Chatbots life

  • Automated Quality Assurance for Voice Apps: Easy, Fast and Affordable. This is How.
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    Creating voice applications is getting easier every day with platforms from Amazon, Google, and Microsoft, and testing and development tools from third parties like Bespoken. And thanks to the constant improvements in voice platforms such as Alexa or Google Assistant, it is possible to create more complex and richer voice experiences. This allows developers to offer easy-to-use and highly useful voice apps to the growing number of users who regularly interact with businesses via voice.Given all this, it’s no surprise the number of voice applications are expanding rapidly, as can be seen in the following graphic for Alexa skillsBut how many of these skills are error-free and offer truly delightful experiences to customers, experiences that bring them back again and again?Top 4 Most Popular Bot Design Articles:1. Ultimate Bot Design Guide2. How to design a Chatbot3. Distributing a slack app4. Chatbot Conference in San FranciscoWe have been digging (*) and found some interesting information:Graph by BespokenMore than 65% of the most popular skills have a rating lower than 4 stars. Undoubtedly, the reasons for having a low rating are varied and go from an insufficiently attractive content to errors in the app code or platform AI components (i.e. speech recognition and NLU issues).Whatever the reason, a user who does not have a positive experience when using a voice application may give your skill a negative review and almost certainly will not return again. To avoid user churn, it is necessary to guarantee that in addition to providing high-quality content, the application is free from errors. And testing is the only way to ensure this.For many working on voice experiences, testing is time-consuming, tedious, and error-prone. At Bespoken, we decided to change that. Using the Bespoken tools is an easy solution to guarantee that your voice app is always performing at its best, without taking too much time or money. Let’s take a look.The 4 layers of testingGraph by BespokenThese pieces together help assist with every aspect of testing for voice, in an automated way. We cover the entire development lifecycle, so whether you are a developer, QA person, or product manager, we have you covered and we tools that can help you do your job better and in turn, ensure your users are consistently delighted.Unit TestingA kind of testing done during the coding phase. It ensures the code is working correctly in isolation. As it is executed locally, there is no need to deploy your changes to the cloud each time you update the code. Needless to say, it executes in a matter of seconds.How to get started?Install the Bespoken CLI and use the proxy command to execute your voice app code locally. It is also possible to debug the code with your favorite IDE to quickly find errors without time-consuming deployments to the cloud.Start creating simple yet powerful unit test scripts with Bespoken’s YAML based syntaxCheck this sample project to see a real-life example of unit testing an Alexa skill.End-to-End TestingThis type of test is executed when the code has been completed to ensure the entire system is working correctly — AI (ASR + NLU), code, and external services. The utterances defined on these tests interact with the real Alexa or Google services.How to get started?Use Bespoken’s YAML-based syntax to create easy to understand and maintain end-to-end test scripts.Use Bespoken’s CLI’s to execute the end-to-end scripts. Check this video to know how.See a full example of end-to-end testing for a skill here.Continuous Testing (Monitoring)This type of test ensures that a voice app, once deployed, works flawlessly by verifying your voice app on a regular interval.How to get started?Sign up to Bespoken Dashboard and get a Virtual Device to start interacting with your voice app programmatically.Create a monitoring script in less than 5 minutes. The script should contain a set of interactions that test the most important functionalities of your app.Enable monitoring for the script you just created. We’ll execute the script every 30 minutes notifying you if the script fails (the voice app stops behaving as expected).Usability Performance TestingThe main goal of this kind of testing is to identify issues with the speech recognition and NLU behavior of the assistant and your app. It consists of comprehensive testing of the interaction model, creating a baseline set of results. These results, in turn, are the basis for making improvements to the interaction model and the code of the skill — once revisions are completed, additional tests are run to ensure everything is working as expected.How to get started?Provide information about your voice app, the interaction model and the terms to test in this form.Wait for the results (you will get an initial grade which will be used as a baseline for next test executions).Make improvements to your interaction model and code based on the results got in the previous step.Repeat the testing to see how your voice app improves speech recognition before releasing it to production.Pulling It AltogetherAs you can see, testing voice apps is easy and takes little time if you have the appropriate tools. Do not wait any longer. Detect errors in early stages to save money, and launch your voice app with confidence doing end-to-end and usability testing! Remember all these kind of testing is automated, silent, and can be repeated as many times as you need.Automated testing can help ensure that you are delighting your users — with an approach that is comprehensive and repeatable. To learn more, just contact us and we’ll be happy to setup a demo — or try it yourself. You can sign up for a free trial here.Yours In Testing,Ivan Perez(*): We have analyzed the most popular skills on Amazon Alexa store.Don’t forget to give us your 👏 !https://medium.com/media/7078d8ad19192c4c53d3bf199468e4ab/hrefAutomated Quality Assurance for Voice Apps: Easy, Fast and Affordable. This is How. was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story. Read more »
  • Deploy a ‘table reservation’ or ‘marketing’ Chatbot for your Restaurant in 5 min.
