How to Create AI HR Onboarding Support Bot for Slack and Reduce Costs by 38%

Updated at: 03/03/2025

By Oleg Kopachovets

Share on Social Media

7 min.

Step-by-step guide: how to create an AI HR Onboarding Support Bot
Tips and recommendations

Yes, you heard right — implementing AI tools does reduce employee onboarding costs by as much as 38%. Imagine how much easier this can make your HR department’s life! It’s not for nothing that 62% of HR specialists are already actively using chatbots as virtual assistants, which successfully cope with 75% of HR requests!

AI tools automate routine onboarding and support processes, help newcomers quickly get comfortable, and provide all the necessary information about salaries, benefits, and job responsibilities. As a result, HR specialists save precious time and can focus on more important strategic tasks. And that’s not all! Effective onboarding increases employee retention by 82% as well as their productivity. We agree, these are impressive numbers!

Let’s figure out how to make the onboarding process for new hires even faster and more comfortable with the help of AI bots. For example, on the Omnimind platform, you can create a bot for Slack, train it on company data, and grant access to new employees.

In this article, we will tell you how to create your own HR Onboarding Support Bot in just 9 easy steps, using Omnimind.ai!

Step-by-step guide: how to create an AI HR Onboarding Support Bot

Let’s go through the Wizard Setup Flow in detail and consider each stage of creating a chatbot from idea to implementation.

Step 1: AI Workshop: Create Your Own Bot

First, you need to Sign up or Log in on the Omnimind.ai platform. You will immediately have access to a magical and convenient dashboard to create AI agents, chatbots, and Tables for different purposes and industries. I am not kidding about magic! With Omnimind.ai everyone can feel like a wizard)) There is also a training video that will introduce you to the features and capabilities of the platform. Ready-made bot and agent templates can be customized to suit the needs of your business.

Let’s look at the differences between chatbots, agents, and templates and explore their capabilities:

Chatbots interact with users in a dialog format. They answer questions and provide information based on data loaded into a knowledge base. They do well in pre-defined scenarios.
Agents are more intelligent than chatbots. They are able to analyze context and understand complex queries, so they can perform a wide range of tasks including data analysis, forecasting, and scheduling.
Templates are ready-made solutions that can be used to quickly create chatbots or AI agents. They are a kind of constructors that can be customized and adapted to specific needs.

Since the chatbot is the protagonist in our case study, let’s move on to creating it!

Step 2: Set up the goal of your chatbot

First, you need to select the “Create Agent” menu item. You will see the roadmap of your bot! At this stage, you need to decide how exactly the bot will work. In this case, for the first question “What should your agent do?” you should select the “Answer with knowledge” option. We choose this item because our support chatbot will pull information from the uploaded files into its knowledge base:

Step 3: Decide on your chatbot needs and integrations

Omnimind.ai. lets you choose from a variety of technologies and integrations. Since the finished chatbot will be integrated into Slack, when asked “Do you need external services, APIs, or scrapers?” you need to add the name of this messenger in the corresponding line.

Step 4: Set your agent’s Knowledge parameters

This is where the magic happens! Knowledge is the data source from which the bot gets information and then processes it. So when asked about access to data, you need to select “Yes, my agent needs to use my own data, documents, websites”:

Step 5: Choose interaction channels

Omnimind offers different options. I am sure that among them, you will find the one that best suits your team:

via a website or application;
via messengers;
personal use.

In our case, the bot will directly interact with the Slack workspace. Therefore, at this stage we select the “Through messaging platforms (e.g., Slack, WhatsApp)” option:

Step 6: Tell the bot in detail what and how it should do

You are almost there! At this stage, you need to describe the logic of actions — what, when, and how the agent should do. In the description field, describe the purpose of the bot in detail, clearly and without ambiguity. AI HR Onboarding Support Bot will search for information on request in Knowledge and act according to the following scenario:

1. An employee asks a question either in a Slack bot, WhatsApp bot, or in a chat widget on a spare page

2. The agent finds suitable information in the knowledge base and provides an answer

Requires Slack integration.

