In an increasingly competitive environment, call centres need solutions that enable them to optimise time, improve contactability and increase agent productivity.

In this context, the predictive dialler has become a key tool for customer service and sales teams seeking outstanding customer experiences (CX), more engaged agents and increased sales.

WHAT IS A PREDICTIVE DIALLER?

A predictive dialler for call centres is a system designed to make calls automatically, meaning agents no longer need to dial numbers or search for contacts the system does it for them.

The dialler calls multiple numbers simultaneously and, when a person answers, connects the call directly to an available agent. This prevents agents from wasting time on unanswered or failed calls.

This predictive dialler software anticipates agent availability and adjusts the dialling pace based on response volumes and the average length of conversations. The goal is simple: more productive calls, less wasted time and better results.

5 BENEFITS OF A PREDICTIVE DIALLER FOR A CALL CENTRE

1. IMPROVED AGENT EFFICIENCY

Predictive diallers free agents from repetitive tasks such as searching contact lists or dialling numbers manually. The system:

• Identifies the best times to call.
• Predicts when an active call will end.
• Automatically launches the next call.

In addition, it can be integrated with Automatic Call Distribution (ACD) systems, allowing incoming and outgoing calls to be balanced according to workload. This significantly reduces idle time and improves overall team productivity.

2. SMARTER, MORE EFFECTIVE LEAD MANAGEMENT

When connected to customer management software, predictive diallers make it possible to keep all customer information organised and up to date. The system knows the best time to call and avoids dialling unsuitable numbers, such as fax lines, voicemail boxes or contacts that should not be called.

All calls are also automatically logged in the CRM (Customer Relationship Management system). This makes follow-up easier and provides real-time metrics and Key Performance Indicators (KPIs) to optimise sales and marketing actions.

3. SPEED UP SALES

Speaking to the right person at the right time is essential to closing a sale. A predictive dialler helps agents prioritise contacts with a higher likelihood of interest, avoiding unnecessary calls. Features such as:

• Call recording
• Automatic call-backs
• Task automation

Enable agents to focus on high-value conversations and close more deals in less time, significantly improving performance by up to 150%.

4. BETTER CUSTOMER SERVICE SATISFACTION

Predictive diallers can boost customer satisfaction by contacting customers at the right time and with the clear aim of offering products and services that genuinely interest them. Reaching customers with relevant offers at optimal times increases loyalty.

5. OPTIMISE RESOURCES

In addition to boosting sales, predictive dialers indirectly help reduce costs. Operators can make more calls in less time by reducing the time they spend on manual tasks.

By integrating directly with the CRM, there is no need for additional hardware or complex integrations, making the system simpler, more efficient and more cost-effective.

HOW A PREDICTIVE DIALLER IMPROVES KEY CALL CENTRE KPIs

Implementing a predictive dialler not only streamlines processes but also has a direct impact on the most important performance indicators:

• Contact rate: increases by avoiding failed calls and invalid numbers.
• Agent productivity: agents handle more live conversations per hour.
• Average Handling Time (AHT): reduced through task automation.
• Abandonment rate: lowered by matching call volume to real agent availability.
• Outbound campaign ROI: higher return on investment by making better use of resources and reaching the right customers.

Thanks to this data-driven approach, the predictive dialler becomes a key tool for managing call centres more efficiently and with a strong results focus.

DISCOVER THE ENREACH OUTBOUND AUTO DIALLER

Boost your business with our cloud-based business telephony software: no installations, no hardware. All you need is a device with an internet connection to create and manage your marketing campaigns, measure their effectiveness in real time, track results and grow your business by up to 400%. You can also seamlessly connect branches, departments and team members.

ITS MODULES AND TOOLS INCLUDE:

• Smart diallers
• Customer information
• Dashboards and analytics
• Real-time management
• Call administration
• Appointment scheduling
• Advanced customer management
• Agent organisation

La entrada Top 5 benefits of a predictive dialer for a call center se publicó primero en Enreach ES.