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    Deploy a ‘table reservation’ or ‘marketing’ Chatbot for your Restaurant in 5 min. (no tech expertise)Chatbots are making news every day and it’s about time that businesses adopt the most efficient communication channel available. Being the automated solution it solves the issues faced during scale-up. Recent studies have found the online chats are the most preferred communication medium of millennials and 69% of them want to solve their issues without any human intervention.without wasting any time lets jump into the process of building our chatbot.Design a conversation map related to your business. understand the requirements of the users when they come to your website or web page.As this is a non-tech tutorial we will use platforms available to help deploy our chatbot. We have a few platforms to choose from(googles dialogue flow, chatfuel, Botsify, Motion.ai). I personally like dialogue flow because of the customisation it allows but as we have to keep it non-technical, we will use chatfuel which is the best I feel in terms the features available.3. Sign up on chatfuel.com, click on create from the template and then select choose a blank bot.4. If you have a facebook page connect it to the bot in the configuration screen, create one if you don’t have a page.status will be updated after successful connection.Top 4 Bot Tutorials1. AWS setup for Deep Learning2. How to Integrate API.AI with Chatfuel3. Building a ChatBot with Watson4. Chatbot Conference in San Francisco5. select automate tab from the left vertical bar. Set your welcome message and default answer accordingly.here is what a simple one will look like.a text message, a picture, a typing icon to make it look real.A good welcome message.the choice to choose the path of the conversation.the quick reply yes leads to process 1 of the bookings.you can set that by clicking on the button and add process 1 as the block.‘No’ can lead to further offerings like the main menu or any Deals.6. Set up your main Menu Section and some other cards like about us etc.here is how my main menu looks likeUse gallery option to create something similar, the buttons can lead to further details.At the end of the conversation, you add options to extend the conversationsDirection information would be another good card to add.use the share location option to easily collect users location info.send them the link to the map showing the direction.sample map URL: https://www.google.com/maps/dir/{{address}}/Pizza+-House+ABCD+Street+-Kuala lumpur+-+Malaysia/7. Create the first section of your reservation processfollow your proper flow.try to collect the information you need.I am collecting the date and time for reservation and saving it to set variables.after collecting the info move to process block 2 using ‘go to block’.In the process block 2, collect some further details.Confirm the collected details from the user.move on to contact block to collect contact information8. Collect users Contact Informationcollect the users choice of contact medium.proceed to the medium of the choice block, phone in this case.using the go-to block proceed to the send booking block.9. finalise, save and send booking.The final Step is to store the information in your database, spreadsheet or email.for the purpose of this tutorial and the time limitation, I have used the send email option from chatfuel.the second easiest and efficient option that you have is to send the data to your reservation google sheet by connecting through zapier.Another option with huge customisation option is to create your own API, host it on firebase etc and send and receive data.10. finally you can press connect to facebook button on the top left. one important step is to test your chatbot and user flows. Try to figure out all the issues and fix them before deploying it. Chatfuel allows you to test your bot on facebook.Tried to cover as much as possible in 5–7 min, I know you will find a lot of things missing from the tutorial, but I tried to make it such that it lets you create a simple working chatbot with an introduction to what more can be achieved. I will try to make 2nd part of this tutorial with more alternatives and features that can be added.I will be happy to answer your questions and feedback and suggestions are welcome too :)Don’t forget to give us your 👏 !https://medium.com/media/7078d8ad19192c4c53d3bf199468e4ab/hrefDeploy a ‘table reservation’ or ‘marketing’ Chatbot for your Restaurant in 5 min. was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story. Read more »
  • The Chatbot Release — Make it a successful one
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    The Chatbot Release — Make it a successful oneAfter a long chatbot development phase the awaited release of your chatbot is finally coming. In the following you can learn more about six relevant aspects.1. The right Marketing StrategyWhenever you are revealing a product it is essential to think about a marketing or communication strategy. This obviously depends on your chatbot case. If we are talking about an internal chatbot that is answering questions in the intranet you want to include emails, blogposts in the intranet or even offline flyers to market your chatbot to your colleagues. With such a chatbot there is a lot of potential to include features that could encourage frequent use or go viral. For example, if questions about the daily menu of the canteen or the employee directory can be answered. Facebook Messenger offers even QR Codes that can be printed out to be directed to the chatbot after scanning it. It also really depends on the messaging platform itself. If you want to establish new communication channels like a WhatsApp number or a new chat window on the website rather than integrating a chatbot in existing running messaging interfaces it also makes a huge difference.2. A “loud” ReleaseFor example a “loud” release of the chatbot makes more sense when a new communication channel is being launched. Let’s say a WhatsApp chatbot. You need to figure out a way on how to market that number to your customers. That means spreading the news via social media channels, newsletters, online ads but also adding it to the “ways to contact” landing page. If your chatbots brings special functionalities to the chat like push notifications in Facebook Messenger it is also recommended to market that since it really brings value to your customers. Overall: Plan a “loud” publication if the communication with the chatbot should be promoted.Top 4 Most Popular Bot Design Articles:1. Ultimate Bot Design Guide2. How to design a Chatbot3. Distributing a slack app4. Chatbot Conference in San Francisco3. A “silent” ReleaseIf you have live chat functionalities on your website and you are thinking about integrating a chatbot in there. A “loud” release would not be