Less than three decades ago, in the late '90s, the first rays of digital disruption shone across traditional banking with the expansion of usage of home PCs and the development in home internet connections. Allowing customers to check their account balances, review their financial transaction and pay their bills from the convenience of their homes, or offices.

A decade later, and as smartphones became the channel of choice for many on the go customers, Mobile banking was born to fulfill the needs of those who need access anytime and anywhere, and although many banks started by just offering mobile-friendly versions of their internet banking channels, the overwhelming customer demand for more functionalities, forced banks to give mobile banking its own identity as a separate channel, developing powerful mobile banking apps with unique functions. Causing mobile banking to become the most frequently used banking channel in many countries around the world.

Fast forward to about three years ago, where development in technology and innovation accessible to the banking industry, allowed banks to consolidate their Internet and Mobile banking services into a single platform that allowed a unified user experience across different channels, whether it was online banking, Mobile banking (Mobile Banking apps, Virtual Wallets, etc .. ), and even through ATM Services, offering customers a unified, more personalized and on the go experience.

Technology role, Machine Learning, and AI

Advances in Machine Learning and artificial intelligence (AI), have allowed more and more banking organizations to leverage artificial intelligence to launch chatbot solutions, reducing costs and serving increasingly tech-savvy consumers, and to facilitate two-way communication, and in many instances, replacing channels such as phone, email or text, allowing customers to ask questions or request services using natural language.

As a result, the last couple of years has seen an increase in the number of banks adopting automated conversational agents or Chatbots in their mobile banking platforms, from Ally Bank’s Ally Assist in 2015, one of the first banks to implement a chatbot, the Bank of America’s Digital Agent Erica that with over 1M users, Wells Fargo’s chatbot, TD Bank’s Clari, Capital One text-based chatbot assistant Eno among others.

The goal is to provide customers with quick service and transactional support, handling the most basic tasks such as balance inquiry, bank account details, loan queries etc. that can be handled efficiently by a chatbot, freeing customer service representatives time for complex issues

“Chatbots will power 85% of all customer service interactions by the year 2020” — Gartner

Chatbots in Banking, common use cases

No AI has “yet” been able to successfully handle 100% of customers queries, and as we await further technology breakouts that will enable us to rely more and more on an automated solution, the banking industry has also its own policy and regulatory limitations that will still require licensed human bankers to handle certain tasks.

This means we’re still a long way from seeing an all automated, AI-powered banking service, yet, the cost of effectiveness of the tasks that a Chatbot can handle in a banking environment is more than enough to have banks racing to integrate such a service for their customers, where some of them has been:

• Frequently Asked Questions (FAQs): One of the most basic tasks of a Banking Chatbot or Digital assistant, providing an automated service that answers questions like where is the closest ATM or branch, how can I reset my password, how can I block my lost card, etc. Can easily free up very important and expensive contact center time, in addition to saving customer’s time by providing an answer on the go instead of the long waiting times, especially in crucial times when every minute counts, such as in the incident of losing your wallet with a credit card for example.
• Account Services: Answering simple account services and payment requests, questions about deposit and credit card accounts, transactions, payments etc … providing a seamless customer experience.
• Financial Goal-setting and spend tracking: Integrated with the right historical data, predictive banking, and other intelligent analysis platforms, Chatbots can answer customers questions around spending and budgeting, helping customers manage their financial life, and becoming their trusted financial advisor that they chat with on the go!

“ Chatbots will be responsible for cost savings of over $8 billion per annum by 2022, up from $20 million in 2017.“ Juniper

Digital Disruption: The Future for Banks

Startups and new entrants are changing customer expectations disrupting business models and revenue streams, development in technology and facilitation in regulations is allowing new players to enter the marketplace, Digital-Only Banks, Fintech disruptors are all looking for a piece of the pie.

Banking leaders who want to succeed in a digital economy need to make fundamental changes to how they operate; respond to opportunities for innovation, introduce services quickly, test and learn from the market’s response, and address the fast changes needed in the core business of banking. Only by adopting a digital mindset they will they be able to create value for customers and stakeholders and survive in the age of digital disruption.

Conversational Banking: Chatbots & the Future of Banks in the age of Digital Disruption was originally published in botique.ai on Medium, where people are continuing the conversation by highlighting and responding to this story.

The rising customer expectations are driving many brand’s technology races towards providing the best customer conversational experience possible, as customers are moving away from old-style ticketing systems, with long waiting times based on the availability of human agents, and looking for meaningful, real-time conversations with brands that understand their needs and are able to provide the experience they are looking for.

Recent studies had shown that within a coming couple of years, over 85% of all customer interactions will be handled by automated self-service systems, and without the need for any intervention from a human agent, achieving this has been facilitated by the recent rapid development in conversational artificial intelligence platforms that has been able to engage users, understand their needs and provide them with answers.

The key point here is the ability of the brand to engage with customers, provide them with answers or resolve their customer service issues before churn, as the vibrant nature of today’s world life, and the fierce competition in many industries is providing users with many alternatives for any service or product they are seeking.

To achieve that, brands are required to integrate their current customer engagement channels with Natural language processing, and machine learning capabilities that are able to recognize the context and intent of a customer’s need and personalize the response, based on the context and the language of the user.

