Empowering Virtual Assistants: 8 Key Strategies for Effectively Training LLMs
Jenny Machado August 31, 2023
In the rapidly evolving technology landscape, large Language Models (LLMs) have emerged as a leading innovation, transforming the way we interact with technology and opening doors to new possibilities. Training Deep Learning-based Language Models to have competent conversations with artificial intelligence is an exciting challenge that involves a combination of supervised learning techniques, reinforcement, and contextual adaptation. Virtual Assistants powered by Deep Learning-based Language Models (LLM) have transformed the way we interact with technology. In this article, we will explore 8 key strategies for training LLMs and building virtual assistants capable of delivering exceptional experiences.

8 Key Strategies for Effectively Training LLMs

  1. Conversation Data Training
The first step in improving an LLM's conversational skills is to provide him or her with a large amount of conversational data. This includes dialogues and discussions covering a variety of topics and interaction styles. This data should cover a range of topics and situations so that the assistant can understand and respond to a wide range of queries.
  1. Reinforcement Learning
Supervised training is essential for the attendant to learn to generate consistent and accurate responses. However, combining it with reinforcement learning can take it to a higher level. Through user feedback and evaluation of the quality of responses, the assistant can learn to improve its responses based on experience.
  1. Advanced Context Modeling
Understanding context is critical in a meaningful conversation. LLMs must be trained to understand not only the current query, but also the context of the previous conversation. This ensures that responses are relevant and consistent throughout the interaction.
  1. Real-time user feedback
User feedback is a valuable source of improvement for virtual assistants. Providing an easy way for users to rate and give feedback on the assistant's responses can help to continuously adjust the model and improve its capabilities. These evaluations can be used as feedback signals to refine the model during the training process.
  1. Generating creative responses
A powerful virtual assistant not only provides accurate, but also creative and natural responses. LLMs must be trained to generate responses that do not sound robotic but reflect how a human being might respond in a similar situation. Models must learn to avoid offensive, inappropriate or misleading responses.
  1. Adaptation to Individual Users
Users have unique conversational styles and preferences. Advanced LLMs can be trained to adapt to a specific user over time. This can be accomplished by allowing the model to interact with the same user multiple times and learn from their choices and feedback.
  1. Multilingual and Cultural Integration
A powerful virtual assistant must be able to understand and respond in multiple languages and cultural contexts. Training in multilingual data and diverse cultural expressions is essential to achieve this capability.
  1. Rigorous Testing and Continuous Optimization
Once the virtual assistant has been implemented, rigorous testing is crucial. Potential problems must be identified and addressed, erroneous responses corrected, and the model adjusted based on actual usage results.

eva: orchestrating LLMs

LLMs have proven to be a milestone in AI and their journey promises exciting and transformative terrain. Their future is characterized by constant improvement, increased personalization, real-world applications, and a pivotal role in creativity and education. As these models become more conversationally proficient, they will be able to play a more integral role in a variety of applications, from advanced virtual assistants to customer support systems and beyond. At NTT DATA, we go together with technological innovation, which is why our eva platform has created an orchestrator for LLMs that simplifies complex interactions. This new functionality enhances our platform's ability to orchestrate calls to orchestrate calls to generative AI tools, such as Azure OpenAI services, making it easier to handle more advanced and complex tasks with unprecedented simplicity and elegance. At eva, we use a variety of generative AI models provided by Azure OpenAI (and other vendors) to meet various needs, such as content generation, classification, and data processing.
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eva’s Evolution: From Conversational AI to Digital Employees
Santiago Santa María July 6, 2023
Artificial Intelligence continues to shape our world, with generative language models, known with GenAI taking the top spot and transforming the field of conversational AI. At the heart of this evolution, eva emerges as the game-changer, transforming companies from conversational interfaces to platforms brimming with intelligent digital employees.