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.

As they’ve shared on social media, the evening will be full of surprises, which we can’t reveal in full just yet (stay tuned!), but we want our loyal readers to be the first to get a glimpse of some exclusive details.

The celebration will bring together around 150 guests, including members and event sponsors. Representing Enreach will be Alfred Nesweda, our CEO, Carlos Jiménez, our CCO and Luís A. González, our Head of CCaaS Sales.

The event will take place at WPP La Matriz, a campus that has established itself as Madrid’s creative hub. With an impressive 35,000 square metres of space, it’s the perfect setting to gather leading contact centre professionals.

Among the attendees, we are delighted to highlight the presence of two industry giants, Emergia and Intelcia, partners who will undoubtedly make this an event to remember.

Of course, the evening will be a first class culinary experience. There will be no shortage of tasting stands and, of course, the Mojito Corner, sponsored by Enreach… which promises to be the life of the party!

We’d like to thank the entire CEX Association team for this fantastic opportunity, with special mention to Iñigo Arribalzaga, the association’s president, Ana Buxó, its secretary general, and Montse Bonastre, its communications manager.

Stay tuned to our social media to make sure you don’t miss a moment of this magical evening!

La entrada Celebrating the 35th anniversary of the Asociación CEX se publicó primero en Enreach ES.

Speech Analytics, or assessing the customer service we are providing at any given moment, can be automatedthanks to artificial intelligence for the contact centre.

This technology is capable of analysing millions of pieces of data, classifying them and presenting an assessment in a matter of seconds, which means we can evaluate every single conversation that has taken place with just one query.

The four steps we need to follow to get the best results are:

1. DEFINING GOALS AND METRICS

First, we need to decide which elements of the conversation we want the bot to consider; for example, politeness, problem-solving skills, protocol adherence, etc.

Once we know what we want to measure, we need to establish metrics for each aspect, such as using a 0-10 rating or qualitative analysis.

2. ACQUIRING A BOT

To achieve high Speech Analytics, the bot must be able to generate summaries. This means we need generative AI with an NLP (Natural Language Processing) model to process the language and evaluate the content.

Important! If we want to monitor the calls in our contact centre, we also need to ensure that the bot is able to transcribe speech to text, which means it should include an ASR (automatic speech recognition) model.

3. ACQUIRING POWER BI

This tool, developed by Microsoft, allows us to have customised charts with the information that the AI extracts from all conversations, as well as tables that record the analysis and summary of each call.

4. DEVELOPING THE WORKFLOW

Once we’ve got the bot and Power BI in place, we need to create the workflow that the AI will follow to collect, analyse and send the information so that it’s synchronised within Power BI.

For example, if we want the bot to provide an assessment of a call that includes a summary, the agent’s courtesy rating, and the original audio of the call, we need to create the following workflow:

Step 1 – User request

The process begins when we ask: “Which agent and which call?

Step 2 – Call identification

The bot searches the database for the specific call using the information we have provided (agent name, date and time of the call, or any other unique identifier).

Step 3 – Audio transcription

Once it has found the audio file, it will transcribe the file and convert it to text.

Step 4 – Conversation analysis and summary

The bot will analyse the conversation to assess the aspects we defined in the first step.

If one of the aspects is ‘agent courtesy’, the model will look for indicators of courtesy in the conversation, such as the use of polite language, respectful tone, etc.

It will then assign ratings or tags to the specific aspects according to the metrics we have defined (for example, a score from 1 to 10).

To create a summary of the conversation, it will look for key points such as the reason for the call, the solution provided by the agent and any relevant issues.

Step 5 – Generating the full report IN POWER BI

The bot will compile the transcript, summary and scores and send them to Power BI, and the tool will sync the information every hour.

