drives powerful real-time insights into customer interactions, showing brands what can be done to improve the experience.

Analytics can uncover trends and root causes for improved handle times, reduced repeat contacts and process improvements.

This real-time guidance also empowers agents to deliver better customer service, leading to happier and more loyal customers. Real-time guidance can also let an agent know when to include an upsell or cross-sell offer, leading to potential revenue opportunities.

Brands that use analytics can also decrease overall costs. Analytics can uncover trends and root causes for improved handle times, reduced repeated contacts and process improvements, leading to more efficient and cost-effective operations.

Thanks to Andy Traba at NICE

Which Areas of the Contact Centre Can Analytics Help to Improve?

Contact Centre Analytics Can Help Improve the Customer Experience

Analytics can help contact centres improve the customer experience by identifying areas for improvement in interactions, such as call handling times, first-call resolution rate, and customer satisfaction scores.

By analysing customer interactions, contact centres can gain insights into common customer issues and improve the overall customer experience.

Analytics can also help identify areas where agents may need additional training or coaching. For example, analysing call recordings can help identify areas where agents may be struggling.

Additionally, analytics can help contact centres optimize staffing levels and scheduling to ensure that they have enough agents available to handle peak call volumes.

By analysing call volumes and agent performance data, contact centres can identify trends and adjust staffing levels as needed.

Lastly, analytics can help contact centres identify areas where they can improve operational efficiencies, such as improving call routing strategies.

By analysing operational data, contact centres can identify inefficiencies and make informed decisions to improve performance.

Thanks to Ben O’Reilly at MaxContact

Identify and Improve Key Drivers of Satisfaction and Pinpoint Improvement Opportunities

Insights from the best AI-powered analytics help customer service leaders identify and improve key drivers of satisfaction and pinpoint improvement opportunities.

Analytics solutions can also help contact centres improve their service by resolving the following issues:

Too Much Data

Too much data, and too many different formats. Most centres have far too much data to analyse, and the formats all vary. AI solves this.

It actually helps to have more data to learn and pull from. Additionally, customer experience analytics solutions that use natural language processing (NLP) can analyse both structured and unstructured data in near real time. This will help a business spot gaps in a variety of areas.

Performance Issues

It can help identify performance issues and spot changes. Sometimes, some contact centre analytics tools aren’t robust enough to identify changes in the nature of interactions.

With the wrong tools, performance issues remain hidden unless someone is specifically researching them. The best customer experience analytics solutions shine a light on changes and issues so leaders aren’t caught flat-footed.

For best-practice tips for performance management in contact centres, read our article: Performance Management Best Practices

Customer Understanding

Finally, analytics can help in finding out who your customers actually are. Some contact centres rely on customer surveys for this, but they’re not always accurate.

The ideal solution is to review every interaction to determine customer sentiment based on what customers are saying, but that task is really beyond human capabilities.

Instead, contact centres should use analytics tools and AI that can analyse 100% of interactions and give managers instant insights into customer sentiment.

Thanks to Andy Traba at NICE

CX, Performance, Efficiency and Planning

Customer Experience:

Contact centre analytics can help to identify pain points in the customer journey and improve overall customer experience. For example, analytics can reveal common customer complaints, which can then be addressed through process improvements, agent coaching, or other interventions.

Agent Performance:

Analytics can provide insights into agent performance, such as call handling times, first call resolution rates, and customer satisfaction scores. This information can be used to provide targeted coaching and training to agents, improving their skills and boosting overall performance.

Operational Efficiency:

Analytics can help identify areas of inefficiency in contact centre operations, such as long wait times or ineffective call routing. By addressing these issues, contact centres can optimize their processes and reduce costs.

Forecasting and Planning:

Analytics can provide valuable data for forecasting call volume or staffing needs. This information can be used to optimize scheduling and ensure that the right resources are available to meet demand.

Thanks to Chris Angus at 8×8

Help Gain Competitive Advantage

When organizations truly understand their customers and employees, they quickly gain competitive advantage.

What is more, as leaders in driving CX excellence, contact centres can strategically drive better performance for all customer-centric marketing and sales professionals, wherever they are in the organization.

Thanks to Jennifer Docken at Calabrio

What to Watch Out for With Contact Centre Analytics Solutions

Six Key Elements to Consider When Choosing a Solution

When selecting a contact centre analytics solution, there are several aspects to watch out for to ensure that you choose the right solution for your organization:

1. Ease of Use:

Look for a solution that is simple and can be quickly adopted by agents and managers. A complicated or cumbersome solution may not be used effectively, defeating the purpose of implementing analytics in the first place.

2. Customizability:

Look for a solution that can be customized to meet your specific business needs and KPIs. A one-size-fits-all solution may not be effective in addressing your unique challenges.