However, can this evolution be attributed to Generative AI alone? The answer is a resounding NO

While Generative AI enhances the quality of Conversational AI, to truly harness its potential, a solid platform is required. A platform that not only creates virtual assistants but also integrates them across multiple channels and systems, crafting intelligent agents capable of performing complex tasks and interacting contextually with users. eva is that platform. This is where NTT DATA's eva platform comes in, which has been quickly adapted to effectively manage and orchestrate the automation process in enterprise communications. eva is a powerful solution that leverages the benefits of Gen AI and improves enterprise communications. It allows to resolve access to different channels and perform the necessary integrations to achieve key transactions, such as bank transfers, user authentication, airline ticket check-in and much more. In addition, eva accelerates the implementation of Gen AI in Contact Centers, facilitating monitoring, governance, control and providing detailed analytics.
eva is ready to lead the game together with Gen AI
Now let's explore some exciting enhancements to eva that are set to redefine your enterprise's AI journey:

GenAI Cell: The Brain of Your Digital Employees

Introducing the GenAI Cell - an innovative module that integrates Generative AI services, enhancing eva's capabilities to a whole new level. It enables eva to identify intents, classify content, generate responses, and provide accurate, context-aware answers. Furthermore, the GenAI Cell simplifies prompt chaining, linking responses from previous interactions to deliver more accurate and empathetic answers, thereby creating intelligent digital employees who are as effective and empathetic as their human counterparts. eva not only enables prompt chaining, but also surpasses open-source alternatives like Langchain in performance. Its robust security features, coupled with its enterprise-ready solutions, make it a superior choice for organizations. [video width="1288" height="782" mp4="https://eva.bot/wp-content/uploads/2023/07/5_-machine_learning__Original__AdobeExpress.mp4" preload="auto" autoplay="true"][/video]

Orchestrating the LLM, prompt chaining: Simplifying Complex Interactions

Our newly introduced functionality enhances eva's ability to orchestrate calls to generative AI tools, like Azure OpenAI services, facilitating the handling of more advanced and complex tasks with unprecedented simplicity and elegance. In eva, we utilize a variety of Generative AI models provided by Azure OpenAI (and other vendors) to cater to diverse needs such as content generation, classification, and data processing. If you wish to link your Generative AI account directly, reach out to us for a seamless integration

API REST Integration: Smooth Integration with Your Existing Systems

With this feature, eva seamlessly connects with your existing systems without the need for additional development. It also allows integration with Generative AI services, saving time and effort, and enabling you to streamline your operations with ease. [video width="1912" height="912" mp4="https://eva.bot/wp-content/uploads/2023/07/RestConnector.mp4" autoplay="true" preload="auto"][/video]  

Looking Ahead: The Future of eva

With continuous innovation at its core, eva is poised to introduce new features designed to elevate your enterprise's AI capabilities:
  • Examples Recommender
  • Answer Assist
  • Tag Funnel
Discover how eva's evolution from Conversational AI to Intelligent Digital Employees is reshaping the landscape of Enterprise AI and stay tuned for exciting developments on the horizon. Together, let us embrace evolution.

How does Gen AI help win the game?

Gen AI's Generative Language Models allow you to create much richer, advanced, friendly, and effective conversations. Best of all, the eva platform is already integrated and ready to orchestrate calls to Gen AI's Generative Language Models and other systems. Gen AI enhances the capabilities of the eva platform in several dimensions. It is now possible to automate many of the actions that were previously performed manually, such as utterance generation, which simplifies the work of linguists. For eva, Gen AI represents excellent news, as it expands and enhances its capabilities. Likewise, for Gen AI, the existence of eva is a great advantage, as it accelerates and simplifies the implementation of this technology in companies, ensuring good governance, solid maintenance, controlled evolution, and efficient management.