Self Service Conversational Artificial Intelligence platforms such as botique.ai are able to provide users with seamless conversational experience, that is able at any point throughout the conversation to jump from any step in the flow of conversation to another based on the customer’s input, unlike structured or flow conversational platforms, they are able to dynamically follow the flow of the conversation, and provide unstructured content in an absolutely no predetermined flow.

Brands who have implemented botique.ai solution in different verticals, such as banking, telecommunications, and insurance companies, have seen a significant increase in customer satisfaction, in many cases, botique.ai self service platform has been able to handle over 60% of the loads of these customer centers, compared to a mere 10%-15% for a speech-enabled or DTMF IVR systems, in which the customer needs to speak on average to three agents before their issue is resolved.

On the other hand, those brands have seen a significant decrease in returning customers, with issues being handled by botique.ai conversational artificial intelligence self service platform faster and with a higher resolution success rate. In addition to a significant decrease in average handling time, and lower internal transfer numbers.

Even in cases where the botique.ai self-service platform was unable to provide an ultimate solution for issues, the average handling time was decreased significantly since the automated platform was able to handle the first tier support and time consuming tasks such as authenticating the customer, collecting issue related information, before elevating the ticket to a human agent who can resolve the issue, resulting in saving 45–60 seconds of agent talk time, which not only helped the customer solve their issue sooner, but also resulted in a significant cost reduction for our clients.

Botique.ai offers brands an innovative solution to providing self-service, automated customer support anytime, anywhere. Offering a conversational self-service experience that provides answers in real time. Brands can easily customize their agents for their specific business needs, providing customers with content recommendations that fit their needs, in the brand’s own voice and tone. In addition, the platform provides brands with deep analytics and insights on customer’s engagements with the automated agents, helping them understand customers needs and behaviors.

Self Service Conversational Customer Engagement Channels are the Future was originally published in botique.ai on Medium, where people are continuing the conversation by highlighting and responding to this story.

As more businesses lean towards the use of a multi-channel approach to engaging with customers, consumer demand is growing for a service that is able to seamlessly cover all channels, from physical to digital, in the US alone, over 213 million adults access the internet with an average of 4 different devices. Customers are more connected, empowered, and have more control over the buying process than ever before.

Understanding the Customer Journey

Long gone are the days where the Customer Journey followed a linear direct path to purchase, what used to be illustrated by the traditional “Marketing Funnel”; Awareness, Consideration, Evaluation, and ended with the decision to Purchase, is now a journey that spans days, times, locations, and channels, switching from digital channels such mobile, social media, blogs, and websites to storefronts, magazines, newspapers or billboards.

Today’s customer’s journey cycles through the stages, customers enter and exit relationships with businesses at much less predictable points going backward as well as forward in their journey, or circling back to previous providers and choices. Customers are frequently checking out other options online while in physical stores; more than a fourth of customers who search for information in-store end up buying in a different channel.

Businesses, on the other hand, are able to leverage new technologies to develop personalized marketing strategies, and to deliver a superior customer experience that educates and engages the customer, but how can this be done?

Omnichannel Marketing

Omnichannel marketing focuses on creating a seamless customer experience across all channels of engagement with customers. Integrating the in-person or physical customer interaction such as in-store experience, printed ads face to face interactions at events or with salespeople, with digital interactions such as websites, social media, mobile, or self-serving platforms. Omnichannel marketing integrates those channels into a holistic approach that unifies every touchpoint the customer has with the business. Or as in the words of John Bowden, Senior VP of Customer Care at Time Warner Cable

“Omni-channel anticipates that customers may start in one channel and move to another as they progress to a resolution. Making these complex ‘hand-offs’ between channels must be fluid for the customer”

But what does that mean for businesses?

To be able to understand what that means on the operations side of the business, let’s explore an in-depth example of how the customer journey works in an omnichannel approach.

Let’s assume that while scrolling through your Instagram stories, you see a promoted story post for one of the well-known electronics stores, featuring a sale on selected items, from the ad, you click on the link that takes you to the store’s website to view the items on Sale.

After viewing the website, you decided to purchase a new gaming console that is on sale, you engage with the Digital Agent or Chatbot sitting on the website to ask questions about the features of the console which the AI-powered Chatbot is able to answer you in free text method, from there you are able to add the console to your cart and check out online using the same chatbot you were engaged with, securely providing your payment information, while you do, the chatbot asks about the delivery method, one of which is in-store pick that is available this evening instead of waiting for three-day delivery. You also ask the intelligent agent about the availability of the item in the store near you, so that chatbot connects to the store inventory system and verifies the availability of the console with the color, storage size that you requested. Excited about your new console, you ask the chatbot for in-store pickup!

You walk into the nearby store where you can find a clearly labeled area for online order pickup, providing your order number and promptly receiving your brand new console. You return home to connect your console while receiving guidance and support from the store’s Automated Support agent (chatbot) via text messages on your mobile phone.

Of the channels used here (social media, the store’s website, automated intelligent Chatbots, SMS, and the bricks-and-mortar store) the entire customer journey was uninterrupted. This is a simple example of how an omnichannel approach would look like from a customer point of view.

