Voice remains the channel of choice for consumers. Therefore, we need call centre software that can help us manage high call volumes without losing sight of the customer experience.

1. ADVANCED CALL DISTRIBUTOR

This feature allows us to automate the prioritisation of the most urgent calls and ensure that they are handled by our best agents.

Through a scoring system, we will assign a higher value to the queues we want to prioritise, and we will value the agent’s skills more highly in areas where they excel.

2. CALL WHISPERING

During the agent training process, this feature is vital as it allows supervisors to listen to a call in real time and provide guidance to the agent without the customer hearing it.

3. VOICE INTEGRATION WITH CRM

Voice integrations within CRM save us from having to switch between applications, allowing us to initiate, answer, record and transfer calls without leaving the customer management tool.

In addition, some integrations automate the display of the customer profile and, when the call is completed, automatically record the date, time and duration of the call, as well as details of the queue and the agent who handled it.

4. REAL-TIME TRANSCRIPTION

This feature allows us to have the telephone conversation in text format, separating the agent’s voice from the customer’s voice, thanks to artificial intelligence.

We can share these transcripts with customers who request them, and we can also quickly analyse them using AI.

5. CALL SUMMARY

Thanks to a ChatGPT bot, we can ask it to summarise each of the calls that have taken place in the contact centre.

We can even ask it to evaluate certain moments of a call, such as the greeting, and indicate whether the agent has satisfactorily resolved the customer’s query.

6. SENTIMENT ANALYSIS

Generative Artificial Intelligence also allows us to analyse the emotions felt by customers at the end of the call.

In this way, we can know the level of satisfaction of customers who called in the last week, last month or last few hours, without having to send out CSAT or NPS surveys.

FINAL THOUGHTS

The combination of traditional and new AI-based functionalities is essential to achieve operational results in terms of availability and continuous improvement of the customer experience.

What does your customer care team need? With over 20 years of contact centre experience, we are the perfect technology partner to help you achieve your goals.

We are committed to continuous improvement and have our own development software to create ad hocfunctionalities.

CONTACT US TO FIND OUT HOW WE CAN HELP YOU!

La entrada 6 must-have speech features for any call centre software 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.

With 523 votes in favour and 46 against, the regulation has been given the green light to come into force by mid-2026.

All that remains is for member states to approve the final text and for it to be published in the EU’s Official Journal.

ORIGIN OF THE ARTIFICIAL INTELLIGENCE LAW

The law has its origins in the European Commission’s 2021 proposal to create the first regulatory framework for AI.

Three years ago, the Commission proposed new rules and measures aimed at making Europe the global hub for trustworthy artificial intelligence.

These rules focused on categorising AI by risk level and proposing regulatory measures for each.

Following the provisional agreement in December, the Commission launched the GenAI4EU initiative, which aims to support start-ups and SMEs in adopting this technology.

And more recently, in February 2024, it was agreed to set up the European Committee on Artificial Intelligence, which will include a representative from each member state to oversee the implementation of the law in their country.

AIMS OF THE AI ACT

With all the pieces in place, this law has two very clear objectives:

• To ensure that artificial intelligence systems in the European Union are safe and respect the rights of citizens.
• To stimulate investment and innovation in AI in Europe.

KEY POINTS OF THE NEW ARTIFICIAL INTELLIGENCE LAW

As mentioned above, this regulation imposes obligations on providers and users based on the level of risk posed by AI.

1. LOW-RISK AI

Narrow AI, also known as weak AI, is AI designed to perform a single task perfectly.

It is the most widely used in Europe and, as it poses no risk, it can be freely used according to the law.

This category includes virtual assistants (Siri, Alexa, Cortana…), spam filters in emails, autonomous vehicles, etc.

2. LIMITED RISK AI

This AI, also known as AGI or strong AI, can perform any intellectual task that a human can do, but like any human, it doesn’t know everything.

The regulation stipulates that, while it does not pose a major threat to citizens, it must meet minimum transparency requirements to allow users to make informed decisions.

For example, when using AI systems such as chatbots, people must be aware that they are interacting with a bot and have the option to end the conversation at any time.

In addition, when using generative AI, such as ChatGPT, providers must state that the content is artificially generated and must incorporate specific models to prevent the generation of illegal content and respect copyright.

3. HIGH RISK AI

Thirdly, there is super-intelligent AI, or ASI, which surpasses human skills and abilities at any task. It is even thought to be able to think better and be more skilled than us.

Of course, the law indicates that this AI could endanger the safety and/or fundamental rights of consumers.

Therefore, it can only be put on the market if it respects fundamental rights and EU values, and it will be subject to greater scrutiny to ensure that it is used safely and responsibly.

