Good, there’s no shortage of reasons. But, before those, let’s present some revealing numbers about customer and company preferences for customer service bots, especially for voicebots.

 

Customers like voicebots

 

A trend during the pandemic, the use of bots for customer service grew by up to 300% during the period of social isolation. According to a survey by Infobip, which interviewed 1,235 consumers, one in every four had used bots for service in banks, stores, or e-commerce. Of these, 69% said the experience was excellent or very good.

 

Companies prefer voicebots

 

According to a Gartner article, in 2021, 15% of all customer service interactions will be completed using Artificial Intelligence – with significant adoption of voicebots.

 

Companies save with voicebots

 

According to a study by Chatbots Magazine, companies can reduce their customer service costs by up to 30% with the use of conversational bots, like voicebots.

 

What is a voicebot?

 

Sometimes, a voicebot is confused with old software that has endless sequential menus requiring the customer to type the desired option.

In fact, voicebots are conversational robots that, through technologies like Artificial Intelligence (AI) and Computational Linguistics, are capable of performing complex interactions with customers using voice as a means of communication.

Through AI, voicebots can listen and speak with customers, performing high-level interactions with fluency, minimizing the need for human consultant participation.

 

Why is it important?

 

The main goal of developing a voicebot is to automate manual, repetitive, and predictable tasks.

This way, human attendants are freed up to focus on tasks that require decision-making and discernment, skills that are uniquely human.

Voicebots, just like chatbots, are tasked with solving simple problems, and can be used throughout the customer journey.

 

Where can a voicebot be used?

 

These voice customer service bots can be used in pre and post-sale actions, locating customers, promoting offers, discounts, notifications and announcements, making collections and agreements, and of course, their main use is to answer questions and solve customer problems.

 

Why add a voicebot to your service?

 

Check out the main reasons to add a voicebot to your customer service processes.

 

Because you want a more humanized interaction

 

According to Dr. Marc Pell, voice can convey an emotion (e.g., happiness, sadness, or anger) in a tenth of a second, making it a much more efficient source of emotional information than written words. So, when properly guided, a professional voice can convey that emotion in the message, making the interaction more humanized with the user.

 

Because you need to reduce costs

 

With voicebots, you don’t need a large customer service team. While a human serves one customer at a time, a voicebot can handle multiple at once. This way, you reduce personnel costs while making each of your collaborators more strategic.

 

Because your service can be faster

 

With direct and objective communication, the voicebot answers questions and solves simple problems with speed and efficiency, just the way customers want and deserve.

 

Because you can serve more

 

Voicebots don’t need the internet to be used, and they can operate 24 hours a day, 7 days a week, all year round. On weekends, holidays, and even during your company’s collective vacations, the voicebot will be there, ready to serve your customers.

 

Because you can personalize the service

 

You can personalize the message, even with different accents, so that your customers feel unique. With deep data analysis, you can identify the wants and needs of the customer and offer the most relevant products and services, increasing the chances of sales.

 

Because your service can be more inclusive

 

Voicebots allow service for people with visual impairments, making companies more inclusive, increasing their sense of social responsibility, and improving their brand image.

 

Because you want to retain and fidélize customers

 

According to a study by Frost & Sullivan with NICE Latin America, acquiring a customer can be up to 25 times more expensive than keeping one.

And to increase retention and loyalty, voicebots have the ability to identify customer behavior and measure satisfaction, creating opportunities for new sales and contract renewals.

 

Because you aim to be more productive

 

Voicebots solve the simpler problems so that your customer service team can focus on more complex issues. This way, your professionals can serve more and better.

 

Because you want standardized data

 

In addition to the more common statistics (such as the number of calls received, missed calls, peak hours, and others), some important data that voicebots can generate (in a standardized way) are the exact friction points in the customer service process.

That’s it! Have we convinced you of the importance of voicebots for customer service? We hope so! Invest in these customer service bots to optimize your processes and improve your results.

 

Thank you for reading. See you next time!

Also read: Machine Learning vs Linguistic Learning: Learn how they complement each other.

With the advancement of technology, companies are paying attention to innovations to start or boost their digital transformation strategies and optimize the customer experience.

