Artificial intelligence (AI) developed for customer service is not intended to replace agents, but to complement them. The emotional intelligence of agents combined with the automation provided by AI is the perfect combination to deliver a flawless customer experience (CX).

But its power does not end there. This technology also has a positive impact on the agent experience (AX), freeing them from managing simple enquiries and performing repetitive tasks where they do not add value.

Here are ten use cases that demonstrate the benefits of integrating AI to help agents be faster, more efficient and work on their continuous improvement.

1. INTENTIONAL QUALIFICATION

Bots are ready to ask an open-ended question like “How can I help you?”, interpret the customer’s response in the moment, and decidewhether to offer self-service (if within their capabilities) or transfer the conversation to the most qualified agent to handle the request.

As with IVR menus, you can use them to identify the user’s intention and intent and create transfer rules that take into account agent skills.

Unlike IVR, conversational and/or generative AI bots do not require you to configure the conversation diagram per channel and provide a better customer experience by understanding the customer’s query first.

2. USER IDENTIFICATION

Another task a bot can do before transferring the conversation to an agent is to identify the person it is talking to.

By querying the CRM, ERP or ticketing tool, it can search the database for the ID card, phone number or any other identifying information the user has provided.

This way, when the agent receives the call or chat, they can address the customer by name and quickly check their call/message history and customer record.

3. CONVERSATION SUMMARY WITH AI

When the customer indicates they want to speak to an agent, or the bot has determined it’s best to transfer the conversation to an operator, the agent receives the call or chat along with a summary of the previous conversation.

In addition to a transcript of the conversation and a record of all actions taken by the bot, the summary of the conversation identifies keywords and the customer’s sentiment.

With this information in advance, the agent can resolve the customer’s query more quickly and efficiently, because they know exactly what the customer needs, what the bot wasn’t able to provide, and what tone to use depending on the customer’s emotional state.

For example, if the bot has detected that a customer is angry because they have a problem with their phone line, the agent will know all this information before answering the call and will be much more effective in their verbal communication and problem solving.

4. RESOLVING COMMON QUERIES

According to a recent study we conducted, bots can handle up to 80% of simple queries in a contact centre.

Whether answering FAQs about a product or service, resolving a technical issue found in a user manual, resetting a password or recommending a credit line, bots free agents from these types of calls or messages, giving them more time to handle inquiries that require emotional intelligence or to assist those customers with special needs.

5. SENDING DOCUMENTS

In addition to resolving simple queries, bots can also provide self-service by sending documents to the customer, such as invoices, contracts, forms, etc.

Whether verbal or written, the bot can instantly deliver the document the customer needs through any platform.

For example, if a customer calls the call centre and asks for their latest electricity bill, the bot can send it via the customer’s preferred channel: WhatsApp, SMS or email.

6. TICKET GENERATION

As part of self-service, bots can also generate a ticket detailing the customer’s problem. By gathering all the relevant information from the conversation, they can create a new ticket, fill it in, and send the customer the incident tracking number.

Especially for queries that cannot be resolved in the first instance, bots can handle this part of the process, reducing human error and freeing agents from repetitive tasks.

7. INSTANT TRANSLATION

As well as being omnichannel, Artificial Intelligence is multilingual, meaning it speaks and understands all languages. This feature opens up a world of possibilities for contact centres, not only to better deal with requests that are not in our native language, but also to provide service in any language.

Whether it is a voice or chat conversation, we can ask the bot to transcribe the customer’s answers in the language we want, and also respond to the customer in their own language.

This functionality is ideal for when we have a spike in Spanish calls in the queue, as we can redirect these calls to agents with basic knowledge and have them assisted by the bot to help customers more smoothly and professionally.

8. KNOWLEDGE BASE

In addition to assisting during a call as a translator, the bot can also help agents when they have a question about a product/service or a clause in a contract.

If we share all our documentation with the AI: manuals, legal documents, blog posts, use cases, etc., we will end up with an internal ChatGPT that is knowledgeable about all our processes and products/services.

This will be the great ally of the agents, because if they don’t know how to answer a customer’s question, they can ask the internal AI Agent, and if it’s in the documentation we’ve provided, it can answer it.

This functionality not only avoids prolonging the conversation, but also allows any agent to provide support on a topic they are not an expert in.

