AI Solutions for Enterprise SaaS - HubSpot

Fellows Fund
June 12, 2023


  • HubSpot: Rong Yan, VP of Engineering


AI plays a crucial role in HubSpot's approach, viewed as a tool to solve customer challenges rather than just a technological advancement. The company focuses on leveraging AI to help customers execute their goals, simplify processes, and learn from repeatable patterns. Within the SMB market, HubSpot aims to make an impact by assisting with data insights, simplifying actions, and connecting systems. They provide examples such as predictive lead scoring, data anomaly detection, and AI-powered content generation tools like ChatGPT. By leveraging insights, simplifying actions, and connecting systems, HubSpot empowers SMBs to thrive in the digital landscape.

HubSpot emphasizes the importance of the data layer, as access to proprietary data and understanding the business context provide a long-term competitive advantage in AI applications. They highlight that AI is a means to solve customer problems and urge the audience not to solely focus on the technology itself. The perception of AI in the market is positive, with many SMB leaders believing it can level the playing field against larger businesses. Overall, HubSpot sees AI as a paradigm shift and believes there is much more potential to explore in the AI space.


Full Transcripts:

Great to see everyone here and super excited to talk about the AI solution for HubSpot. Today, I would love to give you more information about what we're doing at HubSpot in terms of AI. Before diving into that, let me kick things off by sharing more about HubSpot. Our company is based in the beautiful city of Boston, and our focus is on building leading CRM platforms that empower customers to manage their entire life cycles. Our mission is simple: we want to help millions of organizations grow better and stronger.

We have experienced tremendous growth over the past 20 years. In 2006, we released our first CRM application product called Marketing Hub, with a sole focus on marketers. Since then, we have expanded our coverage to include Sales hubs, Services hub, and more recently CMS hub, and Operations hub. Now, with a unified CRM platform, we cover the entire spectrum of CRM use cases throughout their life cycles. Under the leadership of our two co-founders, Brian and Dharmesh, and our CEO, Yamini, we achieved a major milestone of 1 billion ARR two years ago with 100,000 customers. This year, we're doubling those numbers, and reaching 2 billion ARR with our current run rate. It's not just the revenue growth that makes us happy, but also the fact that more and more SMB customers are benefiting from the platform we're building for them. Looking ahead, our total addressable market is projected to increase from 45 billion to 72 billion in the next five years. This is not only a huge market, but also a huge underserved market with tremendous potential for technological innovation.

Before we dive into why AI plays a crucial role, let's take a step back and understand the rise of the SMB community. About 20 years ago, two major paradigm shifts occurred, driven by the internet and search engines in the early 2000s, followed by the mobile and social media revolution in the 2010s. These shifts fundamentally changed how people interacted and gave rise to great companies like Google, Facebook, and Amazon. Today, we have a new generation of digitally savvy users who are not only more technically adept but also motivated to build businesses with technology. Statistics show that 77% of SMBs are willing to use social media for customer communication, and the number of SMBs considering software a priority has significantly increased in recent years. As a result, SMBs have been investing more in SaaS expenses compared to Enterprises.

However, there are significant challenges that SMBs face, particularly when it comes to disconnected solutions and data. In our most recent survey, only 22% of companies reported having an excellent data connection solution, leaving the remaining 78% in search of better opportunities. This prompted HubSpot to change its strategies from building a single app to unified platforms, and we have witnessed tremendous success in addressing customer pain points.

Now, let's shift our focus to the main topic of this section: AI. I don't want to view AI solely as a technological advancement; instead, I want to see it as a tool to solve customer challenges. AI has a long history of development spanning over the last 50 to 60 years, with many significant events that have shaped its trajectory. From defeating humans in specific domains to the recent democratization of AI for everyday tasks, there have been pivotal moments that have propelled AI's impact. The AI landscape is expanding rapidly, and many great companies are exploring the integration of generative AI into their products.

