Category: Chat

A decade ago, cryptocurrency is a strange concept that not many people understand and people thought it was a joke. Who cares about some kind of money that is not even real and existed? At the time we talk about cryptocurrency, this market capitalization value rises to $2.06 trillion U.S. dollars by August 2021. Especially, during COVID-19 pandemic, investing in crypto seem to be a good choice for investors. But crypto is a choppy market, it’s hard to follow up the market every minute, and you need a tool to help you watch any changes in price. With Google App Script, I’ll show you how to make a Telegram Bot to watch Bitcoin’s Volatility.

What we are going to do exactly

• Get API of prices of cryptocurrencies (BTC, ETH,…)
• Create a Telegram Bot
• Write an App Script code, schedule it to run periodically

1. Get API of prices of cryptocurrencies

You can use any API that can get the prices of the cryptocurrency market. But in this tutorial, I’m using CoinMarketCap API. They have a free mock API for testing and free user can register a basic plan account with allow to call maximum of 300 requests everyday for production.

This is mock request example:

curl --location --request GET 'https://sandbox-api.coinmarketcap.com/v1/cryptocurrency/quotes/latest?symbol=BTC' 
--header 'X-CMC_PRO_API_KEY: b54bcf4d-1bca-4e8e-9a24-22ff2c3d462c' 
--header 'Accept: application/json' 
--header 'Content-Type: application/x-www-form-urlencoded' 
--data-urlencode 'start=1' 
--data-urlencode 'limit=5000' 
--data-urlencode 'convert=USD'

After call the API, you can get the JSON below. We will extract this data to make a notification message.

{
  "status": {
    "timestamp": "2021-08-24T09:43:54.669Z",
    "error_code": 0,
    "error_message": null,
    "elapsed": 1,
    "credit_count": 1,
    "notice": null
  },
  "data": {
    "BTC": {
      "id": 1517,
      "name": "zebnlm430ma",
      "symbol": "BTC",
      "slug": "ip0oiwund1",
      "is_active": 6184,
      "is_fiat": null,
      "circulating_supply": 3483,
      "total_supply": 4251,
      "max_supply": 2864,
      "date_added": "2021-08-24T09:43:54.669Z",
      "num_market_pairs": 4058,
      "cmc_rank": 8412,
      "last_updated": "2021-08-24T09:43:54.669Z",
      "tags": [
        "vba025s1i5a",
        "6mtkiszjcsu"
      ],
      "platform": null,
      "quote": {
        "USD": {
          "price": 0.1433590851317259,
          "volume_24h": 0.134253812239719,
          "percent_change_1h": 0.29250982964859773,
          "percent_change_24h": 0.8096078224440977,
          "percent_change_7d": 0.8945916148953752,
          "percent_change_30d": 0.5112814691736627,
          "market_cap": 0.3431455837033053,
          "market_cap_dominance": 8640,
          "fully_diluted_market_cap": 0.11635441670516311,
          "last_updated": "2021-08-24T09:43:54.669Z"
        }
      }
    }
  }
}

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2. Create a Telegram Chatbot

First at all, start with creating a Telegram Bot. Navigate over to Telegram and search for the account “BotFather”. Tap the START button at the bottom of the chat screen with BotFather if you haven’t already, which launches the list of things you can do with it . Then, tap on /newbot and give your bot a name.

After giving your new bot a name, you’ll be given an access token for the HTTP API. Keep it safe and store it somewhere, you’ll need it for integration with Apps Script later.

Next, create a chat group and add a bot. You should add the bot as a member of that channel and promote it as an admin. We also need to get a chat ID of this group. For getting chat ID you can follow the instruction in Stackoverflow.

There you have a bot! Go ahead and click on the t.me link to follow your bot. Now its time for a few enhancements to make your bot functional.

3. Write Apps Script code

At last but not least, all the things we prepare up til now for just the appearance of vedette: Apps Script code to send Telegram notification about the prices of crypto. But before that what is Google App Script?

What is Google App Script?