necessary in this case. Your customers are very likely to write with the chatbot like they did with live agents before. Nevertheless, you still want to announce officially in the start message that your users are writing with a chatbot now. Always be transparent about that. However, also clearly communicate that the user can be directed to a real employee as well if he wants to. Overall: Plan a “silent” publication if the communication should be automated.4. Expectation ManagementSince chatbots are a fairly new technology, expectation towards it’s functionalities especially in regards to a natural conversation can vary widely among people. So it’s really important that communication before hand is going to sensitize future users. If users clearly understand what the chatbots abilities are we can really leverage false expectations and ensure a positive user experience. This is especially true for colleagues but also for managers at work. Scientists have also found that people with a technical affinity in particular are better able to judge the abilities of chatbots and are more likely to forgive mistakes. People with less technical affinity usually approach the use of the chatbot with very high demands and show a higher frustration rate. As a product owner it is important to sensitize such target groups especially before the upcoming release.5. The Release DateThe release day of the chatbot should be well thought out, because there are many factors involved that could influence the Go Live positively as well as negatively. On the one hand, seasonal and temporal events have to be considered. Are there any school vacations at that time? Holidays? Or other important events related to the products or services of your company, which may lead to increased or reduced traffic in customer service. This includes, for example, the launch of new products, special offers, or the relaunch of a new website or app. Before the Go Live, all customer service agents should of course be aware of the use of the chatbot and have completed a training if a human handover should occur.6. The Go Live DayThe actual go live day of the chatbot should have one sufficient above all: Support. Because the testing that should have taken place before could cover many potential sources of error, but you will never be able to publish a 100% perfectly working system. For example, a chatbot release on Facebook Messenger did not take into account that all users who have already interacted with the Facebook page and write a second time will not notice that a chatbot is now responding. Normally a new user sees a “Get started” button and gets a welcome message where the chatbot introduces himself. Now you have to find technical solutions quickly, so that also existing users get to know about the chatbot. It is best to plan sufficient capacities in advance in order to implement technical solutions for such unforeseeable cases as quickly as possible.Interested in more insights? Talk to our chatbot consultants, we’ll be happy to hear from you!Don’t forget to give us your 👏 !https://medium.com/media/7078d8ad19192c4c53d3bf199468e4ab/hrefThe Chatbot Release — Make it a successful one was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story. Read more »
  • it’s coming…
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    Mark your calendars for September 25 & 26th because… something big is coming your way!Get Industry Insights from the top 35 experts in Bots, Voice & AI.You can set your strategy with confidence, using exclusive insights from 35 seasoned industry leaders.We feature speakers from the top Fortune 500s and companies like Google, Facebook, IBM Watson, Amazon, Microsoft and startups like Dashbot, Rasa, Smartloop & many more.Here is what our attendees say about the Chatbot ConferenceAre you facing a major challenge?Chances are that many of our speakers and attendees have faced and overcome similar challenges. We can help introduce you to the right person via our network.Meet other Fortune 500 decision makers during the conference and at happy hour. We can help introduce you to the right person via our network.it’s coming… was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story. Read more »
  • AI powered chatbots: The right way to improve customer service
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    For what the business is? To serve the customers, of course! Customer satisfaction is the key to the success of the business, therefore providing exceptional customer service is essential to win the trust. The provision of phenomenal service is achievable with the help of AI powered chatbots.Why chatbots? They are mechanized by the artificial intelligence which means the chatbots have the capability to make the conversation style and the response mechanism like that of human terms.So how does AI virtual assistant will improve the customer services in the businesses?Customer service’s influence on business revenueDeriving the facts from the Zendesk research, customer service do have an impact on the business — whether it is good or bad.Why good customer service is necessary to deliver? 62% and 42% B2B and B2C respectively did more shopping because of the good customer service experience.In another situation, it is found that 66% B2B and 52% B2C did stopped purchasing the products because of the bad customer service experience. The above facts essentially states the importance of the customer service in the business. The complete brand value of the company is based on the customer satisfaction. There are certain pointers to consider, helping to measure the image of business in the market. Few to highlight:The customer service quality offered to the users describes the image of the company/ brand.Top Articles on How Businesses are using Bots:1. WhatsApp for Business: A Beginners Guide2. Revenue models for bots and chatbots3. The Age of Zero Excuses4. Chatbot Conference in San FranciscoThe satisfied and happy customers are likely to trust the brand to use the service/ product again.The unsatisfied customer would go for other options in the market instead of reconsidering your brand for the same product/ service.For the brands, it is important to deliver the phenomenal customer service. It is an opportunity for the brands to improve their services, retrieve the old customers and earn the new ones.When we are already discussing the impact of the customer service on the business, how does the chatbots help to improve?Chatbots and the improved customer serviceQuick solutions to the customer’s queriesThe good customer service experience happens when the quick solutions are provided to the customer’s issues. Through the chatbots, the automated customer service makes it easy for rapid answers to the user’s query. Going the digital way to improve the customer service makes it easy for the business