To be able to execute this, every business is supposed to invest into developing its own omnichannel strategy that offers its customers the best user’s experience. Understanding the business’s goals and initiatives, and aligning them with the efforts of the different teams, from products, marketing, sales to customer support and customer success. Integrating, of course, the right tools and technologies that will automate and optimize the process for a seamless customer handoff among the different stages of the journey.

Harnessing the power of Context

A no brainer for marketers that still can be easily overlooked is Context. Focusing on context within an omnichannel strategy allows marketers to takes into account the customer preferences, history, devices, platforms used, in the right place, and at the right time to deliver the right content or experience to the right person, making all the difference for a business moving a prospect along the stages of the journey to losing her for competition.

Closing Thoughts

In a 2015 KPMG 2015 Global Consumer Executive Top of Mind Survey, Jeanne Johnson, Head of omnichannel at KPMG, explained how, traditionally, company departments and processes were siloed, limiting their ability to manage and efficiently integrate new sales, promotion or distribution channels. This linear business model has been disrupted as the digital world has consumers “coming at manufacturers and retailers from all directions — and not just through their own channels or in a predictable order.”

Technology advances can quickly disrupt what a business has worked hard to establish. Companies like botique.ai are providing businesses with tools that are able to automate end-to-end customer interactions using conversational AI, while integrating with backend systems to facilitate the customer’s journey from the very first stage of recommending content, answering questions, providing quotes, to sales, and providing customer support. Providing a seamless conversational omnichannel approach that makes it easy for any business to harness the power of AI within its omnichannel strategy.

Omnichannel Strategy, What does it really mean? was originally published in botique.ai on Medium, where people are continuing the conversation by highlighting and responding to this story.

If you have been following the Retail industry for the last couple of years, this was the warning many experts and advisors in the retail industry, and focus of multiple articles.

The Retail Apocalypse

The “Retail Apocalypse” promoters argue that the growth of eCommerce will eventually put traditional Retail to rest. eCommerce is on the rise, as one of the most popular online activities worldwide, with global eCommerce sales reaching 2.3 trillion U.S. dollars in 2017 (a total global retail sales share of 10.2%), and projected to rise to $4.5 trillion by 2021 (a total global retail sales share of 17.5% ).

They argue that the retail industry appears to be going through an existential crisis, many traditional retailers have stopped growing, have been closing traditional brick-and-mortar stores (Macy’s, JCPenney, Staples and Sears Holdings had announced widespread store closing plans last year, The Limited closed all of its remaining stores, luxury retailer Neiman Marcus announced that it is looking at a possible sale of the company after it was forced to drop plans for an IPO.

In addition, according to CNBC, more than 3,000 stores were slated to be closed in 2018 by retailers including Claire’s, Signet Jewelers, Ascena Retail Group, Best Buy. Ralph Lauren announced the closing of its New York’s Fifth Avenue flagship store among others, in a step that came amid considerable upheaval for retailers that rely heavily on physical stores, as shoppers, especially millennials, are making more of their purchase online.

Is this really the case?

On the other hand, the opposing camp argues that the idea of having bricks and mortar is still an important part of businesses, as most companies admit they can’t succeed in retail without stores, with several reports and studies pointing that for every company closing store, there are 2.7 that are opening stores. In addition, it is why one of the only two trillion dollar companies, Amazon, is reportedly planning to open 3,000 Amazon Go stores by 2021.

Although it might seem that, when looking at individual sectors, there are clearly areas with retail that are challenged, overall the retail Industry is healthy, and every industry experiences turnover and change, forcing its companies to adapt their business models to overcome these changes.

What everyone is agreeing upon though …

What both camps do agree upon, is that the rise of eCommerce has been the biggest disruptor to traditional retail in recent years. eCommerce has and will continue to have, a dramatic impact on virtually every aspect of retail. The dramatic share shift from physical stores to digital commerce cannot be ignored, nor the transformative effect of e-commerce on pricing, product availability, and shopping convenience can be underestimated. With more people choosing to shop online, traditional retailers are finding it harder to attract customers to their stores.

Digital First Strategy

With disruption comes change, and what retailers need to do in order to be able to sustain and grow their businesses is to rely on technology tools, introducing technology into the overall consumer experience, as a tool to complement the digital consumer experience with the in-store experience, cleared the way for for the emergence of the “Digital-first Retail” concept, which is the tendency of consumer journeys to be influenced by digital channels, regardless of where the ultimate transaction takes place.

This is why, some of the world’s leading brands, from Apple to Nike to Wal-Mart, are investing money and resources (i.e., people) into creating product content (descriptions, benefits, images, videos, reviews) that serves as the bridge between the online and offline worlds. Rich product content both online and offline (in-store) became a must have for brand manufacturers and retailers looking to increase sales.

And this is also why, eCommerce titan, Amazon, has started investing into brick-and-mortar stores, an area of retail that Amazon originally disrupted, but it’s not about replicating this experience, it’s about trying to move quickly into the new space that is being created, where both the digital and the physical consumers’ experiences complement, rather than contradict, each other in creating an improved retail experience for the consumer, and where traditional retailers are trying to move into in order to sustain.

