Month: July 2021

There are many types of eCommerce AI chatbots available today that help with all different aspects of an eCommerce store. AI chatbots can boost sales and revenue by showing shoppers exactly the product they were looking for which was often hidden in complex menus, acting as a shopping assistant providing product recommendations, and aid customer support by immediately answering customer questions about a product, order status, and more.

An AI chatbot built for eCommerce is not that expensive and has a high rate of return. The average increase in revenues when a shopper engages with the chatbot is 20% to 40%. There are also other benefits such as an average reduction in support tickets of 25% to 45%. You can build your own eCommerce chatbot for free to $100 a month or have an AI chatbot company manage and train the AI starting at $500 a month.

In order to build a successful eCommerce AI chatbot, there are some important features and tactics to incorporate into your AI chatbot. While not all AI chatbot platforms are the same, you will want to make sure your AI chatbot has these basic features for your eCommerce store.

Conversational eCommerce Overcomes Sales Obstacles

Every shopper, whether online or in-person, has a question or two (or more!) when browsing products or learning more about your store and brand. Answering these questions in a timely manner can be the difference between winning or losing a sale. Shoppers make split-second decisions when deciding to purchase or not purchase a product so having a knowledgeable AI chatbot answer those questions immediately helps to overcome sales obstacles — leading to more sales.

The more knowledge you pack into your eCommerce AI chatbot the better so it can answer a wide range of shopper questions and inquiries. In addition, pay attention to how shoppers interact and what questions they ask the AI chatbot so you can make it smarter and smarter over time, becoming more efficient and boosting more revenue.

The AI should also be able to recommend products that the shopper is looking for as well as cross-selling other products that go along with the purchase. Shoppers often need a nudge in the right direction to make a purchase. This will not only increase total sales but also increase AOV (average order value).

Trending Bot Articles:

1. How Conversational AI can Automate Customer Service

2. Automated vs Live Chats: What will the Future of Customer Service Look Like?

3. Chatbots As Medical Assistants In COVID-19 Pandemic

4. Chatbot Vs. Intelligent Virtual Assistant — What’s the difference & Why Care?

Reporting & Analysis For Business Insights

Your AI eCommerce chatbot is interacting and having conversations with your shoppers all day long. To improve and optimize your eCommerce business you need to understand your customers’ issues, wants, and desires. A good reporting system should tell you where shoppers are getting stuck in the purchasing process.

For example, if customers ask the AI chatbot a lot of questions on a particular page or about a particular product then you can see what those questions are and improve the product page by answering those questions in the copy. There is a lot of other information you can learn such as what customers compare your product to, trends in the market, site bugs, usability issues and many others.

Track Customer’s Order Status

By far, the most common question customers ask is “Where is my order?!?”. Delivery times vary widely; especially if the products are manufactured by the company. It is important to keep your customer up-to-date on when they should expect to receive their order. Yes, most eCommerce stores provide some sort of tracking number or process to track the order via an email alert or order confirmation but having your eCommerce AI chatbot provide order status when a customer comes back to your website is key to a convenient customer experience.

When your AI chatbot connects to your product database it has access to orders. This allows customers to enter their order number into the AI chatbot which then searches through the order system and retrieves the order status. The status of the customer’s order is then displayed along with a link to track their package through whichever courier is used. This reduces customer service tickets and frees your customer service team from being bogged down by repetitive order status requests allowing the team to focus and give more attention to higher-level customer support issues.

Recover Abandoned Carts Without Email Required

A key piece to boosting revenue through your eCommerce AI chatbot is reminding shoppers of the items left in their cart from a previous eCommerce store visit. Online shoppers love comparing prices among a number of different stores which leads to a high rate of abandoned carts. Prompting shoppers with items previously left in their cart as soon as they return to your site shortens the sales cycle and caters to convenience so shoppers don’t have to waste time re-building their order.

Capturing abandoned carts also gives the shopper a more personalized experience leading to more return customers. There are several ways eCommerce AI chatbots accomplish recovering abandoned carts including one technique: when the shopper returns to the site, the AI chatbot would display the items left in their cart prompting them to checkout instead of asking the introduction or opening question. This can augment your traditional abandoned cart with registered users via email.

The number of abandoned carts is much higher for those that have not registered increasing revenues as high as 30% for some stores.

Shopping Directly Through Your Chatbot

Online shopping has changed over the years and continues to evolve into a richer shopping experience. Soon shoppers won’t have to scroll through numerous static website pages to find the product they are looking for. With AI chatbots, shoppers can engage your eCommerce store in a conversation to help them find the right product for them.

AI chatbots try to mimic a conversation your shoppers would normally have with a salesperson over the phone or in person. Crafting that AI chatbot conversation correctly is crucial to the shopping experience and increasing revenue. Possessing the ability for shoppers to ask the chatbot for product recommendations then adding the product to their cart all through the chatbot window is a major driver for eCommerce chatbots boosting revenue.

AI chatbots are able to display the product description, image, and pricing for the shopper to review plus a button to add the product to their cart and a button to bring them to the product page for a further product review. eCommerce AI chatbots guide shoppers to the right product — quickly — then adding products to their cart — quickly — transforming the online shopping experience into convenience and ease.

Engaging Customers Wherever They Are In Their Shopping Journey

Every shopper has their own unique eCommerce shopping journey but, for the most part, all follow a general path or format. eCommerce AI chatbots help stores engage their customers differently depending on where they are in that journey.

For example, when a shopper lands on the home page the AI chatbot would ask an introduction or opening question: “How can I help you today?” Or a question about the problem they are trying to solve. Then, when the shopper goes to a product page the chatbot could display a few button options about popular product FAQs, product sizing guides, or social groups to join to connect to the product community.

Finally, when on the checkout page the AI chatbot could offer button options for warranty or shipping information to help the shopper feel more confident in their purchase. These tactics all help boost revenue by first guiding the shopper to the product they are looking for then overcoming sales obstacles at multiple points in the shopper’s journey.