Step 7: Upload data to Knowledge

When creating an agent or bot in Omnimind.ai, in addition to website URLs, PDFs, URL files, Word files, Google Docs, policies, and internal organization documents, you can upload to Knowledge:

Tables: Airtable, CSV Links, CSV Text, Excel, Google Sheets, Xml Sitemap;
Audio and video files from YouTube and Vimeo;
Cloud Storage: Dropbox File, Dropbox Folder, GDrive File, GDrive Folder, OneDrive File, OneDrive Folder and much more.

You can upload various company documents to the knowledge base of HR bots:

manual for new employees;
internal work regulations;
job descriptions;
organizational structure;
corporate culture standards;
procedure for calculating and paying salaries;
information on bonuses and awards;
information on social benefits (health insurance, pension contributions, etc.);
document processing procedures;
issues related to adaptation, training, and development;
contact information for different departments.

Our AI HR Onboarding Support Bot does not use additional tools, triggers, or workflow. The project’s Knowledge contains information on salary and Payment Policies.

Step 8: Integrate the bot into Slack and generate API keys

Congratulations, your chatbot is ready! Now let’s look at the installation process, including generating API keys and integrating it into Slack. In Omnimind.ai, the bot workspace looks like this:

To integrate the bot into Slack, in the Install menu, select Messengers, then Slack:

Now you need to copy the API Key and Project ID:

You can find the API Key here:

You need to copy the Project ID from here:

It’s time to go to Slack and check with the bot about the payroll period!

Step 9: Test and launch the bot

Now we need to go to Slack. To do this, click the “Add Slack” button:

After that, a pop-up appears, on which you need to click “Allow”:

And here we are in Slack! In the top search bar, enter “reconnect”:

In the “Connect to Omnimind App” pop-up window, paste the copied API Key and Project ID, and then click “Submit”:

A message from the bot appears in the correspondence:

Ask the bot a question to make sure it works correctly and receive an answer:

Tips and recommendations

If the chatbot only needs information in the knowledge base to work, update the data regularly. If the data is current and reliable, the agent will provide the correct answers.

Support chatbots help employees integrate into a new team, instantly and at any time receive feedback and access to the necessary information. In addition, effective adaptation reduces stress levels and increases employee engagement and retention by up to 82%.

Of course, the company wins! Such AI solutions automate the HR team’s routine, free up work time, optimize work processes, and increase efficiency, freeing up time for high-quality “live” onboarding of new employees or other administrative issues.
Ready to transform the onboarding process for new employees in your company? Sign up for a trial version of Omnimind.ai and use our step-by-step guides to create your own AI HR onboarding support bot!

By Oleg Kopachovets Published: Feb 6, 2025

Last updated: Mar 3, 2025

Share it with the world

Register

How to Make AI Agent for HubSpot Data Enrichment

Updated at: 03/03/2025

By Oleg Kopachovets

Share on Social Media

9 min.

What is HubSpot Data Enrichment AI Agent?
Conclusion

Did you know that 91% of businesses struggle with incomplete or outdated customer data, leading to poor decision-making, missed sales opportunities, and inefficient workflows?

Data is powerful—but raw data alone isn’t enough. To make smarter business decisions, companies need enriched data—meaning cleaner, more accurate, and more insightful information that goes beyond just names and emails.

💡This is where AI-powered data enrichment agents come to shine!

McKinsey reports around a 30% increase in sales efficiency for companies using AI-driven data enrichment.

An AI agent for HubSpot data enrichment automates the process of retrieving, updating, and verifying customer data within your CRM. Using Omnimind’s AI capabilities, businesses can:

reduce manual workload,
eliminate data inconsistencies,
and gain deeper insights into their customers.

In this step-by-step guide, we’ll walk you through the steps of AI agent creation for HubSpot data enrichment using Omnimind.ai. This tutorial is designed for users of all experience levels, with a straightforward approach to setting up an automated agent that enhances your HubSpot CRM data.

What is HubSpot Data Enrichment AI Agent?

Imagine you’re the Head of Sales at a SaaS company. Every day, new users sign up for your product, some fill out a demo request form, and others download a lead magnet. All these contacts automatically land in HubSpot, and now you’re looking at a list of hundreds of potential customers.

❓But who among them is truly worth your attention?

❓Who is the high-value lead you can’t afford to miss?

❓Who should be assigned a personal sales manager?

❓How can you personalize outreach when all you have is a name and an email?