What’s coming next?

eva is evolving more and more with new Generative AI and Analytics features. Soon you will be able to enjoy the features we are working on today:
  • Examples Recommender:  which makes it easy to create examples in intents from the name and description of the intent.
  • Answer Assist: A wonderful help for the creation and configuration of virtual agent answers. The answer assist will have built-in Rephrasing to generate more empathetic responses with more context for the user.
  • Tag funnel: With the tag funnel it is possible to see the path that the user is following in the different configured flows, in order to validate different business rules, such as which are the most demanded products, detect if the user is following the correct path of the flow, etc.
Start playing to win by testing eva
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Generative AI: A game changer in the coming years that will transform our reality
Joan Lopez May 9, 2023
NTT DATA’s conversational AI platform, eva, has expanded its capabilities with the integration of GenAI to create hyper-personalized, smarter, and more efficient virtual assistants. In December 2022 a new trend was created in the AI world, Open AI made ChatGPT available, using its GPT-3 service. This new milestone brought a new opportunity for conversational AI platforms, such as eva. In an increasingly digitized world, companies are looking for ways to improve efficiency and productivity through process automation and the incorporation of advanced technology. Generative AI uses AI and machine learning to create new digital content (such as text, video, audio, and images) with little need for human intervention, beyond an initial input, such as a keyword or instruction.

The power of eva integrated with LLM and GenAI

ChatGPT started a new trend and a new race. Since then, Google and Amazon have launched their own LLM, and more will come. Thinking about this, eva empowers users with an agnostic architecture, as with NLPs. An LLM Orchestrator is responsible for calling the best LLM, as different functionalities may work better with specific solutions.

Trends and future vision for eva

Advances in Large Language Model (LLM) technology are revolutionizing the world of virtual assistants, and at NTT DATA, we are leading this change towards the future. Committed to ensuring that our client’s investment in virtual assistants is more than worthwhile, we have worked on progressive improvements through LLM technology. With this technology, we can optimize the development and evolution process of existing VAs, to further enhance and simplify them. Additionally, we are developing disruptive new models for creating and designing virtual assistants, using innovative techniques such as Zero-shot, Few-Shot, and Prompt chaining, among others. These techniques allow us to create more efficient and accurate virtual agents, resulting in a more satisfying experience for the end user. But that’s not all! At NTT DATA, we continue to innovate in new channels, such as Digital Humans, which, in combination with LLMs, allow us to offer more natural and efficient conversational experiences than ever before. Digital Humans can emulate human conversations, enabling them to offer users a unique and personalized experience.

What’s coming up in eva with GenAI

As we believe in the importance of staying at the forefront of technological innovation, we work hard to integrate our solutions with leading platforms in the market, such as Open AI and Azure Open AI. In this way, we can implement solutions for our early-adopter clients directly and seamlessly.
We know that for our clients, every second counts, so we want to make the process as fast and easy as possible.We know that for our clients, every second counts, so we want to make the process as fast and easy as possible.
In addition, we are using LLM technology to optimize the traditional virtual assistant development process. Thanks to this technology, we can automatically generate utterances and responses, allowing us to train assistants more efficiently and reduce production times. With this, our clients can be sure that their virtual agents will be ready in less time and with greater accuracy.

In the medium term, eva’s most innovative solutions with GenAI

We are proud to introduce our Zero-shot, Few-shot, and Hybrid Zero + Few Shots virtual assistant solutions. These solutions use LLMs to provide our clients with a more personalized and efficient experience. Our Zero-shot assistants require no training, which means we can quickly implement them without sacrificing quality. The Few-shot assistants allow for fine-tuning through a few classification examples, making them ideal for specific and personalized tasks. And our Hybrid Zero + Few Shots models combine the best of both worlds, allowing for an even more personalized user experience. Finally, our virtual assistants also feature Prompt Chaining, a technology that allows our generalist engines to respond to questions and generate real-time answers. This means our clients can be assured that their virtual assistants will always meet their expectations, even in unexpected situations.

