How to create data source entities
Use data source entities in Bold360 AI to turn your data into smart conversations.
You can now see the conversation in action in your widget ? just enter I want to buy a mobile phone.
Use data source entities in Bold360 AI to turn your data into smart conversations.
A sample CSV file is attached at the end of this article. Learn more about the different data source options and requirements in this article.
The entity name can contain letters, numbers and underscores. Spaces are not allowed.
You can use the description to give the entity a more meaningful name or description that helps you identify it later.
Example: Name your entity MOBILE_PHONES.
You can select the CSV file from your local computer and upload it to Bold360 AI' secure server or you can upload the file to a file hosting service like OneDrive and enter its URL here.
Result: The properties table is now loaded. Properties are the columns that are available in the data source file.
See What are the property options for data source entities? and How do life cycle options work? to learn more about the options.
Example:
You should decide what questions the bot should ask the end users to offer the best possible recommendation about phones. In this example, the bot asks questions about brand, price range, and camera quality.
See What are fallback messages? to learn more.
Example: For this example, we enter Unfortunately, there's no mobile device that matches your preferences. for no results and set up a carousel to be displayed with the image, the brand and model, and the price if there are multiple results based on the customer's responses.
In the article's body, create the final response of the bot: this is what the bot responds when there is a single mobile device to recommend. The response should use the entity to present the details of the selected mobile device. To insert an entity, you can either choose or enter [[ in the text editor and have a drop-down of all entities displayed. Once you add an entity to the response, the entity is automatically added to the article. You can expand the entity to see the questions that the bot may ask the user and adjust them to fit the article if needed.
Example: Intent: I want to buy a mobile phone
Body: ?
You can now see the conversation in action in your widget ? just enter I want to buy a mobile phone.
Property options in Bold360 AI enable you to customize entities.
Option name | Description |
---|---|
Life cycle | The Life Cycle field above the properties table sets the life cycle for the entire entity. You can also set a life cycle for each property. Properties can have a life cycle that is shorter than the life cycle of the entity as a whole. For more information about life cycles, see How do life cycle options work?. |
Name | The expression used to identify the property and add to articles. The property name can contain letters, numbers and underscores. Spaces are not allowed. |
Detect | Specifies the type of input expected from the user, like text, date or number. Validation is completed based on the selection here. For example, if email is selected, the user is expected to enter an email address, otherwise they receive an error. If you choose Date, customers can use a calendar to select the date: ![]() |
Bot Query | The question the bot asks to receive the input from the user. |
Error Message | The error message displayed to the user when they provide an input that is not valid. You can also set the number of times the error message is to be displayed, that is, the number of chances you give the user to provide the correct format. After that the user receives the fallback message. For example, you have a property where Detect is set to Email, the bot query is What's your email address? and the error message is Please provide an email address. which is set to be displayed 3 times. When the user fails to provide an email address for the fourth time, the fallback message or article is displayed if it is set up.
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Life cycle | The Life Cycle field of the property sets the life cycle for the specific property. You can also set a life cycle for the entity. Properties can have a life cycle that is shorter than the life cycle of the entity as a whole. For more information about life cycles, see How do life cycle options work?. |
Property options in Bold360 AI enable you to customize entities.
The options listed here are available in the Properties table of data source entites. Some of them you can find under (More options).
Option name | Description |
---|---|
Life cycle | The Life Cycle field above the properties table sets the life cycle for the entire entity. You can also set a life cycle for each property. Properties can have a life cycle that is shorter than the life cycle of the entity as a whole. For more information about life cycles, see How do life cycle options work?. |
Expose? | Sets the visibility of this property in a conversation. |
Key | Displays the header names as they are in the data source. |
Name | The expression used to identify the property and add to articles. The property name can contain letters, numbers and underscores. Spaces are not allowed. |
Detect | Controls whether the property is visible in a conversation. |
Query | The question the bot asks to receive the input from the user. |
Life cycle | The Life Cycle field of the property sets the life cycle for the specific property. You can also set a life cycle for the entity. Properties can have a life cycle that is shorter than the life cycle of the entity as a whole. For more information about life cycles, see How do life cycle options work?. |
Split by | A syntax value such as a comma or a vertical bar that is used to separate multiple values in a CSV cell or in the value associated with a JSON key. |
Auto Spelling | When selected, the customer's answer doesn't have to be an exact match to a value in a CSV cell or a value associated with a JSON key. |
Is Shared | You can share the selected property with another entity. For example, if you define color in your phone and tablet entities, then you can share the color values across entities. In this case, when the customer selects a phone color that doesn't exist in the phone entity but exists in the tablet entity which is shared, then the bot will know it is a color and present the message defined in the entity for no results. |
Autocomplete | When selected, customers are offered autocomplete, or type-ahead options as they enter the entity value. |
Use Quick Option | The customer can choose from the values that a specific CSV column or JSON key contains. For example, if the CSV contains Apple, Samsung, and Google in the Brand column for a list of mobile phones, these options are displayed as buttons to the customer. See How to use quick options in a conversational article to learn more. |
Parent property | You can set up a dependency between two properties of the same entity. For example, the parent property of Cities can be Country. When the customer is asked about these two properties, the following happens:
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Entities in Bold360 AI enable you to turn your data into smart chatbot conversations.