Typically, your sales team spends 2–3 hours daily manually researching each lead—checking LinkedIn, verifying company details, and gathering extra data. Meanwhile, time is wasted, conversion rates drop, and competitors may reach out first.

❗️What if this entire process could be automated?

That’s where our AI-powered agent steps in. It instantly gathers all essential lead information in the background as soon as a contact enters HubSpot CRM—saving time, improving efficiency, and giving your team the competitive edge.

A HubSpot Data Enrichment AI Agent is an automated system that integrates with your HubSpot CRM to:

Collect missing customer details from various online sources.
Validate and correct outdated information in contact records.
Automatically fill in missing fields like industry, company size, and social media profiles.
Improve lead scoring and segmentation for better marketing and sales campaigns.

By using Omnimind’s powerful AI tools, this agent continuously analyzes and updates customer profiles in real time, ensuring that your sales and marketing teams work with the most accurate data possible.

How Does the Working Logic of This AI Agent Look?

1. We have a trigger that checks HubSpot for a new contact created less than a minute ago every minute.

2. If a new contact is found, the agent takes their First Name, Last Name, and Company name. If there’s no such info, the agent checks the contact’s email address and retrieves the company name from the domain. Also, our agent can check text before “@” to validate if it consists of anything that seems to be a real name.

3. Using the retrieved data, the agent performs google search and looks for a LinkedIn person profile URL.

4. If a suitable URL is found, the agent adds it to HubSpot.

5. Additionally, the agent retrieves the information the user asked from the LinkedIn person profile such as job title, city/country, duration of current employment, etc., and returns it to HubSpot to the respective fields.

6. If the LinkedIn url address wasn’t found with Google search, the agent can run an Apollo tool to search for information with the email address.

👉 Now let’s dive into how you can build your own AI agent to automatically clean, update, and enrich your CRM data in a way that drives real business results!

Step-by-Step Guide to Creating AI Agent for HubSpot Data Enrichment

Sign Up / Login into your Omnimind account. You’ll see a simple interface with step-by-step guidance to build your AI assistant—perfect even for beginners, with a video tutorial to help!

Step 1: Sign Up & Set Up Your Omnimind Account

Log in or create an account at Omnimind.ai.
Navigate to the Create AI Agent section.

Step 2: Define Your Agent’s Purpose

Now, let’s define the core objective of your AI agent and enter the initial settings.

In the Agent Goal section, select “Enrich or process data” as the primary function.

Step 3: Determine Your Integration Needs

When asked: “Do you need external services, APIs, or scrapers?”, choose Yes and add these tools in the appropriate field below: HubSpot, Google Search, LinkedIn, Apollo, Gmail Email Sender.

Step 4: Configure Your Agent’s Knowledge

You’ll be asked: “Will your agent need to access your own specific data or documents for answering?” Choose: No, knowledge base is not needed. Because this agent does not require creating a database for training—it will work directly with your HubSpot.

Step 5: Select Your Interaction Type

Then, when asked: “How will users interact with your agent?” Choose: In the background (scheduled or triggered). In our case, users will not interact with the agent directly. The agent will be triggered automatically when a contact is added to HubSpot CRM.

Step 6: Formulate Brief and Concise Description of Your Agent’s Key Functionality

Finally, you’ll be asked to briefly describe what you want your agent to do. You can add this description, or use your own:

“The HubSpot Data Enrichment Agent automates the process of gathering and updating lead information by pulling data from HubSpot, searching online or through Apollo, and enriching the contact profile with relevant details.”

Then, click the Next step button.

Now let’s wait a bit while Omnimind.ai automatically identifies and adds the tools your agent needs based on the options and descriptions you select. So you can click on the “Next Step” instead of adding everything manually from the list!

Step 7: Interaction Setup

You’ll see an active Background option in the next section—click Next to proceed.

Step 8: Triggers

Our main triggers will be HubSpot Contact Creation and HubSpot List Updated ones, as they are directly related to the data enrichment task in HubSpot.

Step 9: Set Up a Precise Agent Workflow

In the “Briefly flow what your agent will do” field, just copy and paste the workflow prompt we’ve already outlined for you below:👇

## Step 1: Define Lead Source

Retrieve HubSpot contact by HubSpot Get Contact tool. Save contact id, name, email, company_name, and value of the hs_analytics_source property.