Its use will be limited:

• Critical infrastructure such as transport systems, as it could endanger the lives and health of citizens.
• Education or training, such as examination marking or any process that determines a person’s career path.
• Product safety components, such as the use of AI in robotic surgery.
• Employment, workforce management and access to self-employment, such as resume review software.
• Essential public and private services, such as credit ratings that deny citizens credit.
• Law enforcement, which can interfere with people’s fundamental rights, such as the automation of visa application checks.
• Administration of justice and democratic processes, such as AI solutions to search for court decisions.

4. UNACCEPTABLE RISK AI

This type of AI is also known as the Singularity and has been featured in the vast majority of science fiction films.

It is no wonder that it is seen not only as a threat to human beings and fundamental rights, but also as undermining democracy, the rule of law and the environment.

That is why AI that is deemed to pose an “unacceptable risk” will be banned in the EU once the regulation comes into force.

This group includes all AI systems that perform “social scoring”, those that use subliminal techniques, those that exploit the vulnerabilities of certain groups of people, or those that recognise emotions.

FINAL THOUGHTS

Following the adoption of the world’s first law regulating artificial intelligence, we can foresee that this is only the beginning.

This technology, which is increasingly present in more and more aspects of our daily lives, needs regulations that provide security and, of course, encourage its use.

Are you using AI to serve your customers, or thinking about starting? Find out how you can use this technology to free your agents from tasks where they do not add value.

Get in touch with our team of experts by calling +34 900 670 750 or sending a message through our website chat. We look forward to helping you!

La entrada EU Artificial Intelligence Act se publicó primero en Enreach ES.

Most customer interactions now start digitally, with AI-powered bots or intelligent virtual assistants (IVAs) accounting for around 85% of these interactions, according to ZK Research. With the advent of generative AI, bots can handle even more complex transactions.

Despite these advances, there are situations where generative AI falls short, particularly when customers are unable to resolve their queries effectively. This underscores the importance of human involvement in customer service, especially when it comes to complex issues and problem solving.

THE IMPACT OF AI ON CUSTOMER EXPERIENCE

The customer experience is now the most important brand differentiator, surpassing other factors such as price and product quality. According to data from ZK Research, two-thirds of millennials have changed their brand loyalty based on a single bad experience. Today, 90% of companies compete on the basis of CX, a significant increase from 28% five years ago. Improving the customer experience is a top priority for organisations with digital transformation initiatives.

In short, AI is likely to impact most business or customer interactions. 78% of organisations plan to invest in AI to improve the customer experience. Companies that provide a superior experience continue to be patronised by customers, who remain loyal to the brand. On the other hand, those that don’t provide a good experience struggle to retain customers.

Generative AI makes it easy to quickly personalise customer interactions thanks to its ability to analyse vast amounts of data. Natural language processing (NLP) tools powered by generative AI, such as OpenAI’s ChatGPT, are democratising AI beyond the realm of specialised companies. Such tools are now available to everyone.

LINGUISTIC MODELS AND EVOLUTION OF INTELLIGENT VIRTUAL ASSISTANTS

Intelligent Virtual Assistants (IVAs) have had a mixed reception, ranging from scepticism to outright dislike, mainly due to their limited intelligence without AI. An IVA is another form of Interactive Voice Response (IVR) which, despite its role in customer service, has been more frustrating than helpful to users. One of the main problems was the lack of integration between systems, with agents failing to capture the information entered into an IVR. The same was happening with IVA.

With the implementation of large linguistic models, IVAs have become more conversational. Instead of using specific phrases, users can now communicate using natural language. Some IVAs have improved to the point where human agents are preferred in certain scenarios due to their speed and lack of waiting time.

Applying AI to IVAs has made them smarter, more accurate and more capable, resulting in a significantly improved customer experience. People can speak in their own voice and be understood, without having to adapt their speech patterns to the needs of the software.

CHANGING METRICS FOR CALL CENTRE PERFORMANCE

In the age of AI, traditional performance metrics such as average handle time and first call resolution are becoming increasingly irrelevant. Artificial intelligence and advanced routing systems have enabled contact centres to handle complex transactions such as mortgage processing in a single call, improving customer satisfaction and potential revenue generation.

In addition, the customer journey is now a key focus for call centres. The new performance metric ensures that customers who need human intervention reach an agent quickly, while others are served efficiently by AI. This represents a significant shift from high frequency, low complexity interactions to high quality, high engagement interactions.

THE STRATEGIC APPROACH TO AI ADOPTION

Organisations looking to adopt AI should take a strategic approach, which includes identifying key business use cases. For certain use cases, such as understanding the nuances of customer queries, generic AI may not be sufficient. This is where ‘custom AI’ comes in, designed and trained to handle more complex queries. Therefore, companies may need to build AI models using unique data sets that meet specific needs.

