It’s no secret, Artificial intelligence (AI) is transforming the customer service sector in unprecedented ways, opening new possibilities for organisations to reduce operational costs, while driving business performance.
Emerging technology such as Artificial Intelligence, Machine Learning and Robotic Processing are providing organisations with an edge over competitors. Therefore, it is imperative business leaders look at how these innovations and AI powered systems can be used in their own organisation.
If you’re looking to make a case for your business to transform its customer operations and call centre into a forward-thinking, AI-powered operation, this guide will support your efforts. Keep reading to uncover how you can implement AI initiatives, the benefits that can arise as well as the key trends that are shaping the future for AI in call centres.
AI’s emergence in call centres
The emergence of Artificial Intelligence, particularly Generative AI, has reshaped call centre operations. Businesses are now relying on AI tools to automate time-consuming tasks, improve the customer experience and boost agent efficiency. Some common ways of adopting AI in call centres include:
- Predictive routing to the best equipped agents
- AI-powered Virtual Agents
- Intelligent chatbots
- Automated call routing
- Predictive analytics
Benefits of leveraging AI in call centres
Embracing AI call centre innovations brings fort numerous benefits across the customer and agent experience.
Improving customer satisfaction
Call centres have used technology to route calls to the right department for years, but innovations such a predictive routing uses customer information to match customer profiles to agents most likely to be able to help. When customers have their queries resolved faster and more accurately, this improves first call resolution metrics and customer satisfaction.
This then leads to the question – Can AI replace agents?
Due to the complexity of customer queries, AI will not completely replace human agents right now, but this technology can provide significant opportunities for organisations to provide self service capabilities for simple queries such as account balances, service outage notifications and delivery times.
AI can also be used to elevate customer engagement, providing agents with proactive prompts and suggested responses in real-time, while also measuring the sentiment of both the agent and customer to adapt the responses.
Forecast and predict future workload
AI-based predictive analytics enhances a call centre’s workforce management strategy by using historical data to forecast future activity. For example, this technology anticipates future call volume, allowing managers to accurately determine the required staffing levels and allocate shifts for customer service team members accordingly.
Additionally, predictive analytics offers valuable intelligence into customer behaviour. This enables management to identify the reasons behind spikes in interaction volume such as a new product launch, promotional offer or any other company initiative. Armed with this knowledge, business leaders can make data-driven decisions, which could include deploying AI solutions to assist in managing call volume during similar future events.
Enhance agent efficiency and productivity
Customer service teams are required to complete repetitive tasks that are often time-consuming and can lead to job dissatisfaction. Adopting AI tools to automate tasks such as call scoring, summarising the call and more can ease the workload for live agents, allowing them to focus on higher-value, rewarding work.
Automating those tasks enable customer service leaders to drive operational efficiency and improve agent productivity.
Scale operations and reduce costs
A significant expense especially for Australian organisations is the cost of labour. By using AI-powered Virtual Assistants to resolve standard customer enquiries such as status updates, balances and service notifications, your organisation can easily scale according to demand while reducing costs.
Virtual Agents can also be deployed to create a multichannel customer journey including Voice and Chat to resolve common customer inquiries. Integrating your call centre solution with your Customer Relationship Management (CRM) platform enables and organisation to leverage Virtual Agents to harness customer data, create personalised experiences and automatically update the customer’s record with the latest interaction details.
How to implement and utilise Artificial Intelligence in call centres
Here is an overview of some of the AI technologies that you can easily implement and leverage across your call centre.
Reducing call times with intelligent call routing
Average call time is a key operational metric call centre managers aim to keep as low as possible. When a customer calls in, you can integrate Advanced Virtual Agents (AVA) into your call workflows to automate the process of evaluating the nature of the customer’s enquiry. The caller is then intelligently routed to the most suitable agent based on language, skill, expertise or previous interactions.
This AI-powered system ensures each caller is connected with the best equipped agent who can resolve their enquiry as quickly as possible, aiming to reduce call times, minimise transfers and exceed customer expectations.
Call quality control
Measuring call quality is a vital call centre process – this activity indicates the effectiveness of the live agent throughout their interaction with a customer. These are some of the ways AI can help you manage call quality and compliance:
Call Transcription – Quality Assurance through manual listening of call recordings is a labour-intensive, time-consuming task that can only be completed for a sample of calls. Alternatively, AI can transcribe all calls, rate the call based on a trained language model and provide feedback about compliance adherence. Transcripts can be useful for agent training and feedback sessions.
Analysing call data to assess performance – AI-driven tools such as Speech Analytics enable managers to surface insights into compliance gaps, customer sentiment and optimisation opportunities. Utilising the findings, managers are able to evaluate the effectiveness of a customer service team’s performance and conduct targeted agent training sessions, with the aim of enhancing agent skillsets and elevating the customer experience.
Self service and knowledge management
Implementing AI into your call centre processes facilitates your customers to self-serve and complete simple tasks such as checking an account balance, or providing a parcel’s estimated delivery date, so your human agents can focus on more complex calls.
AI systems can be integrated with an organisation’s knowledge management base which ensures Chatbots or Virtual Voice Assistants provide accurate responses to customer enquiries.