If the value of hs_analytics_source is “”OFFLINE,”” you must terminate the workflow and output only “”Offline sources””.

## Step 2: Check if the Name is Given

You must analyze information from Step 1 and if there’s no First and Last name given, you must retrieve the email address and validate if the text before the ‘@’ symbol can be a real person’s name. For instance: ‘gk@omnimind.ai’, ‘i21479124@procoders.tech’, or ‘sales@theibigshop.com’ all aren’t names, while ‘johndoe@procoders.tech’, ‘jenn@luxrecruitment.com’, and ‘andrew.long@outlook.com’ clearly have names in the address (John Doe, Jenn, and Andrew Long respectively).

If there’s no name in the email address, you must return ‘NO NAME’ and ignore all the following steps.

## Step 3: Define the Company Name

You must analyze information from Step 1 and if there’s no company name given, you must retrieve the email address and validate if its domain name (text after the ‘@’ symbol) can be a company’s name. For instance: ‘john@procoders.tech’, ‘andrew@omnnimind.ai’, or ‘jake@thebigshop.com’ all have company names (ProCoders, OmniMind, and The Big Shop), while ‘kate.wolff@outlook.com’, ‘erl.strike@gmail.com’, and ‘hugh.mole@icloud.com’ are clearly personal emails addresses that do not include company names.

If there’s no company name in the email address, you must return ‘NO COMPANY NAME’ and ignore all the following steps.

## Step 4: Search for LinkedIn Profile on Google

It is strictly forbidden to perform this step more than once.

Using the Google Search tool, perform the following exact query:

‘name company_name site:linkedin.com’ where instead of “”name”” and “”company_name”” you use the information from step 1 and return LinkedIn personal profile URL like https://www.linkedin.com/in/*** from the search result. You must return only the first URL from the search results. You must perform only one Google search.

If there’s no First and Last name given, use the information from Step 2.

If no search results are found or there is an error, you must return “”NOT FOUND”” and ignore all the following steps.

## Step 5: Retrieving LinkedIn Profile URL

Retrieve LinkedIn person profile by URL with LinkedIn Person Profile tool.

## Step 6: Enriching data from the contact’s LinkedIn Profile

Using the HubSpot Update Contact tool update HubSpot contact with saved contact id from Step 1 with data retrieved from Step 3 with LinkedIn profile URL, country, city, and job title. It is strictly forbidden to update First Name, Last Name, and Job Title fields – no matter what you find or the result you get. If you didn’t find any piece of information you must return ‘NOT FOUND’ to the property field related to the piece of information you didn’t find.

## Step 7: Task Status Report

Return the information you added to the HubSpot contact profile to the chat.

Step 10: Review & Launch

The next steps are up to you to configure. Choose an icon and a name for your AI Agent. Then you’ll need to grant access to all relevant accounts for the selected tools and APIs to work properly.

After all these settings are done, you can finally LAUNCH your Agent. Congratulations!🎊

Common Issues & How to Fix Them

Why isn’t my AI Agent updating contact records?

✅ Fix: Ensure that API permissions are correctly configured in HubSpot.

What happens if LinkedIn profile enrichment fails?

✅ Fix: Check if the LinkedIn integration has the necessary permissions for scraping external data.

How do I troubleshoot API access issues?

✅ Fix: Reauthorize API connections in Omnimind’s settings.

Please feel free to contact Omnimind Support if you still have any questions or unresolved issues! You will always find access to it by the 🎧icon in the lower-left corner of the screen.

Conclusion

By following this step-by-step guide, you now have an AI-powered HubSpot Data Enrichment Agent that saves time, improves data accuracy, and enhances CRM efficiency.

With Omnimind’s seamless AI integration, your sales and marketing teams will always have the most up-to-date customer insights.

Want to take it even further? Try building additional AI-powered workflows in Omnimind to automate lead scoring, personalize customer outreach, and streamline CRM management.

▶ Get started with Omnimind today! Try it now

By Oleg Kopachovets Published: Feb 4, 2025

Last updated: Mar 3, 2025

Share it with the world

Register

Build AI Customer Support Assistant to Transform Your Support Experience

Updated at: 05/02/2025

By Oleg Kopachovets

Share on Social Media

8 min.