to satisfy their users.There are times when the quick and rapid solutions are required to the emergency issues and the chatbots can help to provide the best customer service. The instant help through the chatbots benefits the business to handle all kind of the issues in the shortest span of time.One-time investment with secured ROITo develop a chatbot essentially costs a lot but it is the one time investment with the guaranteed ROI. How does the chatbots differ from the human for the customer service? Well, consider hiring a human for the efficient customer service.The amount of investment of time, and the efforts is immense to train them compare to training the chatbots. Trained chatbots saves the cost as well as time. Chatbots can be also be called as ‘automated customer service agents.Highly responsive chatbotsThe Natural language processing (NLP) and Machine learning (ML), potential of AI, allow the chatbots to answer the issues unlike the human is able to. Based on the research of the Forrester report 2017, to enhance the conversation with the customers, businesses are integrating the automatized customer service.The AI powered chatbots with the ML and predictive analysis power are capable to reciprocate the customer needs through analyzing the context, customer queries and their preferences. These developed chatbots control the power of the already installed AI, making it smart with the moving time.Better customer interaction and the engagementChatbots are developed and trained to engage in the friendly conversation with the customers. Though the bots are quite active, therefore are able to respond all kind of issues, queries with the apt solutions. The friendly nature makes the customers to stay on the website to stay a bit longer time.AI powered chatbots intuitively acknowledge the customer’s browsing behavior, preferences as well as interests. Based on this acknowledgement, chatbots respond to the customer’s questions, issues, suggesting the relevant solutions, appreciative often. In the simple words, chatbots can up-sell and cross-sell the products efficiently.Adaptive and reliabilityEven within the limited resources, chatbots are adaptive enough to respond the customer queries. The AI powered chatbots first learn the process for how the customer interact. This means the training staff and the need to employ them to speak the native language will be in no need.Final Words…Chatbots possess the exceptional abilities to multi task and responding the customer queries with ease. Customer engagement with the help of chatbots makes it easy for the business to connect with the old as well as the new one.The professional chatbot development company provide the opportunity to the business to work on the interaction model thereby executing the conversational interfaces to boost the revenue stream.Don’t forget to give us your 👏 !https://medium.com/media/7078d8ad19192c4c53d3bf199468e4ab/hrefAI powered chatbots: The right way to improve customer service was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story. Read more »
  • Your Chatbot’s Patience
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    Some clients require a very personalized and highly detailed assistance regarding their requirements as well as specific responses to…Continue reading on Chatbots Life » Read more »
  • Introduction to Natural Language Processing
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    SourceHello folks, I’ve just started my NLP journey and will be happy to share my learning process with you. Here’s an article regarding Introduction to Natural Language Processing.The essence of Natural Language Processing lies in making computers understand our natural language. That’s not an easy task though. Computers can understand the structured form of data like spreadsheets and the tables in the database, but human languages, texts, and voices form an unstructured category of data, and it gets difficult for the computer to understand it, and there arises the need for Natural Language Processing.There’s a lot of natural language data out there in various forms and it would get very easy if computers can understand and process that data. We can train the models in accordance with our expected output in different ways. Humans have been writing for thousands of years, there are a lot of literature pieces available, and it would be great if we make computers understand that. But the task is never going to be easy. There are various challenges floating out there like understanding the correct meaning of the sentence, correct Named-Entity Recognition(NER), correct prediction of various parts of speech, coreference resolution(the most challenging thing in my opinion).Trending AI Articles:1. Machine Learning for Dummies2. Text Classification using Algorithms3. Regularization in deep learning4. Chatbot Conference in San FranciscoComputers can’t truly understand human language. If we feed enough data and train a model properly, it can distinguish and try categorizing various parts of speech(noun, verb, adjective, supporter, etc…) based on previously fed data and experiences. If it encounters a new word it tried making the nearest guess which can be embarrassingly wrong few times.It’s very difficult for a computer to extract the exact meaning from a sentence. For an example — The boy radiated fire like vibes. The boy had a very motivating personality or he actually radiated fire? As you see over here, parsing English with a computer is going to be complicated.There are various stages involved in training a model. Solving a complex problem in Machine Learning means building a pipeline. In simple terms, it means breaking a complex problem into a number of small problems, making models for each of them and then integrating these models. A similar thing is done in NLP. We can break down the process of understanding English for a model into a number of small pieces.My friend recently went for a dive at San Pedro island, so I’ll love to take that example. Have a look at this paragraph — “San Pedro is a town on the southern part of the island of Ambergris Caye in the Belize District of the nation of Belize, in Central America. According to 2015 mid-year estimates, the town has a population of about 16,444. It is the second-largest town in the Belize District and largest in the Belize Rural South constituency”.