Google Apps Script is a development platform that makes it fast and easy to create scripts and small applications that integrate with G Suite. With Apps Script, you can:

• Write code in JavaScript and have access to built-in libraries for favorite G Suite applications like Gmail, Calendar, Drive, and more.
• Have nothing to install — A code editor is available in your browser, and your scripts run on Google’s servers.
• Don’t have to worry about complex topics such as security and data access permissions, since the platform handles it for you.

Apps Script can be used to create a variety of different applications, from chatbots to web apps. However one of the original and the most popular is use it to add additional functionality to a Google Sheets spreadsheet.

Apps Script services have daily quotas and limitations on some features, you can see more about this.

Now let’s get the job done!

First thing, go to https://script.google.com/ and create your new Apps Script.

A default function named myFunction() is automatically created for you, and you’re dropped into the editor to start coding. That’s it… you’re now ready to write your application!

Editing/replacing the (template) code

The “template” code you’re given is empty and doesn’t do much, so let’s replace that with our application.

The function getCryptoPrice() will get data from CoinMarketCap API and parse JSON result data before next step.

After get all the data we need, we just format this data with HTML tag message before sending to Telegram (Telegram support HTML tag and Markdown for Rich Text Message). Also there is the flag isAlert in this code because I only want to send notifications when BTC prices change in 24h is larger than 1.5%.

Now everything is ready. Let’s run the code.

Hooray!!! The code works like a charm. But wait, this job has not done yet. You have to schedule the script to run periodically. Apps Script provides Triggers to do this and you just have to do some simple setup for using.

You can find full tutorial code in here:

GitHub – toannhu96/btc-changes: Simple Google App Script to watch BTC changes and send notification to Telegram

Hope you find the tutorial interesting!

Resources

• CoinMarketCap documentation site
• Telegram Bot API
• Google Apps Script documentation site

Don’t forget to give us your 👏 !

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Create a Telegram Bot to watch Bitcoin’s Volatility using Google Apps Script was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

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Welcome to Lesson 3 in our “Lessons from Our Voice Engine” series, featuring high level insights from our Engineering and Speech Tech teams on how our voice engine works. This lesson is from Siva Reddy Gangireddy, a Senior Speech Recognition Scientist on our Speech Tech team.

What is deep learning?

To understand deep learning, we need a basic understanding of machine learning.

Machine learning is a group of algorithms that focus on learning from data to make predictions and decisions without any explicit programming. It usually involves training a model on huge amounts of data to learn patterns so that predictions and decisions can then be made on new data. For example, the smart speakers we use in daily life are based on machine learning algorithms.

Deep learning is a form of machine learning that’s based on neural networks, a set of algorithms designed to mimic the function of the human brain. Any network with more than three layers is considered a deep neural network and the input is processed through those several layers to predict the desired output. Deep neural networks require huge amounts of data and are extensively used in speech recognition and image recognition. At SoapBox Labs, our models are trained on thousands of hours of audio data and evaluated on in-house datasets regularly.

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Why is deep learning important, and how is it used, in kids’ speech recognition?

The goal of speech recognition is to convert users’ speech to text. Given the variations in audio data (such as pronunciation, accent and noise), machine learning algorithms are used to ensure accuracy. Because of its superior performance, especially for understanding kids’ variable speech, deep learning is at the core of SoapBox Labs’ voice engine and solutions like fluency assessments. We also use deep learning to deliver wake word detection, voice activity detection (VAD), and end-to-end speech recognition for on-device speech recognition.

Catch up on our previous “Lessons from Our Voice Engine”:

#1: Natural Language Processing (NLP)

#2: Custom Language Models (CLMs)

Don’t forget to give us your 👏 !

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Applications of Deep Learning in Speech Recognition for Kids was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

More and more businesses, websites, and social media pages are using chatbots each and every day, and more customers are expecting them when interacting with businesses and trying to figure out whatever it is they want to know. With this in mind, one of the worst things you can do is to offer a low-quality chatbot that creates more problems than solving them.

In this guide, we aim to provide you with the need-to-know tips that will help you script and write out the perfect chatbot that your customers and potential customers are going to love. Let’s get right into it.