Consumers, increasingly demanding and immediate, seek products and services that are easily accessible, with agile and personalized service.

We’ve already discussed here on the blog that no, bots cannot learn on their own, but they can evolve, and for this, technologies like Machine Learning and Linguistic Learning are essential.

Companies have realized that they can save time and money by using customer service bots. And these bots can indeed be great options for customer relationships.

However, rigid service bots, with only pre-set responses, can leave a bad impression, generating customer dissatisfaction, especially when their problem isn’t resolved.

Therefore, organizations of all sizes and from various sectors are investing in innovative technologies to have bots capable of performing complex and natural dialogues.

The ultimate goal is to streamline service, free up human attendants’ time, increase customer satisfaction, and, of course, reduce costs by cutting expenses on personnel or reallocating professionals to more strategic activities.

In this article, you will learn about the concepts of Machine Learning and Linguistic Learning and how these technologies can optimize your customer service. Enjoy the read!

 

What is Machine Learning?

 

Machine Learning, in Portuguese, Aprendizado de Máquina, refers to the ability of machines to learn on their own.

Machine Learning goes hand in hand with Big Data because, from large volumes of data and algorithms, it allows devices to identify patterns and make connections between them.

The goal of Machine Learning, with Big Data, is to collect, analyze, and process data so that machines can learn to perform tasks automatically, without human assistance.

Through algorithms and statistical analysis, machines can, with greater precision, predict possible responses and deliver more accurate results with a very low error rate.

 

Types of Machine Learning

 

Machine Learning can be separated into two categories:

Supervised: In this model, a human supervises the algorithms, controls data input and output, and also conducts machine training.

 

Unsupervised: This is where Deep Learning comes into play to execute unsupervised tasks, that is, independently, without human oversight.

 

What is Linguistic Learning?

 

Conversation is becoming increasingly important for interacting with a variety of technologies, from smart devices to apps and websites.

In this scenario, Linguistic Learning, in Portuguese, Aprendizagem Linguística, appears as an Artificial Intelligence resource that speeds up the construction of conversational systems.

The goal of Linguistic Learning is to build intelligent conversational systems that can be deployed in multiple languages, across different channels, regardless of the operating system.

Through Linguistic Learning, companies can reach a point where their customers respond by stating what they like and dislike, sharing their preferences and other thoughts – whether you ask for their opinion or not.

Thus, it is possible to analyze conversations in real-time to produce even more personalized responses to maintain the conversation and lead the customer to a logical conclusion.

 

How do these technologies complement each other?

 

A hybrid approach between Machine Learning and Linguistic Learning is the ideal world that all companies want to be part of.

These two technologies can provide intelligent machines capable of performing complex dialogues, simulating human interaction as much as possible.

Have you imagined the possibilities of applying these two technologies in your business’s customer service?

 

How to apply them in your customer service?

 

Find out how Machine Learning and Linguistic Learning can be applied to your business’s customer service.

 

Data collection, analysis, and processing

 

Machine Learning can collect, analyze, and process an unlimited amount of data, in real-time, and from this, offer more relevant products and services, with prices and discounts that customers are looking for, for example.

With pattern identification, companies can personalize their actions, from marketing campaigns and customer service to offering more relevant products and services.

With Linguistic Learning, it’s possible to reach the ideal vocabulary and tone of voice, which will generate more empathy and admiration from the customer.

 

Identifying customer behavior

 

Machine Learning provides a better understanding of the wants and needs of customers, both in terms of the products and services they are looking for and the communication platforms they prefer.

 

Identifying areas for improvement

 

Identifying bottlenecks and areas for improvement is another way to apply Machine Learning in your business. With smarter machines, it’s possible to discover, for example, the best days and times to contact the customer and thus increase the chances of closing a sale.

 

Supporting the customer support area

 

Machine Learning has the ability to gather all customer information, as well as all the problems encountered during past contacts and the best solutions for each situation. Linguistic Learning, on the other hand, identifies the best way to address the customer, for a more assertive conversational flow.

That’s it! With Machine Learning and Linguistic Learning, the possibilities are endless. And who benefits from all this is your customer, who has a better experience, and your business, which improves its results.

 

Thank you for reading. See you next time!