To set up an API-based entity you need a custom entity to collect data from the customer for the API, a data source entity with the API as its data source that uses the custom entity and an article you use these entities in. In this example, we have an API for data about concert tickets and we want to create a bot that the customer can ask about the tickets that they already booked.
You create this entity to collect the data required for the API. In this example, we're asking for the customer's email address to display their booked concert tickets.
Example:
Entity name: TicketDeails
Entity description: Collect the customer's email address
Name | Detect | Bot Query | ErrorMessage | Life Cycle |
---|---|---|---|---|
What's your email address? | Please enter a valid email address. | Persistent |
The entity name can contain letters, numbers and underscores. Spaces are not allowed.
You can use the description to give your entity a more meaningful name or description that helps you identify it later.
Example:
Entity Name: TicketsByName
Entity Description: Get a list of tickets by email address
Example: https://api.example.com/v1/tickets/[[TicketDetails.Email]]
Result: The custom entity is listed as a dependent entity under the Properties Table. See What are dependent entities? to learn more.
This way the system knows what a valid response looks like.
Result: The Properties table is automatically filled with the keys that come from the API.
Display settings are available for arrays. See What are the display settings for API-based entites? or more information.
Example: Intent: What tickets do I have reserved?
Body: ?You have the following tickets reserved: [[TicketsByEmail.TicketsByEmail_ARRAY]]
Dependent entities are entities used in other entities.
When you have an entity with an API as data source, you need to set up a custom entity that collects the information from the user and and include this custom entity in the API-based data source entity to pass it on to the API. Dependent entities provide a better understanding of what properties compose the entity.
To add dependent entities, do the following:
You can add an entity on the Parameters,Headers or Bodytab, depending on where it's needed. The entity should be added in [[Entity_Name.Property.Name]].
The dependent entities are listed under the Properties Table.
The life cycle of an entity in Digital DX defines the period during which the bot remembers the user's answer.
You can define a life cycle for the entity as well as for each property of the entity. Properties can have a life cycle that is shorter than the life cycle of the entity as a whole.
Life cycle option | Description |
---|---|
Persistent | The bot remembers the user's answers for the duration of the session, that is, until the user closes the browser. |
Topic | The bot remembers the user's answers as long as the articles returned to the user's questions contain the entity. So as soon as the user asks the bot for an article that does not use the entity, the bot deletes the user's answer from its memory. |
Intent | The bot remembers the user's answer as long as the user is in the same intent. So as soon as the user asks the bot something else, the bot deletes the user's answer from its memory even if the answer to the user's next question contains the same entity. |
Statement | The bot remembers the user's answer until another question is asked from the user. For example, if the bot asks two questions, like What is your first name? and What is your email address?, the bot forgets the user's first name before the second question is asked. |
Use these options when providing a link to a file or an API link in the Data Source URL field of a data source entity in Bold360 AI.
When creating a data source entity, you can either upload a CSV or a JSON file from your local drive or add a URL to such a file or provide the URL of an API as data source.
Entities support two types of HTTP methods to integrate an external URL: POST and GET. You can select a method from the drop-down next to the Data Source URL field.
The following options are also available for data source URLs:
To integrate an external data source, you may need to use specific parameters, headers or include specific data in the body of the request when you send it to the server that stores the data files.
When you select (URL Inputs), you have the option to add parameters, headers and a body in case of POST requests. It is possible to include another entity as a parameter, in the header and in the body in which case this entity is listed as a dependent entity under the Properties table. See How to create API-based entities to learn more.
In several cases, POST requests require specific headers to be sent to the server. When testing a POST request, the tool you're using might automatically add certain default headers without even showing them to you. Make sure you add all headers in the entity configuration.
In the body you can add content. The body of an HTTP request supports different formats for sending content. The format you should use depends on what the receiving server expects. In the AI Console, POST requests in entities support raw format only.
You can map words of a phrasing that are values in an entity to the relevant property of the entity you are using in the article.
Using this example, you could add the phrasing I want to buy a Samsung phone and map Samsung to the MOBILE_PHONES.BRAND to make sure the bot won't ask the question about brand when the user already antered their preference.
Example: In our example, we have the I want to buy a mobile phone article.
Example: Add I want to buy a Samsung phone.
Result: You'll see that the word that is a property value is highlighted in blue.
Display settings are available for arrays in API-based data source entities.