Discover what we have in store for the near future when it comes to integrating with GenAI

We are going to implement NextGen AI on the eva platform. NLG will take a central role in eva, serving as the default categorization tool (replacing NLP) and the long tail solution. As mentioned above, we are working at different speeds to offer the best solutions for now and for the future, in three areas:

Booting automatization for virtual agent development with Generative AI

Optimise the development process of "classic" NLP-based Virtual Assistants by using LLMs. We will provide tools to speed up and reduce design time as well as improve the quality of understanding with these functionalities:
  • Example Generator: The ability to automatically generate utterances from the name and description of an Intent. This will reduce training time and/or quickly improve existing models.
  • Entity Generator: Definition of business entities from prompts. Currently, it is possible to create entities with patterns and synonyms. With Entity Generator, it will be possible to create complex entities with very large datasets with a single instruction.
  • Intent Generator: From a text (such as a product manual, internal procedures, or transcriptions), Eva will propose the list of Intents that need to be created so that a virtual assistant can detect them.
  • Flow Generator: Based on a text that describes a business process, eva will create a basic flowchart to manage a conversation for that use case. These flows should allow business users to work with eva and define the first drafts of the use cases.

Enhancing the Creativity of the Assistants

Generative AI provides a higher level of possibilities for the generation, creativity and rewriting of texts or generation of images, which, within a conversational context, will make it possible to offer experiences that have never been seen before. We will offer the following capabilities in eva:

GenAI Cell:

We started by including the ability to have prompt execution points within the flows. These execution points can be used for many use cases. As we analyze how it is used, we can generate prompt templates or generate new specialized cells or include GenAI in existing cells (such as answer cells or service cells).

GenAI Answer Assistant:

Facilitate and make more creative the creation of virtual assistant responses using the potential of GenAI. It will allow for the Creation of message types, tone, greater creativity in texts, rewriting, summarization, generation of responses in images, video, and audio, creation of carousels, rich text, or auto-generated SSML responses.  

Reinventing Virtual Agent Creation with the Power of Generative A

  • Zero-shot Assistants: Allows for creating an AV without an NLP engine. There is no need for training, just a definition of flows with their intents, entities, etc.
  • Few-shot Assistants: Fine-tuningis possible with a few classification examples. It allows for fine-tuning at specific points in the Assistant to improve classification quality.
  • Hybrid Zero + Few Shots Assistants: For example, the Assistant is generally defined with Zero-shot, but it is possible to specify models with Fine-tuning for some intents.

Improve Conversation Insights

  • Topic Classification & Discovery: This allows us to analyze and categorize the content of chatbot conversations. With topic classification, we can identify the conversation topic, while discovery involves finding patterns or trends in the conversation data. By classifying conversation topics and discovering patterns within the data, chatbot developers can identify areas for improvement and optimize chatbot performance. In general, topic classification and discovery are techniques that can help improve the user experience and increase the effectiveness of chatbots in various applications.
  • Conversation Quality Assessment: The evaluation of chatbot conversation quality is performed by measuring aspects such as coherence, relevance, and usefulness. Its goal is to improve chatbot effectiveness by identifying areas for improvement, such as gaps in its knowledge, and determining if it meets the user’s needs. Various metrics are used, such as natural language processing algorithms, sentiment analysis, and user opinion surveys. The results are used to optimize chatbot conversational capabilities and improve the user experience. It is an important aspect of chatbot development and optimization to ensure effective communication with the user.
In short, at NTT DATA we are committed to innovation and the development of the highest quality virtual assistant solutions. Thanks to our LLM solutions and integration with market-leading platforms, we can guarantee an exceptional user experience for our customers. If you are looking for the best solution in the virtual assistant market, look no further than NTT DATA – contact us today for more information!
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NTT DATA partners with L’ Oréal to enhance its digital e-commerce platforms
Jenny Machado April 24, 2023

