How to use AI for data analysis in HubSpot: A practical guide

HubSpot is a goldmine of customer data. Seriously. It holds everything from marketing campaign clicks and sales pipeline stages to every single service ticket. The entire story of your customer journey is right there.

But let’s be real for a second: having all that data and actually understanding it are two completely different things. It’s easy to get buried in dashboards and reports, trying to piece together what’s really going on.

This is where AI is supposed to step in and save the day. The promise is that it can do the heavy lifting, turning those mountains of data into clear, useful insights. And while HubSpot’s built-in AI tools are a decent place to start, a truly smart strategy means looking at the whole picture. Often, the most valuable nuggets of information aren’t in a dashboard at all, they’re tucked away in help desk conversations, project plans, and team chats.

This guide will give you a clear, step-by-step process for using AI for data analysis right inside HubSpot. But more importantly, we’ll show you how to take it a step further by bringing all your company knowledge together for a view that actually makes sense.

What you’ll need to get started

Before we jump in, let’s quickly cover what you should have handy. Getting these things sorted out first will make the whole process a lot smoother.

• The right HubSpot plan: You’ll need a Professional or Enterprise plan for Marketing Hub to access the AI campaign analysis features we’re about to walk through.

• Some data to work with: Make sure you have access to campaign data, customer feedback, or sales reports in your HubSpot portal. The more history the AI has to look at, the better.

• A clear question: Don’t just go in exploring. Have a specific question you want to answer, like "What are our best-performing marketing assets?" or "What are the common themes in customer support tickets this quarter?"

A step-by-step guide

Alright, ready to dive in? Here’s a simple walkthrough for using HubSpot’s own AI tools to analyze your data.

Step 1: Figure out what you want to know

The quality of any AI analysis really boils down to the quality of your questions. If you ask vague questions, you’re going to get vague answers. So before you click a single button, decide exactly what you’re trying to learn.

Here are a few examples to get your gears turning:

• For your marketing team: "Which blog topics from our Q2 campaign brought in the most new contacts?" or "Can you summarize how our welcome email series performed?"

• For your sales team: "What do the leads from the last 90 days who became customers have in common?"

• For your service team: "Based on support tickets, what are the top three problems our customers are running into this month?"

Step 2: Find HubSpot’s AI-powered reporting tools

Now that you have your question, it’s time to find the right tool for the job. HubSpot has its AI, called Breeze, built into different parts of the platform, but the Campaign Performance tab is one of the best places to begin for marketing data.

Here’s how you get there:

1. In your HubSpot account, go to Marketing > Campaigns.

2. Choose the campaign you want to analyze.

3. Click the Performance tab at the top.

Think of this dashboard as your main hub for understanding how your campaign is tracking.

The HubSpot dashboard provides a central hub for tracking campaign performance and other key metrics.:

Step 3: Get a quick AI campaign summary

Once you’re on the Performance tab, HubSpot gives you an easy way to get a quick overview. The AI-generated summary is perfect for getting a high-level view without getting bogged down in details.

This summary will usually give you a rundown of key stats (like new contacts or sessions), point out your top-performing assets, and highlight any obvious trends. It’s a great first look that helps you spot areas worth investigating further.

Here’s how to do it:

1. Inside the Performance tab, find the Campaign summary section.

2. Click Summarize, and the AI will generate its overview.

3. Read through the key metrics and takeaways. Make a note of anything that surprises you or confirms something you suspected.

Step 4: Ask the Breeze Assistant specific questions

The high-level summary is nice, but the real value comes from digging deeper. This is what the Breeze Assistant is for. It allows you to ask specific questions about your campaign data in plain English.

Using the business questions you came up with in Step 1, you can now get some real answers. For example, you could ask things like:

• "What was the click-through rate of our blog post versus our email?"

• "Which landing page in this campaign converted best?"

• "List the top 5 performing assets from this campaign."

The assistant will look through your data and give you a straight answer, saving you the headache of building a custom report from scratch.

