2. Flow-based: these work on user interaction with buttons and text. If you have used Matthew’s chatbot, that is a flow-based chatbot. The chatbot asks a question then offers options in the form of buttons (Matthew’s has a yes/no option). These are more limited, but you get the possibility of really driving down the conversation and making sure your users don’t stray off the path.
The educators or class organizers can opt for chatbots to simplify daily routine tasks. Chatbots may serve as a helping hand to the teacher in dealing with the daily queries by allowing bots to answer the questions of students on a daily basis, or perhaps even check their homework. Eventually, they offer teachers more time to work with their students on a one-by-one basis.
In 1950, Alan Turing's famous article "Computing Machinery and Intelligence" was published, which proposed what is now called the Turing test as a criterion of intelligence. This criterion depends on the ability of a computer program to impersonate a human in a real-time written conversation with a human judge, sufficiently well that the judge is unable to distinguish reliably—on the basis of the conversational content alone—between the program and a real human. The notoriety of Turing's proposed test stimulated great interest in Joseph Weizenbaum's program ELIZA, published in 1966, which seemed to be able to fool users into believing that they were conversing with a real human. However Weizenbaum himself did not claim that ELIZA was genuinely intelligent, and the Introduction to his paper presented it more as a debunking exercise:
This is great for the consumer because they don't need to leave the environment of Facebook to get access to the content they want, and it's hugely beneficial to Politico, as they're able to push on-demand content through to an increasingly engaged audience - oh, and they can also learn a bunch of interesting things about their audience in the process (I'll get to this shortly).
Kik Messenger, which has 275 million registered users, recently announced a bot store. This includes one bot to send people Vine videos and another for getting makeup suggestions from Sephora. Twitter has had bots for years, like this bot that tweets about earthquakes as soon as they’re registered or a Domino’s bot that allows you to order a pizza by tweeting a pizza emoji.

Chatbots are unique because they not only engage with your customers, they also retain them. This means that unlike other forms of marketing, chatbots keep your customers entertained for longer. For example, let's say you catch your audience's attention with a video. While this video may be extremely engaging, once it ends, it doesn't have much more to offer.
Since Facebook Messenger, WhatsApp, Kik, Slack, and a growing number of bot-creation platforms came online, developers have been churning out chatbots across industries, with Facebook’s most recent bot count at over 33,000. At a CRM technologies conference in 2011, Gartner predicted that 85 percent of customer engagement would be fielded without human intervention. Though a seeming natural fit for retail and purchasing-related decisions, it doesn’t appear that chatbot technology will play favorites in the coming few years, with uses cases being promoted in finance, human resources, and even legal services.
Yes, witty banter is a plus. But, the ultimate mission of a bot is to provide a service people actually want to use. As long as you think of your bot as just another communication channel, your focus will be misguided. The best bots harness the micro-decisions consumers experience on a daily basis and see them as an opportunity to help. Whether it's adjusting a reservation, updating the shipping info for an order, or giving medical advice, bots provide a solution when people need it most.
This reference architecture describes how to build an enterprise-grade conversational bot (chatbot) using the Azure Bot Framework. Each bot is different, but there are some common patterns, workflows, and technologies to be aware of. Especially for a bot to serve enterprise workloads, there are many design considerations beyond just the core functionality. This article covers the most essential design aspects, and introduces the tools needed to build a robust, secure, and actively learning bot.
WeChat combines a chat-based interface with vast library of add-on features such as a mobile wallet, chat-based transactions, and chat-based media and interactive widgets, and exposes it all to businesses through a powerful API that enables businesses from mom and pop noodle shops to powerhouses such as Nike and Burberry to “friend” their customers and market to them in never before imaginable ways. Over 10MM businesses in China have WeChat accounts, and it is becoming increasingly popular for small businesses to only have a WeChat account, forgoing developing their own website or mobile app completely. US technology firms, in particular Facebook, are taking note.