Understand customers with Emotional Intelligence AI
Emotional Intelligence AI is trained to recognise the subtle nuances in varying languages and cultures. While on a phone call, sentiment analysis informs the agent how the customer is feeling based on their expressions and verbal cues. Suggested responses and links to a knowledge management tool can provide support to the agent in a timely manner.
Using data from the Emotional Intelligence AI models, managers can focus coaching activities around the findings that highlight the idiosyncrasies influenced by the customer’s geographical location and cultural background. Such focused training sessions can assist call centre agents to understand customers better, resulting in improving the service delivery and increasing customer satisfaction.
Real-time responses and suggestions
AI’s ability to analyse the conversation, identify customer intent and measure sentiment enables the human agent to be provided with step-by-step assistance throughout a live customer interaction. AI can be used to proactively provide suggestions and recommend responses to improve the customer experience and speed up resolution time.
Here is an example for a Retailer where Tiffany (Customer) has called to explain that her order has not arrived 3 days after the estimated delivery date. The AI assists the agent in real-time through providing a recommended guide for the agent to follow:
Step 1: Sincerely apologise and acknowledge the frustration that this issue has caused
Step 2: Offer the customer an immediate refund of the shipping cost
Step 3: Provide the latest estimated delivery date for Tiffany’s order
Step 4: Notify Tiffany that you will call her back on the new delivery date to ensure the order has arrived
Step 5: Ask if there is anything else Tiffany needs assistance with
AI call centre trends to keep an eye out for
With AI innovations being developed with such velocity, it is an exciting time for business leaders. But where is this heading and what is next? Here are some of the major AI call centre trends that you should be aware of:
Conversational AI to enhance the caller experience
Businesses are modernising the way customer service is being delivered – especially in accordance with the growing popularity of multiple channels such as social media messaging applications, SMS and Web Chat. With this, specific chatbots will need to be deployed across these different mediums and the nature of how customers will be serviced is yet to be determined. Some organisations may choose to deflect these to existing channels such as calls, or some may create automated responses within the platform.
Where customers want to call, Conversational AI models need to be developed and tuned so interactions don’t feel cold and impersonal. This technology is improving with Machine Learning and Natural Language Processing, to better recognise human speech, identify intent and either provide the customer with relevant information or route them to the best equipped agent who can resolve the enquiry. This AI trend will support faster resolution times and increase customer satisfaction by removing the need to navigate a complex Interactive Voice Response (IVR) system.
Advanced Natural Language Processing (NLP) will transform self-service
NLP will gradually become smarter and more in-tune with interpreting the nuances in human language. Currently, NLP aids in delivering fast service and resolve customer enquiries quickly. The future for NLP will not only make it easier for this evolving technology to comprehensively understand speech, but also the underlying tone and sentiment, allowing for more empathetic, relationship-building and human-near experiences.
How you can implement AI into your call centre operations with ipSCAPE
ipSCAPE offers leading-edge call centre technology and also has a dedicated Professional Services team to help organisations develop, train and implement AI programs to meet your business’s specific use case. Here are some of the ways ipSCAPE is currently helping our clients infuse AI into their customer experiences:
Utilise Advanced AI Speech Analytics
Analyse customer conversations in real-time and surface extensive insights into customer service experiences with ipSCAPE’s Advanced AI Speech Analytics. This AI-powered solution monitors both agent and customer language, identifying sentiment, intent, expressions and emotions. The data can be used to monitor compliance adherence, enhance retention strategies and optimise operational processes. Artificial Intelligence is coupled with Machine Learning to produce models that depict key performance metrics such as satisfaction ratings, call reasons and more.
Leverage AI Call Summarisation
Reduce time spent on post-call administration work and improve operational efficiency by automating the task of writing call summaries. Using AI Summarisation, conversations are automatically transcribed and summarised which are then synced into the customer’s record within leading CRMs such as Salesforce and ServiceNow.
Transcribe customer feedback
Automate the customer feedback collection process and harness AI to transcribe your customers voice with AISCAPE Advocate. This solution captures the voice of your customers and their NPS score within an after-call satisfaction survey. The feedback is securely stored in VaultSCAPE, a long-term interaction storage solution that enables managers to filter on the survey metadata including keywords mentioned in the feedback and numeric satisfaction ratings. Uncovering how your customers are feeling enables CX leaders to initiate retention efforts and make data-informed decisions to improve customer service experiences.
Incorporate Virtual Agents into your customer experiences
SCAPE – a multi-channel cloud call centre solution – provides a range of Neural Voices, available in multiple languages, that can be easily integrated into your IVR workflows. Leveraging the power of Azure Cognitive Services, your organisation can choose from over 150 Neural Voices or simply create your own synthetic voice that resembles your brand. Implementing virtual assistants allows your organisation to create a consistent brand experience and empower self-service experiences.
If you’d like to discover how you can implement and benefit from AI call centre software, contact us to find out how ‘SCAPE’ – an award-winning, feature-rich cloud call centre solution can help your organisation automate operational tasks, elevate customer interactions and maximise agent performance.
ipSCAPE enables organisations to create incredible customer experiences through a powerful, easy-to-use platform that provides access to the communication channels of today and the future.
AI technology is embedded within the application to make it accessible for all organisations to create customer journeys that better serve customers, increase sales and deliver operational efficiencies.
Organisations use ipSCAPE’s communication technology platform, SCAPE, to unlock growth by building personalised communication with customers at scale, through their channel of choice.