(source-Wikipedia)It would be really great if a computer could understand that San Pedro is an island in Belize district in Central America with a population of 16,444 and it is the second largest town in Belize. But to make the computer understand this, we need to teach computer very basic concepts of written language.So let’s start by creating an NLP pipeline. It has various steps which will give us the desired output(maybe not in a few rare cases) at the end.STEP 1: Sentence SegmentationBreaking the piece of text in various sentences.San Pedro is a town on the southern part of the island of Ambergris Caye in the 2.Belize District of the nation of Belize, in Central America.According to 2015 mid-year estimates, the town has a population of about 16,444.It is the second-largest town in the Belize District and largest in the Belize Rural South constituency.For coding a sentence segmentation model, we can consider splitting a sentence when it encounters any punctuation mark. But modern NLP pipelines have techniques to split even if the document isn’t formatted properly.STEP 2: Word TokenizationBreaking the sentence into individual words called as tokens. We can tokenize them whenever we encounter a space, we can train a model in that way. Even punctuations are considered as individual tokens as they have some meaning.‘San Pedro’,’ is’, ’a’, ’town’ and so.STEP 3: Predicting Parts of Speech for each tokenPredicting whether the word is a noun, verb, adjective, adverb, pronoun, etc. This will help to understand what the sentence is talking about. This can be achieved by feeding the tokens( and the words around it) to a pre-trained part-of-speech classification model. This model was fed a lot of English words with various parts of speech tagged to them so that it classifies the similar words it encounters in the future in various parts of speech. Again, the models don’t really understand the ‘sense’ of the words, it just classifies them on the basis of its previous experience. It’s pure statistics.The process will look like this:Input →Part of speech classification model→ OutputTown →common nounIs → verbThe → determinerAnd similarly, it will classify various tokens.STEP 4: LemmatizationFeeding the model with the root word.For an example — There’s a Buffalo grazing in the field andThere are Buffaloes grazing in the field.Here, both Buffalo and Buffaloes mean the same. But, the computer can confuse it as two different terms as it doesn’t know anything. So we have to teach the computer that both terms mean the same. We have to tell a computer that both sentences are talking about the same concept. So we need to find out the most basic form or root form or lemma of the word and feed it to the model accordingly.In a similar fashion, we can use it for verbs too. ‘Play’ and ‘Playing’ should be considered as same.STEP 5: Identifying stop wordsThere are various words in the English language that are used very frequently like ‘a’, ‘and’, ‘the’ etc. These words make a lot of noise while doing statistical analysis. We can take these words out. Some NLP pipelines will categorize these words as stop words, they will be filtered out while doing some statistical analysis. Definitely, they are needed to understand the dependency between various tokens to get the exact sense of the sentence. The list of stop words varies and depends on what kind of output are you expecting.STEP 6.1: Dependency ParsingThis means finding out the relationship between the words in the sentence and how they are related to each other. We create a parse tree in dependency parsing, with root as the main verb in the sentence. If we talk about the first sentence in our example, then ‘is’ is the main verb and it will be the root of the parse tree. We can construct a parse tree of every sentence with one root word(main verb) associated with it. We can also identify the kind of relationship that exists between the two words. In our example, ‘San Pedro’ is the subject and ‘island’ is the attribute. Thus, the relationship between ‘San Pedro’ and ‘is’, and ‘island’ and ‘is’ can be established.Just like we trained a Machine Learning model to identify various parts of speech, we can train a model to identify the dependency between words by feeding many words. It’s a complex task though. In 2016, Google released a new dependency parser Parsey McParseface which used a deep learning approach.STEP 6.2: Finding Noun PhrasesWe can group words that represent the same idea. For example — It is the second-largest town in the Belize District and largest in the Belize Rural South constituency. Here, tokens ‘second’, ‘largest’ and ‘town’ can be grouped together as they together represent the same thing ‘Belize’. We can use the output of dependency parsing to combine such words. Whether to do this step or not completely depends on the end goal, but it’s always quick to do this if we don’t want much information about which words are adjective, rather focus on other important details.STEP 7: Named Entity Recognition(NER)San Pedro is a town on the southern part of the island of Ambergris Caye in the Belize District of the nation of Belize, in Central America.Here, the NER maps the words with the real world places. The places that actually exist in the physical world. We can automatically extract the real world places present in the document using NLP.If the above sentence is the input, NER will map it like this way:San Pedro — Geographic EntityAmbergris Caye — Geographic EntityBelize — Geographic EntityCentral America — Geographic EntityNER systems look for how a word is placed in a sentence and make use of other statistical models to identify what kind of word actually it is. For example — ‘Washington’ can be a geographical location as well as the last name of any person. A good NER system can identify this.Kinds of objects that a typical NER system can tag:People’s names.Company names.Geographical locationsProduct names.Date and time.Amount of money.Events.STEP 8: Coreference Resolution:San Pedro is a town on the southern part of the island of Ambergris Caye in the Belize District of the nation of Belize, in Central America.According to 2015 mid-year estimates, the town has a population of about 16,444.It is the second-largest town in the Belize District and largest in the Belize Rural South constituency.Here, we know that ‘it’ in the paragraph stands for San Pedro, but for a computer, it isn’t possible to understand that both the tokens are same because it treats both the sentences as two different things while it’s processing them. Pronouns are used with a high frequency in English literature and it becomes difficult for a computer to understand that both things are the same. Hence, this step is used. This step is indeed the most difficult stepIn the upcoming articles, I’ll try sharing about the history of NLP, how it evolved, various past models and why they failed, NLP Libraries and coding NLP pipeline in Python. I’d love discussing various papers as well.Please, feel free to correct me on any topic if I went wrong somewhere and do let me know about improvements.Cheers!Don’t forget to give us your 👏 !https://medium.com/media/7078d8ad19192c4c53d3bf199468e4ab/hrefIntroduction to Natural Language Processing was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story. Read more »
  • Are we ready to communicate with chatbots?