When evaluating your shopper’s general journey try to identify those points where the AI chatbot could engage your shoppers in a helpful and non-bothersome way.

Conclusion

Adding an AI chatbot to your eCommerce store is a paradigm shift in how you engage with your shoppers. The key to success is always thinking about your customers’ shopping experience. Your eCommerce chatbot should help not hinder that experience. Your eCommerce store will not only increase revenues but your business will grow with the business insights you gain from the AI chatbot

Don’t forget to give us your 👏 !

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How To Grow Your eCommerce Revenue With An eCommerce AI Chatbot? was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

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Slack is good for a lot more than sending hilarious cat GIFs to your coworkers.

Slack can help teams who are used to working at an office stay well while working from home.

Here are 16 Slack apps that will help you in promoting healthy habits and wellness for your team.

1. Trivia

Trivia is the new way to connect with your remote team while playing exciting quizzes and remote games on Slack and Microsoft Teams! Get summarised results at the end of every Trivia quiz and find your very own Quizzard!

2. Count It

Count.It hosts physical activity challenges for teams, and now you can bring all that action into your Slack @channels. Connect tracking apps/devices, get live notifications, check out the leaderboard, right from Slack.

3. Leaderboard

Track your office battles with Leaderboard App! Challenge your co-workers for a game of Mario Kart, Ping Pong, Table Football… And when you’re finished playing, report your score. Ready? set, go! Climb the leaderboard today and be the office champion.

4. Health Hero

Health Hero makes it easy to get the whole workplace to log their #meal, #move and #mind in the way that works for them. Using text or images just tell the Health Hero bot about that healthy meal, that morning run or that bit of meditation this afternoon and it will track your progress.

5. Motivation

Receive motivational reminders directly in Slack. Whether you’re going through hard times, need an extra push to get stuff done, or like sharing inspirational quotes with your team, Motivation has you covered.

Trending Bot Articles:

1. How Conversational AI can Automate Customer Service

2. Automated vs Live Chats: What will the Future of Customer Service Look Like?

3. Chatbots As Medical Assistants In COVID-19 Pandemic

4. Chatbot Vs. Intelligent Virtual Assistant — What’s the difference & Why Care?

6. WFH Surveys

Taking feedback from your remote employees has never been this simple and effortless. Just a simple addition to your Slack app and you’re ready to sail. WFH Surveys helps you take feedback from your remote employees via AI-enabled interactive chat.

7. Good Job

Good Job‘s happiness tracker gives you the data you need to be happier at work. Track your workplace experience daily, to identify trends in what makes you happy and what causes you stress at work.

8. Gratitudely

Gratitudely is a simple, fresh way for your Slack team to keep a shared gratitude journal — a “gratitude wall”. Improve team well-being (boost morale, reduce stress, and more!) by keeping a shared gratitude journal.

9. Platterz

Integrating your Platterz account with Slack makes it effortless to keep your team updated and engaged with your culture programs. The Platterz app will automatically engage each employee with reminders of upcoming meals, and requests for ratings and preferences.

10. Gyroscope

Sitting in an office can be very unhealthy and cause people to have low steps each day. Gyroscope helps to fix this by building software to track your life, encourage workouts and make improvements to your health.

11. Icliniq

The Icliniq slack app is an extension of Icliniq, a leading online telehealth consulting portal for Slack Teams. For any team to use Icliniq, the admin has to authorise the app for their respective teams.

12. &frankly

The &frankly bot notifiers users about open questions they have to answer, and pushes the results to users, groups and the company in order to quickly see what is going on in the company and what you can improve.

13. blankit health

With blankitbot for Slack, your employees can ask questions about their coverage and get an immediate reply. Blankitbot for Slack responds to simple phrases like “”Do I have coverage for a root canal?” and “Can I include my spouse on the plan?” There’s no need to learn new commands to chat with blankitbot.

14. Kiki

In these extraordinary times, we’re all adapting to new ways of working. Kiki is here to help! Kiki helps teams perform regular check-ins and easily share responses. It’s 100% free-to-use, and quick to get started.

15. Joyride

Getting to know people on your team just got a lot easier. Joyride uses icebreakers and fun questions to keep the laughs coming. Team engagement skyrockets. When you add to Slack, a channel called #theride is created and your team is invited in.

16. enso

Meet enso — the first slack bot whose notifications will reduce stress, instead of causing it. Every once in a while he will remind you to pause and breathe. That’s all. And as simple as it may sound, it will turn out to be transformative in practice.

Don’t forget to give us your 👏 !

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16 Slack Bots to Promote Wellness at Your Workplace was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

Have you ever wondered what the future holds for chatbots? The chatbot industry is growing exponentially, and many people are wondering whether or not they should invest in this new technology. In this blog post, we will explore the history of chatbots, their business applications, and how chatbots might be used in the future.

What is an AI Chatbot?

A bot is any virtual agent or software application that interacts with customers on social media channels by using either text or voice messages. “AI” stands for “artificial intelligence,” which means these applications have are given anthropomorphic properties so they can think like people do. Applications such as Siri, Cortana, and Alexa all fit the bill of a chatbot.

Not all Chatbots use ai. Some can be pretty efficient with the help of conditional logic trees built by a human programmer. But the best chat solutions employ both the human-built touch and artificial intelligence.

Chatbots have many uses that range from helping you navigate your bank account to providing customer service for business customers.

Businesses often use them in industries such as healthcare, retail, and travel. Some popular applications include Hipchat bot (Atlassian), Alexa (Amazon Echo), and Facebook messenger bots (Facebook). Instagram also recently jumped on the chatbot bandwagon by releasing Instagram Automations.

