4 min
Level: Intermediate
Implementing automation systems in the contact centre is synonymous with improving service levels, reducing waiting times, improving both the customer and agent experience, better resource allocation and increased efficiency.
Using AI in the contact centre, in addition to all the above benefits, we can make strategic decisions based on data we couldn’t measure before, such as how many customers called us for ‘X’ reason, or how agents performed in each interaction.
The recent democratisation of AI means that the contact centre sector is still in a phase of discovery and testing, so today we’ll demonstrate its potential through eight use cases.
1. FAQ RESOLUTION
Chatbots can handle the most common customer queries. When training the bot to recognise these types of queries, we can either specify the answer it should give, or alternatively let it automatically generate one after reviewing manuals, web pages or conversation histories.
Note: The AI itself will help us identify and add new FAQs in the future.
Use case:
A customer visits our website to check the return policy. After not finding the section, instead of calling customer service, the user can access the online chat on our website and get instructions from the chatbot.
2. SELF-SERVICE
In addition to answering simple questions, bots can perform more complex tasks that may require accessing a database or sending documentation.
Use case:
A customer calls customer service to reschedule their doctor’s appointment, and our call bot qualifies their intent. After understanding the request, the bot identifies the user by asking for their ID, accesses the appointment system and suggests a new date and time. Once the new appointment is agreed, the AI records the change in the system.
3. TICKET MANAGEMENT
AI-powered bots can automate ticket creation and updates to reduce After Call Work (ACW).
If the bot recognises during the intent qualification that it can’t help the customer, it will transfer the call to the best available agent and simultaneously create a ticket in the system.
Note: If the customer calls to follow up on an incident that has already been registered, we can also train the bot to update the associated ticket.
Use case:
A customer calls the contact centre because they have no electricity at home and our call bot qualifies their intent. After identifying the customer, it accesses the ticketing system and creates a new ticket, filling in all the necessary fields.
4. QUALITY MONITORING
AI can also benefit contact centre supervisors or managers, as its ability to analyse a large amount of data can help them generate detailed reports to evaluate agents.
Use case:
The customer service manager can create a report for a team member detailing their performance based on service level, tone and efficiency.
5. FRICTION POINT ANALYSIS
Customer experience (CX) managers will also benefit from AI’s analytical capabilities. As the bot collects data after each interaction, it’s easy to see what friction points customers encounter when contacting customer service.
Use case:
An airline’s CX manager can quickly see how many people have called to complain about lost luggage.
6. CALL TRANSCRIPTION
This powerful technology can also transcribe all calls in real time. In addition to creating a document that separates the dialogue between the customer and the agent, we can also program the bot to summarise and/or label the conversation.
Use case:
An agent is talking to a customer; instead of taking notes, the agent can focus on solving the problem. Then they don’t have to typify the conversation and can move on to the next person in the queue.
7. AGENT SUPPORT
As well as freeing agents from many administrative tasks, AI can also be programmed to assist operators during customer interactions.
Whether it’s through an internal ChatGPT where they can type during a call to resolve a product/service query, or as a proactive bot that analyses the conversation in real time and suggests responses.
Use case:
A customer service agent is on the phone with a customer who has a technical problem. Instead of transferring the call to the technical department, the agent can enter the internal ChatGPT. The bot will check the manuals and provide an immediate answer.
8. EXPERIENCE PERSONALISATION
Generative AI can recommend products/services based on user responses. To do this, we need to feed the bot with our portfolio of products/services and their buyer personas.
Use case:
A user arrives at a bank’s website because they need to apply for a credit card. They turn to the chatbot to ask about the types of cards available and which one is best for them. The bot asks about their spending habits and recommends the most suitable card based on the answers.
FINAL THOUGHTS
There is still a lot of uncertainty about how artificial intelligence can be applied in the contact centre. Contrary to what many may think, this technology doesn’t have the ability to replace humans, but it can replicate the way we communicate and the methodology we use to perform administrative tasks.
AI solutions for customer service have a positive impact on many aspects that are vital to businesses, such as customer experience and, in recent years, agent experience.
So it’s no wonder that after implementation, our NPS increases, our cross-sales increase and our churn rate decreases.
Want to discover the power of Artificial Intelligence for your contact centre? Call us on +34 900 670 750 or fill in this form.
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