Step 1: Begin Your AI Journey
Step 2: Define Your Agent’s Purpose
Step 3: Choose Your Integration Needs
Step 4: Set Up Your Data Access
Step 5: Choose Your Interaction Channel
Step 6: Give Clear Instructions
Step 7: Select Your Tools & Services
Step 8: Upload Your Knowledge & Train Your Bot
Step 9: Set Up Chat Interface
Step 10: Configure Triggers (Optional)
Step 11: Final Configuration and Launch

Are you tired of answering the same customer questions over and over?

It’s a familiar scenario: support agents constantly handle repetitive inquiries, consuming precious hours that could be better spent on more complex customer issues.

In fact, research shows that support teams face an average of 11.9 interruptions per day, often repeating the same explanations. This not only drains time but also leads to frustration for both agents and customers.

But what if there was a way to eliminate this repetitive cycle? Enter the AI Customer Support Assistant—a game changer for modern businesses. Unlike traditional chatbots that are limited to basic scripts, this advanced AI tool can interact with customers in a meaningful way, answering questions, providing explanations, and offering personalized support.

And the best part?

95% of customers prefer getting information from a bot, according to research. By implementing an AI assistant, you can reduce the burden on your support staff by 43%, allowing them to focus on more impactful aspects of customer service. It’s not just automation—it’s a smarter, more efficient way to manage customer support while improving the customer experience.

Ready to transform your customer service?

Let’s dive in!

Step 1: Begin Your AI Journey

Sign up or log in to Omnimind.ai and start creating your first AI Agent!

Click on the “Get started” button in the Create AI Agent section.

You’ll see a friendly interface that guides you through building your own AI assistant—perfect for creating a knowledgeable support agent who understands your business!

Step 2: Define Your Agent’s Purpose

Let’s set your bot’s mission! Select “Answer with knowledge”—this is perfect for helping customers understand your products and services.

Your bot will be able to:

Answer questions about products and services
Explain policies and procedures
Help with troubleshooting
Provide relevant examples from your knowledge base

Step 3: Choose Your Integration Needs

For our support bot, let’s keep it focused on your business materials.

Select “No, my agent doesn’t require any integrations”. This setup is perfect for handling customer inquiries using just your uploaded support documentation.

Step 4: Set Up Your Data Access

When asked about accessing specific data, select “Yes, my agent needs to use my own data, documents, websites”.

This is crucial because your bot will need to understand your key support materials. Here are the essential documents to upload:

FAQs and troubleshooting guides – Your most common customer questions and their solutions
Product documentation – Technical specifications, user manuals, and setup guides
Company policies – Return policies, warranties, and terms of service
Pricing information – Product prices, subscription plans, and discount rules
Support workflows – Step-by-step guides for handling common customer issues
Service descriptions – Detailed information about your services and features
Communication templates – Standard responses and escalation procedures

Pro tip: Make sure all documents are up-to-date and in supported file formats (PDF, DOCX, TXT) before uploading.

Step 5: Choose Your Interaction Channel

Your customers need easy access to help wherever they are! Choose how you want to connect with them:

Website Integration: Embed the chat directly on your website for instant support
WhatsApp Business: Enable WhatsApp integration to provide 24/7 support through the world’s most popular messaging platform, allowing customers to get help through their preferred communication channel
Multi-channel Support: Combine both website chat and WhatsApp to create a seamless support experience across all touchpoints

The WhatsApp integration is particularly powerful as it lets you:

Respond to customer queries instantly through their preferred messaging app
Share images and documents directly in the chat
Maintain conversation history for better context
Scale your support globally through a platform your customers already use daily

Step 6: Give Clear Instructions

This is where you define exactly how your bot should interact with customers.

Feel free to use a simple prompt to outline some functionalities for your chatbot. If you wish to make it even more sophisticated, here are some examples:

Core Support Functions:

Answer product and service-related questions
Provide step-by-step troubleshooting guidance
Link customers to relevant help articles or documentation
Share product images and specifications when needed

Proactive Assistance:

Offer personalized product recommendations based on customer queries
Suggest related items or complementary products
Provide shipping and tracking updates
Send order status notifications

Customer Experience:

Use a friendly, professional tone
Follow up with satisfaction surveys after resolution
Escalate complex issues to human agents
Collect feedback about products and services

Example instruction:
“Assist customers by answering product questions, providing troubleshooting help, and sharing relevant documentation links. Offer personalized product recommendations when appropriate, provide order tracking updates, and maintain a friendly, professional tone. Escalate complex issues to our support team and collect customer feedback to improve our service.”