NTT DATA partners with L'Oréal to enhance its digital e-commerce platforms

L'Oréal's goal is to provide tools that are at the forefront of consumer experience technology, delivering added value using artificial intelligence. NTT DATA announced the recent alliance with the leading global cosmetics and beauty company, L'Oréal Groupe, which seeks to develop innovative technological solutions that allow users a personalized experience at any time of the day they need it through digital channels, also improving customer service responses. Since its inception, L'Oréal Groupe has been characterized as a company that constantly embraces innovation, and this is no exception. As a pioneer in beauty-tech, its goal is to push the boundaries of beauty, using science and technology as the basis of its sustainability strategy, satisfying the desires and dreams of all its consumers around the world. On this occasion, both companies indicated that they are working on technologies that will be pioneers in Latin America, and are being developed through NTT DATA's Conversational AI, eva platform, which uses advanced artificial intelligence with Generative AI, capable of understanding and offering hyper-personalized advice to users. "As a company we are constantly researching and trying to develop processes that facilitate and optimize the shopping experience for our consumers. We are excited to bring cutting-edge technology to our customers, we want to explore the use of tools like GenAI to provide an engaging and personalized shopping experience, helping our customers find the best products for their beauty needs," said Arturo Perez Wong Manager Manager DPGP L'Oréal Chile. At the same time, the companies added that this alliance will allow them to capitalize on the advancement of the latest artificial intelligence and big data technologies and apply them in the multiple communication channels they have with their customers, creating a more dynamic, fluid, and intuitive shopping experience in both online and offline modalities. "We are very happy to be able to contribute with all our potential to accelerate the deployment of Social Commerce at L'Oréal, and help them to improve the customer experience, through a new, simpler and revolutionary way of shopping, which saves time and improves users' lives" concluded Santiago Santa María, Director Conversational AI & Generative AI.  

About L'Oréal

L'Oréal, a world leader in beauty and personal care, is headquartered in Paris, France. With more than a century of history, the company operates in 150 countries and employs around 88,000 employees. L'Oréal's diverse portfolio includes brands such as L'Oréal Paris, NYX, Vogue and Maybelline. The company focuses on innovation, sustainability, and social responsibility, offering high-quality products and personalized beauty experiences for its customers around the world.  


NTT DATA, part of the NTT Group, is an innovative global IT and business services company headquartered in Tokyo. The company helps clients in their transformation process through consulting, industry solutions, business process services, digital and IT modernization and managed services. NTT DATA enables them, as well as society, to move confidently into the digital future. The company demonstrates its commitment to the long-term success of its customers by combining global reach with local focus to work with them in more than 50 countries around the world.
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GenAI: the essential tool for digital customer service in today’s business world
Jenny Machado March 30, 2023
GenAi has turned virtual conversations around with its powerful capabilities, it is amazing how it manages to understand the context and intentions behind thousands of questions to answer users through natural language in an accurate way. This is on everyone's lips; some companies are already riding the wave with this technology developed by OpenAI. A tool trained to perform different tasks related to natural language has become a great plus for the creation of virtual assistants. The application manages to generate texts in a coherent and natural way, improves accuracy in information search systems, enhances the development of chatbots by responding to users in a concise manner, and can also be used to improve natural language processing.

But why is GenAI so attractive for businesses? We dared to ask the tool itself and this is a summary of its answer:

It improves customer service, reduces costs, analyzes data about your customer interactions, responds quickly to questions or queries, can handle multiple conversations, collects customer information to provide personalized communication. Also, we sought the voices of experts to delve into the topic, Santiago Santa Maria, director of Conversational AI and ChatGPT at NTT DATA, talks about the revolution in customer care and how GenAI is changing the game. In his article published on Medium, Santiago Santa Maria, points out that customer care is being radically transformed with this new application.  
"We are still shocked by the disruption that GenAI is causing in multiple industries: content generation (texts, books, scripts articles...), summaries, translations, answers to factual questions... New uses and applications of this powerful technology keep appearing" says the director of NTT DATA.
  He explains how a company can benefit from GenAI to improve customer service, as it is possible to connect this Extensive Language Model (Generative AI ) with different digital channels such as WhatsApp, Instagram, Web, and Call Centers.

