The evolution of artificial intelligence is now in full swing and chatbots are only a faint splash on a huge wave of progress. Today the number of users of messaging apps like WhatsApp, Slack, Skype and their analogs is skyrocketing, Facebook Messenger alone has more than 1.2 billion monthly users. With the spread of messengers, virtual chatterbots that imitate human conversations for solving various tasks are becoming increasingly in demand. Chinese WeChat bots can already set medical appointments, call a taxi, send money to friends, check in for a flight and many many other.
The “stand-alone” application, where the chatbot runs on a single computer, integrates mostly some sort of system interface, allowing your chatbot to control certain aspects and functions of your computer, such as playing media files, or retrieving documents. It usually also has a graphical component built in, as well, in the form of an avatar (often female) that enhances interaction, thus improving user’s experience.
Facebook is among the leading networks for consumers to directly interact with their choice of brand. Over a billion people in a month use this platform to directly get in touch with businesses. A survey reveals that 56% of consumers would prefer any and all form of grievances to be addressed and solved via chat rather than telephonically. Furthermore, consumers expect the response time to be less than 5 minutes per grievance.

Marketer’s Take: This is a good demonstration of how you can add a gaming dimension to your bots. If you’re a marketer that likes to tell stories, then you can design a choose-your-own adventure bot that educates and sells prospective customers that are following along. There are many twists and turns that can be built into a bot like this, so creative marketers will readily take advantage.
In a particularly alarming example of unexpected consequences, the bots soon began to devise their own language – in a sense. After being online for a short time, researchers discovered that their bots had begun to deviate significantly from pre-programmed conversational pathways and were responding to users (and each other) in an increasingly strange way, ultimately creating their own language without any human input.
Interface designers have come to appreciate that humans' readiness to interpret computer output as genuinely conversational—even when it is actually based on rather simple pattern-matching—can be exploited for useful purposes. Most people prefer to engage with programs that are human-like, and this gives chatbot-style techniques a potentially useful role in interactive systems that need to elicit information from users, as long as that information is relatively straightforward and falls into predictable categories. Thus, for example, online help systems can usefully employ chatbot techniques to identify the area of help that users require, potentially providing a "friendlier" interface than a more formal search or menu system. This sort of usage holds the prospect of moving chatbot technology from Weizenbaum's "shelf ... reserved for curios" to that marked "genuinely useful computational methods".
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”.
Other companies explore ways they can use chatbots internally, for example for Customer Support, Human Resources, or even in Internet-of-Things (IoT) projects. Overstock.com, for one, has reportedly launched a chatbot named Mila to automate certain simple yet time-consuming processes when requesting for a sick leave.[33] Other large companies such as Lloyds Banking Group, Royal Bank of Scotland, Renault and Citroën are now using automated online assistants instead of call centres with humans to provide a first point of contact. A SaaS chatbot business ecosystem has been steadily growing since the F8 Conference when Facebook's Mark Zuckerberg unveiled that Messenger would allow chatbots into the app.[34] In large companies, like in hospitals and aviation organizations, IT architects are designing reference architectures for Intelligent Chatbots that are used to unlock and share knowledge and experience in the organization more efficiently, and reduce the errors in answers from expert service desks significantly.[35] These Intelligent Chatbots make use of all kinds of artificial intelligence like image moderation and natural language understanding (NLU), natural language generation (NLG), machine learning and deep learning.