HubSpot's Breeze AI can assist with content generation and data analysis, making it easier to understand campaign data.:

Step 5: Look at qualitative data for customer sentiment

Beyond the numbers, HubSpot’s AI can also help you understand text-based data, like the customer feedback or ticket descriptions you have stored in the CRM. This is where you can start to understand the "why" behind the "what."

But this is also where most people hit a wall. HubSpot’s AI is pretty smart, but it can only analyze data that lives inside HubSpot. What about all the important knowledge stored everywhere else? You might have analyzed your campaign data, but the real story, the reason why the numbers look the way they do, is often buried in your Zendesk tickets, your internal wikis in Confluence, or your team’s brainstorming sessions in Slack.

Analyzing qualitative data from HubSpot support tickets can reveal customer sentiment and common issues.:

The problem with data silos (and how to fix it)

When you rely only on one platform’s AI, no matter how good it is, you create blind spots. Real customer intelligence is spread all over your company’s tools, and if your AI can’t see all of it, you’re only getting a tiny piece of the story.

This leads to a few common frustrations:

• An incomplete picture: The AI can’t see the detailed product feedback sitting in your Google Docs or the urgent customer issues being sorted out in Slack. It’s basically analyzing with one eye closed.

• Generic answers: Without the rich context from thousands of past support conversations, AI responses can feel a bit hollow. It misses the specific details of your business, your brand’s voice, and the solutions that have actually worked for customers in the past.

• Not enough control: You’re often stuck with the platform’s standard automation rules that don’t quite match up with how your team actually works.

This is where a tool like eesel AI really changes things. Instead of being just another separate tool, eesel AI acts as a smart layer that connects to all your existing apps. It unifies your knowledge and gives your AI the full picture to work with.

Here’s how it solves those problems:

• Connect all your knowledge, instantly: You can connect HubSpot with Zendesk, Confluence, Google Docs, Slack, and dozens of other tools in a few minutes. There are no complicated setup meetings or long onboarding processes. Your AI immediately gets access to a complete company brain.

• Train on what really matters: eesel AI learns from your past support tickets, regardless of which helpdesk you use. It analyzes years of real conversations to understand your tone, common problems, and successful solutions, making sure its analysis is perfectly tuned to your business from day one.

• Test it out with confidence: Nervous about letting an AI loose on your data? We get it. eesel AI lets you run simulations on thousands of your past tickets in a safe environment. You can see exactly how it would have responded, get accurate predictions on resolution rates, and adjust its behavior before it ever touches a live customer issue. It completely removes the guesswork.

Quick tips for AI data analysis in HubSpot

Whether you’re sticking with HubSpot’s native tools or using a more connected solution, a few good habits will help you get better results.

• Start small: Focus on automating the analysis for one specific campaign or a single type of support ticket first. Prove the value in one area before you try to do everything at once.

• Keep your data tidy: An AI is only as smart as the data it learns from. Make sure your HubSpot properties are well-organized and your data entry is consistent. A little housekeeping goes a long way.

• Don’t forget the human touch: Use AI-generated insights as a starting point for conversations, not as the final word. Your team’s experience and intuition are still your most valuable assets.

• Keep making things better: The best part of AI analysis is that it often points out gaps in your knowledge base or workflows. Use these discoveries to make improvements. In fact, eesel AI includes reports that automatically highlight these gaps for you, giving you a clear to-do list for what to fix next.

A well-organized knowledge base is key for effective AI data analysis in HubSpot.:

From scattered data to unified intelligence

HubSpot’s AI tools are genuinely helpful for analyzing the data that lives within its world. They can save you a lot of time and help you spot trends you might have missed otherwise.

But to find those truly powerful insights, you have to break down the walls between your tools. The real magic happens when your AI can learn from every customer interaction, every internal document, and every team conversation, no matter where it happens. That’s the difference between simple data analysis and true business intelligence.

Ready to stop guessing and start analyzing your data across all your tools? Get started with eesel AI in just a few minutes and see what a unified approach can do for your team.