In Azure portal, paste the Facebook App ID, Facebook App Secret and Page Access Token values copied from the Facebook Workplace previously. Instead of a traditional pageID, use the numbers following the integrations name on its About page. Similar to connecting a bot to Facebook Messenger, the webhooks can be connected with the credentials shown in Azure.
Increases sales, reduce costs and automates support—that what ChatFuel claims to come with. Qualify your leads and engage with prospects on a 24X7 basis. Automate sales or connect warm leads to a sales representative in a live chat. With ChatFuel, you can share content with the followers and subscribers while they interact with your brand over Facebook Messenger. This tool takes about 7 minutes to come up with a fully functional bot.

Simple chatbots work based on pre-written keywords that they understand. Each of these commands must be written by the developer separately using regular expressions or other forms of string analysis. If the user has asked a question without using a single keyword, the robot can not understand it and, as a rule, responds with messages like “sorry, I did not understand”.
Insidiously and persistently, Facebook is chipping away at other messaging platforms and moving their users to Facebook Messenger. If they keep it up, by the end of 2017 there will be as many people on Messenger (currently 900 million) as Facebook (1.674 billion). But, counterintuitive as that strategy seems (why bifurcate resources on two fronts) that is all part of Mark Zuckerberg’s avec nous le deluge.

ItsAlive provides a platform to easily build chatbots and services for brands by facilitating with your customer care, broadcasting, acquisition and brand awareness. Choose across platforms and services you think the best suit your brand image. “A Chatbot that can’t evolve with your needs doesn’t make sense. We have solutions to communicate challenges, and you choose the options”. ItsAlive is out with a 2.0 version that you can give a shot.


The main challenge is in teaching a chatbot to understand the language of your customers. In every business, customers express themselves differently and each group of a target audience speaks its own way. The language is influenced by advertising campaigns on the market, the political situation in the country, releases of new services and products from Google, Apple and Pepsi among others. The way people speak depends on their city, mood, weather and moon phase. An important role in the communication of the business with customers may have the release of the film Star Wars, for example. That’s why training a chatbot to understand correctly everything the user types requires a lot of efforts.

The main challenge is in teaching a chatbot to understand the language of your customers. In every business, customers express themselves differently and each group of a target audience speaks its own way. The language is influenced by advertising campaigns on the market, the political situation in the country, releases of new services and products from Google, Apple and Pepsi among others. The way people speak depends on their city, mood, weather and moon phase. An important role in the communication of the business with customers may have the release of the film Star Wars, for example. That’s why training a chatbot to understand correctly everything the user types requires a lot of efforts.
If a text-sending algorithm can pass itself off as a human instead of a chatbot, its message would be more credible. Therefore, human-seeming chatbots with well-crafted online identities could start scattering fake news that seem plausible, for instance making false claims during a presidential election. With enough chatbots, it might be even possible to achieve artificial social proof.[56][57]
According to Richard Wallace, chatbots development faced three phases over the past 60 years. In the beginning, chatbot only simulated human-human conversations, using canned responses based on keywords, and it had almost no intelligence. Second phase of development was strictly associated with the expansion of Internet, thanks to which a chatbot was widely accessed and chatted with thousands of users. Then, the first commercial chatbot developers appeared. The third wave of chatbots development is combined with advanced technologies such as natural language processing, speech synthesis and real-time rendering videos. It comprises of chatbot appearing within web pages, instant messaging, and virtual worlds.

Enter Roof Ai, a chatbot that helps real-estate marketers to automate interacting with potential leads and lead assignment via social media. The bot identifies potential leads via Facebook, then responds almost instantaneously in a friendly, helpful, and conversational tone that closely resembles that of a real person. Based on user input, Roof Ai prompts potential leads to provide a little more information, before automatically assigning the lead to a sales agent.
Despite all efforts during almost half a century, most chatbots are still easily uncovered, but over the next decades they will definitely get smarter and finally we will distinguish human beings by them giving us silly answers as opposed to the much smarter chatbots. All of this will really start accelerating as soon as one single chatbot is smarter than one single human being. They will then be able to learn from each other, instead of learning from human beings, their knowledge will explode and they will be able to design even better learning mechanisms. In the long run, we will learn language from chatbots instead of the other way around.
However, as irresistible as this story was to news outlets, Facebook’s engineers didn’t pull the plug on the experiment out of fear the bots were somehow secretly colluding to usurp their meatbag overlords and usher in a new age of machine dominance. They ended the experiment due to the fact that, once the bots had deviated far enough from acceptable English language parameters, the data gleaned by the conversational aspects of the test was of limited value.