Utility bots solve a user's problem, whatever that may be, via a user-prompted transaction. The most obvious example is a shopping bot, such as one that helps you order flowers or buy a new jacket. According to a recent HubSpot Research study, 47% of shoppers are open to buying items from a bot. But utility bots are not limited to making purchases. A utility bot could automatically book meetings by scanning your emails or notify you of the payment subscriptions you forgot you were signed up for.
Malicious chatbots are frequently used to fill chat rooms with spam and advertisements, by mimicking human behavior and conversations or to entice people into revealing personal information, such as bank account numbers. They are commonly found on Yahoo! Messenger, Windows Live Messenger, AOL Instant Messenger and other instant messaging protocols. There has also been a published report of a chatbot used in a fake personal ad on a dating service's website.[55]
Just last month, Google launched its latest Google Assistant. To help readers get a better glimpse of the redesign, Google’s Scott Huffman explained: “Since the Assistant can do so many things, we’re introducing a new way to talk about them. We’re them Actions. Actions include features built by Google—like directions on Google Maps—and those that come from developers, publishers, and other third parties, like working out with Fitbit Coach.”

However, the revelations didn’t stop there. The researchers also learned that the bots had become remarkably sophisticated negotiators in a short period of time, with one bot even attempting to mislead a researcher by demonstrating interest in a particular item so it could gain crucial negotiating leverage at a later stage by willingly “sacrificing” the item in which it had feigned interest, indicating a remarkable level of premeditation and strategic “thinking.”


Chatfuel is one of the leading chatbot development platforms to develop chatbots for Facebook Messenger. One of the main reasons of Chatfuel’s popularity is easy to use interface. No knowledge of programming is required to create basic chatbot. People with non-technical background too can create bots using the platform and launch on their Facebook page.…
Es gibt auch Chatbots, die gar nicht erst versuchen, wie ein menschlicher Chatter zu wirken (daher keine Chatterbots), sondern ähnlich wie IRC-Dienste nur auf spezielle Befehle reagieren. Sie können als Schnittstelle zu Diensten außerhalb des Chats dienen, oder auch Funktionen nur innerhalb ihres Chatraums anbieten, z. B. neu hinzugekommene Chatter mit dem Witz des Tages begrüßen.
Need a Facebook bot? Well, look no further, as Chatfuel makes it easy for you to create your own Facebook and Telegram Chatbot without any coding experience necessary. It works by letting users link to external sources through plugins. Eventually, the platforms hope to open itself to third-party plugins, so anyone can contribute their own plugins and have others benefit from them.