 

Also read: Learn how to increase customer satisfaction in your business

 

Today, customers have more and more options when it comes to buying a product or service. These same customers, more demanding and immediate than ever, seek the most efficient and affordable products and services, as well as the best customer experience possible.

And this experience involves all stages of the customer journey, covering before, during, and after the sale or even a simple customer interaction through the company website, for example.

The journey starts when the consumer gets to know your brand, talks to one of your attendants (or bots) through the website, makes a purchase, and even after that, when support comes into play.

In this scenario, companies need to invest in people and also in technological solutions to increase customer satisfaction, which is increasingly critical when it comes to brands.

But, before diving into tips on how to have happier customers, learn how to measure your current satisfaction index to compare the results.

 

How to measure customer satisfaction?

 

The Net Promoter Score (NPS) is undoubtedly the best, simplest, and most efficient metric for measuring customer satisfaction, and it comes down to a single question: “On a scale of 1 to 10, how likely are you to recommend us to a friend or family member?”

Scores of 0 to 6 are detractors, dissatisfied customers, 7 to 8 are neutrals, customers who are satisfied but not willing to praise, while scores of 9 to 10 are promoters, loyal customers who will spread the word about your products or services.

 

How to increase customer satisfaction?

Now that you know why measuring satisfaction is important, here are some tips on how to make your customers happier with your brand.

Put the customer at the center

First, get to know your customer. Then, educate them so they understand the purpose and value of your products or services. And then, put your customer at the center, improve their experience, recognize their importance, create promotions, offers, and discounts, and thus make them feel valued.

 

Optimize your service

It’s important to invest in omnichannel service, but beyond being present on multiple channels, you need to integrate all your communication platforms and train your service team so they can offer the best support.

 

Make access to your product easy

It’s essential to minimize, as much as possible, the effort that your customer needs to make to talk to your business, ask questions, resolve problems, and of course, buy your products or services. The options are endless, so making it easy for the customer to access your company is crucial to avoid them turning to the competition.

 

Resolve demands with agility

With chatbots, for example, companies can resolve simple issues more quickly, without human intervention. Every business has less complex problems, such as frequently asked questions from customers, and with chatbots, these resolutions can be automated.

 

Surprise your customers

Be creative and innovate in your business, from marketing campaigns and outreach to customer service and the offering of products and services, and beyond. Personalize your actions and make your customer feel unique, turning them into a fan who will spread your brand without asking for anything in return. Always aim to act with empathy and respect to win over more customers.

 

Invest in post-sale

The customer journey doesn’t end at the sale, quite the opposite. After all, would you rather make just one sale or several to the same customer? After selling a product or service, ask for feedback from the customer about their purchase, about the service, and take the opportunity to offer advantages for future purchases. A proactive post-sale can boost your results.

 

Increase customer satisfaction with a chatbot

A chatbot can be used to answer customer questions and solve simple issues, but it can also be used to capture leads, personalize service, and enhance the customer experience.

A chatbot can collect data, and from that information, offer more relevant products and/or services to prospects, increasing the chances of lead capture and sales conversions.

With the history of products searched by a particular customer, the chatbot can personalize its communication, making it an important tool for marketing and sales strategies.

By streamlining service, the chatbot also improves the customer experience, allowing them to get what they need more quickly and with less effort.

 

The chatbot for CRM

 

Instead of relying on several attendants to update your business CRM, you can invest in a chatbot that, on its own, can do the work of an entire team.

The difference is that a chatbot can serve hundreds and even thousands of customers simultaneously, automatically and personalized, while being available 24 hours a day, 7 days a week.

While your chatbot collects and stores data, your team can focus on more strategic activities that require discernment and decision-making, skills that are uniquely human.

 

The chatbot for WhatsApp

 

WhatsApp is the most used instant messaging app in the world, and is a unanimous choice among smartphone users.

According to WhatsApp itself, 2 billion people use the app daily.

100 billion messages are exchanged by the app every day. And in Brazil, 99% of smartphones have the messenger installed.

With WhatsApp Business, for example, your chatbot can be programmed to answer customer questions, send documents like invoices, and perform more complex interactions.

