{"id":13,"date":"2020-08-17T07:52:18","date_gmt":"2020-08-17T07:52:18","guid":{"rendered":"https:\/\/machine-learning.webcloning.com\/2020\/08\/17\/chatbot-best-practices-8-tips-tricks-you-can-benefit-from-today\/"},"modified":"2020-08-17T07:52:18","modified_gmt":"2020-08-17T07:52:18","slug":"chatbot-best-practices-8-tips-tricks-you-can-benefit-from-today","status":"publish","type":"post","link":"https:\/\/salarydistribution.com\/machine-learning\/2020\/08\/17\/chatbot-best-practices-8-tips-tricks-you-can-benefit-from-today\/","title":{"rendered":"Chatbot Best Practices: 8 Tips &#038; Tricks you Can Benefit from Today"},"content":{"rendered":"<div readability=\"138.18791946309\">\n<p class=\"p1\">Designing an AI chatbot is a tricky exercise that cannot be improvised. Following a set of best practices will help you avoid common mistakes and pitfalls that other companies have encountered. This will ensure that you create a bot that is helpful, engaging, and meets customers\u2019 expectations every time. We have compiled the top 8 chatbot best practices when it comes to designing state-of-the-art conversational experiences. Use these to make your chatbot a success.<\/p>\n<h2 class=\"p1\"><b>Chatbot best practice #1: set a goal for your chatbot<\/b><\/h2>\n<p class=\"p2\">As obvious as it may seem, this is the number one chatbot best practice to keep in mind when starting to design a conversational agent. You can create a bot for almost anything nowadays, so setting a clear goal for yours and outlining what it\u2019s supposed to do, right from the beginning, will prevent you from getting carried away.<\/p>\n<p class=\"p2\">Defining what can be automated is a good place to start, but remember to always keep your user\u2019s needs in mind when doing so. It can be as simple as answering user\u2019s queries, or more complex, like allowing employees to request annual leave, but your chatbot has to be user-centric and help solve their problems if you want it to be successful.<\/p>\n<h2 class=\"p1\">\n<b>Chatbot best practice #2: <\/b><b>give your chatbot a personality<\/b><br \/>\n<\/h2>\n<blockquote readability=\"4.0860215053763\">\n<p class=\"p2\"><i>\u201cPersonality is the new user experience.\u201d<br \/><\/i>(Source: Ultan O\u2019Broin from <a href=\"https:\/\/chatbotsmagazine.com\/avoiding-a-clash-of-personalities-chatbot-design-is-no-different-3f0bcd30defd\" target=\"_blank\" rel=\"noopener noreferrer\"><span class=\"s1\">Chatbots Magazine<\/span><\/a>)<\/p>\n<\/blockquote>\n<p class=\"p2\">The second important point that you should think about when creating your <strong><a href=\"https:\/\/www.inbenta.com\/en\/blog\/conversational-chatbot\/\">conversational chatbot<\/a><\/strong>\u00a0is to ensure that it doesn\u2019t sound like a robot. That means giving it a personality and a tone of voice that\u2019s aligned with your brand\u2019s values.<\/p>\n<p class=\"p2\">This is a tricky exercise as a lack of personality will make your chatbot sound dull and uninteresting, on the other hand, too much personality can also ruin an otherwise well-designed experience.<\/p>\n<p class=\"p2\">Ask yourself these questions to help you find the right balance:<\/p>\n<ul class=\"ul1\">\n<li class=\"li2\">\n<b>How would your target audience speak?<\/b><br \/>A chatbot often mirrors the personality of its audience by writing in the style they speak.<\/li>\n<li class=\"li2\">\n<b>What\u2019s the name of your chatbot?<\/b> It can be straightforward such as your brand\u2019s name followed by \u2018bot\u2019 or \u2018chatbot\u2019, or a play on words for example.<\/li>\n<li class=\"li2\">\n<b>Does it have a gender and a visual representation?<\/b> Inbenta gives you the option to choose from a vast gallery of avatars so that you can find the one that will become the perfect representation of your brand.\u00a0<b><br \/><\/b>\n<\/li>\n<\/ul>\n<h2 class=\"p1\">\n<b>Chatbot best practice #3: i<\/b><b>ntroduce your chatbot and set expectations<\/b><br \/>\n<\/h2>\n<p class=\"p2\">As mentioned at the beginning of this article, you have to set a goal for your chatbot. Now that you know what your bot was designed to do, you have to clearly communicate that to your users. Your welcome message is the perfect place to introduce your bot and list all of its capabilities.<\/p>\n<p class=\"p2\">By being upfront about functionalities, as well as limitations, you will manage the user\u2019s expectations and prevent frustrations and disappointment.