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    We’ve entered a phase of the digital Era in which “artificial intelligence” and “virtual assistants” are on the agenda and the stories from the 80’s and 90’s we saw projected on the big screens are transitioning from science fiction to reality. In our modern world, where robots are becoming more human, there’s something we must ask: are you ready to communicate with a robot or a chatbot?“A chatbot? What is that?” — you may ask.Even if you don’t know, it’s highly likely that you’ve already communicated with one or, surprisingly, the device you’re using to read this article may have one of these systems.“Oh really?”Yes. And, if this wasn’t amazing enough, these digital robots are available in two flavors:Virtual assistants. Siri, Alexa, Google Assistant and Microsoft Cortana are some of the examples available on the market. These kinds of chatbots, usually available on smartphones, are equipped with artificial intelligence and machine learning, two features that enable them to learn and understand what they’re asked.Or in messaging apps, which companies are increasingly adopting to solve basic questions and to have a customer service available 24/7. These assistants are available on platforms like Facebook Messenger, WeChat, LinkedIn and, more frequently, on institutional websites.Top Articles on How Businesses are using Bots:1. Is Chatbot a synonym for great Customer Experience?2. Five Inspirational Startups Using AI and Chatbot Technology3. How Businesses are Winning with Chatbots & Ai4. Chatbot Conference in San FranciscoIt is, then, highly likely that you’ve already talked to a chatbot without realizing it. According to a study by Drift, in 2017, 15% of the respondents had communicated with a messaging chatbot. But are people ready to communicate with chatbots if they know they’re talking to a robot?63% of people say “yes” to chatbotsStudies show us that yes — we are ready. The Humanity in the Machine report, for example, indicates that 63% of people are predisposed to communicate with a brand or a business via chatbot. Another study points out that 29% of consumers would prefer to contact businesses via chatbot, more than those who would rather do it by email (27%).Among millennials, a generation whose behavior partly differs from its predecessors for preferring to communicate with messages, 48% say they’re ready to receive recommendations of advice from chatbots, as reported by research from DigitasLBI.All these studies point to a positive scenario shouldcompanies use these modern tools in their operations. However…Consumers are not willing to deal with bad chatbotsAlthough they are ready to connect with robots, consumers are not ready to carry out a conversation with bad chatbots. The same study from DigitasLBI indicates that 73% of Americans wouldn’t contact a company via chatbot again if they had a bad experience initially. Humanity in the Machine points in the same direction with the conclusion that 61% of people find robots that can’t answer something more frustrating than if it’s a person.So, are we ready to communicate with chatbots? Yes, but if companies want to create value with these systems, they need an efficient assistant that’s capable of answering the simple questions that customers ask.Are you ready to adopt chatbots? Contact us via info@visor.ai and let us introduce you to this brand new world.Don’t forget to give us your 👏 !https://medium.com/media/7078d8ad19192c4c53d3bf199468e4ab/hrefAre we ready to communicate with chatbots? was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story. Read more »
  • 3 Practical Ways AI in the Contact Center Gets Real
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    No matter what kind of work you do, it’s getting harder and harder to steer clear of conversations about how artificial intelligence is poised to change everything. If it feels like the mid-90’s all over again to you — when it seemed every conversation was about the World Wide Web and the Information Superhighway (thank you Al Gore) — I get it.Here’s the plain truth: as real and as revolutionary as the Internet was in the 90s, so will be the case for AI in the coming years, in what’s being hailed as the Fourth Industrial Revolution.Closer to home and much more practically, let’s take a look at how AI is changing the contact center and customer experience, and where the impact is most significant. Specifically, we’ll focus on three applications of AI that will forever change how we build and run contact centers: Chatbots, analytics, and the agent experience.AI-powered ChatbotsChatbots — automated conversation programs designed to replicate talking with human agents in an effort to help brands eliminate wait times — are nothing terribly new, first appearing on the scene around 1966. The modern chatbot era began in 2010 with Apple’s Siri, and today they are more or less mainstream, with an Oracle report from 2016 stating that 80% of C-suite leaders and senior marketers have already implemented chatbots or plan to do so by 2020.To be clear, there are chatbots and then there are AI-powered chatbots (read this to understand the difference). Chatbots that run on keywords and without the benefit of tools such as Natural Language Processing (NLP) are a dime-a-dozen, easy to spin up, and acceptable in the right context. Wire them up with AI, and now you’re into a whole new level of customer engagement. That’s because AI (or specifically the NLP branch) lets chatbots partake in far more natural conversations; they’re far better at understanding your customers’ intentions, and as a result can respond more accurately.Top Articles on How Businesses are using Bots:1. Is Chatbot a synonym for great Customer Experience?2. Five Inspirational Startups Using AI and Chatbot Technology3. How Businesses are Winning with Chatbots & Ai4. Chatbot Conference in San FranciscoIf you’ve deployed a non-AI chatbot before and had some success, well ‘you ain’t seen nothing yet’. AI-powered chatbots interact better with your customers, leading to better experiences for them and higher satisfaction scores for you. When integrated with your core business systems, AI-powered chatbots are a huge step up from their non-AI ancestors. I’ll leave the human evolution analogies out of this one.I deliberately opened this story with chatbots as they are the most recognized and most widely adopted form of AI. That’s because they’re also the most press-friendly AI implementation. But the reality is that the impact chatbots have on customer experience pales in comparison to the next two use cases.AI-powered AnalyticsIf you remind yourself that AI is, in its simplest definition, the application of computer programming to human brain-like activities, then it becomes easy to think of AI involvement in areas other than speech or communications.The human brain has an amazing capacity to process vast amounts of data simultaneously. How else can you explain how you’re able to recognize your best friend from 100 yards away just by the way she walks? Your brain has concurrently recognized height, build, gait, gestures, and loads of other data points to tell you ‘hey, there’s Sarah!’