4. CONFIGURING THE APIs

Once the process is defined, there are two things to consider. Firstly, if we are using a third party tool for transcription and analysis, we need to ensure that the API works with the bot.

We also need to configure the API to ensure that the bot and Power BI are integrated and can automate report generation.

FINAL THOUGHTS

After following these steps, our bot will be ready to provide us with scores for every agent and every call in our contact centre.

All we need to do now is test and tune the model, deploy the system and, as always, monitor its performance.

Of course, we’ll also need to ensure internally that staff know how to use the bot, and technically that the AI meets privacy and security regulations to comply with GDPR.

If this process is too complex for your team or you don’t have someone with the skills to set up a bot, don’t hesitate to contact our technical team to help.

WANT TO OPTIMISE YOUR CONTACT CENTRE MONITORING?

La entrada How to use AI to monitor conversations in the contact centre se publicó primero en Enreach ES.

We had the pleasure of interviewing Jorge García, our Product Director, for several articles on artificial intelligence. During one of those informal meetings where we were discussing potential use cases in the contact centre sector, he told us:

“The philosophy behind self-service should be nothing more than automating customer service without losing the quality of experience you would get when talking to an agent.”

It’s true. The word “self-service” can have a certain negative connotation because it evokes a scenario where the customer is alone in the face of danger.

For example, we call the checkout machines in supermarkets self-service, but the machine does not help the consumer to scan the products, the consumer scans them alone.

So when we talk about an AI-powered chatbot that serves users who come to the website and provides answersto their questions or redirects them to the best available agent, we are talking about a system that automates responses.

We have been stressing this a lot lately, but we think it is very important to remind those companies that are thinking of investing in this technology that if it is not applied with certain criteria, the bot can end up truncating the customer experience.

WHAT ARE THE KEYS TO MAINTAINING QUALITY WHEN AUTOMATING RESPONSES?

1. PROCESS SIMPLE AND REPETITIVE ENQUIRIES

The first thing we can start automating are FAQs. Frequently Asked Questions are those that come up all the time, either before buying a product/service or after.

One of the questions a telecommunications company could automate would be “Why has my phone bill gone up this month?”.

If we connect the AI to our customer service agent, the bot can access the customer’s bill, analyse the document and inform the customer of any additional charges.

2. TAKING THE CUSTOMER’S EMOTIONAL STATE INTO ACCOUNT

The AI that powers the chatbot not only understands the user’s request, but also has the ability to extract their emotions. As a result, it knows from the outset the severity of the incident and the emotional state of the customer.

The bot is not a human, so no matter how much we train it to deal with serious problems, it will always lack emotional intelligence.

So if the bot is talking to a customer who has a power cut at home, for example, we need to train the AI to transfer the conversation to an agent.

3. TRANSFER THE CONVERSATION TO THE AGENT WHEN THE USER REQUESTS IT

There is nothing more frustrating for a user than talking to a bot when they want to talk to an agent. So it’s always a good idea to give the user instructions on how to get in touch with an agent.

In addition, it will soon be illegal to offer customer service based on voicemail or bots that do not allow you to speak to an operator. When the new Spanish customer service law comes into force, companies that do not comply will be fined up to €100,000.

4. AVOID BOT HALLUCINATIONS AT ALL COSTS

We don’t want our bot to give a customer the wrong answer. So we need to learn how to maintain the knowledge bases properly.

When we create a knowledge article, we must avoid explaining multiple processes in the same document.

WANT TO ADD A CHATBOT TO YOUR BUSINESS?

La entrada How not to lose quality when using a chatbot to automate responses se publicó primero en Enreach ES.

Yes, artificial intelligence enhances our customers’ experience by providing immediate responses. In fact, 68% of consumers cite this as their favourite feature, according to Userlike.

“68% of consumers cite this as their favourite feature”.

Userlike

However, a good experience can turn into a nightmare if the chatbot isn’t programmed correctly.

Here are four mistakes we see on some websites and how to fix them.