9. ACW OPTIMISATION

The After Call Work (ACW), refers to all the tasks that agents must complete after each interaction before moving on to the next customer.

Artificial Intelligence can speed up this process by creating a real-time transcript of the conversation, analysing customer satisfaction by highlighting keywords that serve as typification, and linking this data to the details of the conversation.

The ability to automate AWC time as much as possible is essential to increasing agent efficiency.

10. AGENT EVALUATION

AI also has Speech Analytics capabilities, which means it can evaluate the performance of agents. This data helps contact centre managers to identify each agent’s areas for improvement and work on strengthening them.

We can train AI to generate a report after each interaction that includes: the ID number of the interaction, a title, a summary and, for example, an assessment of the agent’s presentation, friendliness and effectiveness.

This functionality contributes to the continuous improvement of agents and therefore to their speed.

FINAL THOUGHTS

As we have seen from these examples, AI provides automation across the entire customer service cycle: from the tasks that precede the interaction to the assistance it provides during and after the conversation.

Currently, there is no other technology that can optimise so many processes at once, taking into account both the customer and agent experience.

Want to meet the artificial intelligence that will revolutionise your customer service? Call us on +34 900 670 750 or fill in this form.

La entrada 10 examples of AI automation to help agents work faster se publicó primero en Enreach ES.

In fact, research shows that 35% of businesses fear that AI could make mistakes that negatively impact the customer experience (CX).

Here’s the uncomfortable truth: AI isn’t perfect. But then again, are humans? Just as you trust your best agents, knowing that they might occasionally make a mistake, AI works on the same principle. The mistakes it makes aren’t due to its nature, but rather to unforeseen scenarios or a lack of continuous improvement.

However, AI has one undeniable advantage over humans: it’s far more consistent. It sticks to the guidelines you give it, it doesn’t get tired, it doesn’t go off script, it doesn’t improvise.

So the key question isn’t whether AI can make mistakes, but rather: “What can I do to make sure it doesn’t make mistakes that my best agents would never make?” Read on, because we’ve got the answers you need.

3 KEYS TO GETTING AI RIGHT

1. KEEP YOUR KNOWLEDGE BASE ORGANISED AND UP-TO-DATE

The challenge:

A bot that relies on disorganised or out-of-date information will not only provide incorrect answers, but may even “hallucinate” by making up details that don’t exist.

How to fix it:

• Develop a clear strategy outlining who is responsible for keeping the knowledge base up to date and how often it should be reviewed.
  Organise your information by separating similar processes, such as the steps for subscribing to and unsubscribing from a service, to avoid the bot mixing things up and confusing customers.
  Use an AI solution that flags conversations by satisfaction level, and assign someone from your team to review the bot’s responses in interactions flagged as “unsatisfactory”.

2. TRAIN YOUR BOT TO HANDLE MALICIOUS QUERIES

The challenge:

A bot that isn’t prepared to recognise requests that have nothing to do with your business, or attempts by hackers to exploit it for free services or products, puts your brand at risk.

How to fix it:

• Configure the bot to respond only within its area of knowledge. Irrelevant queries should be redirected to a human agent or met with clear responses such as: “Sorry, I can’t help with that.”
  Protect your brand by limiting the bot’s capabilities: don’t allow it to process payments, close sales or access sensitive data without supervision.
  Implement AI tools that label conversations by query type. Regularly review interactions in the “other” category to monitor how the bot handles unknown topics.

3. USE A BOT THAT UNDERSTANDS EMOTIONS

The challenge:

A bot that can’t detect a customer’s emotional tone could escalate a tense situation or mismanage a complex request, ultimately damaging the CX.

How to fix it:

• Make sure your bot uses natural language processing (NLP) algorithms to detect emotions such as frustration, urgency, or dissatisfaction in customer messages.
  Train your bot to distinguish between simple queries, such as FAQs, and complex issues that require human attention.
  Design a clear process for the bot to automatically escalate emotional or critical queries to a rep, letting the customer know that a specialist will be handling their case.

IS AI READY TO REPRESENT YOUR BRAND?

The answer is yes – but only if you take the time to implement it properly and focus on continuous improvement.