 

The proactive chatbot

 

A proactive chatbot is used to guide and instruct your customers on how they can make the most of your solutions, with tips and examples from other customers, for example.

You can also educate your customer and keep them informed about your business’s goals and differentiators to keep expectations aligned.

That’s it! What did you think of our article on customer satisfaction? We hope that with these tips, you can please your customers, increase your sales, and improve your business profitability.

Thank you for reading. See you next time!

Also read: Learn everything about NLP (Natural Language Processing)

The modern consumer is increasingly demanding and immediate. Therefore, a conversational bot that doesn’t understand the user ends up bringing more disadvantages than advantages, leading to extra costs for companies and customer dissatisfaction.

For us, who are used to getting search results on Google in a matter of seconds and are also adapting to customer service bots, building a conversational bot might seem like a simple task. But believe me, it’s not.

In this article, you will learn what NLP is, how this resource works, and examples of use that can be applied to your business.

Enjoy the reading!

 

The concept of NLP

 

NLP (Natural Language Processing) is a technology that enables devices to converse via text or voice with a person.

This is because programming languages (for example: Java, Python, Ruby, and others) are very different from Portuguese, English, and other languages through which we, humans, normally communicate.

NLP, therefore, serves as a translator so that devices and technological solutions can understand what we write or say, even if it’s not in the programming language.

And in addition to understanding, NLP allows technologies to respond to human interactions and queries, as in the case of customer service bots (chatbots and voicebots) used by companies on websites and communication platforms.

 

How it works

 

The word “bank,” for example, can mean a bench or a financial institution. We, humans, understand the difference according to the context. The technology, to understand such cases, uses NLP.

NLP enables technologies to consider aspects like the context of the conversation, understand syntactic and semantic meanings, and also interpret texts, analyze sentiments, and much more.

To handle text interpretation and complex dialogues, NLP can learn from human interactions and evolve its conversational capability.

Of course, behind NLP, there is an entire multidisciplinary team with developers, programmers, data scientists, content curators, copywriters, computational linguists, psychologists, anthropologists, and AI, UX specialists, etc.

A whole structure is needed to create a knowledge base, where vocabulary, tone of voice, and the entire conversational flow, along with all possible responses that the technology can provide to the customer, are defined.

All of this ensures that computers and other technological solutions understand, respond, and learn from human interactions. This leads us to understand that NLP is just one of the elements of AI and Machine Learning, as part of a package aimed at improving the user experience.

 

Deep Dive

 

With NLP, conversational bots are created with a high level of interaction complexity with humans thanks to highly specialized development tools.

Through NLP, robots are capable of performing complex conversational flows, leading a natural conversation with the user, simulating a human conversation to resolve a procedure or demand.

It is now possible to deliver a conversational bot capable of solving any type of contact reason, from a simple static response to scheduling a technical visit with a technical support sales negotiation.

To execute these procedures, customer service bots use systems integrated with the client’s platforms to query data or perform an action to resolve the user’s demand.

Thus, it’s possible to create a fluid and natural interaction with the user through text or voice messages. But we remind you that the goal is never to try to deceive the user, but to make the conversation so natural that the user forgets they’re talking to a bot.

 

Examples of Use

Check out where NLP is commonly embedded!

 

Search Engines

In search engines, NLP interprets what users are looking for and also analyzes what the content says, presenting the best and most relevant possible results.

Additionally, in search engines, NLP also makes suggestions about the user’s query. This happens when you start typing a question in Google, for example, and the search is automatically completed.

 

Voice Assistants

Alexa and Siri are examples of virtual assistants activated by voice, which recognize user commands in seconds, and from there, are capable of playing your favorite music, turning on your coffee maker, etc.

 

Customer Service Bots

Customer service bots, such as chatbots and voicebots, are already quite common as first contact in call centers, aiming to filter repetitive and simple problems to free up time for attendants to focus on high-value issues.

This is undoubtedly the primary example of NLP usage, and also the one that brings the most benefits to companies. This is because bots can handle hundreds or even thousands of simultaneous interactions. Thus, companies reduce personnel costs and optimize their processes, increasing employee productivity.

 

That’s it! We’ve reached the end of this article on NLP, and we hope you’ve understood that it’s one of the most important elements of AI, especially when it comes to customer service bots for businesses.