Start with an Introduction

From the moment the chatbot opens, you need to start working on a positive experience, and this means leading with introductions. The easy way to do this is to write something like;

“Hey there, <username pulled from social page>

I’m BusinessBot, and I’m here to help with whatever you need. Say Hello in chat to see options, or click an option below if you know what you’re looking for. Let’s get things started!”

As you can see, this introduction starts the interaction off strong and positively begins solving whatever problem someone has come to your page to solve.

Guide Your User

You know when you call up a telephone helpline, and you’re told to choose the options to direct you to the right department, but the options are confusing and don’t really help you find where you want to go? You don’t want that to happen with people using your chatbot, so make sure you’re making special efforts to be precise and lead people to where they want to go.

This might take a little bit of trial and error as people come to you with various queries that you may not have expected, but be proactive in addressing issues, getting feedback and fixing issues, and you’ll be able to guide your users exactly to where they need to be as quickly as possible. The more efficient your chatbot experience, the happier your customers will be!

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The Voice Should Match Your Brand

“However you’re typing your chatbot, you need to ensure the language you’re using is in touch with the rest of your brand. For example, is your brand professional and formal or casual and informal? What kind of language and writing style should you be using to reflect this? This is something you need to consider before you even start writing so your text will remain consistent throughout,” shares Mark Taylor, a writer at Ukservicesreviews and Simplegrad.

Remember, customers are used to talking conversationally in chatbot-styled text boxes, so continue this on with your chatbot in order to resonate most effectively with your customers.

Define Your Option Goals

“There’s no point trying to cover every basis with your chatbot options because this is only going to make your bot confusing and hard to navigate and understand. Instead, you need to make sure your bot options are purposeful and have a goal, which means taking the time to define your goals,” explains Marie Harper, a scriptwriter at Studydemic and Assignment Services.

Are you trying to solve your customer’s problems, make sales, educate and inspire, or inform? Of course, you might have the goal to do all of these, but making your priorities clear in your head will massively help when it comes to structuring your chatbot while ensuring the experience is as smooth as possible.

Proofread Your Content!

This point should go without saying, but it’s incredible to see how many businesses let this simple point slip through the cracks. After writing your content and before you go live, you must absolutely make sure that you’re proofreading your work so it’s free from errors.

Any spelling mistakes, grammar errors, or typos are going to stick out of your content like a sore thumb, and it just looks unprofessional, makes your business lose credibility, and overall lessens the quality of your chatbot experience. The fewer mistakes, the better!

Emily Henry is a tech writer at Best Essay Writing Services and Student Writing Services. She writes about Chatbot and aims to help businesses make the most of their modern online opportunities. Emily is also an editor at Assignment writing services reviews.

Don’t forget to give us your 👏 !

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8 Essentials Tips for Writing a Chatbot Script That Gets Results was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

Chatbot personality traits and their effect on user satisfaction amongst Gen Z: A research and hotel case study

I remember when I used a chatbot for the first time. It was the chatbot of Dutch shipping company, Post NL. My package still hadn’t arrived 3 days after its expected delivery date. Slightly annoyed and unable to immediately talk to a real company representative, I got in touch with chatbot Daan. Unfortunately, chatbot Daan did not comprehend my questions, lacked personality, and was unable to redirect me to a real human. All this resulted in me leaving the conversation more frustrated than I was to begin with.

This unsuccessful encounter led me to choose the topic of chatbots as inspiration for my thesis research on artificial intelligence. More specifically, I wanted to dive into the effect of personality within customer service chatbots on Gen Z’s user satisfaction.

Why Gen Z you might be asking? That’s because research indicates that Gen Z and Millennials are most likely to agree that chatbots make it easier and quicker for their issues to get resolved. Understanding which personality traits within customer service chatbots trigger a positive response for one of these generations therefore seemed like valuable knowledge.

So, I went ahead and started researching which of the following personality dimensions from the ‘Big Five’ model* my population responded to best:

1. Extraversion: Social, talkative, assertive, and funny.
2. Agreeableness: Compassionate, kind, empathic, compliant, trusting, co-operative.
3. Conscientiousness: Dutiful, competent, reliable, organized, task-focused.
4. Openness: Insightful, original, daring, clever, independent, broad-minded.