Even generic AI solutions marketed as “easy to implement” require time and effort. It’s important to define the bot’s purpose from the outset, tailor its tone of voice to reflect your brand identity, and test it thoroughly with malicious queries before deploying it on your channels.

This initial phase is essential to correct up to 90% of the bot’s potential errors. Bear in mind, however, that the remaining 10% can’t be identified and resolved until the system is live, as it’s simply impossible to predict every future scenario.

Remember, well-configured AI can reduce errors by 40%, but poorly implemented AI can damage not only your reputation, but also consumer trust in the technology as a whole.

So if you decide to invest in a bot, make sure you do it right. The AI you choose and how you manage it will reflect your commitment to your business, your customers and the future of technology.

READY TO TALK AI?

La entrada 3 tips for implementing AI in customer service without compromising CX se publicó primero en Enreach ES.

The contact centre industry faces a significant challenge: how to train new agents quickly and effectively so that they can deliver quality service from day one. 

Typically, the training period is very short, and agents begin handling customer interactions without fully understanding all the concepts, often relying heavily on the constant supervision of a colleague or supervisor. 

The cost of a key team member taking time out of their day to help a new colleague is quite high. However, Artificial Intelligence for contact centres can take on this role and even tailor the process to each individual. 

Here are three use cases for automating the training and support of new agents: 

1. CREATE A BOT TO TRACK PROGRESS

By breaking down all the documentation that agents need to learn into different sections, we can create a bot that scores them once they’ve completed each module. By shortening the training time, agents are less likely to forget what they’ve learned. 

At this stage, the AI doesn’t just act as an examiner; it can also identify the format in which the agent learns best and personalise the learning process, for example by providing more video rather than text. 

2. CREATE A BOT FOR INTERACTIVE SIMULATIONS

Once new agents have read all the documentation, we can develop a bot with a simulator to allow them to practice real cases in a controlled environment. 

By feeding the bot historical call data from the contact centre, it can mimic a real customer and challenge the agent. 

After each simulation, the AI can also provide real-time feedback and even generate a report for the supervisor, ensuring they are kept informed of the agent’s progress.

3. CREATE A BOT FOR REAL-TIME GUIDANCE

When the agent starts handling real customer interactions, we can implement a bot to monitor their responses during calls. If they make a mistake, the bot can immediately suggest the correct response. 

In this scenario, AI acts as a support tool for all agents, but for newcomers it provides an extra layer of confidence, taking the pressure off them to deliver a great customer experience. 

AI IN THE CONTACT CENTRE IS NOT HERE TO REPLACE AGENTS

The foundation of customer service is people, and that should never be lost. In an ideal world, we would have the resources for the best agents to personally mentor new recruits, but this isn’t always possible. 

At first glance, having a bot accompany new team members may seem impersonal, but it’s actually quite the opposite. By involving agents and supervisors in the creation of the bot, we can give the AI a human touch, using the same tone that a colleague would. 

READY TO TRANSFORM YOUR AGENT TRAINING PROCESS?

La entrada 3 AI automations for agent training se publicó primero en Enreach ES.

AI in customer service has many facets, and one of them is using AI Agents to help team supervisors or managers train and support agents on a daily basis, whether they are new to the team or have been with it for years.

Keeping the department well trained will always help to improve their performance, as it is impossible to provide the best customer experience without the relevant knowledge, which can result in the user being put on hold to seek information.

Perhaps the most important aspect for the industry is improving agent engagement. It’s no secret that the contact centre faces a significant talent retention challenge, as the constant interaction with customers takes a lot of energy.

Therefore, providing agents with a tool that can instantly resolve all their queries is essential to avoid the stress and tension of not being able to address a customer’s concern, thereby contributing to their well-being.

4 USE CASES OF AI FOR AGENT TRAINING

1. AI AGENT AS AN INTERNAL KNOWLEDGE BASE

Imagine a ChatGPT for internal use, integrated into the call centre programme and ready to handle queries.

Both new agents and those handling queries outside their area of expertise can quickly access procedures,policies, product information or solutions to recurring problems during calls or messages.

This helps to broaden perspectives and share knowledge across the team, eliminating information silos.

2. AI AGENT AS A CUSTOMER INTERACTION SIMULATOR

In a completely private environment, a simulator can be programmed with a AI Agent to emulate customers, allowing agents to practice their responses.