1. POORLY STRUCTURED FAQS

With a conversational AI chatbot, we’re obliged to create a menu of options (similar to a written IVR menu) for users to select the most relevant question.

But what if there isn’t a suitable option, or worse still, there’s no place to ask an open-ended question? This hampers the customer experience.

The philosophy behind self-service is to automate customer service without sacrificing the quality of the agent-assisted experience.

If we don’t embrace this premise, we’ll create a bot that won’t benefit the user and will result in a flood of phone complaints.

SOLUTION 1: OFFER A VARIETY OF FAQS

Especially at the beginning, when you are unsure of which FAQs to offer, we recommend offering a range of options, from pricing and product information to job applications or demos. Once the bot is up and running, it is important to continually improve these FAQs.

Using the bot’s configuration panel, you can track how many queries each topic receives and replace those that have no queries within a month.

SOLUTION 2: IMPLEMENT A HYBRID CHATBOT

Another approach is to enable a hybrid chatbot that combines a conversational AI tree menu with open-ended, generative AI queries. This reduces user frustration when they can’t ask for what they want.

While generative AI can be creative and susceptible to trolling, it is important to limit it to specific knowledge bases and test it before activating it on our website.

This option is particularly attractive for contact centres, which can use open-ended questions to incorporate the most common ones into FAQs.

2. INABILITY TO SPEAK TO AN AGENT

Customers who contact a chatbot are generally looking for a quick, out-of-hours response. However, some may have more complex queries and prefer not to call.

“The customer is always right” is a mantra when dealing with the public. Even if phone channels are reserved for incidents, if a user contacts the chatbot with a serious problem, it is necessary to allow the chatbot to transfer the request to an agent.

TRAINING THE BOT PROPERLY

We train our generative AI to automatically transfer the chat to an agent if it doesn’t understand the nature of the query, without the customer explicitly requesting it.

Firstly, because with the new Spanish Customer Service Act, we must always offer human support as an alternative to chatbots, or face fines of up to £100,000.

And secondly, it significantly improves consumer readiness: according to Simplr, 80% of consumers are more likely to engage with a chatbot if they know the conversation will be transferred to an agent.

“80% of consumers are more likely to engage with a chatbot if they know the conversation will be transferred to an agent”.

Simplr

3. NOT ASKING FOR FEEDBACK

If we’ve recently activated the chatbot on our website, we’re missing a significant opportunity to measure customer satisfaction by not requesting feedback after each interaction.

The AI can analyse and identify user sentiment during conversations, and send us a rating for each one. However, it’s also beneficial to contrast the bot’s automated assessment with direct user feedback.

Consumers like to be heard, so while we can measure their sentiments independently, it is always valuable to involve them in the bot’s improvement process.

4. 4. ARTIFICIAL INTELLIGENCE HALLUCINATIONS

AI hallucinations occur when the bot confidently gives a wrong answer because it thinks it is the right answer.The purpose of AI in customer service is to free agents from routine queries, not to give us headaches.

To avoid this, we recommend that knowledge bases are well structured. This means avoiding mixing concepts in the same article.

For example, if a document explains how to activate a service, don’t include the steps to deactivate it.

READY TO IMPLEMENT A CHATBOT FOR YOUR BUSINESS?

La entrada 4 common chatbot implementation mistakes and how to avoid them se publicó primero en Enreach ES.

After evaluating all the available entries, we decided to submit our applications for “Best Automation and Robotisation Project” with EVA and “Best Cloud Computing Project”, showcasing our Omnichannel Contact Centre.

The good news filled us with joy! So we travelled to Madrid, our second home, to enjoy an evening surrounded by colleagues, friends and outstanding professionals in the industry.

After the presentation by Lourdes Álvarez, CEO of Peldaño, Alfred Nesweda, our CEO, and Carlos Jiménez, our CCO, took to the stage to receive the two awards, which undoubtedly recognise our hard work and dedication to the customer experience.