Other benefits identified by the director of Conversational AI and GenAI are:

  • Understanding and accurately responding to user needs.
  • Providing solutions to complex user problems
  • Deliver personalized and satisfying user experiences
  • Handle multiple languages and dialects
  • Understanding context and providing relevant responses across different digital channels
  • Deliver personalized recommendations and suggestions to users
  • Handle high emotional stress situations and provide empathy and appropriate solutions
  • Increase efficiency and reduce costs associated with customer support and sales.
He also gives us a view from his experience, of the value of GenAI to improve sales by connecting it to digital channels. His vision regarding Contact Centers is that GenAI has the potential to automate tasks that today are performed by many people. With this application, cases would be automated to free up hours of attention by Contact Center executives.
"GenAi has shown us the disruptive change that Generative AI bring to the Conversational AI industry."
NTT DATA’s Conversational AI platform, eva, already makes uses Generative AI and is powered by OpenAI technology to complement its capabilities and help clients boost their customer service processes, drive up sales, reduce costs, increase efficiency, and improve their users' experience, giving brands a more salient vision.
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Introducing our latest features with new dashboards, enhanced workflows, and GPT-3
Angela Rodriguez February 7, 2023
Our eva product, recognized by Everest Group as a Major Contender, continues to evolve with new features that will help you grow your business and improve your users' conversational experience. We know the importance of knowing your customers, so we have created tools to analyze and segment users and provide them with a much more focused and personalized conversation. In addition, today the value of speed in transactions is a plus to keep customers happy, so we include improvements that will allow leaps in the flows. The best part is that we also think about reducing your costs with the Voice Gateway. Innovation is key to our product, that's why we've already connected with the powerful GPT-3 tool.
These new features of eva will leave you happily shocked, take a closer look at what's new

Analyze your users to personalize conversations - a whole new level of experience!

We have created a new dashboard for message details and a section for conversations, which will help your business turn customer interactions around. You will be able to visualize each message sent and received by the bot in a complete and exhaustive way to retrain and improve it more and more, this way, you will be able to understand the context of each conversation to further analyze your users' needs and their behavior to address better solutions. Now you will be able to make a more exhaustive analysis and concentrate the information in one place, thanks to the implementation of message and conversation reports, which will allow you to export an excel document with the detail of the messages and the summary of the conversations.

Segment your customers and target them quickly Give them the answers they need and add value to your business!

With this important advance, you will be able to segment your users and define to which range they belong to focus the information and give them a differentiated communication according to their interests.

Not Expected Flow

To improve the user experience, the not expect flow now accepts several cells, enabling you to process information before answering the user when the virtual agent doesn’t understand his input. You can differentiate the response based on user context, deliver sequential answers or even call APIs to fetch information that could answer the user’s input from external sources.

Welcome flow

Because you asked for it... just like the Not Expect flow, you can now build flows when welcoming the user, loading context information, calling external services, disambiguating user segments, delivering different messages based on user profile and for better management of user data. This feature also allows you to deliver sequential responses without entering a specific flow, and to jump to another flow from these two flows.

Reduce costs thanks to Voice Gateway implementation

eva is now able to manage telephone conversations. With the Voice Gateway it is possible to implement and automate use cases with all the power of eva's dialog manager. With this new functionality, you will be able to forget about external platforms because in eva you will have everything condensed to create a Cognitive Contact Center.

Improve the user experience even further

Now, through the Conversation API, you can force the execution of a flow by passing its name in the code field. This feature allows you to start a flow without an intent and force its execution – even in the middle of another flow. For example, you can create a menu in a webchat that allows the user to jump directly to a payment flow, even if the user was already running a flow. This way, you can create a custom chat window with a cart button.

Amazon Lex inside eva AMAZING!

We've added another NLP to our list! If your knowledge base is in Amazon Lex, you can now integrate it with eva to create flows and manage the entire conversational user journey.