 

It was a pleasure to have you with us. See you soon!

Also read: Customer Experience (CX): Learn everything about it.

 

Customer Experience (CX), or Client Experience in English, can be considered one of the “buzzwords” within companies striving tirelessly to achieve operational excellence.

The problem is that, according to a study by Harvard Business Review, only 15% of companies consider themselves very effective in their CX strategies, while 53% claim to be somewhat effective and 32% not very effective.

On the other hand, 73% of business leaders acknowledge that Customer Experience is essential for business success, and 93% agree that it will become even more critical in two years, according to another study by Harvard Business Review.

In other words, organizations recognize the importance of Customer Experience but struggle to implement effective strategies.

 

The concept of Customer Experience (CX)

The concept of Customer Experience (CX) encompasses all stages of the customer journey, including before, during, and after a sale or even a simple interaction with the company’s website, for example.

CX can also be defined as the combination of all perceptions and impressions a consumer has about a company after interacting with it.

This experience begins when the consumer discovers your brand, learns about your products, talks to one of your representatives (or bots) on your website, completes a purchase, and even afterwards when support comes into play.

Throughout this journey, the 4.0 customer, increasingly demanding and immediate, is not just concerned with the product but also with the service and unique features the company can offer.

 

The 3 pillars of CX

The 4.0 customer seeks memorable experiences whenever they show interest in a product or service. To delight and surprise this consumer, companies usually rely on three pillars that give meaning to Customer Experience.

 

1. Effort

This isn’t about your business’s dedication to providing the best CX but rather the effort the customer must make to contact or buy from you. Therefore, it’s crucial to review the entire customer journey to minimize the effort required to receive assistance or purchase a product or service.

 

2. Emotional

Joy, fulfillment, and satisfaction are some emotions companies can evoke in customers, helping them remember your brand fondly. Building emotional connections is the first step to creating a deep, lasting, and profitable customer relationship.

 

3. Success

Helping the customer achieve their goals easily and quickly ensures their success. However, Customer Success (CS) isn’t just about meeting expectations but exceeding them. This is an indispensable pillar for an efficient CX strategy.

 

The importance of CX

By offering an unforgettable CX, you can retain your customers and more: transform them into advocates and promoters of your brand. This can result in customers recommending your business to others, creating a community that promotes your business without any cost.

 

Putting it into practice

There’s no magic formula. But here are some tips applicable to companies of all sizes and across various industries. Check them out!

 

Create an internal culture

Put the customer at the center. This must be your business’s mantra, and your employees should be aware of it. It’s also essential to invest in team training, especially in customer service.

 

Understand your customer

You need to understand your customer’s needs and desires and even where they prefer to be assisted to avoid being invasive or inconvenient. This way, you can offer the right solution, at the right time, through the ideal channel.

 

Improve the relationship

Be present across all communication channels and platforms. Providing omnichannel support is essential to enhance customer relationships, without overwhelming them with messages and calls.

 

Invest in personalization

Who doesn’t like feeling unique? Whenever possible, personalize your service as well as your product or offering, and try to be creative to surprise your customer, generating empathy and admiration.

 

Monitor results

Today’s consumer preferences and behaviors aren’t the same as five years ago. And in another five years, they’ll change again. Therefore, continuously review your strategy and adapt to market transformations.

 

Metrics to evaluate

NPS: The Net Promoter Score (NPS) boils down to a single question: “On a scale of 1 to 10, how likely are you to recommend us to a friend or family member?” This simple yet effective metric measures customer satisfaction.

 

CSAT: Ranging from 1 to 5, Customer Satisfaction (CSAT) is another key metric to define customer satisfaction, where 1 is the minimum score and 5 is the maximum.

 

CES: The Customer Effort Score (CES) measures how much effort a customer had to make to communicate or buy from the company, identifying areas for improvement.

 

TTR: The Time to Resolution evaluates the average time it takes the service team to resolve a problem. The calculation is based on the total time spent divided by the number of resolved cases.

 

The benefits for companies

Besides fostering loyalty and creating brand advocates and promoters, investing in Customer Experience also increases your business’s trustworthiness and credibility, becoming a competitive advantage over competitors while also contributing to cost reduction with streamlined and efficient processes.

