This content has been relocated to a new article, BoltBot Skills. For the most up-to-date information, please use that article.
Overview
BoltBot's Inquiry Flow skill gathers key information from prospective students and submits an inquiry on their behalf.
How it works
When BoltBot detects the intent of the user is to inquire to study at your institution, BoltBot will initiate the Inquiry Flow. Phrases such as these are examples.
I am interested in studying at Element University
I am interested in studying [program/major]
Can you send more more info about {{program/major}}
BoltBot will ask the student to provide the following information:
Intended major
Intended term
First name
Last name
Email address
After gathering the information, BoltBot will take the following actions:
If the student has an existing record, a prospect milestone will be added.
If the student record does not exist, a user will be created with a prospect milestone.
Pro Tip: Combine Conversation Starters and Inquiry Flow
You can make the Inquiry Flow more effective by using conditional Conversation Starters to prompt students to kick off the flow.
For example, set up a Conversation Starter on your biology program page that says, "I'm interested in studying biology." When a student clicks on it, BoltBot will initiate the Inquiry Flow.
Benefits of combining these features:
Drives more inquiries by prompting students in relevant contexts.
Collects more qualified leads by targeting key pages like academic programs.
Gathers more accurate major information since the major is directly prompted.
Provides a smoother experience by initiating the flow from a student prompt.
Important Notes
The Inquiry Flow skill must be enabled for BoltBot to launch the flow. To enable the skill, make sure the Inquiry Flow chip is green in your BoltBot settings.
When enabled, BoltBot can also list available majors and terms.
The inquiry submitted by BoltBot does not authenticate the user via email address provided. The inquiry flow behave the same as submitting a form.
Majors are matched using machine learning since they can vary semantically when entered as natural text. This can lead to some mismatches particularly for majors with similar names.