ELIZA's key method of operation (copied by chatbot designers ever since) involves the recognition of clue words or phrases in the input, and the output of corresponding pre-prepared or pre-programmed responses that can move the conversation forward in an apparently meaningful way (e.g. by responding to any input that contains the word 'MOTHER' with 'TELL ME MORE ABOUT YOUR FAMILY').[10] Thus an illusion of understanding is generated, even though the processing involved has been merely superficial. ELIZA showed that such an illusion is surprisingly easy to generate, because human judges are so ready to give the benefit of the doubt when conversational responses are capable of being interpreted as "intelligent".
In 1950, Alan Turing's famous article "Computing Machinery and Intelligence" was published,[8] 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:
Not only is this bot a saviour when it comes to knowing weather updates in a jiffy, it is very quirky with its replies sometimes. If you love having conversations with a bot, Poncho will entertain you pretty well with his witty and personalised replies for some queries. On my query, see how I was informed that the mighty cat-bot herself had DJ’ed in Bengaluru and loved the crowd!
24/7 digital support. An instant and always accessible assistant is assumed by the more and more digital consumer of the new era.[36] Unlike humans, chatbots once developed and installed don't have a limited workdays, holidays or weekends and are ready to attend queries at any hour of the day. It helps to the customer to avoid waiting of a company's agent to be available. Thus, the customer doesn't have to wait for the company executive to help them. This also lets companies keep an eye on the traffic during the non-working hours and reach out to them later.[43]
Tay, an AI chatbot that learns from previous interaction, caused major controversy due to it being targeted by internet trolls on Twitter. The bot was exploited, and after 16 hours began to send extremely offensive Tweets to users. This suggests that although the bot learnt effectively from experience, adequate protection was not put in place to prevent misuse.[55]
Earlier, I made a rather lazy joke with a reference to the Terminator movie franchise, in which an artificial intelligence system known as Skynet becomes self-aware and identifies the human race as the greatest threat to its own survival, triggering a global nuclear war by preemptively launching the missiles under its command at cities around the world. (If by some miracle you haven’t seen any of the Terminator movies, the first two are excellent but I’d strongly advise steering clear of later entries in the franchise.)
“It’s hard to balance that urge to just dogpile the latest thing when you’re feeling like there’s a land grab or gold rush about to happen all around you and that you might get left behind. But in the end quality wins out. Everyone will be better off if there’s laser focus on building great bot products that are meaningfully differentiated.” — Ryan Block, Cofounder of Begin.com
Marketer’s Take: The bot was surprisingly effective yet fell short several times when queries like “Show me Blue Jeans” came with a canned bot response, “Sorry, I didn't find any products for this criteria.” Yet I know they sell “blue jeans”. Still, the bot was one of the best eCommerce bots I’ve seen on the platform thus far, and marketers should study it.
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.
However, as irresistible as this story was to news outlets, Facebook’s engineers didn’t pull the plug on the experiment out of fear the bots were somehow secretly colluding to usurp their meatbag overlords and usher in a new age of machine dominance. They ended the experiment due to the fact that, once the bots had deviated far enough from acceptable English language parameters, the data gleaned by the conversational aspects of the test was of limited value.
Properly building a chatbot will help you change the way consumers interact with your brand, increasing customer satisfaction and monetizing your social media platforms at the same time. By following the tips outlined above you will be able to create a chatbot that is line with your brand and that best portrays your company as a whole and you don't have to be a chatbot expert to get started.  
They have an intuitive visual interface for those without a coding background, but developers will like the editable front-end and customization options. While you can build a bot for free, a lot of the more complex (and interesting) tools are only available with Chatfuel Pro accounts. Either way, it might be helpful to know that Chatfuel integrates with Hootsuite Inbox using the Facebook Messenger handover protocol.
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