Retailers need to focus on creating a retail experience, where both the digital and the physical consumers’ experiences complement rather than contradict each other in creating an improved retail experience for the consumer

To make the digital transition, forward-thinking companies have been implementing technologies that allow the branding and product interaction to be intensely customizable and personalized.

Consumers’ journeys to purchase are being constantly and dramatically influenced by digital channels in a variety of locations, from in-store displays, augmented reality-equipped stores that allow the user to experience a product before purchasing, mobile engagement with AI-powered Digital Agents and Chatbots that facilitate product discovery, recommendation and support, QR code based payment solutions that help customers skip long payment queues, Artificial Intelligence, Machine learning, and deep data that helps retailers understand consumers behaviors and needs, Robotics, Sensors, and Cameras, are utilized as well to help optimize in-store economics, design better product offerings, and marketing campaigns.

How do Chatbots fit into that mix?

A Chatbot is a computer program designed to simulate conversation with human users, especially over the Internet, Artificial Intelligence Chatbots are able to identify the user’s intent and answer questions in a conversational human style

Harnessing Conversational Artificial Intelligence, or AI powered Chatbots, retailers will be able to provide consumers with a combined digital, personalized, and instant conversational experience. Available 24/7, during all the steps of the consumer’s journey from discovery and research, to purchase, and later on support. Chatbots are able to provide retail with valuable tools to engage consumers, whether in-store or even before they make the purchase decision and step a foot in the store.

In addition to Customer Engagement, some Conversational AI platforms, such as botique.ai provide data and analytics regarding consumer behaviour, information on brands and products they engage with, customers’ frequently asked questions, and support cases, all of which is valuable insights for brands or retailers to help them understand their consumers, analyze issues in their value chains or consumer journeys, and align products and content to customers’ needs.

Recommendations about specific products, answering consumers’ questions, real-time advice on brands and products, processing orders and purchases, accessing product and inventory updates, in-store availability for purchases and pickups, providing fast and responsive 24/7 customer service. Chatbots are able to engage consumers along the different stages of the consumer journey, and across all digital channels; text, email, in-app, website, etc…

“Chatbots will be an important part of every Retailer’s digital arsenal for the coming change”

Retail is not going away, traditional retail is, the block and mortars, will eventually evolve from the way we know them as a place that drives sales, to a hub where customers learn, engage, and experience brands and products, a place where Sales will not be the main focus, but where both the digital and the physical experiences complement, rather than contradict, each other in creating an improved retail experience for the consumers, in-store customer experience will be the most profitable product retailers will sell in their stores.

eCommerce, The new dawn of Retail, and the rise of Chatbots was originally published in botique.ai on Medium, where people are continuing the conversation by highlighting and responding to this story.

Prior to the Internet, success in retail was said to hinge on location. Now, the Internet is a global marketplace, affording even the smallest retailer a national — if not an international — presence.

This presents a different kind of challenges, the challenges of success, scaling up, meaning retailers might reach to a “breaking point”, where they are unable to keep up with incoming orders, constantly changing inventory levels, customer support, etc .. and while hiring more people isn’t always a valid option or a solution to this challenge, the need for Automation tools emerges to help retailers succeed; by saving time, money, and human effort.

On the other hand, customers are becoming more demanding, not just in the way they choose to buy, but also in the ways they wish to communicate with businesses, many traditional online experiences simply aren’t capable enough. The advances in conversational AI and the development of AI Chatbots allowed for the emergence of a new field, the field of Conversational Customer Experience, and Conversational Process Automation.

Chatbots have a huge impact on the ways businesses engage their customers. Powered by natural language processing, machine learning, and Process Automation capabilities, are able to perform all sorts of tasks that help businesses better serve their customers. 24/7 availability, offering detailed and personalized customer service, and can easily manage huge volumes of clients in multiple languages.

So what exactly can they do?

In this article, we will be discussing the 5 ways a Chatbot can boost your e-commerce business.

1- Enhancing Customer Service

Customer service is the main reason that makes consumers return to an online store or not.

Today consumers are determined and savvy, they will spend lots of time researching products online, reading reviews, and comparing prices in order to get the best deal possible. According to Statista:

“Around 42% of U.S. consumers had searched and purchased products or services online, while 14% prefer searching online and buying in store.”

A customized service that caters consumers needs, provides recommendations and suggestions, the same way a traditional knowledgeable Salesperson would (if only a Salesperson was able to learn an infinite amount of information and process them in milliseconds!), and that’s what a Chatbot can do!

Enhancing your customer service with Chatbots guarantees an upgrade of quality in customer service. A Chatbot can engage website users and answer all their questions throughout the different stages in the customer journey, recommending different products to customers, encouraging customers to make a purchase, answering questions regarding products, shipping, and delivery.

2 — Reducing Abandonment

Customer abandonment is one of the major challenges in the e-commerce industry, Abandonment is an e-commerce term used to describe a visitor on a web page who leaves that page before completing the desired action. Examples of abandonment include shopping cart abandonment, referring to visitors who add items to their online shopping cart, but exit without completing the purchase. Statistics form Baymard Institute report cart abandonment rate of up to 81.40%, which costs e-marketers up to 4 trillion dollars per year.

