Belitsoft > Custom Chatbot Development for a Chatbot Store / PAAS for Bot-Building

Custom Chatbot Development for a Chatbot Store / PAAS for Bot-Building

Client

Our Client is a startup. The company offers an innovative chatbot-building PaaS (Platform as a Service) with an easy interface to create new chatbots with no deep coding skills and also a Store with ready-to-use chatbots. This Store has a great variety of chatbots or chatbots’ “templates” (design+script/scenario) for almost every industry (Finance/Insurance, E-commerce, Healthcare, Education, IoT and so on). The platform’s users can modify the existing chatbots' templates and publish them to a variety of high-traffic channels such as Facebook Messenger, Skype, Slack, Viber, Telegram Messenger, and others.

Challenge

Our Client asked us to augment his offshore outsourcing development team in order to develop chatbot (Ordering & Loyalty Program Chatbot, Weather Forecast Chatbot) for his Store. He also needed to add 2 testing specialists to the project in order to provide a high quality of the platform and stable chatbots’ functionality.

Process

Our development process

To start the creation of the Ordering & Loyalty Program Chatbot, our team analyzed the market and found some innovative ways to use bots for business purposes. Belitsoft always focuses on the best practices and latest trends, so we decided to follow the Starbuck’s example, but create a chatbot that not only receives orders from customers but also invites them to take part in a loyalty program.

Overall, our work consisted of 5 parts:

  • Creating a scenario (a set of interactions) for the chatbot;
  • Adding arithmetic operations to the price calculation;
  • Adding logic and arithmetic operations to the bonuses calculation;
  • Improving the scenario and logic of the bot, adding new interactions;
  • Testing the chatbot.

Thereby, our team created the scenario, proposed it to the Client and started chatbot’s creation right after his approval. Our team successfully managed to create and test the chatbot. Now the users of our Client’s cloud-based platform can easily use this template, modify it according to their business needs and publish a ready-made chatbot on their websites or other public channels.

Stages of the Weather Forecast Chatbot development:

  • Our developer successfully connected 2 APIs (the Client’s web app’s API (Laravel) and the weather forecast web service’s API) using JSON API.
  • Our designer prepared the mockups to show weather forecasts in a user-friendly manner in the PNG format.
  • Our developer used the HTML2PDF and ImageMagick libraries to convert HTML to PNG.
  • Testing the chatbot.

Our testing process

The project work was divided into 2 phases:

  • Testing planning and creation of the checklist;
  • Implementation of testing.

Our team organized the project work as follows: one tester is responsible for the website testing, and the other – for testing the user area and chatbots’ functionality.

Our testers analyze the Client’s requirements, plan a testing process, create checklists and test cases for the most complex scenarios, perform positive test cases (when chatbots are being created, changed and filled with content) and negative test cases.

Because the project is big and evolves rather fast (new features are constantly being added), the start of the third project phase seems to be obvious and will possibly include regression testing, bug fix testing, and new functionality testing.

Our communication approach

Our team uses JIRA as a bug-tracking system. That makes the process of testing transparent and objective because every team member, as well as our Client, can access the project anytime and monitor our testing process in real time.

In addition, our team uses Skype to support active communication with the Client that increases our efficiency.

Results

1. We created the Ordering & Loyalty Program Chatbot that stimulates people to make an order and get bonuses for their purchase. The main functions of the bot:

  • Extract a customer’s name;
  • Propose the menu;
  • Calculate the cost of the order (add more items to the order or cancel the last added item);
  • Calculate bonuses for the purchase (if a customer saves up 100 bonuses, the bot proposes a free lunch that can be added to the order; the bot also automatically checks if a user has enough bonuses to get a free lunch);
  • Receive the order and propose a delivery method (the bot extracts a user’s address if a user chooses delivery).

2. We created the Weather Forecast Chatbot that provides a weather forecast using the API of a weather forecast web service. The main functions of the bot:

  • Show today’s weather (temperature, max temperature per day, min temperature per day, cloud cover, wind speed, pressure, humidity);
  • Show the weather for the next 1-5 days (for a certain day with a 3-hour forecast);
  • Show the weather for the next 5 days (a summary table with a 3-hour forecast).