Step 7: Select Your Tools & Services

Let’s enhance your support bot with some powerful tools!

In the Tools & Services section, you’ll want to select:

AI Prompt: Perfect for generating clear explanations and responses to customer inquiries
Scrape webpage: Great for pulling information from your website about your products, services, and policies
Google Sheets: Useful for managing and accessing structured data like pricing or product specifications

You can also explore other helpful tools like:

Google Calendar for managing support schedules
Gmail Email Sender for automated follow-ups
Google Search for finding additional resources

Step 8: Upload Your Knowledge & Train Your Bot

Now it’s time to give your bot access to all your support materials. You can add knowledge in several ways:

Website Links:

Paste URLs of your help center pages
Add links to your product documentation websites
Include links to your policy pages
Share URLs of your public knowledge base

Google Workspace Integration:

Paste links to your Google Docs containing support information
Add Google Sheets URLs (Important: Also add these same URLs in the “Google Sheet Data Reader” tool configuration for proper access)
Include links to Google Sites with product information

File Uploads:

Upload PDFs of product manuals and guides
Add DOCX files containing policies and procedures
Include CSV files with product specifications
Upload TXT files with FAQs and troubleshooting steps

Pro tip: Make sure all your Google Docs and Sheets have appropriate sharing permissions set before adding them as knowledge sources.

Step 9: Set Up Chat Interface

Select “Popup Chat” as your interface option.

Popup chat is perfect for support chatbots. This will allow you to:

Embed the chatbot on any page of your website with a simple code snippet
Deploy across multiple domains and web properties
Customize the chat widget’s appearance to match your brand
Position the chat button wherever you want on your pages
Configure when the chat widget appears to visitors
Set up on both desktop and mobile versions of your site

After selecting popup chat, you’ll receive an embed code that you can add to any webpage where you want the chat widget to appear. The chat will appear as a floating button that expands into a full chat window when clicked, providing a seamless experience for your visitors.

Step 10: Configure Triggers (Optional)

While your bot will primarily respond to customer questions, you can also set up helpful automated interactions:

Follow-up satisfaction surveys
Regular check-ins on open issues
Automated status updates

Step 11: Final Configuration and Launch

We’re at the last step!

Name and Identity:

Choose an appropriate icon that represents customer support
Name your bot “Customer Support Assistant” or something that reflects its role
Make sure the name is clear and approachable for customers

Configure Your Selected Tools:

AI Prompt Settings: Choose your preferred model (OpenAI, Anthropic, etc.) and configure response style to be helpful and professional
Google Sheet Data Reader: Connect to your product databases and link to your Google Sheet
Webpage Scraper: Set up access to knowledge base and enable FAQ and resource page scanning

Review Your Complete Setup:

Agent Type: Answer with knowledge
Tools Connected: AI Prompt, Google Sheet Data Reader, Webpage Scraper
Knowledge Sources: Ready for your support materials
Interaction Widget: Popup Chat
Triggers: Webhook enabled for automated responses

Once everything is configured, hit that Launch button, and your AI support assistant will be ready to help your customers!

Leveraging an AI Customer Support Assistant is not just a luxury—it’s a necessity for modern business. By automating the repetitive task of answering common questions, you free up valuable time for both support agents and customers, creating a more efficient and focused support environment.

This technology doesn’t just lighten the load for your staff—it transforms the way customers engage with your business, providing instant, personalized support whenever they need it. Ready to reduce your staff workload, improve customer satisfaction, and elevate the support experience? The solution is simpler than you think—start building your AI Customer Support Assistant today!

By Oleg Kopachovets Published: Jan 28, 2025

Last updated: Feb 5, 2025

Share it with the world

Register

Build an AI Product Catalog Assistant to increase sales by up to 43%

Updated at: 05/02/2025

By Oleg Kopachovets

Share on Social Media

4 min.

