Alerts Panel - User Guide
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Nodes
Data Input Node
Conversational Data Capture Node.
19 min
overview the conversational data capture node is designed to make user input collection seamless and engaging unlike traditional form based input capture, which disrupts the conversational flow, this node interacts with users contextually to gather the necessary information to access this feature, you must have llm (large language model) capabilities enabled and subsequently integrate esensegpt on the alerts panel platform note recommended models gpt 4 turbo, gpt 4o, gpt 4o mini features engaging and contextual user interactions validate user input data configurable bot tone for enhanced user experience and alignment with brand values set limits on follow up attempts to control how many times the bot will ask for essential or mandatory user inputs steps to access and add the node step 1 log in log in to your alerts panel portal select a bot from your account with llm enabled, and esense gpt connected step 2 navigate to the builder in the left navigation bar, go to builder click on add node a popup displaying all available data input nodes will appear search for and select the conversational data capture node node configuration input field dropdown select the data you want to capture (e g , name, email, phone number) for custom input type, choose the custom field option and define your desired field note select custom input for any other use case apart from the default ones mentioned above instructions (optional) this is an optional field with default instructions already in place, however, this section is mandatory for custom input types for predefined fields like name, email, and phone number, default instructions are already provided, but you can customise it as needed an example instruction for capturing the name input type would be “please craft a user friendly message to ask the user for their first name ensure the message clearly explains that this information is requested solely for registration purposes and explicitly assures the user that their name will not be misused provide an example of how the data should be entered (e g , 'john') to ensure clarity” validation (optional) if left empty, default input wise validations will apply for predefined fields like name, email, and phone number for custom inputs, however, defining validation rules is mandatory to ensure proper data capture if filled, custom validation rules will override the default settings bot tone select the tone of the bot from the following options professional ideal for formal interactions, focusing on clear, respectful, and precise communication friendly best for creating approachable and warm interactions humorous adds a touch of humour, making conversations light hearted and engaging, perfect for informal contexts neutral maintains a balanced and straightforward tone, suitable for general purpose interactions attribute name define the attribute name corresponding to the database field where the data will be stored for example "name conversational data node" follow up limit set how many times the bot should prompt the user for the input if it is not initially provided options include not mandatory (asks 1 time) low (recommended) (asks 2 times) medium (asks 3 times) high (asks 4 times) note the "low" option is recommended as it strikes a balance between encouraging user input and maintaining a positive user experience during the conversation this approach increases the likelihood of capturing user data without overwhelming the user fallback action trigger a node if the user fails or refuses to provide the requested data this ensures that users who do not provide inputs are guided through an alternative chatbot experience, differentiating their journey from the path designed for users who share the required information conclusion the conversational data capture node revolutionizes data collection by making it conversational, contextually relevant, and user friendly by leveraging the power of esensegpt and llm capabilities, this node ensures an enhanced and personalized user experience