. To do this, your brain uses something called crystallized intelligence — the application of knowledge acquired through experience. A traditional computer’s equivalent would be its programming; it can do what it knows how to do, and not much else as it has no capacity to learn new things. AI is not burdened by this limitation.Business intelligence is one domain already witnessing a massive overhaul thanks to AI. When you point AI at vast amounts of disconnected data — sales history, customer profile, website cookie data, chat history — it will be able to see patterns and deduce insights in ways that humans can’t, because it takes us much longer to ingest and store all this data. To put a blunt point on it, when you use AI applications to comb through your customer data, you will begin to identify key indicators of critical business traits including risk, revenue opportunities, churn, and much more. The deductive power of AI hooked up to the computational power of today’s business hardware puts more and deeper insights within short reach. Your ability to use data more intelligently will completely revolutionize how you run your business, let alone your customer experience operation. There are many examples of businesses already doing just that.AI-powered Agent AssistantsI’ve saved this one for last because to me it’s not only the most exciting to ponder, it’s also perhaps the most accessible. AI for your agents — for, not instead of — will change the contact center more profoundly than the first telephone switchboard or softphone ever did. It will make your agents faster and more efficient and will leave them more challenged and fulfilled on the job than ever before.Here’s how that happens.A customer starts a conversation with you via chat, social media, messaging, email, wherever. Your AI-powered agent assistant ‘listens in’ on the conversation, determines what the customer wants to do, and presents your agent with a range of answers or resources to resolve the question. The agent chooses the best option based on their sense of the situation and passes it along to the customer themselves (unlike a bot which would handle the conversation completely). Their problem solved, the customer goes away happy.What just happened?1. The customer received a highly accurate, high-quality answer2. The entire conversation took about 15–20% less time3. The customer gave you a 5-star rating, promising future loyalty and earning you more share of walletWhat else just happened?1. Your newer agents ramped up more quickly, saving you serious money through quicker payback2. All your agents learned how to handle questions about new products or services with less training thanks to an AI application that helped them find answers to questions they have not yet seen firsthand3. If the customer’s question was entirely new with no pre-existing resource available, then your agents can flag it as a gap that needs closing. This will make it incredibly easy for your agents — the ones who need the answers most but who until now had no way to ask for help without totally disrupting their routine — to help your organization fill in the knowledge gaps.I mentioned this type of AI application being more accessible, so let me explain that. Aside from offering substantial productivity gains, agent-facing AI is also the easiest and least risky to implement. That’s because when you take away the customer-facing angle, a whole lot of anxiety disappears. I refer to the naturally human hesitation and concern that you and your management team may have around adopting customer-facing AI technology like the chatbots mentioned above. Internal applications are understandably easier to swallow.Now do you see why this AI application is the most exciting to me? First of all, any technology that makes the contact center faster and more productive is a good thing. Second, any technology that strengthens the role of human agents is also a good thing (yes, I know chatbots can be seen as replacements, but realistically, if all your agents face are the simple, boring questions then you’re likely experiencing considerable agent churn or at least having to constantly deal with poor motivation and productivity).Lastly, and most importantly, there’s no putting this stuff back in the box. But you wouldn’t want to because then you’d miss out on all the amazing enhancements these technologies stand to deliver for your business. Chatbots aren’t your thing? I get that (sort of). Data analytics not in your domain? Fair enough. But AI applications that make your agents better? Why on earth would you not go there? Let AI find the answers, and let your agents deliver them with care and compassion. It’s a win-win.To learn more about Comm100 and AI in the contact center, click here.Don’t forget to give us your 👏 !https://medium.com/media/7078d8ad19192c4c53d3bf199468e4ab/href3 Practical Ways AI in the Contact Center Gets Real was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story. Read more »
  • Conversational AI in Media & Entertainment — Haptik Blog
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    Conversational AI in Media & Entertainment — Haptik BlogConversational AI, in the form of AI-powered chatbots and voice bots, has been disrupting a number of key industries across the globe, including E-Commerce, Travel and Hospitality and the Financial Services sector. The Media and Entertainment industry is certainly no exception to this trend.From information dissemination, to advertising and promotion, to product discovery and more — there are a wide range of applications for Conversational AI in the rapidly evolving Media and Entertainment space.In a sense, Conversational AI is an ideal fit for Media and Entertainment. After all, Artificial Intelligence and Machine Learning are technologies that process vast amounts of data to realize business outcomes. What could be more natural than putting them to work in businesses where data itself (in the form of written and audio-visual content) is the product offering?Conversational AI offers a wide range of benefits to media companies. An AI-powered chatbot can boost the effectiveness of communication on any platform in an era where millennial viewership across digital channels is taking precedence as the primary engagement metric. They can even help audiences pinpoint the information they are searching for or swiftly and effectively complete tasks.Top Articles on How Businesses are using Bots:1. Is Chatbot a synonym for great Customer Experience?2. Five Inspirational Startups Using AI and Chatbot Technology3. How Businesses are Winning with Chatbots & Ai4. Chatbot Conference in San FranciscoLet’s take a close look at some of the most interesting use cases for Conversational AI in the Media and Entertainment industry:Customer service and efficient information dissemination are among the most natural and widespread use cases for Conversational AI.Recent studies suggest that as many as 96% of consumers across the globe today consider customer service as a key aspect of deserved loyalty to a brand. Moreover, about 72% of them expect customer service staff to know everything about them. With numerous OTT (over-the-top) content platforms breaking into the industry today, Conversational AI can serve as a reliable means of providing customers with instant solutions at scale. This includes news updates, entertainment blogs, music, and video streaming, gaming updates, and much more.The successful implementation of Haptik’s Customer Support solution for Dream 11 only reaffirms this. With a support base of only 30 agents, handling a 10X spike in customer queries during the IPL season was a challenging situation. By deploying a dedicated support bot for the website, Android, and iOS apps of Dream 11, and training it to respond to routine queries and FAQ’s about the sports game, Haptik was able to automate the resolution of