I encourage everyone to embrace the uncertainties and opportunities that AI brings. Let's always keep in mind the customer challenges we are addressing and utilize AI as a powerful tool to provide effective solutions.

And this is exactly what we do at HubSpot. When we consider the data opportunities, it can be viewed as a flywheel of three things: data, insights, and actions. We begin with customer data to generate insights, and through those insights, we take actions. With the actions we take, we generate more data. If you can execute this flywheel effectively, you will have a healthy cycle of leveraging data and generating valuable customer information. AI plays a crucial role in this process. Underneath this framework, we have execution memories that capture user preferences, and above that, we strive for a customer experience that aligns with their goals.

Let's explore the opportunities within AI by considering three principles. First, does AI help customers execute their goals? Second, is there a substantial amount of human effort involved in certain areas? If so, AI can simplify those processes. And third, are there repeatable patterns that we can learn from? If there are, AI can help summarize and predict future outcomes based on that knowledge.

Now, let's apply this framework to small and medium businesses (SMBs). There are three main dimensions where we can make an impact. Firstly, SMBs often lack data science teams and struggle to extract insights from their data. Secondly, simplifying actions is crucial because SMBs find it increasingly challenging to navigate SaaS products with a growing set of functionalities. Lastly, there are a multitude of systems that SMBs currently use. Can we leverage AI to connect these systems into a unified flow and align them with a single goal? These are three areas we can explore.

In HubSpot, we have specific use cases that align with each of these dimensions. For instance, predictive lead scoring is an AI use case that helps sales teams prioritize potential leads based on the likelihood of closing deals. We also focus on data anomaly detection to automatically identify and alert users of any issues or errors in their data workflows. It's essential to highlight that when delivering predictive AI features, expectation management is crucial. Customers often have high expectations, so it's important to communicate the limitations and provide actionable insights rather than just presenting numbers.

Moving on to the actions themselves, AI can play a significant role in assisting SMBs. One example is Content System, which uses AI-powered engines like ChatGPT or GPT-3 to generate comprehensive answers based on prompts. This tool has proven to improve content quality and save marketers a significant amount of time.

Lastly, we address the challenge of connecting systems with a product called Chatbot, which combines chat engines with HubSpot. This dialogue-based system allows users to interact with HubSpot features in a unified manner, simplifying their experience and driving towards a single goal.

These are just a few examples of how AI is being utilized in HubSpot to empower SMBs and solve their unique challenges. By leveraging insights, simplifying actions, and connecting systems, we can help SMBs thrive in the digital landscape.

This is our founder, Dharmesh, who ideated and developed this entire project single-handedly. It's very impressive. If you haven't used the chatbot yet, I encourage you to go to and give it a try. It's a dialogue system that facilitates interactions with a lot of HubSpot data. There are numerous use cases you can explore. One of my favorites is using the chatbot to generate reports for HubSpot, creating a powerful business intelligence tool. Now, you might ask, why is the ChatSpot better than other dialogue systems like ChatGPT? The answer is simple. The ChatSpot has access to your specific context and proprietary data. This, in my opinion, will be the long-term competitive advantage for these types of applications. It's not just about the model itself, which will be democratized. It's about the data and understanding the business context. Here's an example. On the left side, we have the ChatGPT's answers, and on the right side, the ChatSpot answers. The ChatSpot provides more structured and rich responses when it has access to proprietary data. For those of you interested in exploring new ideas and directions, I believe this data layer is something to consider.

There are many more AI use cases in HubSpot, but unfortunately, I don't have enough time to cover them all in this 20-minute conversation. However, I hope these slides have convinced you that there's so much more we can do with AI. It is truly a paradigm shift for us. And here are a few interesting numbers: 80% of SMB leaders in sales, marketing, and services believe that AI can make it easier to compete against large businesses in their industries.

The perception of AI is quite fascinating in the market right now. But let me end the conversation with this slide: AI is a tool, a means to solve customer problems. Don't focus solely on the technology itself.

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