Workflow Automation

AI Interviewer

Learn how to build an autonomous AI assistant that conducts interviews, collects data, and performs chat-based questionnaires.

Turn hours of interviews into minutes with Lindy. This AI assistant automates your entire interview process from start to finish - handling everything from data collection to results export, so you can focus on analyzing insights and making informed decisions.

Here's what this Lindy does:

Initiates conversations with participants through a customizable chatbot interface
Stores participant data in a spreadsheet for easy tracking
Conducts a series of questions based on your specific needs
Handles inadequate answers by following up and asking for more details, ensuring all necessary information is captured
Provides a seamless experience for both interviewers and participants

By the end of this guide, you’ll have your very own AI-powered interviewer, and it will take less than 10 minutes to set up.

Let's get started!

Setting Up Your Interviewer Lindy

To begin, we'll configure the Lindy Embed Message Received (Greet participant) trigger. This feature lets you create a custom chatbot interface for your interviews or questionnaires. You can read more about Lindy Embed and how to build a chatbot here.

Click on the Lindy Embed Message Received (Greet participant) trigger to access its configuration settings.

You'll see several options to customize your chatbot:

Domain Name: Restrict where your Lindy can be embedded. Leave it empty to use on any domain, or enter a specific domain like "yourcompany.com".

Display Name: Set the name of your bot as it will appear to participants. For example, "Technical Interview Assistant" or "Customer Survey Bot".

Accent Color: Choose a color that matches your brand for the top of the chatbot window.

Popup or iFrame: Decide between a floating popup chatbot or a fixed iFrame embedded directly in your page.

Logo: Upload your company or project logo to appear in the top left of the expanded chatbot.

Icon: Select an icon for your chatbot's collapsed bubble.

Greeting Message: The introductory message the user sees when they start a chat.

Conversation Starters: Customize messages next to your bot to prompt engagement.

Callout message: Create a prompt to encourage participants to interact with your chatbot.

Understanding The Greeting Message

Your Interviewer Lindy is configured with a greeting message designed to serve two important purposes:

It welcomes the participant and explains the purpose of the interview or questionnaire.
It asks for a specific piece of identifiable information.

Customize this for your interview, but ensure you keep a question that asks for identifiable information, this way Lindy can track the user.

For example, your greeting message might look like this:

Welcome to our Technical Interview Assistant! I'm here to guide you through a series of questions about your programming experience. To get started, could you please provide your full name?

This greeting is crafted to capture a key piece of identifiable information about the participant, such as:

Full name
Email address
Username
Account name

After customizing the Embed settings, click Done to save your changes.

How Lindy Validates Responses

After the greeting, Lindy uses a Condition (Received info?) step to ensure the participant has provided the required information. Here's how it works:

The Condition (Received info?) step checks if the participant's response meets certain criteria. For instance, if you're asking for a full name, the condition will verify that the full name was given, not just a first name, etc.

If the condition is met, Lindy proceeds to the next step in the workflow, storing this information in your database (a Google Sheet in this example) for later use.

If the condition isn't met, Lindy is set up to politely ask the participant again for the required information.

Click the Condition step to view the default prompts:

you got their email address and full name

you did not get their email address and full name

Change this to ensure the data you requested in your greeting message aligns with the Condition prompts.

Click the Lindy Embed Send Message (Get Info) action under the “you did not get their email..” condition to view the prompt Lindy uses to ask the participant for the information needed to continue.

Storing Participant Information

Once a valid response is received, Lindy is set up to store this information. This data is crucial for tracking responses throughout the interview or questionnaire process. We’ll set up a Google Sheet to store this information effectively:

Create a new Google Sheet and give it a name. Set up your column headers following these best practices:

Column A: Date of the interview
Column B: User information (captured in the greeting message as the unique identifier)
Columns C onwards: Interview questions or question numbers (e.g., 1-10)

Now that your sheet is ready, let's configure Lindy to use it:

Click the Google Sheets Append Row (Add participant info) action in your workflow. Select your newly created Spreadsheet from the dropdown menu and select the Sheet Title where you created your column headers.

To ensure Lindy adds the collected information correctly, we'll use “AI Prompts” for the “Date” and “User Info” columns:

For both the “Date” and “User Info” column parameters, switch the fields to "AI Prompt" mode. Add the following prompts:

For the Date column:

Use today's date formatted DD/MM/YYYY

For the User Info column:

Use the full name given to you by the user

These prompts instruct Lindy to automatically fill in the date of the interview and the participant's name (or other identifier) as provided in their response to the greeting message.

Conducting the Interview

After setting up your greeting and Google Sheet for data storage, it's time to dive into the heart of the interview process. Lindy uses a combination of Lindy Embed Send Message actions and Condition steps to ask questions and ensure quality responses.

Asking Questions

The Lindy Embed Send Message action is used for posing questions to participants.

To configure the interview questions, click on the first Lindy Embed Send Message (Question 1) action after the Google Sheet step in your workflow. You'll see a "Message" field containing the prompt for Lindy:

Ask them the interview question (no yapping, just ask the question): 

1. Where do you live?

This format ensures Lindy asks clear, concise questions without unnecessary preamble.

Verifying Responses

After each question, a Condition (Received answer?) step verifies that the participant has provided an adequate response. This step contains two conditions:

They responded with where they live
They did not respond with where they live

If the response meets the first condition, Lindy moves to the next question. If not, Lindy loops back to ask the question again.