Back to the Future: A Brief History of Chatbots and Ai

The first type of chatbot was created on May 13, 1966, by Joseph Weizenbaum at MIT’s Artificial Intelligence Laboratory (AI Lab). The ELIZA program ran conversational text with a human user to simulate conversation while using keywords from an input dialogue to respond accordingly. It then replied to those inputs until it reached another keyword triggering a new response.

In 1973, a variation of ELIZA was created by Kenneth Colby at Stanford University called PARRY. Unlike ELIZA, PARRY simulated conversation with a human user and attempted to respond as if it were paranoid or schizophrenic in nature. Weizenbaum had programmed ELIZA using psychoanalytic principles from his studies at Harvard Medical School. He worked there between 1964–1970. He had developed an interest in psychiatry because of its close relationship to artificial intelligence research: “I felt that psychiatrists should be more concerned about AI than most.”

Since these first chatbots emerged onto the scene, any number of bots have been coded, including SmarterChild (1999), Cleverbot (2005), and AliceBot (2006).

Chatbots can be built and maintained by humans or artificial intelligence. And while many small businesses previously struggled to tap into these fast-moving technologies, new tools and platforms have emerged to help companies tap into these technologies.

Tools like ManyChat allow you to build conditional logic and intelligent chatbot automation for Instagram, Facebook Messenger, and even your website using their visual builder tools. No coding experience is needed. They even offer a free course! You can also learn about ManyChat and use the platform on the Baby Got Bot YouTube Channel.

If you want to integrate ai into your ManyChat Chatbots, you can use tools like Janis AI or DialogFlow by Google to create your chatbot, train it with natural language processing and build an engaging experience for customers.

Another excellent tool for those in the Restaurant industry is Feebi which is ai built specifically for the Restaurant industry. Feebi allows the chatbot to answer up to 80% of chat inquiries that come in and quickly hands off messages that need the human touch.

Also, for Restaurants, there is an all-in-one platform called Tap The Table, making a fully integrated chat automation strategy a breeze.

These tools make it easy for companies to start using Chat automation to help more customers and land more business.

Many businesses wrongly believe that chatbots are annoying and may scare customers away, but the numbers tell a different story. The vast majority (87.2%) of consumers have neutral or positive experiences with chatbots (Source: Drift). Additionally, the average satisfaction rate of bot-only chats is 87.58%. This is almost two percentage points higher than the satisfaction rate for conversations that get passed over to human agents! (Source: Comm100)

The vast majority (87.2%) of consumers have neutral or positive experiences with chatbots

Businesses that are not utilizing chatbots cite a lack of knowledge about the technology and its potential. In addition, some companies may worry that bots will replace human employees. Still, in reality, they’re more than happy to work alongside their robotic counterparts — especially when it comes to repetitive tasks where humans excel.

Trending Bot Articles:

1. How Conversational AI can Automate Customer Service

2. Automated vs Live Chats: What will the Future of Customer Service Look Like?

3. Chatbots As Medical Assistants In COVID-19 Pandemic

4. Chatbot Vs. Intelligent Virtual Assistant — What’s the difference & Why Care?

Use Cases for Chatbots

Let’s explore how companies use chatbots today to help customers, drive sales, and become more efficient.

Chatbots drive sales:

By 2023, $112 billion worth of eCommerce transactions will be made via chatbots. By leveraging push factors to drive retail sales and upselling certain products, the power of a Chatbot can help your company reach new levels in both online marketing and cart recovery notifications which keeps customers coming back for more. As Juniper Research predicts, it’s only going to grow exponentially from here on out!

Using abandoned cart chatbots alongside Messenger boosts eCommerce revenue by 7–25%.

Chatbots can also help recover lost sales with the help of abandoned cart automation. According to Chatbots Magazine, using abandoned cart chatbots alongside Messenger boosts eCommerce revenue by 7–25%. And Consumers are not turned off by chatbots either. Approximately 74% of consumers say they use chatbots to research or buy products and services.

Kia is one such company that is using Messenger bots to drive engagement and sales. Users can interact with Kia’s ‘Kian’ by searching ‘Kia Motors America’ in the Messenger app. Kian began as a promotional tool during the 52nd Super Bowl in February 2018 for the new Niro car model. Since then, Kian has expanded to handle any of the questions that a salesperson would be able to answer. Kian can also help with roadside assistance, bill payment, and locating a Kia dealership near you.

The Kia Messenger bot sees 115,000 users per week on average and gets three times more interactions than the Kia Website. Octane AI developed Kian in conjunction with CarLabs and mobile agency Ansible. Learn more about this case study at https://digiday.com/marketing/personalization-allows-media-optimization-kia-seeing-3-times-conversions-chatbot-website/.

Chatbots simplify customer service support and answering FAQs.

Chatbots can help take a huge chunk of the burden of customer service and inquiry off of human agents, plus save a company thousands of dollars. Chatbots can save businesses as much as 30% on customer support costs. (Source: IBM).

A great example of a FAQ and customer service support bot is Evernote. The Evernote Chatbot was created using Sprout Social and helps customers with technical issues, customer support ticket status, and feature requests. It also Prompts customers for the information that agents need to assist the customer (e.g., ticket number, version number), making the chatbot to human handoff efficient and straightforward.

The Evernote chatbot has been a success with a reported 18% decrease in replies sent per conversation, and an 80% increase in customers helped on Twitter (this is a Twitter chatbot). (Source: https://sproutsocial.com/insights/case-studies)

Another company that found profound success with a chatbot is Charter Communications. Charter Communications found a way to save its company money and time by switching to an automated chatbot. Before, they received 200,000 live chats per month, with 38% of these being forgotten passwords or usernames for services that can be handled automatically through the bot. When Charter switched over, it only took six months before there was 300% ROI, and the bot managed 83% of all of the chat communications! (Source)

When Charter switched over, it only took six months before there was 300% ROI, and the bot managed 83% of all of the chat communications!