The AI Agent can also evaluate agents, highlighting areas for improvement and acknowledging successes, thereby supporting their training process.

3. PROACTIVE INTERVENTION AI AGENT

Similar to copilots in search engines or CRMs, contact centre AI vendors are developing proactive AI Agents that suggest responses or provide tips during conversations.

These AI Agents can suggest next steps or offer solutions to problems.

By constantly analysing interactions and evaluating them against pre-defined parameters, they proactively offer suggestions that agents can choose to apply.

4. SPEECH ANALYTICS AS AI AGENTS

Supervisors or managers can now evaluate all agent conversations.

The bot can be programmed to send reports on conversations categorised as negative experiences, summarise interactions, rate aspects such as empathy and problem-solving skills, and provide full transcripts if required.

Reviews can generate objective ratings from the AI, helping to provide evidence and quickly identify training needs for each agent.

INTERESTED IN INTEGRATING A AI AGENT INTO YOUR CUSTOMER SERVICE TEAM?

La entrada How to use an AI Agent to train call centre agents se publicó primero en Enreach ES.

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

AI Agents 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 AI Agent.

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. SPEECH ANALYTICS

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 AI Agent 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.

La entrada 8 of the most common AI automations used in customer service se publicó primero en Enreach ES.

THE IMPACT OF AI

The day began with a welcome from our CEO, Alfred Nesweda, who highlighted the importance of artificial intelligence in the sector, noting that there are more and more AI solutions for the contact centre.

“Every week I discover a new company offering AI solutions for the contact centre.”

Alfred Nesweda

Alfred Nesweda, CEO of Enreach ES, welcomes attendees to the CX Brunch by Enreach.

This technology, which is now gaining significant momentum, could become a new business model and “new economy” in the future, as it is expected to contribute $15.7 trillion to the US economy by 2023, according to PwC.

SPANISH LEGAL FRAMEWORK FOR AI

Our CEO then handed over to Daniel Vidal, a lawyer and legal director of Webpilots España, who began his presentation by explaining the nature of AI and its rapid development.

“The train is leaving, and those who don’t catch it now may not be able to get on at the next station.”

Daniel Vidal

After this metaphor, he moved on to the topic of AI regulation, making it clear that Spain is a global leader in the regulatory field, highlighting that a Royal Decree was issued as early as 2023 to oversee artificial intelligence on Spanish territory, long before the AI Act was approved at the European level last month.

Daniel Vidal, Legal Director of Webpilots España, during his presentation at Enreach’s CX Brunch.

Another piece of Spanish legislation that will regulate the use of AI in customer service is popularly known as the ‘3-Minute Law’, which, once passed, will, among other things, limit phone hold times to three minutes and prohibit the exclusive use of auto-attendants or conversational bots to assist consumers, among others.

As a result of users’ bad experiences when calling customer service and wanting to speak to an agent, or at least a more advanced bot that understands their queries, this bill is the perfect opportunity to adopt technological solutions that enable quality self-service while reducing waiting times to zero.

THE ROLE OF AI IN THE CONTACT CENTRE

The third and final presentation of the CX Brunch was a live demonstration of our virtual agent: EVA (Enreach Virtual Assistant).

Led by Marc Brunés, an AI specialist, and Jorge García, Product Director, they were able to demonstrate how our virtual assistant works and is configured through a user case.

Our AI solution for customer service was able to engage in a chat conversation with a fictional customer, recognise their problem, check the customer’s record in Salesforce, log the issue raised by the user and return the tracking number in a matter of seconds.

On the other side of the spectrum, Enreach’s virtual assistant is programmed to leave a note for the agent with the incident alert, the ticket and the history of the conversation it had with the customer.

On the left, Jorge García, Product Director, and on the right, Marc Brunés, AI Specialist, during the demonstration of Enreach AI.

EVA has been programmed to follow the steps that any other agent would take, but in a fully autonomous manner, freeing operators from tasks where they do not add value, and allowing them to focus on providing a more personalised and humanised service.

We have no doubt that consumers who still prefer human contact will appreciate being assisted by a person who takes the time to listen to them, while those looking for a quick solution will marvel at the efficiency and immediacy of the bot.

EAGER TO KNOW MORE?