The quantitative research showed that the sample had a clear preference for the dimensions agreeableness (61.1%) and conscientiousness (29,6%).

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However, only adding personality without taking into account the background of the company the chatbot is operating for does not have the desired effect. It’s still necessary for companies to align their chatbots with their brand and users.

So, in order for companies to deploy an effective customer service chatbot, it needs to:

• Identify its customer segments
• Map out what the brand stands for
• Decide upon the necessary functionalities
• And finally add the personality layer that the customer segment has a preference for

I decided to test out these steps and create a prototype chatbot for hypothetical case hotel CitizenM, as this is a hotel that focuses on a segment that is generally more technologically competent.

Two prototype chatbots were created: one with the added personality dimension, and one without. After letting test participants interact with both, they were asked to fill out a user satisfaction survey.

The chatbot with the added personality scored significantly higher in all areas. Although it is not safe to generalize the sample outcome for the entire population, the test did make it evident that adding personality traits to a chatbot indeed has a positive effect on user satisfaction.

Although further research on the topic is recommended, I hope this article serves as a guideline on how to create an effective chatbot for hotels and other companies offering some sort of customer service.

If I learned one thing from this research it’s that a one-size-fits-all chatbot doesn’t cut it anymore. In order for companies to create a successful digital customer experience, they will need to have a personalized approach.

• One of the dimensions, neuroticism, was left outside of the research scope as it’s only associated with negative traits.

Don’t forget to give us your 👏 !

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Chatbot personality traits and their effect on user satisfaction amongst Gen Z: A research and… was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

With the world moving online in the post-pandemic world, it is now more critical than ever for businesses to provide the best possible customer experiences in order to sustain in this competitive market. A crucial part of this customer-centric strategy requires brands to support their customers in a language they prefer.

Most brands choose English as their primary language for all types of customer communications. However, using only a single language for a diverse customer base speaking multiple different languages, not only creates unnecessary barriers but also frustrates the end customer. Various statistics show how businesses are missing out on tremendous opportunities by not supporting multilingual conversations:

1. 29% of businesses have lost customers because they don’t offer multilingual support
2. 72% of consumers are more likely to buy when help/information is in their own language
3. 70% of customers are more loyal to brands that support their native language

These numbers tell us that while English is a popular language, it does not suffice for all customers. This particularly holds true for a country like India, which is known for its language diversity.

The need for Hinglish

The digital revolution in India has exponentially broadened the Internet user base in the country to include large numbers of non-English speakers that outnumber English speakers. While Hindi & English are more popular than all other vernacular languages, it has given rise to a new language: Hinglish with 350 million+ speakers versus only 125 million+ English speakers.

This shift in language is primarily because users find texting and having conversations in Hinglish more convenient. It is easier for users to type their Hindi queries in Latin script instead of Devanagiri script. Since a vast majority of India lives in semi-urban and rural regions and isn’t as fluent in English, it becomes even more critical for brands to adapt to the customer’s preferred language instead of a one-size-fits-all approach with English or Hindi.

Here are some ways users often frame their queries in Hinglish:

“Mujhe help chahiye””Mera order kahan hai””Mujhe refund chahiye”

When we checked with two of our customers — Howtouse and Jiomobility, we found that lack of Hinglish support was the reason behind 40–80% of the bot breaks happening. These numbers were expected to go even higher with Diwali, a prestigious festival in India just a few months away.

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Why do basic chatbots fail in supporting Hinglish?

When users ask queries in Hinglish, basic chatbots fail to respond and either transfer it to an agent or send an incorrect response. Not only does it impact the customer experience negatively but it also costs extra human resources even when there’s no need.

The reason for this gap is because chatbot localization is not as easy as taking an English-language chatbot and translating all its content to Hinglish. Most basic chatbots mechanically translate chats back and forth without understanding the context. A fully functional multilingual chatbot needs to be able to decipher the language, understand exactly what the user wants, and respond naturally. The legacy translation services are not equipped with this natural language understanding, which is essential to make or break multilingual customer experiences.