<\/p>\n<h2 class=\"p1\">\n<b>Chatbot best practice #4: b<\/b><b>reak up the information into small chunks<\/b><br \/>\n<\/h2>\n<p class=\"p2\">A well-designed bot can present users with lots of informative and interesting content. That\u2019s great, but don\u2019t forget to break up the information when pushing useful and engaging material. That means sending multiple short messages rather than a long one. Huge blocks of text are difficult to read and may frustrate, discourage, and\/or overwhelm users. By shortening messages, your bot will provide a better user experience and also mimic the flow of human messaging.<\/p>\n<p class=\"p2\">When developing your chatbot with Inbenta, you also have the option to use a side-bubble where you can develop more in-depth content, which is another great way of breaking up the information.<\/p>\n<p><img class=\"aligncenter size-full wp-image-37662\" data-cfsrc=\"https:\/\/www.inbenta.com\/wp-content\/uploads\/2020\/06\/Inbenta-chatbot-side-bubble.png\" alt=\"Inbenta chatbot best practice: use a side-bubble\" width=\"713\" height=\"522\" srcset=\"https:\/\/www.inbenta.com\/wp-content\/uploads\/2020\/06\/Inbenta-chatbot-side-bubble.png 713w, https:\/\/www.inbenta.com\/wp-content\/uploads\/2020\/06\/Inbenta-chatbot-side-bubble-300x220.png 300w\" sizes=\"(max-width: 713px) 100vw, 713px\"><\/p>\n<p><noscript><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter size-full wp-image-37662\" src=\"https:\/\/www.inbenta.com\/wp-content\/uploads\/2020\/06\/Inbenta-chatbot-side-bubble.png\" alt=\"Inbenta chatbot best practice: use a side-bubble\" width=\"713\" height=\"522\" srcset=\"https:\/\/www.inbenta.com\/wp-content\/uploads\/2020\/06\/Inbenta-chatbot-side-bubble.png 713w, https:\/\/www.inbenta.com\/wp-content\/uploads\/2020\/06\/Inbenta-chatbot-side-bubble-300x220.png 300w\" sizes=\"(max-width: 713px) 100vw, 713px\"><\/noscript><\/p>\n<h2 class=\"p1\">\n<b>Chatbot best practice #5: t<\/b><b>est, monitor, tune<\/b><br \/>\n<\/h2>\n<p class=\"p2\">Going through an alpha and beta testing phase before releasing your chatbot is quite obvious, but you have to keep on monitoring results even after going live. It is surprising to see how many companies forget about this simple chatbot best practice and forget about their bot once it\u2019s been developed.<\/p>\n<p class=\"p2\">Inbenta\u2019s Workspace will provide you with lots of data and analytics to help you analyze your <a href=\"https:\/\/www.inbenta.com\/en\/blog\/10-key-metrics-to-evaluate-your-ai-chatbot-performance\/\">bot performance<\/a>, perform a gap analysis by detecting questions that did not get an answer, or the ones that got an answer but were not viewed by the user.<\/p>\n<p><img class=\"size-full wp-image-37664\" data-cfsrc=\"https:\/\/www.inbenta.com\/wp-content\/uploads\/2020\/06\/Inbenta-back-office.png\" alt=\"Inbenta chatbot best practice: test, monitor, tune\" width=\"1626\" height=\"704\" srcset=\"https:\/\/www.inbenta.com\/wp-content\/uploads\/2020\/06\/Inbenta-back-office.png 1626w, https:\/\/www.inbenta.com\/wp-content\/uploads\/2020\/06\/Inbenta-back-office-300x130.png 300w, https:\/\/www.inbenta.com\/wp-content\/uploads\/2020\/06\/Inbenta-back-office-1024x443.png 1024w, https:\/\/www.inbenta.com\/wp-content\/uploads\/2020\/06\/Inbenta-back-office-768x333.png 768w, https:\/\/www.inbenta.com\/wp-content\/uploads\/2020\/06\/Inbenta-back-office-1536x665.png 1536w\" sizes=\"(max-width: 1626px) 100vw, 1626px\"><\/p>\n<p><noscript><img decoding=\"async\" loading=\"lazy\" class=\"size-full wp-image-37664\" src=\"https:\/\/www.inbenta.com\/wp-content\/uploads\/2020\/06\/Inbenta-back-office.png\" alt=\"Inbenta chatbot best practice: test, monitor, tune\" width=\"1626\" height=\"704\" srcset=\"https:\/\/www.inbenta.com\/wp-content\/uploads\/2020\/06\/Inbenta-back-office.png 1626w, https:\/\/www.inbenta.com\/wp-content\/uploads\/2020\/06\/Inbenta-back-office-300x130.png 300w, https:\/\/www.inbenta.com\/wp-content\/uploads\/2020\/06\/Inbenta-back-office-1024x443.png 1024w, https:\/\/www.inbenta.com\/wp-content\/uploads\/2020\/06\/Inbenta-back-office-768x333.png 768w, https:\/\/www.inbenta.com\/wp-content\/uploads\/2020\/06\/Inbenta-back-office-1536x665.png 1536w\" sizes=\"(max-width: 1626px) 100vw, 1626px\"><\/noscript><\/p>\n<p><span>Monitoring your bot thanks to such a dashboard will allow you to tune it by adding content or improving matching between user\u2019s requests and content in the knowledge base, thus improving its performance over time to reach amazing results.