Together with Webpilots España, we are preparing a whitepaper with the aim of sharing, free of charge, the main contents discussed during the two sessions of the CX Brunch.

Subscribe to the blog and you will be the first to receive our report on the latest trends in AI in the contact centre.

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La entrada Challenges of AI in customer service: Summary of the second CX Brunch se publicó primero en Enreach ES.

Images of the event by Ruth Llausí.

In partnership with Webpilots Spain, and with the support of Relación Cliente and the AEERC association, we brought together leading contact centre professionals to discuss the impact of Artificial Intelligence in the sector.

We invited Daniel Vidal, lawyer and Legal Director of Webpilots Spain, to speak to us about the main challengesthat contact centre operators must face when implementing this technology in their business.

His presentation was based on three main pillars: what is Artificial Intelligence, how is it applied in the contact centre and what are the legal issues involved in its implementation.

WHAT IS ARTIFICIAL INTELLIGENCE?

It’s clear that AI is everywhere, but do we know what it is? It is essentially a combination of techniques: Machine Learning, Deep Learning and Natural Language Processing.

It is mainly used to analyse large amounts of data, automate processes and generate content of all kinds.

HOW IS AI USED IN THE CONTACT CENTRE?

Artificial Intelligence applied to customer service is often used as a virtual agent.

Capable of handling any channel, verbal or written, in any language, and able to recognise the customer’s intent and purpose.

Once the conversation flow has been configured, the virtual agent is ready to recognise the customer’s needs and either offer self-service or transfer the conversation to a designated agent.

Virtual agents can also be used to assist agents during a conversation, either by generating suggested responses or by providing data to help resolve queries.

WHAT LEGAL ISSUES DOES AI RAISE?

This technology is crucial not only for optimising contact centre services, but also for meeting the legal requirements of the future Customer Service Spanish Law.

AI will therefore be our main ally in streamlining service processes, centralising ticket management, transcribing calls and being available 24/7.

However, it will be necessary to keep in mind that service companies will have to inform about AI processes in their general terms and conditions, according to the current and applicable European Digital Services Regulation, and take appropriate measures to comply with the GDPR.

La entrada We talked about AI in the contact centre: Recap of the first CX Brunch se publicó primero en Enreach ES.

Looking at the most popular questions we ask ChatGPT, we’ve realised that in our personal lives we use this new technology for almost everything. 

It’s almost anecdotal to discover that the vast majority of us ask it to tell us a joke, recommend TV series or help us with our maths homework.

The applications are so varied that they make us reflect on how much our lives have changed by having a chatbot ready to answer our questions 24 hours a day. 

While we’re using artificial intelligence in our personal lives to turn on light bulbs, we’re not there yet in the business world. 

This may be because there are still many unknowns to be resolved: the price, the level of data security and, above all, how to use it correctly to add value.

Artificial intelligence in contact centres has already taken its first steps with intelligent IVR menus: those that can connect us to customer service by simply saying “I want to unsubscribe”. 

But now AI is ready to go one step further.

We see our artificial intelligence as part of the customer service team. Broadly speaking, it takes on tasks where humans don’t add value. 

It also provides us with data that helps us to identify improvements to the content of our website or even a feature of our service. Seriously, we’re not exaggerating.

Without any programming knowledge, but with a good understanding of question structure, you can program a bot in less than thirty minutes to work wonders, as we’ll describe below.

CASE 1: MANAGING RESERVATIONS

If your customer service department spends 40% of its time managing reservations or product deliveries, you’ll love this use case.

You’ve probably heard a thousand times that these processes no longer need human intervention. 

Until now, there was no AI on the market that could successfully handle this task. Now things have changed.

The most advanced AI can identify the customer, check a reference number, show alternative dates and recordchanges in both written and voice channels. 

But it doesn’t stop there; you can also have it send the reservation/order update via SMS or email for written confirmation. 

As you can see, AI is not only answering queries during office hours, it is also querying databases and modifying records. Amazing!

CASE 2: GATHERING QUALITATIVE DATA

Contact centres typically work with quantitative data: how many calls were handled, how many users left a queue, how many seconds a call took… 

The only way to get qualitative information was to conduct satisfaction surveys after the call. We’re happy to use the past tense to say that artificial intelligence, while not a replacement for NPS or CSAT surveys, provides very valuable qualitative data on a daily basis.

