Your cart is currently empty!
Category: Chat
-
Looking for chatbot
I have previously stumbled upon a chatbot project that is able to convert Q&A write-up/document/chunk of text into a functional chatbot. I can’t recall the name of the platform already, any of you have seen something similar?
submitted by /u/Misterkoga
[link] [comments] -
Top 3 Alternative to Manychat
Most companies want to incorporate a chatbot to support their customers with an exquisite experience. But in case, you are confused about which chatbot platform to choose and what would be a more feasible option over ManyChat, then you have to look here.
submitted by /u/botpenguin1
[link] [comments] -
How Chatbots Are Transforming The Automotive Industry?
Chatbots are conversational assistants that use artificial intelligence (AI) to converse with diverse kinds of consumers effectively. Industries such as the automotive industry make most of the chatbots as a part of their marketing strategy.
https://technostacks.com/blog/chatbots-for-the-automotive-industry
submitted by /u/MichaelOconnor1
[link] [comments] -
How to test your chatbot designs before release
In this tutorial, I will show how you can perform a chatbot test without having to wait for the bot to be actually released. This feature is very useful to start grabbing real user feedback and see how real people will react to your bot. By prototyping early on, you will be able to adjust your design based on how users react to it — specifically, it’s important to discover:
- What do the users type when confronted by your design?
- What do users expect when using your chatbot?
- Are the utterances (training phrases) realistic and will they work?
With the prototype feature, you can use the user test to inform your design decisions, as well as improving your training phrases.
We also have released an AI-powered user testing — it allows you to leverage OpenAI GPT-3 to test your chatbot as if it was a human. It works like magic! More on that later.
Chatbot test: Set up your conversational design file
For the sake of this tutorial, I am using our grumpy weather chatbot example — you can find it there. To copy it to your account click on the main menu on the top right > File > Make a copy, like so:
Make a copy in Botsociety
You can of course use your own design as well as this example one. The important caveat is that your design has to sport a somehow complete experience. You can technically test a design with only two messages for example, but it would not be very interesting. If you are not sure how to design a conversation with Botsociety in the first place, check out our workshop on Youtube or this Getting started blog post.
Trending Bot Articles:
1. 3 Tips for your Voice and Chatbot Program from Gartner’s Customer Service Hype Cycle 2020
2. Deploying Watson Assistant Web Chat in Salesforce Lightning Console
3. Are Chatbots Vulnerable? Best Practices to Ensure Chatbots Security
Switch to prototype mode
Now that your design is ready to be tested, you can switch to prototype mode. To do so, click on the prototype mode icon on the left-hand side of your canvas, like so:
Prototype mode will activate. Here you can do multiple things:
- Invite human testers to your design
- Trigger an A.I. test of your design
- Check the results of your tests
Note that in prototype mode you can’t edit your design. For example, clicking on a message will not open the message editor. To edit your design, you can go back to design mode. To do so, just click on the pencil icon right on top of the prototype mode icon.
Inviting users to your chatbot test
Inviting users is very simple and fast. Just click on the top right button that says Invite Testers like so:
Now you will be able to invite other people to try out your design. You can do so by sending them a link, or by inviting them via email. Both methods work and they are equal. You can try out what the testers will see yourself by copying the link and then opening it up in another browser tab. In short, the tester will experience your design like an interactive video:
The tester will be able to:
- Type their own messages (or say them if your design has voice capabilities
- Pick the path they would like to see
- If they reach the end of your design, test again
- Add comments
Note that the testers (since they don’t have edit access to your design) will not be able to:
- Change your design
- See the complete canvas — in other words, they can’t stop the play and roam around your design as you do
There are no limits to the number of tests and testers that you can invite. So invite as many as you want.
Auto-testing: Have an A.I. do the hard work
Note: This feature is currently in Beta. Let us know what you think at info@botsociety.com
Auto-testing is very powerful as it allows you to leverage OpenAI’s GPT-3 to test your design, without having to engage and wait for human testers. The A.I. will act as the human in your conversation and provide feedback.
Let’s use this feature as well — while the testers that you have invited try out your design. To ask the A.I. to use your design, just click on ‘Automatic test’ on the top right corner:
Then click on ‘Automatic test’ to kick off the automatic test. The A.I. will take from 3 seconds up to some minutes to try out your design, depending on how complex your design is. If you are using the example design in this tutorial, 8 seconds will do. Now just refresh your page to see the results! You should see results on the right-hand side, like so:
If not, wait for another 10 seconds and then refresh again. We will eventually add email notifications to let you know when a chatbot test is completed.
Checking the result of your chatbot test
If you asked a human or an A.I. to test your design, you will see the results on the right-hand side of the prototype mode as shown above. These results do not change your design structure — they are just ready for you to review. Let’s do that! Click on the first entry, it should be something like 1 text in Dedicated path:
Once you clicked, you should see something like this:
Reviewing the results of a chatbot test
Botsociety highlights the section of your design that was interested in your test (in blue), so you will get context about the data that you are reviewing. You will see the user in the balloon on the right of your message. You can do multiple things with this data:
Approve it. If you click on ‘Approve’, the message will be added as an utterance (training phrase) to your design. This is useful if you think that the data added by the user is a valid utterance of the message that you already designed. The utterance will then be used as a training phrase in your NLP engine once you export.
Create new. If you click on ‘Create New’, you will create a new message with the content of the text written by the user. This is useful if you think that the data added by the user represents a new intent or use case yet not covered by your design; or if you want to edit it separately in general.
Discard. Removes the data added by the user so that is not marked as pending anymore. This is the right option if you don’t consider the data meaningful or useful.
Edit it. Just click on it to change the message. Useful if you think that the data needs some adjustment before clicking on Approve or Create New.