The future is here: eva now with OpenAI's GPT-3

We couldn't leave out this powerful new tool, GPT-3 will help us to have much more dynamic and accurate responses in real time to give users an amazing experience and streamline the creation of virtual assistant conversations. This is just the beginning! More information coming soon If you have any questions or feedback, don't hesitate to reach out to us here 
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Best practices in Conversational AI training
Natalia Lombardi January 26, 2023
It is strange that nowadays a company does not have a tool as important as chatbots to connect with its customers and offer them fast and efficient customer service. A guide for Guide to standardize the registration in NLPs will help you. However, making users happy with the virtual assistant is the most complex part. A bad practice could cause the end of a relationship between the person and the company's brand. Behind the machine, there are several profiles that give life to chatbots, _which are not built overnight, much less alone_. One of the people who design the conversational flows are the UX Writers, responsible for creating the conversational design and the interaction between customers and brands. UX Writers need basic knowledge to create good conversational flows. At the beginning, it is normal that they get a little lost among so many technical terms, but well focused, it is simpler than you might think. At NTT DATA we want to help every conversational experience designer to make their job simpler, while at the same time helping companies to make their customers happy with their virtual assistants. Beyond the conversational text best practices that many UX writers and linguists have already mastered, understanding some more technical concepts and how NLPs work is a fundamental process to build a good experience. That's why we invite you to read our practical guide to normalizing records in NLP. Download here this interesting paper and learn the most elementary thermals to create a good conversation with artificial intelligence. Know the basic but most important concepts to consider when creating a chatbot: intention, statement, and entity.
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How to create a chatbot on Facebook messenger?
Ivan Labra Muñoz December 19, 2022
Facebook has undoubtedly been one of the most important social networks during the last 10 years, with almost 3 billion active users up until this day. With this quantity of users, Facebook makes for an incredible platform to not only promote your business but also, to make a difference and help people by taking advantage of its capabilities. Among the many features that Facebook possesses, one of the most important has to do with Facebook Messenger, the app that allows users to chat with each other and really connect through chatting and video calling. This powerful tool not only works in Facebook itself, but also in Instagram -app owned by Facebook- which is also among one of the most popular apps in the world, with its almost 1.2 billion active users.
Combine these two apps and you have an amazing platform to make your business notice.

Facebook connects businesses with their customers

But these users are not only trying to connect between themselves, they also want to reach the companies and brands that they use every day, hence the need for creating chatbots that can help these users in a range of requests, so they don’t have to move from their houses, something that we have become accustomed to. Nowadays there is a demand for fulfilling requests from home, especially in those business areas where the use cases allow this type of interaction.

How to create chatbots in facebook messenger?

For this instance, we consulted Enzo Norambuena, Sales & Marketing Leader at NTT DATA, a company that has been recognized by Everest Group as Major Contenders, on how to create a chatbot on Facebook Messenger and the importance of it for companies. Regarding the importance of having it as an available channel, Enzo tells us:
Expanding the communication channels makes a company to be always connected with the customer. Facebook Messenger is a good strategy for this, as it allows you to have communication with people of any age range any day of the week, 24/7
When it comes to creating a chatbot, using eva it’s the fastest way.

Step by step

  • It is always recommended to start based on use cases, once we define those, we can create the flow that will represent each use case.
  • Once we have defined this, we can take the flow to eva - our enterprise conversational AI platform - there we can visually create the flows, with its corresponding cells (answer cells, intention cells, etc).
  • For our flows to work with Facebook, we must select a “Channel”, in this case it will be the Facebook Messenger channel, connector which was developed by our team and helps to link the flow created in our platform with the Facebook Messenger or Instagram apps.
  • Once we have linked eva with these apps, we have a functioning chat bot with its own case uses and that works for both Facebook and Instagram, since both apps are part of the same conglomerate, Meta.
As you can see, having an available chat bot in Facebook Messenger/Instagram, your company can reach billions of users and help them get through some of the simplest use cases, which will benefit both parties and will improve the user experience and the value of your company. Also, creating a chat bot while using eva and its connectors it’s simple and effective, try our products and check by yourself how easy it is!
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