about 80% of the 1 million+ support queries that Dream11 received. What’s more, the average resolution time stood at only 32 seconds!Needless to say, Conversational AI is a great way for media companies to effectively and inexpensively provide information to their customers, and resolve their queries.Branded ContentOne of the most interesting aspects of Conversational AI is that it is perfect for user personalization. By sifting through the vast amount of user data, AI chatbots can showcase relevant content to users and thus garner more views/clicks. This in turn ends up boosting both CTR and customer satisfaction.Branded content on chatbots enables you to humanize your brand and connect with users in a more authentic, conversational manner. For instance, you can create a friendly character as a bot that can even be tagged as your brand’s digital ambassador. In this way, a well-designed and conceptualized chatbot can serve as an appealing piece of content on its own!But this is just the tip of the iceberg.Chatbots can also serve as an active distribution channel for branded content. Take any leading media publication house and search for their Facebook bot. They will engage you in a hearty conversation within a minute, with the goal of motivating you to subscribe to regular updates. Here’s a look at the chatbot of the Washington Post below:The bot features the top news stories of the day. Users have the option to swipe through five news headlines along with the ability to read more similar stories. And when asked about a general news question, the bot can share specific stories around the topic. These features are enhanced only during specific events. For instance, during elections, users can share their zip codes and the bot returns with relevant election results based on their locations.Of course, the use of Conversational AI in the Media and Entertainment sector is not restricted to text-based chatbots alone. In a world where the adoption of voice-based conversational interfaces such as Amazon Alexa and Google Home Assistant is steadily becoming widespread, there is tremendous potential for companies to develop and distribute voice-based branded content.One such innovative example of voice-based entertainment is “The Inspection Chamber” — an interactive sci-fi/comedy drama produced by the BBC, available on Amazon Alexa and Google Home. Dubbed as “conversational radio”, the series allows audiences to be a part of the story using voice commands. All users need to do is ask their smart speaker to “ open the Inspection chamber” and they can then directly interact with characters in the story for a truly next-generation, immersive storytelling experience.Advertising and PromotionAnother unique application of chatbots within the industry is in marketing, advertising, and promotions. They can be leveraged as an integral part of a promotional campaign for an artist, book, movie, or even a TV show. For instance, just before the recent season of Game of Thrones hit media streaming platforms (such as Hotstar in India), the marketing team of the power-packed show deployed a neat chatbot on Facebook that took the form of major GOT characters (decided based on user input) that are widely loved by audiences.Such a media marketing strategy can prove to be highly effective, since it can engage both ardent and casual followers of a media product. But the masterstroke lies in the fact that customers can engage with the chatbot based on their preferences. This effectively translates to customers engaging with the marketing campaign to make it more relevant and targeted for themselves, which contributes to a positive feedback loop that further increases their engagement!Such chatbots, paired with impeccable timing, have the potential to clock soaring press awareness. In the first week of the launch itself, the bot was picked up by all leading media publication houses such as Mashable, The Verge, CNet and more. This resulted in about 3.92K social shares of press articles along with 5.5 million estimated coverage views! And it did not stop here. After the end of the first two weeks, the bot had handled over 20,000 conversations with 15,000 Game of Thrones fans around the world with an impressive average conversation time of nearly 5 minutes.Haptik has developed Conversational AI solutions for a number of enterprise partners in the Media & Entertainment sector. You can read more about our work hereProduct (Content) DiscoveryBy understanding the past behaviour of the user on a content platform, Conversational AI can learn about their preferences. With countless media works and digital copies of video, audio and textual content, chatbots can use notifications to help users come across content that they would love to consume. In this manner, Conversational AI optimizes the quality of search results while eliminating the very need to search!All this and more is enabling content creators to better manage their content lifecycles and accelerate the media production process. Conversational AI serves as a hands-on digital assistant that aids content discovery. Algorithms in the space are not only influencing what customers witness on platforms but even how content is created in the first place!AI-powered chatbots also provide a great opportunity to push evergreen content if your SEO efforts are failing. If you are able to figure out when, where, why, and how users will want or need your content, you will be able to rest easy. Take the case of the Food Network chatbot that lets users easily discover relevant recipes from their website.In this way, chatbots eliminate the need for users to interact with a passive multi-panel interface. They can directly interact with dynamic chatbots, share their preferences and receive highly relevant product/content recommendations. Users can even specify particular features of the product/content that they prefer and prioritize their options accordingly. Some experts even refer to such dedicated bots as content bots, whose sole purpose is to deliver content and not to perform tasks.Conversational AI can also be used to extend personalized recommendations to users. This is made possible through predictive analytics and modelling. The AI analyzes the data, digs through it to unearth relevant statistics, and ultimately leverages it to extend personalized recommendations to users for maximum conversions.To sum up…The examples presented above are only a glimpse of the myriad applications of Conversational AI in the Media and Entertainment industry. Chatbots in the media and entertainment sector contribute to significant reductions in customer service costs and help customers come across content that they love engaging with. Leveraging the power of Conversational AI, media companies can significantly expand their range of offerings, improve user experience, and grow their customer base.So if you’re part of a media or entertainment company, and you’re looking for the ‘next big thing’ that will help you revolutionize content creation, promotion and distribution, as well as transform the way you engage and serve your customers, then you do not need to look much further than Conversational AI.Are you interested in developing a Conversational AI solution for your business?Get in TouchDon’t forget to give us your 👏 !https://medium.com/media/7078d8ad19192c4c53d3bf199468e4ab/hrefConversational AI in Media & Entertainment — Haptik Blog was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story. Read more »
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