How to Make Your Call Centre 'Smarter' with AI

If you are a leader in the call centre industry, you might be curious about how artificial intelligence (AI) can help you take your business to the next level. AI is changing our landscape at pace, and it is not a magic wand that can fix all issues, but it can be a powerful ally that can help enhance performance, customer satisfaction, and employee engagement. As I am going deeper into the possibilities, I'm thinking about how I move this forward, so I am keen to share as I go. I think we all acknowledge that these next steps will require careful planning, execution, and evaluation - and I know I don't have all the answers. In this article, my aim is to provide some useful (I hope) steps to follow through this journey, based on my own experience and investigation.

Step 1: Set your goals and boundaries.

Before you embark on any AI project, you need to have a clear vision of what you want to achieve and why. What are the problems or opportunities that you want to tackle or solve for with AI? How will AI benefit your customers, employees, and business? How will you measure the success of your AI projects? These are some of the questions that you need to answer to set your goals and boundaries. You should also consider the feasibility, cost, and timeline of your AI project, and prioritise the most important and urgent ones.

Tip: Use the SMART framework to set your goals: Specific, Measurable, Achievable, Relevant, and Time-bound.

Step 2: Find and gather relevant data sets.

Data is king!

AI is fuelled by data, so you need to have access to high-quality and relevant data sets that can provide meaningful insights. Depending on your goals and boundaries, you might need to gather data from various sources, such as customer interactions, feedback, surveys, CRM, analytics, etc. You should also ensure that your data is clean, consistent, and compliant with privacy and security regulations. You might need to use data cleansing, integration, and anonymisation tools to prepare your data for AI.

Example: If you want to use AI to analyse the sentiment of your customers, you might need to collect data from voice recordings, chat transcripts, emails, social media, etc., and label them with positive, negative, or neutral sentiments.

Step 3: Select and implement the right AI solutions.

Once you have your data ready, you need to select and implement the “right” AI solutions that can help you achieve your goals and boundaries. There are many types of solutions available in the market, such as chatbots, voice assistants, sentiment analysis, Gen AI IVR, speech recognition, natural language processing, etc. You should evaluate the features, benefits, limitations, and compatibility of each solution, and select the ones that best suit your needs, the needs of your customers and budget. You might also need to customise or integrate the AI solutions with your existing systems and platforms, such as IVR, web, mobile, etc.

Example: If you want to use AI to improve your customer service, you might need to implement a chatbot that can handle common queries, a voice assistant that can provide personalised recommendations, and a sentiment analysis tool that can monitor customer satisfaction in real time with a AI co-pilot.

Step 4: Engage and train your stakeholders and staff.

Making your call centre smarter with AI is not only a technical process, but also a human one. You need to engage and train your stakeholders and staff to ensure that they understand, support, and adopt your AI initiatives. You should communicate the value proposition, expectations, and outcomes to your stakeholders, such as senior management, internal and external partners, team leads, front-line staff etc., and get their buy-in and feedback. You should also provide adequate training and guidance to staff, especially your front-line call centre agents, on how to use, interact, and collaborate with the AI, and how to handle any issues or queries that might arise from the customers or the AI itself.

Tip 1: Use the ADKAR model to facilitate change management: Awareness, Desire, Knowledge, Ability, and Reinforcement.

Tip 2: Evaluate your current position descriptions and reset these to be aligned with how these roles will change with AI.? Assess the current capability of your existing resources, understand any gaps and work to bridge these gaps with training.? This early work will also enable you to assess future recruitment and support you in identifying the skill sets for the new world you are creating, rather than the old world you are currently transforming.

Step 5: Monitor and evaluate your AI initiatives.

After you have deployed your AI initiatives into your call centre, you will need to monitor and evaluate their performance and impact. You should use the metrics and indicators that you defined in step 1 to measure the success of your AI project, such as customer satisfaction, retention, loyalty, revenue, cost, efficiency, productivity, etc. You should also collect and analyse the feedback and data from your customers, employees, and AI solutions, and identify the strengths, weaknesses, opportunities, and threats as it pertains to your original objectives. You should use this information to improve, optimise, or scale your AI initiatives, or to pivot or terminate them if necessary.

Implementing AI into your call centre, I believe will be a rewarding and challenging journey. It can help you enhance your customer experience, employee engagement, and business performance. However, it will also require careful planning, execution, and evaluation. Remember, AI is not a one-time project, so do not think of it as a set and forget, but a continuous process of learning and improvement. So, keep exploring, experimenting, and innovating with AI. I am keen to keep the conversation open, so please share your thoughts and personal experiences so we can all learn together.