3. Scalability:

Consider whether the solution can grow with your business as your needs change and expand. You might only use voice channel reporting now, but if your organization decides to digitalize the contact centre, you will need an analytics solution that is able to process and analyse digital interactions as well.

4. Data Security:

Ensure that the solution provides robust data security features to protect sensitive customer information and comply with industry regulations.

5. Cost:

Consider the cost of the solution, both upfront and ongoing. Ensure that the solution provides good value for your organization and aligns with your budget.

6. Customer Support:

Look for a vendor that provides excellent customer support and has a reputation for resolving issues quickly and effectively.

Thanks to Chris Angus at 8×8

Be Aware of Staff Behaviour

When using data analytics in the contact centre, businesses need to be aware that staff behaviour can be driven by what they are measured against.

When choosing analytics solutions, businesses should look for tools that are flexible and adaptable to changing needs.

To avoid unintended consequences, it’s important to have a set of complementary KPIs that provide a holistic view of performance.

Additionally, it’s crucial to avoid setting arbitrary targets that can demotivate staff and fail to account for exceptional performers. When choosing analytics solutions, businesses should look for tools that are flexible and adaptable to changing needs.

Finally, the analytics cycle is an ongoing journey of discovery, and it’s important to analyse, review, provide rapid feedback, assess, and repeat.

Thanks to Sean McIver at MaxContact

For sneaky things contact centre employees do to avoid taking calls, read our article: 7 Tricks That Call Centre Employees Play

Data Needs to Be Completely Accessible

To harness the power of analytics, data needs to be completely accessible. Data silos trap valuable information, preventing it from being shared across applications and teams.

Businesses need to host their CX operations on a single, cloud-native platform with a suite of the most advanced solutions. This allows data to be shared across the organization, driving powerful analytics and insights into the business.

It’s also important for businesses to be able to easily access and understand the information that is generated through analytics. If not, the power of analytics is wasted. It needs to be easy for non-analyst users to be able to access information, no special training required.

Thanks to Andy Traba at NICE

Reveal the Value of Analytics Before You Buy

Here are our top 3 tips for helping contact centres see the value of contact centre analytics:

Achieve More in Analytics Implementations

Start with a goal and choose an analytics champion who can work successfully with IT to align technology strategies with business goals and ensure the whole project happens.

Next, focus on low-hanging fruit, the quick wins that are likely to demonstrate the true value of the tool in a short space of time. Anything extra will contribute to the bottom line.

For many organizations, these low-hanging fruit will be similar and often relate to quality scores, voice of the customer (VOC) feedback and process improvements. Be open and transparent. Use dashboards so everyone can see how you are improving over time.

Maximize Your Analytics Potential

Thanks to Jennifer Docken at Calabrio

How Much Does Contact Centre Analytics Cost?

Costs Can Vary Widely Depending on the Vendor

The cost of contact centre analytics solutions can vary widely depending on the vendor, the features included, and the size of your organization.

Some solutions are priced per agent or per user, while others may be priced based on the volume of data processed or the number of channels analysed.

As a general rule, basic contact centre analytics is included as a bundle in the overall cost of the contact centre, being part of the core product and functionalities.

The insights and improvements gained from analytics can lead to significant cost savings and revenue growth, making it a worthwhile investment for many organizations.

For more advanced features, such as speech and text analytics or screen recording, you can expect to pay between £40 and £150 per seat per month.

However, the actual cost may be higher or lower depending on the specific features and functionality you require, as well as any additional services or support you need.

It’s important to consider the return on investment (ROI) when budgeting for contact centre analytics. The insights and improvements gained from analytics can lead to significant cost savings and revenue growth, making it a worthwhile investment for many organizations.

When budgeting for contact centre analytics, it’s important to factor in not only the cost of the solution itself but also any additional expenses such as training and implementation costs. It’s also important to consider ongoing costs such as maintenance, upgrades, and support.

Thanks to Chris Angus at 8×8

Contact Centres Need to Achieve More and Regret Less

In uncertain economic times, contact centres need to achieve more and regret less. Wherever possible, start by focusing on the end goal and ROI instead of a fixed budget figure.

Analytics helps to address the top three contact centre challenges today: rapid business growth, operating in the new normal and hybrid working.

Finally, avoid introducing new analytics features for features’ sake. Listen to your frontline people and listen to your customers to deliver the right analytics technology and CX opportunities that really matter.

Thanks to Jennifer Docken at Calabrio

For more on the topic of contact centre analytics, read our articles:

• Customer Data Analysis – How to Analyse Data in 7 Steps
• An Introduction to Customer Data Analysis
• 16 of the Best Uses for… Voice Analytics Tools
• Interaction Analytics in Contact Centres – An Executive Briefing

Author: Robyn Coppell