“Major shifts on large platforms should be seen as an opportunities for distribution. That said, we need to be careful not to judge the very early prototypes too harshly as the platforms are far from complete. I believe Facebook’s recent launch is the beginning of a new application platform for micro application experiences. The fundamental idea is that customers will interact with just enough UI, whether conversational and/or widgets, to be delighted by a service/brand with immediate access to a rich profile and without the complexities of installing a native app, all fueled by mature advertising products. It’s potentially a massive opportunity.” — Aaron Batalion, Partner at Lightspeed Venture Partners

NBC Politics Bot allowed users to engage with the conversational agent via Facebook to identify breaking news topics that would be of interest to the network’s various audience demographics. After beginning the initial interaction, the bot provided users with customized news results (prioritizing video content, a move that undoubtedly made Facebook happy) based on their preferences.
Facebook Messenger claims to have recently hit the much coveted ‘billion’ with 1.2 billion users on the platform. Last year, at Facebook’s Developer Conference, F8, the support for bots on Messenger platform was unveiled. And since then, developers from around the world have been working to leverage the next-gen technology. There are more than 100,000 bots available on Messenger today. David Marcus, Messenger’s CEO, states that the number of messages sent between businesses and customers has reached to 2 billion a month.

There has been a great deal of controversy about the use of bots in an automated trading function. Auction website eBay has been to court in an attempt to suppress a third-party company from using bots to traverse their site looking for bargains; this approach backfired on eBay and attracted the attention of further bots. The United Kingdom-based bet exchange Betfair saw such a large amount of traffic coming from bots that it launched a WebService API aimed at bot programmers, through which it can actively manage bot interactions.


Marketer’s Take: A great example of a chat bot that makes purchasing products and services easy. In its next generation, I expect 1-800-Flowers to ping me on special occasions, send Facebook messages to the recipient automatically, and notify me on Facebook that the flowers have been delivered. The combined digital and physical experience will up the game in the flower delivery business.
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.

The idea was to permit Tay to “learn” about the nuances of human conversation by monitoring and interacting with real people online. Unfortunately, it didn’t take long for Tay to figure out that Twitter is a towering garbage-fire of awfulness, which resulted in the Twitter bot claiming that “Hitler did nothing wrong,” using a wide range of colorful expletives, and encouraging casual drug use. While some of Tay’s tweets were “original,” in that Tay composed them itself, many were actually the result of the bot’s “repeat back to me” function, meaning users could literally make the poor bot say whatever disgusting remarks they wanted. 
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".

The term Chatbot is closely related to chat bot and chatterbot. Chatterbot is more popular in relation to chatbot who talk a lot, and is not necessary very intelligent in processing the user answers. Chat bot is used by technical people who consider the word ‘bot’ as a normal term for ‘robotised actions’, and for them ‘chat bot’ is a special kind of bot. The term Chatbot is actually the most popular amongst these three terms and has the broadest meaning.
This particular tool also specializes in personalization. Implement ZoConvert and make personalized updates, conversations, interactions with bots minutely picking on the customer behavior, pattern and interaction. With ZoConvert you can Broadcast your messages which results in better open and click rate. You can also create your own flows and make changes depending on your marketing strategies and send personalized updates at the same time.
Chatbots are certainly the quickest and most cost-effective way to be able to connect with the largest group of audience available on a single platform viz Facebook. Higher engagement rate than emails this trend is here to stay for a long time if not forever. Good for you, now that you have a proper list of tools that can be used to build chatbots in a snap of a finger. It’s no more a rocket science formula to implement them and let the results surprise you for yourself.
One of the key advantages of Roof Ai is that it allows real-estate agents to respond to user queries immediately, regardless of whether a customer service rep or sales agent is available to help. This can have a dramatic impact on conversion rates. It also eliminates potential leads slipping through an agent’s fingers due to missing a Facebook message or failing to respond quickly enough. 
Yes. Messenger bots are approved by Facebook before being made available inside the Messenger app so you can rest assured that they aren’t trying to steal your identity (or anything else). What’s more is a bot is tied to a Facebook page and a Facebook app making it all the more inconvenient to use for fraudulent activity. That said, don’t exchange private and/or personal information with a bot. Finally, because Messenger doesn’t support credit cards and purchasing just yet, anything you buy will likely be done via a browser with a bot aiding you so far as to place an order. If you want, you can always block a bot.
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