If you’ve ever interacted with a bot, you’ll know that it usually starts by asking how it can help, and then presents a series of options to choose from. Every time a user selects one of these options, their choice is recorded in the statistics panel. 

This information is very useful for identifying the most common reasons for contact and acting accordingly – making changes to our website, improving a service functionality, etc.

CASE 3: BREAKING DOWN INFORMATION SILOS

In addition to managing reservations and collecting data, AI can also be used as an internal source of knowledge. 

Just as ChatGPT was trained to analyse and store millions of pieces of web data, there are chatbots for internal use that can be trained with product manuals, company presentations or legal documents.

Once it has all the knowledge it needs, employees can chat with it and ask any question, from product configuration to delivery times or contract clauses. 

Whether it’s for customer service or any other area, the internal ChatGPT streamlines the onboarding process and promotes a workspace where knowledge is accessible to everyone and there are no silos of information.

FINAL THOUGHTS

With a mission to put artificial intelligence in the hands of contact centres, we help millions of professionals integrate this technology into their daily lives. 

Tell us about the processes you want to streamline by calling +34 900 670 750 or using the chat below. Our team of experts will be happy to help.

La entrada 3 use cases of artificial intelligence in the contact centre se publicó primero en Enreach ES.

Customer service agents are the ones who deal directly with your customers: they listen when they have a problem, follow up on their issues and help them find solutions. Essentially, they are the public face of your brand. If they are demotivated or uncomfortable in their role, they will never be able to provide excellent service.

Considering that 61% of customers have switched brands after receiving poor customer service, looking after the agent experience should be part of your customer loyalty strategy.

“61% of customers have switched brands after receiving poor customer service.”

Microsoft

While financial compensation is a direct factor in motivating customer service reps, a good salary is useless if they don’t feel heard or valued, for example.

That’s why we’ve compiled seven best practices to help you motivate your customer service agents by investing in their long-term happiness.

7 WAYS TO MOTIVATE CUSTOMER SERVICE AGENTS

1. RECOGNISE AND ADDRESS EARLY SIGNS OF BURNOUT

You’ve probably heard the term “burnout” lately; it’s a phenomenon that affects millions of workers worldwide. According to Jeff Toister, an expert on the contact centre agent experience, 59% of agents are at risk of burnout.

“59% of agents are at risk of burnout.”

Jeff Toister

Excessive workloads and daily stress in the contact centre directly contribute to burnout. Poor attitude, failure to meet targets or repeated absenteeism are some of the ways in which this phenomenon manifests itself. 

If some of your reps are exhibiting these symptoms, it is time to take action. The reasons for agent burnout may be due to one specific factor or a combination of things, so it’s best for supervisors to talk to each team member personally.

If you notice widespread burnout, we recommend evaluating customer feedback. With a contact centre tool that can store an intervention history, you can review recent complaints and identify common issues.

2. RECOGNISE THEIR SKILLS AND TALENTS

Did you know that agents who use their skills during customer interactions are 8% more productive? This data from Gallup reveals something important: people feel fulfilled when they can use their talents and achieve results.

The best way to ensure reps are using their soft and hard skills is to have customer service software that enables skills-based routing.

By identifying each agent’s skills, advanced contact centre programs can route specific inquiries to the best available agent who can handle them more effectively.

3. ENSURE AGENTS HAVE THE RIGHT TOOLS

Agents should only have to worry about listening and resolving customer queries. If the programme they’re using doesn’t make this task easier, they won’t be able to remain productive. 

The most powerful technology currently supporting millions of contact centre agents is artificial intelligence. With the ability to automatically transcribe conversations, query the CRM to identify a customer, and solve common queries, AI multiplies agent productivity.

Having customer service software that incorporates new technologies such as AI allows agents to focus on more complex tasks, freeing them from mechanical and unproductive actions.

4. PROVIDE FEEDBACK TO AGENTS

Feedback is the most powerful and cost-effective tool contact centres can use to increase agent productivity. Both a sense of progress and recognition are key motivators in the workplace. 

There are two ways to create a feedback culture:

• Monthly: Schedule monthly follow-up meetings to gather agents’ opinions, identify potential shortcomings and set new goals.
• After each interaction: After every customer interaction, create a survey for customers to rate the agent who helped them.