Spot is a chatbot developed by Criminal Psychologist Julia Shaw at the University College London. Using memory science and AI, Spot doesn’t just allow users to report workplace harassment and bullying, but is capable of asking personalized, open-ended questions to help you recall details about events that made you feel uncomfortable. The application helps users process what happened, to understand whether or not they experienced harassment or discrimination and offers advice on how they can take matters further.
Poor user experience. The bottom line: chatbots frustrate your customers if you are viewing them as a replacement for humans. Do not ever, ever try to pass of a chatbot as a human. If your chatbot suffers from any of the issues above, you’re probably creating a poor customer experience overall and an angry phone call to a poor unsuspecting call center rep.
The bottom line is that chatbots have completely transformed the way companies interact with their consumers. And guess what? This is just the very beginning. And the truth is that even though to some company leaders it may seem challenging to incorporate the omnichannel customer experience, it opens up a fantastic opportunity that allows businesses to engage with customers in a fresh, modern way. The outcome of this may prove to be an excellent opportunity to build more meaningful and long-lasting relationships with the customers.
A chatbot that functions through machine learning has an artificial neural network inspired by the neural nodes of the human brain. The bot is programmed to self-learn as it is introduced to new dialogues and words. In effect, as a chatbot receives new voice or textual dialogues, the number of inquiries that it can reply and the accuracy of each response it gives increases. Facebook has a machine learning chatbot that creates a platform for companies to interact with their consumers through the Facebook Messenger application. Using the Messenger bot, users can buy shoes from Spring, order a ride from Uber, and have election conversations with the New York Times which used the Messenger bot to cover the 2016 presidential election between Hilary Clinton and Donald Trump. If a user asked the New York Times through his/her app a question like “What’s new today?” or “What do the polls say?” the bot would reply to the request.
The most advanced bots are powered by artificial intelligence, helping it to understand complex requests, personalize responses, and improve interactions over time. This technology is still in its infancy, so most bots follow a set of rules programmed by a human via a bot-building platform. It's as simple as ordering a list of if-then statements and writing canned responses, often without needing to know a line of code.
Customer service departments in all industries are increasing their use of chatbots, and we will see usage rise even higher in the next year as companies continue to pilot or launch their own versions of the rule-based digital assistant. What are chatbots? Forrester defines them as autonomous applications that help users complete tasks through conversation.   […]
On the other hand, early adoption can be somewhat of a curse. In 2011, many companies and individuals, myself included, invested a lot of time and money into Google+, dubbed to be bigger than Facebook at the time. They acquired over 10 million new users within the first two weeks of launch and things were looking positive. Many companies doubled-down on growing a community within the platform, hopeful of using it as a new and growing acquisition channel, but things didn't exactly pan out that way.
Another benefit is that your chatbot can store information on the types of questions it’s being asked. Not only does this make the chatbot better equipped to answer future questions and upsell additional products, it gives you a better understanding of what your customers need to know to close the deal. With this information, you’ll be better equipped to market more effectively to your customers in the future.
Want to initiate the conversation with customers from your Facebook page rather than wait for them to come to you? Facebook lets you do that. You can load email addresses and phone numbers from your subscriber list into custom Facebook audiences. To discourage spam, Facebook charges a fee to use this service. You can then send a message directly from your page to the audience you created.
Each student learns and absorbs things at a different pace and requires a specific methodology of teaching. Consequently, one of the most powerful advantages of getting educated by a chatbot is its flexibility and ability to adapt to specific needs and requirements of a particular student. Chatbots can be used in a wide spectrum, be it teaching people how to build websites, learn a new language, or something more generic like teach children Math. Chatbots are capable of adapting to the speed at which each student is comfortable - without being too pushy and overwhelming.
Another option is to integrate your own custom AI service. This approach is more complex, but gives you complete flexibility in terms of the machine learning algorithm, training, and model. For example, you could implement your own topic modeling and use algorithm such as LDA to find similar or relevant documents. A good approach is to expose your custom AI solution as a web service endpoint, and call the endpoint from the core bot logic. The web service could be hosted in App Service or in a cluster of VMs. Azure Machine Learning provides a number of services and libraries to assist you in training and deploying your models.
Marketing teams are increasingly interested in leveraging branded chatbots, but most struggle to deliver business value. My recently published report, Case Study: Take A Focused And Disciplined Approach To Drive Chatbot Success, shows how OCBC Bank in Singapore is bucking the trend: The bank recently created Emma, a chatbot focused on home loan leads, which […]
Chatbots such as ELIZA and PARRY were early attempts at creating programs that could at least temporarily fool a real human being into thinking they were having a conversation with another person. PARRY's effectiveness was benchmarked in the early 1970s using a version of a Turing test; testers only made the correct identification of human vs. chatbot at a level consistent with making a random guess.

“Bots go bust” — so went the first of the five AI startup predictions in 2017 by Bradford Cross, countering some recent excitement around conversational AI (see for example O’Reilly’s “Why 2016 is shaping up to be the Year of the Bot”). The main argument was that social intelligence, rather than artificial intelligence is lacking, rendering bots utilitarian and boring.
A rapidly growing, benign, form of internet bot is the chatbot. From 2016, when Facebook Messenger allowed developers to place chatbots on their platform, there has been an exponential growth of their use on that forum alone. 30,000 bots were created for Messenger in the first six months, rising to 100,000 by September 2017.[8] Avi Ben Ezra, CTO of SnatchBot, told Forbes that evidence from the use of their chatbot building platform pointed to a near future saving of millions of hours of human labour as 'live chat' on websites was replaced with bots.[9]
Creating a comprehensive conversational flow chart will feel like the greatest hurdle of the process, but know it's just the beginning. It's the commitment to tweaking and improving in the months and years following that makes a great bot. As Clara de Soto, cofounder of Reply.ai, told VentureBeat, "You're never just 'building a bot' so much as launching a 'conversational strategy' — one that's constantly evolving and being optimized based on how users are actually interacting with it."
Most chatbots try to mimic human interactions, which can frustrate users when a misunderstanding arises. Watson Assistant is more. It knows when to search for an answer from a knowledge base, when to ask for clarity, and when to direct you to a human. Watson Assistant can run on any cloud – allowing businesses to bring AI to their data and apps wherever they are.