Chatbots for lead generation:

When a company creates an engaging chatbot experience on their website or social media page (and gets shared), this helps create leads for companies without using advertising dollars. 55% of businesses that use chatbots generate more high-quality leads. (Source: Drift)

One of the easiest ways to drive lead generation and sales is through a Facebook Messenger bot and a comment growth tool. The Comment Growth tool enables a Facebook business page to automatically initiate a Messenger conversation after a user comments on a page post. This means you can make money directly from your Facebook posts, and even better, you can track the user and the sale from beginning to end.

Book Tickets To Events/Shows With Chatbots

Chatbots are used to purchase tickets. For example, built into Ticketmaster’s mobile app, users can chat with a bot which then helps them navigate their way through the purchasing process and ensures they get the best seats possible for their budget! The Ticketmaster chatbot utilizes natural language processing to help users search for tickets and purchase them. Payments happen via lined Credit Card or Gift cards right inside the app, and e-ticket and receipts are delivered instantly in the user’s linked email account. The Ticketmaster app is made more intelligent by using Google Dialogflow ai technology. (source: https://cloud.google.com/dialogflow/docs/case-studies/ticketmaster)

Use Chatbots to book appointments.

Many businesses are using chatbots to help manage customer inquiries and book appointments. For example, Sales Rabbit Is a company that books meetings for sales teams. They were using a form that then exchanges emails between the rep and prospect. After switching to a chatbot, they can qualify leads and immediately book time on their sales team’s calendar. SalesRabbit has a 40% lift in the conversion rate of requests to meetings held and a 50% increase in qualified leads. source https://www.drift.com/case-studies/

These are only some of the ways chatbots are helping businesses and consumers alike. No matter what industry you’re in, there are likely many ways your business can be helped by using Chat automation with bots! As We say in the chat marketing industry, “There is a bot for that.”

The Future of Chatbots

Chatbots will continue to grow in popularity and increase their use cases. They will be used as customer service, sales assistants, among other tasks. The chatbot market size is projected to grow from $2.6 billion in 2021 to $9.4 billion by 2024 at a compound annual growth rate (CAGR) of 29.7%. (BusinessInsider) More Businesses will adopt this technology, with 80% of businesses expected to have chatbot automation by the end of 2021. (Outgrow).

The chatbot market size is projected to grow from $2.6 billion in 2021.

And with more messaging users than actual social media users already here and that number to continue to grow, the future of chat is bright. We’ll see how this technology evolves, but one thing is sure: business applications lie ahead for those who invest now!

Are you ready to learn more about Chatbots? I have many resources for you to explore!

• Free Chat Marketing and Automation tutorials on Baby Got Bot YouTube Channel.
• My other Chat Marketing Services can be found at www.StellarMediaMarketing.com

Don’t forget to give us your 👏 !

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A Beginner’s Guide to the History, Business Applications, and Future of Chatbots was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

I can say for sure that many of us have already noticed the increase of Amazon Echo users worldwide. This means more people will use Alexa Skills, which means more users for those who create Alexa Skills.

But, creating successful Alexa Skills is not that easy. You may have the best idea for a Skill, but it won’t reach enough users or probably none if not executed correctly.

What to consider when you want to learn to create Alexa Skills?

There are a few things to consider when creating an Alexa Skill. Starting from the type of Skill you will build, to its design. In between, you will have to take care of the customer journey, its conversational capabilities, and the quality of the content provided to the user.

So, the next time you ask yourself how to create an Alexa Skill, these are the main checkpoint you will need to go through. This is where Ipervox can help you with an entire course dedicated to the process of creating a successful Alexa Skill, along with use cases and best practices.

What’s in it for you with Ipervox

The voice world is filled with apps from individuals & companies that can make your life easier.

They do so by letting you communicate in a way that’s more natural and efficient. Voice technology has changed the way we connect — and it’s only going to get better.

In our increasingly voice-driven space, it is of the utmost importance that you are included in the growing voice market. And we have no doubt you already know that. However, you should consider that voice apps are being used around the world to improve every service we already use — and even offer new ones — through voice commands.

What Ipervox offers in its courses is the possibility to start learning more about how voice applications work, how to create one, and their potential.

Here are the phases you can go through:

Learning the basics of Alexa Skills

With Ipervox, the first step in your learning process to create Alexa Skills is the free training called “Play with Ipervox”. It is constructed in such a way, it will allow you to learn the internals of how a voice application works. To make things easier to understand the course is focused only on Alexa Skills.

This first course is separated into 9 different chapters, explaining different steps to follow during the Skill development, which is focused on:

• How to navigate the Ipervox Dashboard during the development process.
• How to create a new Alexa Skill, how to name it, and the type of Skill you can create.
• The variety of content you can add to your voice app and how to channel it.
• How to test your Skill, send it for approval by Amazon, publish it and later on analyze its performance.

Of course, everything mentioned above you can complete using our platform. Here you don’t need to have coding knowledge since it has been simplified to make the development process available for everyone. However, if you want to do so, you will have the option available.

Trending Bot Articles:

1. How Conversational AI can Automate Customer Service

2. Automated vs Live Chats: What will the Future of Customer Service Look Like?

3. Chatbots As Medical Assistants In COVID-19 Pandemic

4. Chatbot Vs. Intelligent Virtual Assistant — What’s the difference & Why Care?

Taking the first steps towards successful Alexa Skills

With this course, called Voice Tech Starter, you will go deeper into the voice development space.

You will learn how to create and implement a Voice Application in your business using the right tools for your industry and sector. You will know the features an application should have, how to engage with users, and set up your product for success in a competitive market.

In this course, you will learn about topics like:

• Why Voice & Why Alexa.
• Are Voice Apps Ok for every business category?
• Principles of Voice Designing.
• Choosing the best activation phrase.
• Numerous case studies to take into consideration.

This, along with the needed materials & tools to put into test your newly acquired capabilities.