On the bright side, Chatbots are able to understand consumer behavior, initiate a conversation based on consumers intents, help provide the consumer with answers to his questions without having to leave the page or the cart and look for shipping info or return policy, recommend different products, and potentially help the consumer finalize the transaction.

3- Improving your marketing

A Chatbot can be your next Marketer! While many consumers might ignore your promotional Ads or site popups, botique.ai statistics has shown that almost 83.1% of consumers opted in for notifications from a botique.ai powered Chatbot about new products and updates after a successful engagement with the Chatbot on a Website or Social Media. botique.ai Content Recommendation engines learn customer’s interest, needs, and likings based on information from the conversation and historical data, and provide customized recommendations for content or “products” tailored upon the customer’s needs.

4- Omni-Channel and Conversational

Customers must be able to communicate with the brand or business 24/7, and as phones aren’t used to make phone calls anymore, millennials grew up with the gradual introduction of instant messaging, texting, email, and other forms of written communication. Thus being able to provide a text base conversational channel is vital to any business as people around the world are now connecting to chat apps not only to chat with friends but also to connect with brands, search for different services or products and watch video content.

And while many brands already provide engagement and support tools over different Social Channels, an Omni-channel will surely help any e-commerce business cut cost and effort by being able to engage customers over different channels from social media, to SMS, Email, or other conversational apps and platforms, thus reducing the hassle of managing different Platforms.

Chatbots will definitely do a lot for your e-commerce website by being omnipresent and conversational.

5- Increase Effectiveness and lower cost

Chatbots create direct lines of communication with multiple potential and existing customers at the same time. A Chatbot will help to Collect Leads, Recommend products, Retrieve and update account and payment information, answer frequently asked questions regarding products, services, billing, shipping, etc .. in addition to reducing response time and first call resolution times. Thus increasing your businesses effectiveness, and reducing costs.

According to a Business Insider report on the B2C Customer Experience:

• 69% of consumers would use a chatbot before engaging with a human, as consumers would prefer to receive an immediate answer.
• 43% percent of consumers said they perceive companies that use chatbots as innovative. Moreover, 21% of respondents noted the chatbot they engaged with was fun to talk to.
• Over a fifth of respondents would consider buying products and services through an interaction with a chatbot, and these respondents are willing to spend $410 on average.

If you’re in the field of e-commerce, Don’t waste more of your business time and money, contact botique.ai team for more info!

Five Ways a Chatbot can boost your E-Commerce Business was originally published in botique.ai on Medium, where people are continuing the conversation by highlighting and responding to this story.

Did you ever come across one of these terms during a research on Machine Learning or Chatbots? NLP, NLU, and NLG?

With all the buzz around Artificial Intelligence recently, I thought it would be useful to identify some of the core building blocks of Conversational AI while giving an example of its application in botique.ai Conversational Process Automation Chatbot Platform for Contact Centers.

NLP, NLU, and NLG all have one thing in common: They are always thrown around while talking about Conversational AI and Chatbots, and for many people, it usually seems that they’re all interchangeable with each other!

But don’t confuse them yet, it is correct that all three of them deal with human language, but each one is involved at different points in the process and for different reasons.

This quick article will try to give a simple explanation and will help you understand the major difference between them, and give you an understanding of how each is used.

What is the difference between NLG, NLP, and NLU?

These are the three basic acronyms used most frequently when discussing language related AI-technology:

• NLP — Natural Language Processing
• NLU — Natural Language Understanding
• NLG — Natural Language Generation

Employing these technologies builds conversationally intelligent applications that are able to engage with humans on a conversational level. Let us explore each one, and a real-life application will follow shortly!

Natural Language Processing (NLP)

NLP is the used to describe the ability of a system or a machine to ingest what is said, break it down, comprehend its meaning, determine appropriate action, and respond back in language the user will understand, according to Wikipedia “Natural Language Processing is a subfield of Artificial Intelligence that is concerned about the interaction between computers and human natural language”. NLP makes it possible for computers to read text, hear speech and interpret it, measure sentiment and even determine which parts are relevant. It has become really helpful resolving ambiguity in language and adds numeric structure to the data for many downstream applications.

Some of the basic NLP tasks are parsing, stemming, part-of-speech tagging, language detection and identification of semantic relationships. If you ever diagrammed sentences in primary school then you have done this manually before.

In general, NLP falls under the larger umbrella of Artificial Intelligence (AI), and it (NLP) combines both NLU & NLG as part of it.

Natural Language Understanding (NLU)

NLU is a subtopic of Natural Language Processing that uses AI to comprehend input made in the form of sentences in text or speech format. It enables computers to understand commands without the formalized syntax of computer languages and it also enables computers to communicate back to humans in their own languages.

NLU goes beyond just understanding the words, it interprets meaning in spite of human common human errors like mispronunciations or transposed letters or words. The main purpose of NLU is to create chat and speech-enabled bots that can interact effectively with a human without supervision.