Choose for an array in the Properties table of your API-based data source entity to set up the following options:
You can use built-in, or system entities even without defining your own ones. These Entities let you define the following:
Entities in Bold360 AI enable you to turn your data into smart chatbot conversations.
Entities serve as a database for the information that the conversational bot needs to answer your customers' questions. You set up an entity with a data source and provide different questions the conversational bot will ask the customer about the same set of data. For example, you have a data source for mobile phones and you want to create a conversational bot that recommends your customers the best mobile devices based on their needs. Your data source contains information about the brand, the model, the price, the screen size and so on of the mobile phones available. In the entity, you can set up questions about these bits of information, like Any specific brand you're looking for? and What is the price range?. The customer answers these questions and the conversational bot provides the best fit or fits based on their answers.
With entities, you can provide a smart conversational experience to your customers:
Bold360 AI supports the following types of entities:
As a content manager, you can create conversations that verify answers that end-users provided and to prevent any typos or other human errors. To do that, create a new step in the process of API-based entities that will do the following:
Use data source entities in Bold360 AI to turn your data into smart conversations.
Data source entities can be based on a CSV or a JSON file or can retrieve data from an external data source through an API. In terms of the data source, you have the following options:
Makes sure the CSV or JSON file you use with entities meet the following requirements:
Use custom entities in Bold360 AI to gather information from your customers and use it to offer a personalized experience.
You can also use custom entities as an auxiliary for API-based data source entities as they help collect the information required for the API and then trigger the API itself.
Instead of asking your customers to fill in a form, you can create a conversation to gather information about the customer. For example, you can set up a custom entity that asks for the customer's name and then include their name in articles. Here's how to do that:
The entity name can contain letters, numbers and underscores. Spaces are not allowed.
You can use the description to give your entity a more meaningful name or description that helps you identify it later.
Example: Name your entity UserDetails.
This way, the bot does not forget the user?s first name once they enter one.
You can also a set a life cycle for the individual properties keeping in mind their life cycle can't be longer than the life cycle of the entire entity. See this article to learn more about how the different life cycle options work.
Example:
Name | Detect | Bot Query | ErrorMessage | Life Cycle |
---|---|---|---|---|
FirstName | Text | Hi, I'm your virtual assistant. What's your first name? | N/A | Persistent |
To learn more about the property options for custom entities, see this article.
Example: Intent: I want to go to Greece for a vacation
Body: ?Here are our current offers for you, [[UserDetails.FirstName]]:?
<add options to the article>
When an article that uses the UserDetails entity is returned as a response, first the entity question is presented then the article is presented with the name they provided. If the conversation continues and the another article with this entity is returned as a response, the bot won't ask the question again, because the customer name is retained for the duration of the session, as defined by the persistent life cycle option.
Bold360 version 21.10 contains the following new enhancements:
Going forward, there will no longer be an option to choose (non-secure) HTTP-only connections when generating widget touchpoint scripts. HTTPS will be enforced across all touchpoints going forward and HTTP-only widget configurations will no longer be supported as of December 31, 2021. Any widget script using HTTP only will need to be changed by this date in order to continue uninterrupted
Access to the Genesys DX AI management (*.nanorep.co) will only be accessible through HTTPs
In-product announcements will be present to raise awareness of this change
Important: Any widget script using HTTP only will need to be changed by this date in order to continue uninterrupted.
As part of the transformation to Genesys DX, the product interfaces are now rebranded to reflect this change. Logos, product names, and company links are now updated to Genesys branding and is present within each of the product interfaces.
Using the "getEstimatedWaitTime" API call will provide the estimated wait time that the visitor would spend waiting before starting a live chat with an agent.
Details on using this API can be located in this article.
Bold360 version 21.11 contains the following new enhancements:
New KB Launchpad Intent Library for COVID-19/Vaccinations
In order to help businesses with providing just-in-time information related to updates to COVID-19 and vaccination protocols, a new entry in the KB Launchpad is now available with intents that can be used to deploy knowledge to keep your workforce informed of new policies and information that you may need to enforce.
Not familiar with the KB Launchpad? The KB Launchpad contains pre-defined intent libraries to help you add industry and use-case specific questions/intents to your KBs with your own specific responses to help with adding commonly asked questions for newly created KBs.
We will be enabling the KB Launchpad as a default setup option on all accounts shortly but contact your Account or Success Manager to get it enabled early if necessary.
ICO Cookie Compliance
In order to support ICO cookie compliance in regions that require end-user consent for allowing cookies to be set, Genesys DX now complies with this standard by making the tracking and analytics related cookies that are set through the touchpoint and visitor monitoring HTML snippets to be optional.
By default, all cookies will continue to be set upon page load. To restrict these cookies from loading automatically and only upon end-user consent, additional steps will be required on the website that the Genesys DX code is being deployed to.
You can learn more about what this compliance is and how to update your Genesys DX deployment to be compliant by reviewing the details in this article: ICO Cookie Compliance.
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