Human oversight remains essential in the use of artificial intelligence, especially in critical applications such as healthcare and finance. All companies should have policies in place to implement technologies such as ChatGPT effectively and ethically.

Companies should ask their vendors how they plan to integrate AI, and assess their own data to determine if they are ready to take advantage of it. Although it’s still early days, there will be many new opportunities and challenges ahead as we move into an exciting future with artificial intelligence at the forefront.

La entrada What is the role of generative AI in modernising the customer experience? se publicó primero en Enreach ES.

In the healthcare sector, ChatGPT is an important topic of conversation among doctors and patients alike. This innovation has the potential to automate daily tasks such as generating patient records or writing reports. While it is still in the early stages of development and use, it is anticipated that it will see diagnostic and therapeutic use in the future.

But like other AI systems, ChatGPT faces challenges and tests before it achieves widespread use in healthcare.

What Is ChatGPT?

ChatGPT is the latest evolution of a language model developed by OpenAI known as GPT-3. It is trained to learn language patterns from large amounts of data. The process is designed to ensure accuracy in predicting what’s next in a sequence of words.

It is taught and refined through a combination of supervised and reinforcement learning. According to IBM, it is the “use of labelled data sets to train algorithms to classify data or accurately predict outcomes.” This approach instructs computers on how to learn or identify topics.

It is optimized through reinforcement learning from human feedback. Here, people teach the machine likely and ethical responses or decisions to help users. OpenAI describes ChatGPT’s dialog functions as capable of “answering follow-up questions, admitting mistakes, questioning incorrect premises, and rejecting inappropriate requests.”

Potential Uses of ChatGPT for Physicians

According to an article on Yahoo! Finance, ChatGPT amassed 1 million users in its first week. Among these users are healthcare professionals who are leaning towards AI as the near future of medical management. Therefore, this technology is ushering in a new phase of healthcare in the following ways:

1) Summarize Records And Patient Information

By applying the capabilities of Artificial Intelligence (AI) and Machine Learning (ML), ChatGPT can be taught to act as a digital assistant for clinicians. The technology would extract essential information from patient records, grouping the data into family history, symptoms, current medication, potential allergies, lab results, etc. With AI ensuring this information is readily available, clinicians can assess patients’ needs faster. This feature allows for a clearer focus on the main areas of attention.

2) Improve Clinical Decision Systems

Clinical decision support systems have long played an important role in physician recommendations for patient care. Optimizing these systems through the use of AI and ML tools can improve patient outcomes and treatment decisions.

3) Personalization of Patient Information

Patient interactions and care inherently need to be delivered via chat first, virtual care second, and in-person care third. Moving to conversational systems powered by AI models like GPT-3 (and others), which are contextualized with patient information, will provide more personalized and clinically accurate responses.

4) Automation of Administrative Functions

Studies have shown that doctors and their staff spend about 16.4 hours a week navigating insurance approvals for patient medications, procedures, and other medical services. Focusing on administrative tasks allows less time to deliver medical care.

The ChatGPT can be used to perform administrative tasks such as scheduling appointments, simplifying notes, and other repetitive daily tasks. Thus, conversational AI can support automation and the delivery of improved clinical care. Using proper prompts, ChatGPT can be trained to compose letters requesting prior authorizations, appeals of insurance denials, and other claims.

Potential Uses Of ChatGPT For Patients

1) Improve Patient Education

Using the algorithm’s simplified syntax, clinicians can use ChatGPT to keep patients informed during treatment. Currently, clinical notes documenting medical history, treatment plans, and follow-up procedures are often in professional language, making it difficult for patients to understand. ChatGPT can learn to simplify medical notes, prescriptions or even suggested lifestyles for a better understanding of the patient.

2) Provide Answers to Frequently Asked Questions From Patients

Doctors work in fast-paced environments, which often makes it difficult for patients to have direct contact with them and get answers to their questions. Only occasionally can you grant patients frequent and direct contact with the opinion of specialists. ChatGPT can help clinicians by filling in the gaps in care information. The algorithm’s projected features are intended to answer patients’ questions about the diagnosis or management of their conditions.

Enreach’s Artificial Intelligence, at the Service of Patients

In this post, we have already seen the possibilities that AI offers for the health sector. In its Omnichannel Contact Centre, Enreach has developed an AI module with a chatbot and voicebot service that allows optimizing communications and increasing the effectiveness of a call centre by evaluating the customer’s intention and offering the expected response 24/7.

Enreach’s Artificial Intelligence engine trains your bot to understand the needs of patients and solve their queries. By connecting our bots with external systems, it is possible to complete the responses with information from each customer interaction, also analysing the reason for contact. In addition, they can be configured in more than 120 languages.

La entrada What Value Does ChatGPT Have In The Health Sector? se publicó primero en Enreach ES.