Natural Language Generation (NLG)

The task of NLG is to generate natural language from a machine-representation system such as a knowledge base or a logical form. To simplify this, NLG is like a translator that converts data into a “natural language representation”, that a human can understand easily.

Some of the most common implementations are; written analysis for business intelligence dashboards, reporting on business data/data analysis, personalized customer communications via email and in-app messaging, IoT device status maintenance reporting, individual client financial portfolio summaries and updates, e-commerce product descriptions, and category landing page content.

How do NLP; NLU and NLG relate with each other?

Architecture Diagram for Chatbots ( https://goo.gl/3fRAvH )

When NLP breaks down a sentence, the NLU algorithms come into play to decipher its meaning. It is quite possible that the same text has various meanings, or different words have the same meaning, or that the meaning changes with the context.

Knowing the rules and structure of the language, understanding the text without ambiguity are some of the challenges faced by NLU systems. NLG does exactly the opposite; given the data, it analyzes it and generates narratives in conversational language a human can understand.

To build machines that understand natural language, we need to use NLP to perform the Sentiment analysis or opinion mining; which deals with using automatic analysis to find sentiments, emotions, opinions, and attitudes from a written text towards a subject. sentiments must be extracted, identified, and resolved, and semantic meanings are to be derived within a context and are used for identifying intents.

• Intents* activities that a user intends to do, or verbs (activities that the user needs to do). If we want to capture a request, or perform an action, use an intent. Like I want to purchase a data package, or I want to cancel my subscription.
• Entities* are the nouns or the content for the action that needs to be performed. In this example above “data package” and “subscription”.

For example, one use cases of botique.ai’s Digital Agent is the case of Travel Insurance. botique.ai Digital Agent receives a simple text from the customer wanting to purchase a Travel Insurance Coverage:

User: “I want to purchase insurance to Berlin starting tomorrow till Dec 9.”

Using Proprietary NLP Algorithms, the Digital Agent breaks down the sentence to understand it as follow:

purchase {intent} / Insurance {Entity} / Berlin {Entity} / Tomorrow (Nov 28) {Entity} / Dec 9 {Entity}

Using the geographical context and the current location of the user to set the destination details: Berlin, using the Time Context it to understand that Start Date “Tomorrow” and the End Date: Dec 9, 2018,

The platform is able to understand the request of the user, a Travel Insurance Package to Berlin from Nov 28 — Dec 9. The platform can verify further information like Age, Email, etc… to best decide the package. Request verification information like Account ID or password (or Two-way authentication). Connect to the enterprise system to provide the user with a price quote, user can proceed with payment, where the platform can verify the payment details and proceed with the purchase. Full Conversational Process Automation, without any human interaction.

Customer service is reaching a pivotal point where businesses must either embrace the technological tools of the future or risk their reputation by falling behind competitors. Either way, it will no longer be an option to stay the status quo. Exciting advancements are being made in this field. Follow botique.ai to stay up to date!

NLP, NLU and NLG Chatbots explained. was originally published in botique.ai on Medium, where people are continuing the conversation by highlighting and responding to this story.

Let’s take a closer look at the features of the dashboard of botique.ai Digital Agent Platform, and learn what can be done.

Edit your questions and Answers. By using our Small talk feature you will be always able to access your QnA database. There, you can edit, remove or add any question that you left out or you found out was being asked but did not take into account when designing your Frequent Questions and Answers and using botique.ai Quick Predict© feature automatically analyses questions, suggest different keywords and synonyms of words to be used, in addition, to providing alternative questions users might ask. (Want a watch our tutorial! click here).

Check your users’ behavior. Review your user behavior analytics and calculate your ROI. botique.ai’s personalised dashboard gives you the complete analytics and insights to help you better understand users’ behavior and engagement as well as to present it to your team and management.

Here are some of the numbers you can get with our Chatbot Dashboard:

• Total users engaged
• Returning users
• Total conversations
• Questions asked
• Questions answered

and many others…

Manage Roles. The Dashboard allows you to manage the roles of each of your team, from Team Managers, to Customer Service Rep. Each will have their own rights and access. The Dashboards makes sure you manage who is allowed to use, admin and deploy chatbots, and to access the administrative consoles.

Built-in Live Chat Platform. This feature allows your users to contact you directly without using any other application or software. Connect with your users and escalate your conversations to Human agents at any time, at no extra cost!

Test the console. Engage your bot and test its behaviour and answer to certain items. With this feature, you will be able to check your updates and added questions.

Personalize your Chatbot appearance. Customize your Chatbot’s default messages background color, text bubble colors, fonts, change or upload your logo, among others.

Integrating business tools and more. When publishing the Chatbot you are able to integrate it into your business systems (Content, Customer Relations, Management Systems) web applications, and websites.

Check our new and easy to install QnA Digital Agent at botique.ai and enjoy managing and customizing your Chatbot from our Dashboard.

botique.ai fully Customizable Dashboard, uses and benefits was originally published in botique.ai on Medium, where people are continuing the conversation by highlighting and responding to this story.