3. Both chatbots were tested manually using positive and negative test cases.

Within 4 months, our testers found 550 bugs and 482 bugs (88%) were resolved by the development team.

The website, user area, and chatbots’ functionality were successfully tested in the required environments:

  • Cross-browser testing: Chrome, Firefox, Internet Explorer, Microsoft Edge, Safari;
  • Cross-platform testing: Windows (PC), macOS (Mac mini, iPad), Android 7 (Tablet Google Nexus 10, Mobile Phone Samsung Galaxy S6), iOS 9, 10, 11 (iPhone 5, 6);

4. The main parts of the chatbot-building platform were enhanced:

  • Our testers identified the problem with the auto-save option during functionality testing. It didn’t work correctly, therefore users were losing much info. Some other problems were also identified and fixed.
  • All the non-working pop-ups and buttons were fixed, and fields’ verification was set up. The website became highly responsive and user-friendly after the bugs, discovered during usability testing, had been fixed.
  • The external interface of the user area (a control panel) was improved, and chatbots’ display was corrected after GUI testing.

Today, our chatbots are widely used and help the customers of our Client to deliver the best possible messaging experience to the end-users.

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Use cases of AI chatbots for Learning and Development in corporates 1. Employee coach Corporate learning is not something people love. But it doesn’t have to be this way. And when the companies compete for better employees, good learning opportunities can be an edge. The learning process can be performed through a Facebook messenger bot which trains and quizzes employees. It is designed with microlearning approach in mind – small chunks of information for brief attention spans. The bot can adapt messages to individual employees and boasts a 98% engagement rate. The developers of such chatbots claim that corporate learning bots can save employees about 2-5 days per year which would be spent on actual work, rather than study. 2. Curriculum Customizer Personalized learning is one of the top trends right now. Just as chatbots are. No wonder people look for ways to combine them. 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And because data is constantly collected along the way, the chatbot can identify the skills students need to work on to increase their score and will suggest practicing the skill again. Knowre Another popular AI chatbot application is language learning. A good example is Duolingo that has been investing in AI and machine learning to make language learning more engaging by automatically tailoring lessons to each individual — kind of the way a human tutor might. The great thing about using an AI bot is that it will get smarter the more it is used. The purpose of an AI-powered chatbot is to simulate a human for practicing scenarios that users are likely to encounter. They focus principally on functional skills and prepare students to use their language skills in the real world. The language learning chatbots use AI algorithms to understand the user context and be able to answer contextually and uniquely. It means that every user gets a different response for a similar inquiry. 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Presented through a mobile application, it leverages chatbots, artificial intelligence, voice recognition, and a predictive analytics engine to deliver personalized advice and services, guided assistance, and curated content. It gives students easy access to their unit information, results, timetable, or answers to common student questions. Genie Genie is a proactive agent. So if you have an exam in two days and you haven’t been reading the material, Genie is going to remind you that the exam is coming up and you haven’t touched your material,” Deakin's chief digital officer William Confalonieri said. “To know that, we need to know that you haven’t been reading material (because the learning management system hasn’t been accessed) - we collect all that information in a predictive analytics engine that gathers data and allows Genie to react.” However, software developers realize the limits of AI and use AI chatbots to facilitate conversations with the right support staff when needed. Need your own chatbot? Contact us for a free quote! Use cases of AI chatbots for improving educators’ productivity To educational leaders who struggle to reach a generation that shuns official websites and mass emails, the use of a chatbot in education solves the issue. The reason is students feel communicating in chats more personal. Besides, chatbots are available 24/7 and respond instantly. The response time for 99 percent of queries ranges from 6 to 10 seconds. The increasing number of administrations and teachers recognize this cost-effective and valuable way to keep their students hooked and streamline educational and administrative processes more efficiently. For education stakeholders, AI-powered chatbots come especially handy as: Tool for automation of administrative tasks to save educators’ time and switch their focus on more critical tasks. Tool for gathering feedback about learning material to understand the efficiency of teaching methods and improve the curriculum. 