Mastering the process of creating Alexa Skills

If you want to build your own voice applications and get ahead of the competition, then this course is for you. It’s packed with with more than 60 lessons in which we cover everything from planning to testing. We have included all the relevant videos so that you can learn how to plan, build, and promote a successful voice application. It’s also really well-designed with a great course layout that makes it easy to navigate and follow along.

Here you will learn about how to:

• Find the best voice application needed for a specific brand or business.
• Find the right kind of content the voice app will contain.
• Create a Voice Project from scratch.
• Create the customer journey throughout the voice app.
• Create a unique yet helpful experience for every user.
• How to create voice apps for marketing or monetization.
• How to use a voice app for lead generation.

Voice search is becoming a growing trend. It has taken off because it’s convenient and the best way to navigate through web pages. Voice-based search is useful for older audiences as well as younger generations.

To become discoverable by voice-based searches, web content should be optimized to sound like what people say when they ask a question. This means using keywords that match the user’s actual query and making the search results sound similar to the way people speak.

Well, do not worry since this course covers it also, with topics like:

• Understanding how voice search works.
• Successfully optimize content for voice search.

Now it’s your turn

Voice is a new technology that has been integrated into almost every device in our lives, from computers and televisions to phones and cars. Thanks to the proliferation of smart devices, voice commands have become a critical part of our everyday lives. Voice is not only used in our homes and offices but it can also be used on our phones, cars, and even appliances as well.

This is where having a deep knowledge of this industry comes in handy, especially for companies that are looking to create a voice strategy for their products. You can also create a new career path with a focus on voice application development.

Don’t forget to give us your 👏 !

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Where & How To Efficiently Learn to Create Alexa Skills The Right Way was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

In our previous article, we talked about what virtual onboarding is, how it works, and why it’s important. We even shared a teaser on how you can instantly improve your virtual onboarding process.

If you’ve been waiting patiently for those tips, today’s your day.

Digital-first marketing is a growing trend, even if you think you’re miles ahead of your competition. What you might be missing is conversational AI.

The conversation is the defining element of a digital-first customer experience, and a major shift in the way businesses communicate with customers. Artificial intelligence has led to an evolution of customer service that’s more human than ever before, and customers are beginning to expect much more from their interactions with businesses.

Conversational marketing allows companies to interact with their customers and prospects in the most personal way. Conversations between brands and their customers online facilitate the building of relationships and trust. This technology is proven to generate a happier environment for both the customer and the company.

This will help you convert more and faster, which means happier customers and a happier company.

What is Conversational AI & Conversational Marketing

We’ve become accustomed to automatic responses and a conversational interface, which has increased the expectation for businesses to be able to act quickly. Conversational AI has made it possible for businesses to respond in real-time with a customized experience, resulting in an increase in customer satisfaction.

You’ve probably interacted with a conversational AI these past days.

What is Conversational AI?

Conversational AI is a form of artificial intelligence that uses conversations to help an end-user complete a task. They can be used to engage customers in many types of services such as support, marketing, enter a funnel, and even sales.

As the world moves toward conversational marketing, brands will only become more human. Artificial intelligence, instead of removing the human feeling, has the power to make brands more human, and help engage with customers on a more personal level.

A common use for AI to create different types of conversational marketing experiences is through voice assistants such as Amazon Alexa.

Also, we need to consider that voice assistants like Alexa and Google Home are now built into the homes of millions of users. This means that real-time conversational marketing will let brands participate in direct and uninterrupted conversations at scale.

What is Conversational AI in Marketing?

Conversational marketing is an automated way to engage with customers. It allows internal communication between the business and its customer base in a form of enjoyable, one-on-one communication that directly targets your audience. This makes it more relevant, engaging, and valuable to them than traditional forms of direct mail, messaging, or advertising.

It is utterly important to consider that, in brand-user conversations, giving them a human touch will cause a big difference. And this is where conversational AI in marketing needs to be heading. Human-to-human interaction is always appreciated more than chatbots or other means from customers.

However, technology is making great advancements in NLU (Natural Language Understanding) and NLP (Natural Language Processing). It means that computers have started to become even more capable of understanding what is spoken or written to them. Therefore, more capable of providing an acceptable answer, if not a pleasing one.

Trending Bot Articles:

1. How Conversational AI can Automate Customer Service

2. Automated vs Live Chats: What will the Future of Customer Service Look Like?

3. Chatbots As Medical Assistants In COVID-19 Pandemic

4. Chatbot Vs. Intelligent Virtual Assistant — What’s the difference & Why Care?

How conversational AI works for marketing purposes

Conversational AI is a great tool for marketers to use to gather insights such as key data points, purchasing patterns, consumer habits, and preferences.

AI can be programmed to learn what questions are being asked during conversations and how those questions are answered. It can store that information in the cloud to facilitate the creation of a more personalized customer experience. Later, this will offer you better tools to guide upsell conversations.

Brands can use this technology to be better prepared when it comes time to engage customers and solve problems.

Increasing user engagement

When companies enable their customers to start conversations with their brands, they increase user satisfaction and the chances of being followed up with. Visitors won’t have to fill out lengthy forms. Instead, they’ll be able to have a conversation instantly.

The data and insights you get from the conversations are invaluable, especially the feedback collected from them. For most businesses, it means higher conversion rates, more opportunities to engage with customers, and a more personalized experience.

A Deeper Understanding of Your Customer’s Desires & Needs

Conversational platforms can be used to ask questions to get to the right people and give them the right information at the right time. They are great for tasks that require simple searches and questions. Also, they can help manage complex customer service interactions and increase the efficiency of your customer support. Thereby saving you time and money.

You can also customize your conversational AI to fit your needs by asking more targeted questions based on the information the customer provides.

All this will help you reach a better understanding of what your customers need at that moment, what they wish for, or maybe how to persuade them better.