Wrapping it up
In this tutorial, we’ve seen how to test your chatbot design with both humans and an A.I., and how to leverage this data to improve your training phrases. If you have any questions, leave them in the comments. Check out the complete documentation on this feature here.
Don’t forget to give us your 👏 !
How to test your chatbot designs before release was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.
-
Use chatbots to easily surface firm intelligence from multiple Line of Business data sources?
How to use chatbots to easily surface firm intelligence from multiple Line of Business data sources?
Firm intelligence is the next data revolution, and organizations today to be successful must gain value from the information it has access. Businesses to achieve productivity, as well as performance enhancements, must have an intention of transformation, as developing an intelligent organization is not possible without a digital transformation plan. Firm intelligence is workforce or organization focused and enables effective collaborative communications between internal as well as external users.
Although several organizations realize the enhancements, digital transformation can bring in to the firm, around 35% of firms still do not plan for digital transformation(1).
The chatbot does it all!
Chatbots have proven out to be one of the best digital transformation efforts to transform the way an organization gathers and utilize their knowledge.
Chatbots perform multiple business operations and process a massive chunk of data to deliver relevant answers quickly. A firm employee can have two roles as a manager as well as an assistant on two different portals. Here chatbots play a significant role in understanding access rights and delivering confidential data. Other than retrieving information from portals, a chatbot also makes it possible to write back or reply within the portal.
A chatbot goes through a sense think and act cycle to provide organizations with diversified communication models and conversation flows. Chatbots first collect the data required to complete a task and then thinks (thinking signifies an important essence of AI). Then the final step involves chatbots deciding to respond. These chatbots deliver responses faster than human agents and in a user-friendly manner.
Why a company creates a chatbot? Are chatbots everywhere?
The growing adoption of conversational AI chatbots is empowering enterprises to deliver sophisticated employee experiences. These chatbots have the capabilities and intelligence which are required to meet the present complicated needs of any business, including a vast number of communication channels and 24/7 availability.
Chatbots are one of the best solutions, especially for firms working with multiple data sources. Several firms across verticals are increasingly using AI-enabled chatbots to replace repetitive human work and strengthen their efficiency.
Trending Bot Articles:
1. 3 Tips for your Voice and Chatbot Program from Gartner’s Customer Service Hype Cycle 2020
2. Deploying Watson Assistant Web Chat in Salesforce Lightning Console
3. Are Chatbots Vulnerable? Best Practices to Ensure Chatbots Security
AI-enabled chatbots are changing the way businesses are done by allowing employees to access information from multiple portals seamlessly. With a strong knowledge base, these intelligent chatbots can identify patterns and respond aptly with quality answers. These AI chatbots serve as a front-line virtual agent for firm employees dealing with numerous data sources.
What is the best AI chatbot builder platform available?
Determining the right chatbot that best fits an organization’s needs and strategy is a crucial step for any firm. A firm may need a chatbot for internal as well as external uses, and creating those intelligent chatbots requires a bot builder platform. One such platform is “KLoBot,” which is a DIY no-code AI chatbot builder platform for any firm.
With KLoBot’s easy drag and drop user interface, a chatbot can be quickly designed for simple as well as complex bot interactions. KLoBot can be configured with several popular channels, including MS Teams, Facebook, Twilio, Slack, and Cortana, among others.
KLoBot is an incredibly intelligent platform that can assist and accelerate a firm’s digital transformation with its intuitive conversational UI. Chatbots built on KLoBot come with skills such as speech to text, language understanding, text analytics, web search, and much more. To know more about KLoBot and the benefits it can offer to your firm, please click here.
KLoBot — create intelligent chatbots to meet organizations custom requirements
The introduction of KLoBot 3.0 allows firms to surface firm intelligence from multiple lines to business data sources and empower remote workers to experience human-like conversations. KLoBot helps firms in developing AI chatbots to perform tasks such as collect, modify, and post information in the line of business systems.
The AI-enabled chatbots build on the KLoBot platform empower organizations to achieve a goal of enhancing business performance across a firm.
Don’t forget to give us your 👏 !
Use chatbots to easily surface firm intelligence from multiple Line of Business data sources? was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.
-
How To Optimize Remote Team Communication — ChatC
Have you implemented a communications strategy for remote workers yet?
-
Reasons Your Business Needs a Facebook Messenger Bot
Let your pillar of marketing getting more robust and make your business more productive. You might be wondering how then a Facebook bot can be your ultimate way of getting things done instantly. Let your customers have a seamless experience and connect with your brand over the most popular social media platform. For more detail, on “Reasons Your Business Needs a Facebook Messenger Bot.” Click the link.
submitted by /u/botpenguin1
[link] [comments] -
Methods to get raw information into chatbot database?
I’ve created a good chatbot architecture to potentially allow selling the service to clients. Which is great. But I’m trying to figure out a streamlined way for me or customers to enter information into a database for each client so that a chatbot could represent them and that keyword matches trigger the right content.
The problem I’m having (conceptually) is that different customers are so completely different.
For instance, if I were to use a questionnaire format, the range of questions would branch out into the hundreds depending on how a client answers a question. And it would require me creating those question templates, which would probably be a larger job than creating the chat bot itself! There is just too much different between the needs of a swimming pool salesperson, an artistic painter, and a dog kennel operator.
Another approach I’m considering is to simply feed the system raw text from a client’s website or supplied information, so that it’s not as nicely structured, but may at least make the information findable. For instance, keyword matches could bring up the paragraph that the keywords were found.
It seems that overall, creating GOOD chatbots for customers involves a lot of back end dev to massage different info to fit whatever architecture the chatbot works with.
does anyone have any insight on this, ideas to streamline the process for wildly different use cases?
submitted by /u/dyselixc
[link] [comments]