1. Automation of administrative tasks with AI chatbots Admission & Enrollment Forward-thinking educational leaders use AI-powered chatbots both to relieve admissions staff work by answering repetitive questions and to reach students for matters like encouraging them to enroll.  Using a chatbot reduces the summer melt, the phenomenon when students who apply and are accepted to a college fail to enroll. Summer melt affects 22,8% of college-intending high school graduates each year.  By using the AI chatbot to send personalized reminders and walk students through admission processes, Georgia State University reduced summer melt by 19 percent in the first year of implementation and increased the percentage of students completing pre-enrollment processes. An AI virtual chat assistant can answer questions about documents or deadlines and give instructions. Answer common inquiries about types of financial aid (e.g. grants, scholarships, loans) and provide standard fees info.  The chatbot isn’t just the recipient of inquiries and questions – schools, colleges, and universities can use it to proactively send reminders, messages, or news. AdmitHub Retention Poor support is one of the reasons students drop out of college. This means it is necessary for every institution to always guide their students by giving them timely and accurate information. But with no optimization, it is almost impossible to ensure each student is getting proper support. That’s when AI-chatbots come to help. They are programmed to answer common questions instantly and help students with administrative topics 24/7. An AI chatbot has a knowledge database based on real students’ conversations. Once it gets a question, a bot responds in seconds. However, when a bot doesn’t know an answer, the question is sent to a human team. As a human answers new questions, the AI learns by adding new data to its database. It leads to the chatbot’s capability of handling an increasing array of circumstances and questions without human input. 2. Gathering feedback about learning materials with AI chatbot Seeing students’ performance is easy for a teacher. Understanding which of your methods contributed to achieving such performance is another thing entirely. AI chatbots are ideal for teachers and institutes to collect students’ feedbacks. Its usage upgrades the learning processes thanks to increasing the participation of students. Replacing the traditional surveys, a chatbot talks to students via a special messenger and processes their feedbacks, letting the teacher know what works well, what is ineffective, and what else they can implement. HelloTars As the answers are coming in, the AI software analyzes the semantics of what the students have said and prepares a report that a teacher or administrator can review.  NLP and ML are those technologies that can analyze the feedback and understand the sentiment, looking for specific nouns or verbs as well as positive or negative words, the frequency of certain words to derive the overall tone. Then feedbacks are divided into positive (green), neutral (grey), and negative (red) based on the words and associated emotions. As a result, educators can understand the pain points faced by dissatisfied students and find out effective ways to identify and remove those bottlenecks. Belitsoft specializes in both chatbots and e-learning. If you have a project in mind, contact us for a free quote. No strings attached. How to implement AI chatbot in education Building AI chatbots in eLearning differs a lot from basic Q&A bots and needs a thorough analysis.  Implementing an AI chatbot for educational institutions may include the following stages:  Start with the analysis of your objectives. Based on the primary needs of your administration, teachers, and students, it’s necessary to decide what features your chatbot must have and what tasks it must solve. The use cases described in this article can help you analyze. Find an expert development and consulting team. Building an AI bot capable of a human-like conversation requires highly professional programming skills, thorough analysis, and strategy. That's why many educational stakeholders decide to hire outsourcing companies to implement their ideas professionally, cost-effectively, and fast. Such services usually cover all the stages of the bot implementation and include consulting, development, and post-launch support, saving educators’ time and headache. Test your chatbot. At this stage, an AI-powered chatbot is tested to communicate with a restricted group of real students to see if it can be helpful and resolve the assigned task. Deploy and assess. Deploying a chatbot is not time-consuming. Your development team will just need to ensure that all endpoints are connected, and the bot is integrated with your entire infrastructure.  AI chatbots in the education industry can be used both to optimize the teaching process and to make the learning process more engaging and personalized for students. They can also significantly reduce the workload of the administrative staff of the educational institutions. As a result, we can expect an immense growth of the education sector, beneficiary interactions between students and educators, and a superior classroom environment. Feel like starting your own eLearning project yet? Hire a dedicated team for it!
Dmitry Baraishuk • 7 min read

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