Personalized & Adaptable Customer Journey

Personalization is essential for conversational marketing. When crafting robust responses to questions, brands should ensure that they take into account previous interactions with their user base.

Personalization helps brands deliver an exceptional service to their customers, increasing loyalty and nourishing a more personal relationship with consumers.

The same goes for the customer journey. By tailoring their services and offerings to fit the needs of their customers, businesses can be able to satisfy them in the best possible way and build a strong relationship.

Offering personalized and adaptable interactions can become a key component in building customer loyalty and increase brand awareness.

Conversational AI applications you might consider & why

What’s the best way to reach customers these days? It’s the conversation that matters the most. Companies need to focus on customer experience and listen to what their customers are saying.

Technology is changing rapidly and businesses need to be ahead of the curve. Conversational marketing is a major trend in the industry and companies that fail to embrace this approach will most likely fall behind.

With digital interaction gaining more power as audiences and customers grow more fond of them, conversational AI is something every brand should aim at.

Let’s look at why brands need to leverage conversational marketing to get ahead.

Attracting new customers by offering amazing experiences

It is important to consider how messages are conveyed around the brand and how they resonate with customers. Consumers are always seeking a positive brand experience. They want to be treated as customers and not as consumers.

If your brand communicates a more traditional or conservative image, consumers may be put off by this. Therefore, communication strategies are incredibly important.

In this case, Conversational AI can become a powerful tool that helps marketing campaigns and facilitate purchase decisions. It can help address issues and questions for customers at every stage of the customer lifecycle, from discovery to checkout.

It’s also an important tool for building customer loyalty because it provides a positive experience for customers.

Reaching and, why not, surpassing your competitors.

There is a high, positive impact Conversational AI can have on a brand’s strategy and campaigns. Precisely this is the exact motive why many brands have embraced them and integrated them into their processes.

Considering this, integrating a Conversation AI platform into your team rises as a key tool towards better performing campaigns and funnels.

Top applications of Conversational Ai in Marketing

Chatbots

Web chatbots are an invaluable resource for any marketer. Chatbots can automate your business processes and save you time, but they are also really useful for specific tasks. For example, chatbots can be programmed to answer common questions at any time of the day. They can also learn over time and become more conversational, so they can answer more questions as you add more products or services to your website.

Voicebots

Voice bots are the solution to today’s customer service challenges. They don’t just allow customers to interact with companies in a way that’s faster and more convenient than typing in a query. They also help them connect with a company that provides high-quality customer service. Their added convenience and efficiency are worth strongly considering.

When it comes to customer self-service tools, Voicebots are essentially a type of customer service tool. They eliminate the need for individuals to call or email and interact with a live person. Instead, they can use voice prompts to get personalized information directly to them.

Digital Assistants for Enterprises

Another use case for conversational AI is as an assistant for company employees. You can use it to assist employees with their work, including meetings, reminders, communication, and much more. It can definitively lower the internal costs, thus saving money to a company. It can also increase employee efficiency and productivity.

Voice Assisted Websites

Having a website with an integrated VoiceBot is a revolutionary service that allows websites to connect to their customers and provide them with real-time assistance. With such a tool, websites can provide personalized directions and information about a product/service quickly and easily. It can also transfer people over to customer support or sales teams. The service is like a virtual assistant that recognizes the voice of each visitor and knows everything about the company’s product/service, guiding them from one point to another.

Voice Applications

The digital generation, those who grew up with technology at their fingers, understand that there is a huge advantage to being connected to the information you need when you need it.

But, as much as the younger generations seek convenience, they also value quality service. Many want to do business online, but they also demand more than simply placing a purchase order.

Voice applications, in this case, have the right capabilities to cover such demands. They enable users to start conversations with brands and to receive support. A brand can customize a voice application to allow users to enter a funnel, get information about their products/services, and buy them.

Using voice technologies like Amazon Alexa and Google Assistant, you can create a more personal relationship with your audience & customers. Later, this will translate to more sales and an increase in customer loyalty.

Why? Because of the convenience, easiness, and unique perspective voice interactions have.

The key benefits of Conversational Marketing

Users seem to like having a support system available 24/7, be it a chat-bot or a voice-bot.

According to Drift, 64% of internet users consider the use of chat-bots as a fast solution for most of the questions. Other studies show that, in the next couple of years, Conversational AI platforms will handle more than 80% of customer care cases.

However, there are more convenient platforms available

The use of voice assistants like Amazon Alexa and Google Assistant has gained a lot of interest lately.

Not only for its Smart Home features or as an in-car assistant but also as a way to connect users with their favorite brands. Also, you need to consider how easy it is to create Alexa Skills or Google Actions.

By doing so and launching yourself in the voice space, you will have the chance to better attract, sell, and assist customers.

The fact that there are more than 65 million Amazon Echo users worldwide, gives a hint of this platform’s reach and the potential it holds.

Also, diving deeper into data, a study from Voicebot, shows that 18% of Millennials use Amazon Alexa for product search or voice-assisted shopping.

Key benefits

A conversation with a brand can be more engaging than traditional marketing initiatives. With conversational marketing, businesses can personalize interactions with consumers through digital experiences that are tailored to their individual needs and preferences.

The result is a unique experience that extends throughout the customer journey as brands leverage various digital channels to engage with customers on a variety of devices such as digital advertisements, websites, mobile & voice apps, and more.

Some of the main benefits Conversation Ai can bring to marketing include what follows:

Customer satisfaction & deeper relationships

Conversational marketing is a powerful way to target and engage customers at each digital touchpoint. By providing conversations, businesses can increase user satisfaction, build trust and confidence, and foster loyalty.

Trust takes time to develop, but it can be built by listening and addressing problems in real-time. By listening to consumer needs, your organization can begin to build a stronger customer relationship.

Better insights, data & analytics

Conversational AI is able to scan through large volumes of data to understand your customer’s behavior and use this information to predict future needs.