Customizing Your Interview

To tailor this Lindy to your specific interview needs:

Edit Questions: Click each Lindy Embed Send Message action. Replace the existing question in the "Message" field.
Update Conditions: Click the Condition (Received answer?) step following each question. Modify the conditions to match your new question.

For example, changing the question to "What is your job title?"

Would require updating the conditions to:

They responded with their job title
They did not respond with their job title

Remember, clear and specific conditions are crucial. They should:

Define what constitutes an acceptable answer
Account for various response phrasings
Be specific enough to catch inadequate answers

Concluding the Interview

After collecting the interview data, Lindy takes three final steps: concluding the interview with the participant, updating the database and notifying you of the completed interview.

Sending a Conclusion Message

The first step is to properly conclude the interview with the participant.

Click on the final Lindy Embed Send Message (Conclude interview) action in your workflow.

In the "Message" field, you'll see the following prompt:

Thank the user and let them know that this concludes the interview. 

(No additional info - never ask them a question)

This prompt ensures that Lindy politely ends the interview, thanking the participant for their time without introducing any new topics or questions.

Updating the Interview Data

After the interview has concluded, Lindy uses a Google Sheets Update Row step to record the collected information in your Google Sheet.

This step ensures that all responses are properly organized and stored for later analysis.

Click on the Google Sheets Update Row action in your workflow. You'll see several fields that need to be configured:

Spreadsheet: Select the same spreadsheet you chose for the "Add Row" step earlier.

Sheet Name: Choose the specific sheet within your spreadsheet where the data should be recorded.

Lookup Column: This is your unique identifier column, typically the one containing the participant's name or email.

Lookup Value: In this field, enter a prompt that refers to the unique identifier given to you by the participant.

Example:

The name given to you by the user

This ensures Lindy can find the correct row to update for each participant.

Mapping Responses to Columns

For each column in your Google Sheet, you'll see a corresponding field in the Update Row action. You have two options for filling these:

Auto Mode: If you leave these fields on "Auto", Lindy will use its intelligence to match the answers given in the chat with the appropriate columns based on your Google Sheet header titles.

AI Prompt Mode: For more control, you can switch each field to "AI Prompt" mode and provide specific instructions for how to fill each column.

For example, if you have a column titled "Job Title", you might use the prompt:

Use the job title provided by the user in response to the job title question.

Benefits of Auto Mode

Using Auto mode can save time and reduce the chance of human error in setting up prompts. Lindy's intelligence allows it to:

Interpret column headers accurately
Match responses to the most appropriate columns
Handle variations in how information might be phrased

However, for complex interviews or when you need very specific data formatting, using AI Prompts can provide more precise control.

By properly configuring this Update Row step, you ensure that all the valuable information gathered during your interview is accurately recorded and easily accessible for future reference and analysis.

Notifying You of Completed Interviews

After updating the Google Sheet, Lindy uses a Slack Send Direct Message action to alert you that a new interview has been completed.

To configure this notification, click on the Slack Send Direct Message action in your workflow.

You'll see two main fields to configure:

User: To increase reliability, switch this field to "Set Manually" mode. Then, enter your email address associated with your Slack account.

Message: In this field, you'll find the following prompt: New interview done! (link / hyperlink gsheet)

This prompt instructs Lindy to send you a message with a direct link to your Google Sheet database, allowing you to quickly access and review the newly completed interview data.

By setting up these final steps, you ensure that:

Each interview ends on a positive note for the participant
You're promptly notified of each completed interview
You can quickly access new data for review and analysis

Observing Without Responding

The last action in your Interviewer Lindy workflow is the Lindy Embed Observe action.

This step allows Lindy to observe any additional messages from the interviewee without responding. It effectively concludes the chat, ensuring the interviewee cannot restart or initiate a new conversation with Lindy after the interview process is complete.

Review The Lindy Context

Before deploying your Interviewer Lindy, review and customize its Context. To access it, click the "Settings" tab beside the Flow Editor and Tasks tab, then locate the "Context" field.

Context is a set of overarching instructions that Lindy follows throughout the workflow. These instructions are included at every step, giving Lindy a helpful reference for the task she’s performing.

This Lindy’s Context outlines the task and allows you to add interview questions as a reference for Lindy. Including questions isn’t mandatory, but it can help Lindy stay on track if the conversation starts to drift.

Consider also including:

Brand voice guidelines
Key points to emphasize
Specific interview guidelines

This gives Lindy a clear, consistent framework, helping her conduct interviews that align perfectly with your goals.

Deploying Your Interviewer

There are three ways a user can interact with your Interviewer.

A public link
A popup chatbot
An iFrame

To send Lindy as a public link, click the Lindy Embed Message Received trigger.

Click the Configure Embed Settings button on the right panel.

Under the “Accent Color” section, select iFrame.

Copy the URL between in the iFrame Code Snippet:

Example:

< iframe src="https://chat.lindy.ai/embedded/lindyEmbed/1773cb20-15f5-42e9-a196-ea99f9030c07" width="100%" height="100%" style="border: none" title="Lindy Embed">

Link:

https://chat.lindy.ai/embedded/lindyEmbed/1773cb20-15f5-42e9-a196-ea99f9030c07

You can now share this link to participants!

To embed Lindy onto your website, follow the steps outlined here.

Now you have everything you need to automate your interview process with Lindy! Whether you're conducting technical assessments, job interviews, or customer surveys, your AI interviewer will consistently gather quality responses while you focus on analyzing the insights. Get started with your first automated interview today!

Guides

Getting Started With Lindy: 101

Triggers

Setting Up A Webhook Trigger

Lindy Mail

Image Recognition

Tips For Reducing Costs