In line with the launching of the new (free of charge) botique.ai QnA AI-powered Chatbot platform for Small & Medium businesses, we saw that it is imperative to show our clients how to use botique.ai Visual Platform to build, train, and deploy their AI-powered Chatbots with absolutely no coding experience whatsoever, and within less than 10 minutes!

botique.ai enables businesses to deploy highly intelligent, conversational chatbots, powered by unique NLP & NLU algorithms, and the powerful QuickPredict™ feature that utilizes supervised and unsupervised machine learning skills to provide our clients with the easiest, seamless AI training procedure, generating and matching synonyms, keywords and intents.

We had made it easy to build and deploy the QnA Chatbot using botique.ai Chatbot platform, following only a number of steps, to customize the bot, add questions and answers, and deploy it via a single line of code to your website (Wordpress, Wix supported) or publish it to the business's Facebook Page to answer users and engage visitors.

• Go to botique.ai dashboard, Create a username & Password, or log in using Google or Facebook Credentials,
• Verify your email address, you’ll be directed to the Chatbot creation wizard, set up your Agents (Chatbot) name, Language, and Welcome Message, Click Next.

• The Chatbot offers a way for customers to follow up directly with the business either by leaving a message, Call, or requesting a call back, or transfer to a human agent through the botique.ai Live Chat platform, or by integrating into an existing live chat or ticketing system, On the Contact Us page, Choose the way you want your customers to connect with your business, enter the appropriate details and click on Next.

• This is where the magic happens! Add a link to your Questions and Answers page, Frequently Asked Questions or a CSV file with Questions and appropriate answers for your business. Hit Import, the Artificial Intelligence NLP powered QuickPredict™ engine, will analyze the questions, highlight the keywords and their synonyms, and add them to the library in order to provide them to users appropriately.

This process will take a few moments depending on the size of the import, once you’re done the system will automatically direct you to the dashboard. From there, you can monitor and review all your Agents (Chatbot) actions, interactions, engagement, and conversations, in addition to Add, modify, delete questions and answers.

Publishing the Agent hasn’t been easier, from the left side navigation panel, click on Publish, and add the code line in the sandbox to your website following the instructions on the Publish Page.

You can also publish the Chatbot to Facebook, by clicking on Publish to Facebook (Facebook login might be required) make sure to grant the Chatbot appropriate rights on the business page, and you’re good to go!

Rajai Nuseibeh, botique.ai head of Marketing and Business Development, an executive, a former CEO & Founder with over 10 years of Technology and Innovation Experience.

Deploying a Customer Support AI Chatbot with botique.ai QnA Platform in less than 10 minutes was originally published in botique.ai on Medium, where people are continuing the conversation by highlighting and responding to this story.

Customer Service, things are changing

Today’s consumers are expecting a certain level of service, companies like Chick-fil-A, Amazon, Trader’s Joe, Thrivent Financial and Wells Fargo, among others, have already raised the bar, Quality, Value, Customer Expectation, Customer loyalty are all key indicators that consumers are researching and asking about, before even approaching your brand for a product or a service, and any red flag or alarm will result in complaints, negative feedback, or even worst, churn.

Where to start?

The Keyword here is your Customers! Understand your customers and their personas to be able to understand how to better serve them; Customers are already using new ways to get tasks done, digital assistants on smartphones, such as Google Assistant or Siri, Alexa in living rooms and smart homes, and others, the fact that people are relying more and more on automated systems, digital assistants, or Chatbots is opening a new era for Business-Consumer interaction.

Customers today are driven by a global “always-on” economy, the convenience of a 24/7 service, from online shopping, paying the bills, filing insurance claims, looking for information on a scholarship or asking about the safe use of prescription or over-the-counter (OTC) medicines. Which means that your company is entitled to provide your customers with an “always-on” 24/7 service that is convenient, easily accessible via a smartphone or a website over text, scalable to adapt to seasonal spikes, and at the time cost-effective for your company. A bit tricky no?

Chatbots for Customer Service

So here is where Chatbots were introduced to help firms and enterprises perform the routine functions essential to running the business and communicating with consumers, increasing organizational efficiency and worker productivity. In addition, to help simplify the process of finding and consuming information, improving customer loyalty, offering an easy-to-access, simpler, anytime/anywhere, personalized service. Or simply, the type of service today’s consumers expect.

What to Look For?

There are Chatbots Platforms that are designed to make it easy for enterprises and developers to build, host, and manage bots. Bringing instant value to employees and customers. Top-ranking platforms provide a complete, customizable, secure, and cost-effective framework that ensures a consistent and scalable process for building bots without the need for expensive hosting, time-consuming coding, or complex custom software, platforms such as botique.ai, for example, offer businesses an interface to build, deploy, and manage AI Chatbots with a simple UI, no use of code for building & training the Chatbot, and seamless integration.

What to Look for: in an AI Chatbot Builder platform?

1. How easy and intuitive is it to learn and use?
2. How long does it take to deploy and train?
3. What kind of support will you receive during and after implementation?
4. How long does it take to build & deploy chatbots using the solution?
5. What is the pricing and pricing structure in relation to the most important features?

What to look for in a Customer Support Chatbot?

A powerful NLP engine; allowing your chatbot to process text, find and understand the semantics, syntax, and grammar of a sentence in order to process user requests and identify intent and parameters for executing tasks.