 

The role of technology

It’s impossible to think about Customer Experience without leveraging technology. Artificial Intelligence (AI), applied to service bots like chatbots and voicebots, is an example.

Virtual Reality (VR) and smartphone applications are also trends that appear as excellent options for enhancing the Customer Experience.

We hope you enjoyed this article. See you next time!

Read also: What are the new professions related to bots?

In 2020, the bot market was valued at $17.1 billion, with projections to reach $102.2 billion by 2026, according to data from Mordor Intelligence.

In Brazil, there are about 17,000 bots, handling a monthly traffic of 800 million messages, according to the Brazilian Bot Ecosystem Map.

Studies suggest that 50% of the workforce will be replaced by 2050, and companies will reduce approximately $8 billion in annual costs by 2022.

This rapid growth is a divisive topic. Some believe that service bots are here to replace humans, thus taking their jobs, as seen in the case of call centers.

Others, more optimistic or perhaps better prepared for change, argue that service bots require skilled professionals to function effectively.

The truth is that bots are indeed replacing many roles, but at the same time, conversational bots have created new professions.

In another article on Sovran’s Blog, we discussed how bots cannot learn by themselves and that there is always a team working behind the scenes.

 

Bots (still) depend on humans

 

Behind every bot, there is a team managing user interactions, data, and the entire conversational flow.

The message we receive from a bot undergoes a process of construction and evolution, where every word is carefully chosen, from the creation of the knowledge base to defining its vocabulary, tone of voice, and more.

This meticulous analysis is typically (and should be) carried out by a multidisciplinary team comprising professionals from various business areas: management, administration, sales, legal, marketing, and others.

This is because bot developers and programmers excel at the technical aspects but generally lack comprehensive knowledge about all the business and customer service-related subjects.

Thus, a single phrase or response might go through analysis and approval by several professionals from different departments before being implemented into the bot.

 

Professions related to bots

Here are the main professions behind bots!

 

Developers and programmers

DevOps developers handle the architecture, development model, operation, and maintenance of the bot. Software engineers focus on writing the bot’s programming code and creating connectors to integrate the bot with the contracting companies’ legacy systems.

 

Data scientists

These professionals determine research lines to maximize the value of data generated by bots during their interactions with users, playing a crucial role in directing the bot’s services effectively.

 

Knowledge curators

Knowledge curators are responsible for creating, updating, and validating all content for the bots’ conversations, including questions and answers.

 

Bot trainers

Bot trainers, or bot teachers, build associations between word sequences and likely intentions to enable the bot to solve users’ real problems without human intervention.

 

Bot writers

Usually journalists or linguists, bot writers are responsible for crafting the text messages sent to users, ensuring they are clear and well-received by customers or consumers.

 

Computational linguists

Computational linguists develop systems capable of reproducing and recognizing information conveyed in natural language, or human language, using logical-formal modeling.

 

Artificial Intelligence specialists

These professionals are typically developers and programmers with expertise in programming and applying machine learning algorithms, working closely with data scientists.

 

Customer Experience (UX) specialists

With strong ties to the technical team, UX (User Experience) specialists are highly business- and customer-focused, understanding the entire customer journey and the company’s product or service better than anyone.

 

User Interface Specialists (UI/VUI)

Experts in user navigation, UI/VUI Designers focus on the service channels (e.g., phone, web, WhatsApp, Facebook, Instagram) where bots will be deployed.

 

Test analysts

A bot cannot be launched without approval from test analysts or the testing team. These professionals are responsible for quality control, identifying potential issues and collaborating with developers and programmers to find the best solutions.

 

Continuous Improvement Analysts

When a bot fails to respond to a user, it should transfer the interaction to a human agent. Continuous improvement analysts investigate the causes of such failures, proposing solutions to prevent them from recurring in future interactions.

 

That’s it! As you’ve seen throughout this article, bots rely on a large team for their design, deployment, and maintenance.

This article highlights some future professions that are already common and will continue to grow in demand within companies.

We hope you enjoyed it. See you next time!

Read also: Can bots learn on their own, or is that just a myth?