Step 1: Begin Your AI Journey
Step 2: Define Your Agent’s Purpose
Step 3: Choose Your Tools and Integrations
Step 4: Set Up Your Data Access
Step 5: Choose Your Interaction Channel
Step 6: Define the Agent’s Goal and Interaction Parameters
Step 7: Configure Advanced Tools
Step 8: Establish Knowledge Framework
Step 9: Set Up Chat Interface Select “Popup Chat” as your interface option.
Step 10: Implement Strategic Triggers
Step 11: Final Configuration and Launch
Elevate Your E-commerce Experience

Are you tired of customers struggling to find the perfect product?

It’s a familiar scenario: shoppers browse your catalog endlessly, unsure which product best meets their needs, while sales teams repeatedly answer the same product questions. In fact, research shows that customers spend an average of 15 minutes searching before making a purchase decision—often abandoning their cart due to uncertainty.

But what if there was a way to guide every customer to their perfect product?

Meet the AI Product Catalog Assistant

A game changer for modern e-commerce. Unlike traditional search functions, this advanced AI tool can:

Interact with customers in a meaningful way
Understand their needs
Compare products
Offer personalized recommendations

And the best part? Over 50% of e-commerce businesses have already adopted AI technologies to enhance their operations. AI is no longer a future trend—it’s becoming standard practice. Omnimind is here to help you become an early adopter!

By implementing an AI assistant, you can increase sales by up to 43% while transforming your product discovery experience. It’s not just a catalog—it’s your most knowledgeable sales associate, available 24/7.

Step 1: Begin Your AI Journey

Sign up or log in to Omnimind.ai and start creating your first AI Agent!
Click on the “Get Started” button in the Create AI Agent section.

Step 2: Define Your Agent’s Purpose

Clearly outline what your AI assistant should accomplish.

Step 3: Choose Your Tools and Integrations

Equip your AI assistant with powerful capabilities:

Essential Tools for Maximum Effectiveness:

AI Prompt – The engine behind contextually relevant recommendations
Webpage Scraper – Automates product information curation
Google Sheets Data Reader – Dynamically manages inventory
WhatsApp Integration – Expands customer reach with seamless multi-channel guidance

Step 4: Set Up Your Data Access

Empower your AI with comprehensive product intelligence:

Detailed product specifications
Dynamic pricing structures
Comparative analysis frameworks
Verified customer insights
High-resolution product assets
Real-time inventory data
Comprehensive usage documentation

Step 5: Choose Your Interaction Channel

Optimize accessibility through strategic deployment:

Seamless integration across product pages
Multi-domain functionality
Instant customer engagement
Consistent brand experience
WhatsApp integration for personalized product guidance

Step 6: Define the Agent’s Goal and Interaction Parameters

Craft precise instructions to enhance every customer interaction:

Advanced Product Guidance
- Preference-based recommendations
- Comparative analysis
- Feature prioritization
- Alternative suggestions
- Real-time availability updates
- Direct product navigation
- Strategic cross-selling

Example: Deliver exceptional product guidance by analyzing customer requirements, providing detailed comparisons, and offering strategic recommendations. Maintain professional expertise while ensuring clear pathways to purchase through direct product links.

Step 7: Configure Advanced Tools

Enhance your product discovery agent with the right tools:

AI Prompt – Natural language product expertise
Webpage Scraper – Automated content synchronization
Google Sheets Data Reader – Dynamic inventory intelligence

Step 8: Establish Knowledge Framework

Integrate product information through multiple channels:

Digital Resources:

Product page URLs
Best-selling products
Product comparison breakdowns

Google Workspace Integration:

Detailed product documentation
Dynamic pricing sheets (sync with Google Sheets Data Reader)
Technical specifications

Document Repository:

Product catalogs (PDF)
Specification sheets (DOCX)
Inventory data (CSV)
Product descriptions (TXT)

Select “Popup Chat” as your interface option for maximum impact:

Strategic placement across product pages
Seamless website integration
Brand-aligned design elements
Cross-platform optimization
Responsive design implementation

Step 10: Implement Strategic Triggers

Design intelligent engagement protocols through webhooks:

Context-aware product introductions
Cart abandonment recovery
Product launch announcements
Strategic pricing notifications

Step 11: Final Configuration and Launch

We’re at the last step!