<\/span><\/p>\n<h2 class=\"p1\">\n<b>Chatbot best practice #6: r<\/b><b>equest user feedback<\/b><br \/>\n<\/h2>\n<p class=\"p2\">Giving the option for users to rate answers \u2013 using a thumbs up or down button for example \u2013 is an easy way to gather feedback. You can also offer them the option to provide written feedback when a negative mark is given so that they can provide more in-depth explanations of why interactions with your bot were not satisfactory.<\/p>\n<p class=\"p2\">Ratings and written feedback can be very helpful and instructive. They give you the opportunity to detect gaps in your knowledge base or ways to use your bot or formulate questions that you did not think of.<\/p>\n<h2 class=\"p1\">\n<b>Chatbot best practice #7: d<\/b><b>etect frustration and handoff to a human<\/b><br \/>\n<\/h2>\n<p class=\"p2\">No matter how good or well-designed your chatbot is, every bot has its limitations. These limitations will sometimes create frustrations, that\u2019s why you need a technology that can detect your users\u2019 emotions by analyzing their tone and the type of language they use.<\/p>\n<p class=\"p2\">Inbenta\u2019s <strong><a href=\"https:\/\/www.inbenta.com\/en\/technology\/ai-nlp\/natural-language-technology\/\" target=\"_blank\" rel=\"noopener noreferrer\"><span class=\"s1\">NLP technology<\/span><\/a><\/strong> and intent detection can do exactly that and provide an option to escalate the conversation to a human agent when\/if necessary. Using our HyperChat is the best way to complement your chatbot when it reaches its limits. Escalating the conversation can be done as a reaction to the user\u2019s frustration or explicit request, but can also be offered proactively by the bot when it can\u2019t answer a question after it\u2019s been rephrased once or twice.<\/p>\n<h2 class=\"p1\">\n<b>Chatbot best practice #8: c<\/b><b>hoose your provider and technology wisely<\/b><br \/>\n<\/h2>\n<p class=\"p2\">Last but not least, the most important best practice when developing a chatbot is to choose wisely when it comes to picking the technology (and by extension the provider) that your bot will use.<\/p>\n<p class=\"p2\">As mentioned in a previous article, there are <span class=\"s1\">different types of chatbots<\/span>. Some basic ones based on buttons or keywords and some best-performing ones, such as Inbenta\u2019s conversational chatbots which use <strong><a href=\"https:\/\/www.inbenta.com\/en\/blog\/symbolic-ai-vs-machine-learning\/\" target=\"_blank\" rel=\"noopener noreferrer\"><span class=\"s1\">NLP technology coupled with symbolic AI<\/span><\/a><\/strong>. This is by far the best combination when it comes to <strong><a href=\"https:\/\/www.inbenta.com\/en\/blog\/best-ai-chatbots\/\">obtaining the best results out of your AI-powered chatbot<\/a><\/strong> and that\u2019s something that you should keep in mind when deciding on your technology provider.<\/p>\n<p class=\"p2\">With 15 years of experience and over 250 customers globally, Inbenta has built a solid reputation and can help you supercharge how you interact with your users, thanks to our patented and proprietary NLP technology. Want to know more? Get in touch today!<\/p>\n<p><center><a class=\"btn btn-special btn-color\" href=\"https:\/\/www.inbenta.com\/en\/schedule-demo\/?utm_medium=cta&amp;utm_source=blog&amp;utm_campaign=website\" target=\"_blank\" rel=\"noopener noreferrer\">Let\u2019s get in touch<\/a><\/center><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>https:\/\/www.inbenta.com\/en\/blog\/chatbot-best-practices\/<\/p>\n","protected":false},"author":1,"featured_media":14,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[3],"tags":[],"_links":{"self":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts\/13"}],"collection":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/comments?post=13"}],"version-history":[{"count":0,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts\/13\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/media\/14"}],"wp:attachment":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/media?parent=13"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/categories?post=13"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/tags?post=13"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}