OmniChannel: The platform should allow you to deploy your bots where your customers are — from social media platforms to popular messaging apps, websites, and more.

Support on-premise and cloud deployments: based on your operational, security, and compliance standard, you might need to consider a solution that will allow you to select the appropriate deployment option.

Integration: the chatbot platform should provide the ability to easily and securely connect to business systems (Content, Customer Relations, Management Systems) web applications, and websites.

Learning: The Platform learning capabilities should consists of both, Supervised and Unsupervised Machine learning skills. As a Customer Support Agent, there are certain questions and procedures that need to be taught to the Chatbot to follow according to business need, still, as a Chatbot solution, it is imperative for it to be able to self learn and develop its conversational skills on the go, thus the ability to learn both ways is important!

Multilanguage Support: The platform should allow you to deploy your chatbots in the language of choice of your customers, especially when if you’re a national or international brand, Chatbots that are able to understand and communicate in multiple languages (and detect language switch within a conversation) provide a better user experience for your consumers and avoids making them feel left out when engaging your brand.

Administration and User management: The platform needs to allow you to manage roles and permissions to control who can use, manage, and deploy chatbots and access administrative consoles.

Analytics: Customer Satisfaction is all about understanding the data from your customer’s behaviors and journey, thus the platform should allow you to easily track chatbot usage with comprehensive reporting and analytics, learn what customers are asking or what they are searching for, and present the data neatly.

The Bottom Line!

Understanding the must-have features in both the platform and the Chatbot itself (mentioned above) will help you make an easier decision, better selection, and help ease your headache moving forward after selection and deployment.

Make sure, to ask for your free trial of any platform selected before going forward, take the time to test it, get access to some of your employees and customers who will be using it, ask them to engage the Chatbot and the AI, test its Natural language processing (NLP) engine, Intent identification, and other capabilities before even proceeding with investing lots of resources with some vendors who will not deliver on what they promise.

Rajai Nuseibeh is the Head of Marketing and Customer Satisfaction at botique.ai, The Leading AI Chatbot Platform.

Conversational Artificial Intelligence Chatbots in Customer Service, Are you getting what you’re… was originally published in botique.ai on Medium, where people are continuing the conversation by highlighting and responding to this story.

From build your own Chatbot platforms to Customized Artificial intelligence solutions, Decision Trees to Natural Language Processing (NLP) and Natural Language Understanding (NLU) algorithms. The more you learn the more you get confused, and like with any service, the fine print at the very end of the service website is what is important to your use case, and which makes or breaks the deal!

I am here today to summarize what I have learned throughout my journey to providing my customers with the best experience I can get while insuring to save up on time and cost.

Chatbot builders

Chatbot Builders are platforms that provide tools to create a Conversational Agent or a “Chatbot”. In order to better understand the difference between all of the platforms out there, I decided to classify them into two main categories; “Visual Chatbot Builders” and “Machine learning NLP Powered engines”.

Visual Chabot builders and Decision Trees

Visual Chabot builders are the easiest to use, using a visual interface to map a step-by-step process to provide your customers with the exact answer. The more specific the inquiry, the more branches will be needed to answer it. Below is a sample design framework for a chatbot.

Restricted to building basic flows, they are usually convenient for basic data collection chatbots, marketing stunts, and simple interactions. Using them to build a proper conversational user interface, contextual understanding, or handing out-of-flow sceneries is out of the question!

In addition, completing a decision tree framework could take up days, not taking into consideration the very basic IF-THEN process the Chatbot goes through in every conversation forces the user to go through specific questions that need to follow a defined track or the Chatbot will be unable to answer. Unless you have experience with designing decision trees and you can invest a lot of effort and time into your Chatbot mapping, you can easily end up with a dead-end bot. This will most probably cause more customers to ask for a human agent! hurting engagement rates, and burdening your Agents even more.

What is the solution?

botique.ai is an enterprise platform that will help you create an AI-powered Chatbot/Digital Agent with a very easy, visual interface (click here for more info) with absolutely no coding experience. By using this Platform you can easily import your business content from your Website, Knowledge Base, or other resources, and then deploy your Digital Agent on your website or social media with a single line of code.

Want to add a caption to this image? Click the Settings icon.

Why use botique.ai Digital Agent solution?

• botique.ai is the first solution that provides you with the power of AI algorithms with a simple visual interface.
• botique.ai in-house developed NLP & NLU (Natural Language Understanding) engines are is fully developed to analyze users inquiries, and automatically decide the best match and the course of action to provide the answer. This spares you the mapping of the hideous Decision trees and leaves the AI to botique.ai team who are experts on the matter.
• botique.ai provides end user with “human-like”, conversational, enterprise-grade AI experience.
• A complete comprehensive dashboard for managing the agents, and a for understanding user’s behavior. Reporting and Analytics for your R&D and Marketing teams.

If you are looking for a better user experience and engagement, lower bouncing rates and fewer drop-offs while optimizing costs then botique.ai is just the better choice.

botique.ai vs Traditional Chatbot Builders was originally published in botique.ai on Medium, where people are continuing the conversation by highlighting and responding to this story.