Conversational AI can analyze and learn from your customers, automating processes and capturing important data points. These insights can help drive sales and improve customer service. They can also provide an endless stream of questions that you can answer so you can upsell or provide additional information in the future.

Outreach & Engagement

AI-powered conversational tools can engage leads in real-time. They help you get to the heart of a customer’s needs and build a direct relationship with them. Recent researches show that lapses between first contact and marketing or sales contact affect whether leads are converted into customers. Later, you can use such platforms to reach leads with information, offers, and relevant marketing messages. This can help you convert more leads and increase revenue.

Higher conversion and quality leads

If you use conversational AI correctly, your customers will be more likely to convert than if you rely on traditional live chat. You can set up Conversational AI to respond to customer questions right before they’ve made a decision. Conversational AI can improve conversion rates by as much as 40%.

Since AI technology is constantly improving, it works very well to analyze big data blocks and find out the ideal customers for your business. Chatbots are an excellent way to collect huge data sets while also searching through them to help you identify potential leads.

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The importance of using Conversational AI in Marketing & reasons to consider it for your Brand was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

In this article, I am going to delve into some metrics used to measure how well classifiers do their job. So after reading this article you will know how to evaluate classification models and know the difference between the different metrics that we can encounter evaluating classifier models.

In the image shown above, we can see a classification problem. How can we know if this model is good or bad? Let’s delve into this in the following paragraphs.

The most common metric.

The goal of each classifier is to assign one label to one input according to their characteristics, in other words, classifiers can distinguish the instances belonging to different categories. But how can we measure how well a classifier performs this task?

The first idea that comes to our minds is probably to calculate the ratio between the correct predictions and the total of instances. This is, in fact, the definition of accuracy, formally it is:

With the equation shown above, we can calculate how well our model performance is, right? One issue using this method is that in many scenarios we have unbalanced datasets, this is, the number of instances belonging to each class is different. Let’s see a simple example and let’s suppose we have a classifier that identifies malignant tumors and benign tumors. Our imaginary dataset conforms in the following way:

• 10 malignant tumors.
• 90 benign tumors.

If we have a classification model that for every input assigns the label “benign tumor” we can calculate the accuracy as:

We have 90 % of accuracy, a really good model, right? in this particular problem, the model says that all malignant tumors are benign, and this can be a big problem. But how can we know if our model is good or bad?

Positive and Negative labels.

The scenario presented before is a clear example of an unbalanced classification problem when we have a dataset with a different number of instances per class. Due to this, we need to use other kinds of metrics to evaluate the model performance. But first, we need to establish over what label we want to know if its classification is good or bad. To do this, in binary classification problems we used the terms positive and negative labels.

According to this definition, for binary classification problems, we can encounter the following outputs.

• True Positive (TP): A true positive output is an instance from the positive class that was classified as positive. This is one correct prediction.
• True Negative (TN): A true negative output is an instance from the negative class that was classified as negative. This is one correct prediction.
• False Positive (FP): A false positive output is an instance from the Negative class that was classified as Positive.
• False Negative (FN): A false negative output is an instance from the Positive class that was classified as Negative.

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Defining Accuracy, Precision and Recall in terms of TP, TN, FP and FN.

Now let’s express accuracy in terms of both Positive and Negative predictions. The equation is:

Precision

Let’s say we want to know how many mistakes the model makes predicting positive labels, in this kind of scenario we can measure the ratio between the number of correct predictions and the total of positive predictions. Thus we have the definition of Precision.

So, models with high precision will make few mistakes predicting the positive label, that is, the number of False Positive outputs tend to be close to zero. In the extreme scenario where the model is 100 % precise we can trust that all the instances predicted as positive are, in fact, the positive class. Let’s see a simple example of a model with high precision.

In the image shown above, we can see the most simple model that we can build, a simple line, this line separates the Positive instances (blue) from the Negative instances (red). Let’s calculate the precision for this simple model.

• True Positive: we have 2 positive instances classified as positive instances, then TP =2
• True Negative: We have 6 negative instances classified as negative instances, then TN = 6.
• False Positive: There is any negative instance classified as positive, so in this case FP = 0
• False Negative: We can see on the left side 2 positive instances classified as negative, so the FN = 2

The model shown above can classify positive instances correctly, however, we can encounter some positive instances classified as negative, thus the model cannot identify all the positive instances. We might have a high number of False Negatives.

Recall

But what happens with False Negative Outputs? Is one model with high precision able to find all the positive instances? probably not. So, how can we measure the ability to find all the positive instances?. If we want to measure how well the model identifies positive instances, we have to take into account all the positive instances in the model output, this implies considering both the True Positive and False Negative instances. Thus, we can define the Recall metric as:

If the model can find all the positive instances, the False Negative outputs tend to be close to 0, then a model with high recall can identify all the instances belonging to the positive class.

Now in the image, we have a model with high recall, let’s calculate both recall and precision for this example.

• True Positive: In this case we have 4 instances from the positive class classified as positive instances, then TP = 4
• True Negative: We have 2 instances from the negative class classified as negative instances, then TN = 2
• False Positive: On the right side of the line we can find 4 instances from the negative class classified as positive, then FP = 4
• False Negative: On the other hand, the left side does not have any instance from the positive class, then FN = 0

The model can find all the positive instances, nonetheless, it makes some mistakes classifying negative instances as positive ones.

Which is better, presenting the F-score?

So, how can we know if our model is doing the task good or bad? how can we compare this model with others?, To answer these questions we can use a metric that combines both recall and precision. This metric is called F1-Score and is defined as:

The F1-Score penalizes both low precision and recall, thus in models with high F1-score we’ll have high precision and high recall, however this is not frequent.

We can use the last equation when both recall and precision are equally important, but if we need to give more importance to one specific metric we can use the following equation, which is the general F-Score definition.