Ongoing feedback not only prevents burnout, but also keeps the team motivated.

5. CREATE A POSITIVE WORKING ENVIRONMENT

Did you know that 83% of contact centre agents have at least one toxic colleague? Toister identifies toxic agents as dishonest individuals who deliberately provide poor service to customers or harass other team members.

“83% of contact centre agents have at least one toxic colleague”.

Jeff Toister

Recognising these behaviours and taking action is vital to creating a positive working environment. If agents are caught in a spiral of negativity, you’ll notice a drop in their productivity.

6. SUPPORT AGENTS DURING CALLS

Sometimes agents are faced with difficult customers or requests they can’t handle. That’s why it’s important to have customer service software that allows supervisors to monitor agents in real time. 

Supervisors can see how much time each agent is spending on a call and even connect live to provide guidance without the customer hearing it.

7. OUTLINE A CAREER PLAN FOR EACH AGENT

You’ve probably wondered whether it’s better to hire new talent or promote someone internally. Making this decision will be much easier if you work on a career plan for each agent. 

Remember that agents who move to positions of greater responsibility or change departments have a great deal of internal knowledge and culture that you want to preserve.

BOTTOM LINE

Turn agent burnout into motivation by continuously improving the contact centre. Establish a culture of recognition and feedback, eliminate potentially toxic agents, create personalised career plans, and above all, empower agents with software that makes their daily tasks easier.

Discover the real impact that advanced customer service software can have on agent productivity. Contact our team of experts on +34 900 670 750 or chat below.

La entrada 7 ways to motivate customer service reps se publicó primero en Enreach ES.

According to a recent study by Capgemini, 76% of customers who have interacted with AI have had a positive experience. And it’s no surprise! Access to information and speed of response are factors that already appeal to 64% of respondents to the consultancy’s survey.

“76% of customers who have interacted with AI have had a positive experience.”

These data, along with those presented below in this article, were the main topics we discussed at our first edition of the Enreach Congress last week.

Titled ‘AI Made Human: AI in Customer Service’, we kicked off the event to discuss revolutionary advances and trends in the technology that is changing the world: Artificial Intelligence.

Our CCO, Carlos Jiménez, one of the speakers, began his speech by saying that 2023 is the year of AI, and during his presentation he revealed some important data about the expansion and strategic importance of this technology.

For example, the latest Statista data announcing that the global AI market has already surpassed $500 billion, or the Deloitte report stating that companies can save up to 70% in costs thanks to Artificial Intelligence.

“Companies can save up to 70% in costs thanks to artificial intelligence.”

Finally, he also revealed to attendees that conversational AI in particular will reach $32.62 billion by 2030, according to Global Opportunity Analysis data.

It’s no coincidence that several analysts predict that of all the types of artificial intelligence available today, conversational intelligence will have the greatest future projection in the business sphere. Its ability to process natural language and voice recognition makes it the perfect technology to power chatbots and virtual assistants dedicated to customer service.

To put it to the test, we had a presentation by Marc Brunés, our AI specialist and product owner for omnichannel contact centres, who introduced a conversational AI called EVA. It is revolutionising customer service with features such as omnipresence, multilingual capability and customisable creativity.

Our latest measurements show that EVA has already resolved 52% of 200,000 cases out of 370,000 calls in internal training and customer service, and doubled the productivity of human agents by resolving 51% of 31,000 cases out of 60,000 calls.

“EVA has already resolved 52% of 200,000 cases out of 370,000 calls in internal training and customer service”.

By reducing the number of calls handled by agents and facilitating real-time transcription of conversations, EVA has contributed to 20% savings in contact centres, demonstrating its effectiveness in optimising business processes.

According to Alfred Nesewda, our CEO, “The many benefits of Artificial Intelligence, coupled with the widespread lack of knowledge in many organisations in the contact centre sector, were the reasons why we decided to address the topic of AI in this first edition of the Enreach Congress.

From the outset, this congress has had a clear purpose: to provide companies with a unique opportunity to learn from experts in the field of artificial intelligence and customer service, and to create a networking environment in which they can share their experiences and concerns.

La entrada 76% of customers who have interacted with AI have had a positive experience: conclusions from the first Enreach Congress se publicó primero en Enreach ES.