Die Herausforderung bei der Programmierung eines Chatbots liegt in der sinnvollen Zusammenstellung der Erkennungen. Präzise Erkennungen für spezielle Fragen werden dabei ergänzt durch globale Erkennungen, die sich nur auf ein Wort beziehen und als Fallback dienen können (der Bot erkennt grob das Thema, aber nicht die genaue Frage). Manche Chatbot-Programme unterstützen die Entwicklung dabei über Priorisierungsränge, die einzelnen Antworten zuzuordnen sind. Zur Programmierung eines Chatbots werden meist Entwicklungsumgebungen verwendet, die es erlauben, Fragen zu kategorisieren, Antworten zu priorisieren und Erkennungen zu verwalten[5][6]. Dabei lassen manche auch die Gestaltung eines Gesprächskontexts zu, der auf Erkennungen und möglichen Folgeerkennungen basiert („Möchten Sie mehr darüber erfahren?“). Ist die Wissensbasis aufgebaut, wird der Bot in möglichst vielen Trainingsgesprächen mit Nutzern der Zielgruppe optimiert[7]. Fehlerhafte Erkennungen, Erkennungslücken und fehlende Antworten lassen sich so erkennen[8]. Meist bietet die Entwicklungsumgebung Analysewerkzeuge, um die Gesprächsprotokolle effizient auswerten zu können[9]. Ein guter Chatbot erreicht auf diese Weise eine mittlere Erkennungsrate von mehr als 70 % der Fragen. Er wird damit von den meisten Nutzern als unterhaltsamer Gegenpart akzeptiert.
In sales, chatbots are being used to assist consumers shopping online, either by answering noncomplex product questions or providing helpful information that the consumer could later search for, including shipping price and availability. Chatbots are also used in service departments, assisting service agents in answering repetitive requests. Once a conversation gets too complex for a chatbot, it will be transferred to a human service agent .
It may be tempting to assume that users will perform procedural tasks one by one in a neat and orderly way. For example, in a procedural conversation flow using dialogs, the user will start at root dialog, invoke the new order dialog from there, and then invoke the product search dialog. Then the user will select a product and confirm, exiting the product search dialog, complete the order, exiting the new order dialog, and arrive back at the root dialog.
Despite the fact that ALICE relies on such an old codebase, the bot offers users a remarkably accurate conversational experience. Of course, no bot is perfect, especially one that’s old enough to legally drink in the U.S. if only it had a physical form. ALICE, like many contemporary bots, struggles with the nuances of some questions and returns a mixture of inadvertently postmodern answers and statements that suggest ALICE has greater self-awareness for which we might give the agent credit.
Google, the company with perhaps the greatest artificial intelligence chops and the biggest collection of data about you — both of which power effective bots — has been behind here. But it is almost certainly plotting ways to catch up. Google Now, its personal assistant system built within Android, serves many functions of the new wave of bots, but has had hiccups. The company is reportedly working on a chatbot that will live in a mobile messaging product and is experimenting with ways to integrate Now deeper with search.
Oftentimes, brands have a passive approach to customer interactions. They only communicate with their audience once a consumer has contacted them first. A chatbot automatically sends a welcome notification when a person arrives on your website or social media profile making the user aware of your chatbots presence. This makes you seem more proactive, thus enhancing your brand's reputation and can even increase interactions, having a positive effect on your sales numbers, too.
Last, but not least coming in with the bot platform for business is FlowXO, which creates bots for Messenger, Slack, SMS, Telegraph and the web. This platform allows for creating various flexibility in bots by giving you the option to create a fully automated bot, human, or a hybrid of both. ChatBot expert Murray Newlands commented that "Where 10 years ago every company needed a website and five  years ago every company needed an app, now every company needs to embrace messaging with AI and chatbots."
“There is hope that consumers will be keen on experimenting with bots to make things happen for them. It used to be like that in the mobile app world 4+ years ago. When somebody told you back then… ‘I have built an app for X’… You most likely would give it a try. Now, nobody does this. It is probably too late to build an app company as an indie developer. But with bots… consumers’ attention spans are hopefully going to be wide open/receptive again!” — Niko Bonatsos, Managing Director at General Catalyst
Chatbots are often used online and in messaging apps, but are also now included in many operating systems as intelligent virtual assistants, such as Siri for Apple products and Cortana for Windows. Dedicated chatbot appliances are also becoming increasingly common, such as Amazon's Alexa. These chatbots can perform a wide variety of functions based on user commands.
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