We recently launched a portfolio that covers all the solutions businesses need to communicate internally and externally. These awards confirm our leading position as a provider of all-in-one solutions that combine contact centre software, collaboration platform, fixed and mobile telephony, business numbering and artificial intelligence.

EVA: THE AI FOR CUSTOMER SERVICE

Our artificial intelligence speaks all languages and handles calls, chats, WhatsApps, SMS, emails and social media.

It excels at increasing service levels, reducing waiting times, improving the customer and agent experience, better allocating resources and increasing efficiency.

To date, EVA has successfully resolved more than 50% of requests for one of Europe’s leading airlines, or 150,000 requests out of a total of 300,000, without human intervention.

In addition to doubling agent productivity, the company has reduced costs by 50% and increased customer satisfaction by 60%.

And this is just one of many examples. Explore other automations designed for all customer service teams.

OMNICHANNEL CONTACT CENTRE

Our advanced customer service software allows agents to manage all communication channels from a single platform: calls, chat, WhatsApp, email, Click&Talk and SMS.

Supervisors, meanwhile, have full control over lines, queues and agents, and can monitor service levels from a wallboard and real-time statistics panel.

Its intuitive interface, integration with CRMs, ERPs and ticketing systems, automated call distribution and artificial intelligence capabilities take customer service to new heights.

In addition, the use of agile methodology allows us to deliver bi-monthly updates based on customer feedback, with our innovation and development team customising the tool to meet customer requirements.

THANKS AND ACKNOWLEDGEMENTS

First and foremost, we would like to congratulate our team of 1,000 people who work tirelessly and passionately, and thank our customers and partners for the trust they have placed in us, some for over twenty-five years.

We would also like to thank the members of the Platinum Customer Experience Awards Jury and the entire Peldaño team, especially María Muñoz, Contact Centre Hub Director, and Mario Martelo, Communications Consultant .

WANT TO BE OUR NEXT SUCCESS STORY?

La entrada We won two awards at the Platinum Customer Experience Awards se publicó primero en Enreach ES.

Generative Artificial Intelligence, such as ChatGPT, is the best ally for customer service. Not only is it known for its ability to generate personalised responses, but it also doesn’t need a content tree to work, which makes it easier to implement.

Both qualities stem from its ability to learn and reason independently, taking into account the context of the conversation and the previous interaction history with other users.

ChatGPT for customer service has hundreds of applications. In this article, we explain the most common ones used by our customers to automate tasks, gather more information and ultimately be more effective with customers.

6 USE CASES FOR CHATGPT IN A CONTACT CENTRE

1. CHATGPT TO SUMMARISE A CUSTOMER INTERACTIO

AI is known for its ability to analyse large amounts of data and extract behavioural patterns, so we can use it to summarise any type of interaction (emails, phone calls, video calls and chats).

Once the agent has finished the conversation, we can use ChatGPT to process the tone of voice, keywords and the evolution of the dialogue and generate a summary.

2. AUTOMATIC CATEGORISATION OF A CONVERSATION WITH CHATGPT

Another administrative task that can be delegated to artificial intelligence for customer service is categorisation. Not only do we free agents from a routine task where they don’t add value, but we can also standardise a specific tagging protocol.

For example, if ChatGPT detects that a user has revealed their religious orientation in a conversation, it can tag the conversation so that the supervisor knows to remove sensitive information that should not be stored.

3. CHATGPT TO EVALUATE AGENTS

At the end of the conversation, we can also use ChatGPT to generate a report on the agent’s performance. This will allow us to evaluate all conversations, create more objective reports and provide written evidence.

When building our generative AI, we should specify the particular aspects we want it to analyse, be it the agent’s problem solving skills, the way they present themselves, their tone of voice, etc.

4. USING CHATGPT TO TRAIN CALL CENTRE AGENTS

Just as we use ChatGPT on a personal level to search the Internet for us, we can also create an AI that is fed only with internal company information (manuals, instructions, return policies, etc.).