This more general equation uses a positive real factor beta that is chosen such that recall is considered beta times as important as precision. The two most common values for beta are 2, which weighs recall higher than precision, and 0.5, which weighs recall lower than precision.

It’s all about context.

For every problem that we are dealing with, we need to pay special attention to the problem context. In this way, we might prefer a model with high precision rather than one with high recall or vice versa. For example, let’s consider again our tumor classifier, in this scenario we want to identify all the possible malignant tumors (high recall) even if this implies making some mistakes and classifying some benign tumors as malignant tumors.

Let’s consider this situation, if one patient has a benign tumor and by error is detected as a malignant tumor, it is probably that this patient will obtain more medical attention, and eventually this error will be detected. Conversely, if we classify a malignant tumor as a benign tumor, this patient maybe won’t have more medical attention until the consequences of this mistake be evident and perhaps too late to fix this error.

Conclusions

In this post, I talked about the importance of considering other metrics to evaluate models, beyond the simple definition of accuracy, and also we learned that we have to pay attention to the context. The problem can give us clues to decide what metric can be better according to the specific problem that we are trying to solve.

However, in real life we can find scenarios where we need to consider more than two classes, these problems are called multi-class classification, and in these cases, we don’t have Positive or Negative instances, nonetheless, we can make some assumptions to deal with this kind of problems.

I am passionate about data science and like to explain how these concepts can be used to solve problems in a simple way. If you have any questions or just want to connect, you can find me on Linkedin or email me at manuelgilsitio@gmail.com

References

• F-core from Wikipedia.
• Recall vs. Precision.

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Evaluating classification models. Accuracy, Precision and Recall. was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

Is customer success just a buzzword? A jazzed-up, rebranded version of customer service?

Or could it be something more?‍

What is customer success?

Customer success is all about making sure that your customers get exactly what they want while using your offerings. It revolves around the philosophy that you succeed only when your customers succeed. An effective customer success strategy could be the difference between having a high churn rate and having customers that turn into brand evangelists.

Essentially, customer success is exactly what it sounds like — setting your customers up for success.

How is customer success different from customer support?

Customer service tends to be reactive in nature. It’s all about resolving the customer issues after they arise. You solve their problems and hope to make them happy.

Customer success takes another approach. It’s proactive. Customer success teams try to solve problems before they even arise. Customer success involves constantly looking at feedback and data, hunting for ways to streamline the experience and help customers achieve their goals.

Customer service representatives help with customers only when they have questions or issues, but customer success teams work together with customers proactively to help them get the most out of their purchase.

While customer service tends to be transactional, customer success is all about building and nurturing relationships. Customer success involves understanding your customers’ organizational goals and KPIs, ensuring that your offerings help them exceed their goals.‍

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Why is customer success important for your business?

Your business cannot succeed in the long run if you do not focus on helping your customers succeed. That would leave you with abysmal retention rates, forcing you to spend a ridiculous amount of time, money, and energy trying to acquire new customers, most of which would not stick around with your business for too long.

Customer success management is very effective at helping you retain customers for the long haul, but it even helps you earn new customers. When you make efforts to help them achieve their goals, your customers will turn into brand evangelists.

Research shows that only 1 in 26 customers who face issues tend to reach out and complain. And 91% of customers who don’t complain, simply leave. That means, without a proactive customer success strategy, without looking to resolve issues before they arise, you stand to lose most of your unhappy customers. Now you’re back to spending absurd amounts of money hunting for new customers when you could have got recurring revenues from your existing ones by focusing on customer success.‍

How does customer success influence your customer experience?

Customer success helps your business look at the customer experience and understand it better. It involves using data and feedback to find potential gaps in the customer experience and also looks for ways to improve the experience and create new peaks.

Essentially, customer success is a part of the overall customer experience, but it plays an important role in understanding the improving the overall customer experience.

How does customer success drive revenue for your business?

The most obvious way in which customer success helps drive revenue is by renewals. When you set your customers up for success and guide them, solving problems before they arise and help them get the most out of your offerings, they’re likely to stick around. If you have a subscription-based business, this means they won’t need to spend too much time figuring out whether renewing their subscription is worth the investment.

But that’s not the only way it helps you increase your revenue.

Your acquisition activities got them in the door, your customer success activities got them to stay, and they played a key role in getting your customers to trust you. This means that it paved the way for you to cross-sell and upsell them.

They already know that you will be there for them when they need help with these new solutions as well.

3 powerful customer success tips

1. Do not limit customer success to silos

Your customer success team should never alienate itself from other departments in your organization. They should work with all these departments, collaborating with the common goal of eliminating customer problems and helping them get the most out of your solution.

If yours is a SaaS company, this could involve working with the tech team to solve problems before they arise.

2. Create a well-defined customer success program

You can’t just wing it. You need to have a clearly thought-out plan and allocate dedicated resources if you can afford it.

But, you need to remember that planning it is not a one-and-done activity. As your business evolves, so should your customer success program.‍

3. Provide your customers with all the information they need

You know that most customers who face issues don’t reach out. A lot of them will try to solve the issue on their own — give them the resources they need to do that.

Create a knowledge base and maintain a blog that deals with common issues that might arise.

To make it even easier, create a chatbot that helps them find the information they need without having to navigate through your website. Or eliminate the effort involved in opening your website by deploying the bot on WhatsApp, Messenger, Telegram, and other channels which they spend time using.

TLDR

It is impossible for your business to succeed if you do not focus on helping your customers succeed. Set up a dedicated them that focuses on helping them make the most of your offering and eliminates issues before your customers even face them.

Deploy an intelligent bot that can answer all their questions in their language of choice, without making them wait at all.

Setting your customers up for success is a surefire way to increase customer loyalty and cause a massive spike in your customer lifetime value.

Don’t forget to give us your 👏 !

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What is customer success? Does it drive revenue for your business? was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.