Hinglish chatbots powered by Linguist Pro

At Haptik, we understand the gaps of traditional translation services and instead use a hybrid of basic translation and custom native translation capabilities, called Linguist Pro to power the most accurate multilingual conversations. Learn more about Linguist Pro here.

Haptik has first launched Hinglish with Jiomobility whose mission is to make superior internet & network accessible to every person in every corner of India. This strategy helps the brand to

1. Expand user base to tier-2, tier-3 cities of India & provide localized services
2. Provide flexibility to customers to speak in their lingo and colloquialisms
3. Resolve a higher number of queries with automation & accuracy

How does it work

When we look at how the technology behind Hinglish chatbots works, it can broadly categorize it into 3 simple steps:

Language auto-detection: As soon as a user initiates a conversation in Hinglish, a Haptik multilingual chatbot automatically detects the language in the first three messages and understands that the user is more comfortable in reading Hindi than English for the rest of the conversation.

Natural Language Understanding using Transliteration: To further understand what the user wants to say in the query, Haptik’s proprietary NLU engine transliterates the Hindi text in Latin script to Devanagiri script. Once the translation is complete, the NLU engine uses deep machine learning algorithms to understand the query in Hindi and respond accurately.

“Family plan mein kaise add kar sakte hain” is transliterated to “family plan में prepaid कैसे ऐड कर सकते हैं”

Respond in preferred language: Brands can choose either Hindi or Hinglish as their bot language to resolve and respond to their user queries without requiring any human agent

To Sum Up

There’s no doubt that multilingual chatbots, especially Hinglish are an indispensable tool for brands that want to strengthen their presence in India. For Hinglish chatbots, the translation and NLU are two major components that can make or break the customer experience. Fortunately, Haptik excels as both by using Linguist Pro. Join us in our mission to help brands break all language barriers become by making conversations customer-centric & truly vernacular.

Interested to explore more or want to try out a chatbot of your own?

Don’t forget to give us your 👏 !

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The Next Big Thing for Multilingual Chatbots: Hinglish was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

1. Decide how you want to use chatbots

Before you start building your chatbot, you need to decide how you want to use it. Is it going to be an interactive customer support tool, or a tool to help your sales team generate leads?

2. Build a prototype

Once you’ve decided how you want to use your chatbot, the next step is to build a prototype. This is basically a working model of your chatbot that you can try out and ask people for feedback on.

It’s a good idea to build a prototype before you start coding, because it gives you a better understanding of how your chatbot will work and helps you to spot any problems in the user experience early on.

3. Don’t use canned responses

If you want your chatbot to have a more natural and conversational feel, it’s a good idea to use a combination of dynamic responses and canned responses.

Canned responses are pre-made responses that you can use in some situations, while dynamic responses are responses that are generated using your conversation history.

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4. Don’t rely on one-word answers

Even if you use a combination of dynamic and canned responses, the responses you get from your chatbot will probably be one-word answers.

To make your chatbot feel more human, you need to add more detail to these responses. For example, if you ask your chatbot “What’s your favorite movie?” it could reply with “Star Wars”. A better response would be “I like Star Wars because it’s full of action and adventure.”

5. Use analytics to track and improve your chatbot

To make sure your chatbot is getting used and to see how people are interacting with it, it’s important to set up analytics tools for your chatbot.

If you’re using the Microsoft Bot Framework, you can use the built-in analytics tools.

If you’re using Chatfuel, you can use the built-in analytics tools or use a third-party analytics tool like HotJar or Google Analytics.

Conclusion

The process of building a chatbot is straightforward, but it can be time-consuming. It’s also easy to make mistakes when you’re building your chatbot, which can mean you have to go back and redo things.

But if you follow these 5 tips, you’ll be able to build a chatbot that’s easy to use and is better than most of the chatbots you’ll find online.

Don’t forget to give us your 👏 !

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My 5 steps for creating a chatbot was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.