To make agents more autonomous and faster at resolving queries, they can ask the bot a question and, after consulting the knowledge base, it will provide a concise and immediate answer.

5. CHATGPT AS A SUPERVISOR TO PROACTIVELY HELP AGENTS

ChatGPT can also provide proactive assistance to agents by eliminating the need for manual information searches. Like a ubiquitous entity, it integrates with contact centre software, analysing nuances and helping each agent in a personalised way.

It can even suggest text to speed up an email response, detect and correct spelling mistakes and indicate when to offer a discount, based on the history of interactions.

6. PROACTIVELY HELP CUSTOMERS WITH CHAT

Anticipating customers’ problems before they need to contact you is key to delivering a great customer experience.

In the automotive sector, one brand created a bot that automatically scheduled a service appointment every time the vehicle displayed an oil change warning.

7. CHATBOT FOR AUTOMATIC PERSONALISED RESPONSES

Yes, generative AI is known for its great ability to generate personalised responses because, as mentioned above, it “gets to know” the user through previous interactions with other consumers.

Recently, we analysed several success stories in the retail sector and showed how some brands could use a chatbot with ChatGPT to offer personal shopper services to users visiting their website.

HOW TO USE CHATGPT TO SERVE YOUR CUSTOMERS

To use ChatGPT in your contact centre, you need to hire a virtual customer service assistant that integrates with ChatGPT, such as EVA (Enreach Virtual Assistant). This AI assistant can be used on all your channels, whether phone or written (chat, email, WhatsApp, etc.) and can be more easily connected to third party systems.

Discover all you can do with EVA, the customer service AI integrated with ChatGPT.

La entrada How to use ChatGPT for customer service se publicó primero en Enreach ES.

A cloud contact centre is a customer service solution that allows us to receive and send calls and messages via digital channels (such as chat, WhatsApp and email) over the internet. Because it’s hosted in the cloud, we don’t need physical servers or a switchboard, nor do we need to worry about maintaining and updating them.

The transition from on-premises to the cloud in Spain was gradual until the arrival of the COVID-19 pandemic, when more than three billion Spaniards worked from home. The need to manage services and teams remotelyforced many call centres to migrate to the cloud.

BENEFITS OF THE CLOUD CONTACT CENTRE

1. GREATER ACCESSIBILITY

One of the main advantages is that we can work from anywhere in the world, as long as we have an Internet connection, a computer and headphones.

2. MORE SCALABILITY

With less hardware, we can increase headcount during peak service periods or expand our business to other countries without having to buy more phone terminals.

3. LESS MAINTENANCE

Our provider takes care of software maintenance and updates, so we don’t need to employ a technical team for these processes.

4. LOWER RUNNING COSTS

In addition to not having to invest in hardware or pay for licences, the most common model for cloud-based services is pay-as-you-go, so we can only subscribe to the features we need.

5. MORE INTEGRATIONS

Speaking of the operational level, cloud contact centres offer APIs and integration tools that make it easy to connect to other existing systems, such as a customer relationship management (CRM) system.

6. MORE SECURITY

Contrary to popular belief, data is much more vulnerable on a company’s local server than in a cloud-hosted data centre. These providers are subject to very strict GDPR or HIPAA regulations and have the highest security infrastructures.

7. FIND OUT MORE

The vast majority of customer service software providers have real-time service status information, allowing us to make immediate adjustments to meet SLAs and make informed decisions at a brand level.

WANT TO MIGRATE YOUR ON-PREMISES CONTACT CENTRE TO THE CLOUD?

We have helped many contact centres go digital over our 20 years in the industry, so if you are unsure about how to migrate your services to the cloud, do not hesitate to contact our team of experts.

La entrada What is a cloud contact centre and what are its benefits? se publicó primero en Enreach ES.