How setup Lead Collection
- How setup Lead Collection
- What is Lead Collection?
- How to enable Lead Collection?
- Options
- How Lead Collection Works?
- Export the leads to CSV
- CSV file advantages
What is Lead Collection?
Lead Collection is a powerful feature of ChatLab that allows your chatbot to gather essential visitor details such as email, or phone number. This information can be invaluable for identifying your customers faster and enhancing your engagement strategies. By enabling Lead Collection, you can ensure that you have the necessary contact details to follow up with potential leads effectively.
How to enable Lead Collection?
From the main ChatLab administration page, select Chatbots in the main menu, click on selected chatbot, select Settings and scroll down to Lead Collection
Options
- Message encouraging user to leave details: The message displayed to the customer when the Lead collection form appears.
- Show lead collection form after X messages: The number of messages sent by the customer after witch the Lead collection form appears.
- Collect E-mail/phone/both: You can ask your customers for their E-mail, phone number or both. You can also edit the default text displayed above the labels.
- “Thank you” message after submitting the form: The message displayed to the customer after leaving the details.
How Lead Collection Works?
When the Lead Collection feature is enabled, visitors interacting with your chatbot will be prompted to fill out a form requesting their contact details. This form appears after a specified number of messages or at the beginning of the conversation, depending on your configuration.
How to access collected leads?
From the main ChatLab administration page, select Chatbots in the main menu, click on selected chatbot and select Leads.
Export the leads to CSV
In order to export leads to CSV, click on Export to csv file button.
CSV file advantages
A CSV file (Comma-Separated Values) is easier to interpret and organise by programming languages. It is especially useful when dealing with large datasets.