10 Best Machine Learning Stocks According to Analysts

7. HubSpot, Inc. (NYSE:HUBS)

Number of Hedge Fund Investors  in Q1 2024: 55

Analyst Average Share Price Target: $663

Upside: 40%

HubSpot, Inc. (NYSE:HUBS) is a cloud computing company that focuses on customer relationship management (CRM) products. The consumer facing nature of its products, which allow businesses to meet their customer management also creates significant room for HubSpot, Inc. (NYSE:HUBS) to integrate machine learning into its platform. One such use case comes through HubSpot, Inc. (NYSE:HUBS)’s Marketing Hub which uses machine learning for advertising. Yet, due to the growth intense nature of the cloud industry, the firm remains vulnerable to any growth slowdown, or a market downturn that affects its recurring revenue. To  combat the slow industry in H1 2024, HubSpot, Inc. (NYSE:HUBS) has introduced 70 AI features for its customers, reduced its entry level prices, and attempted to beef up retention by allowing customers to upgrade their packages  easily. Its shares did fall in July, but this was unrelated to fundamentals as investors reacted negatively to the report that Google parent Alphabet wasn’t buying HubSpot, Inc. (NYSE:HUBS).

HubSpot, Inc. (NYSE:HUBS)’s management commented on its new features during the Q1 2024 the earnings call:

Customers are looking at consolidating on our platform. They want to be very, very sure, and so there’s, like some additional proof-of-concepts there. In terms of AI though, we have, it’s been about a year, right? Last year, about this time, is when we launched our first set of products. And, most of the products are now in GA. In fact, in April, as part of our new spotlight, we launched about 70 additional AI features. And, what we are seeing, in terms of adoption is there are customers who are leading with AI.

They’re looking at like every single department within the go-to-market function saying, how can I leverage AI? And, those customers are moving fast. And, we can see that in terms of content use case adoption. We can see that in terms of service, summarization as well as deflection of call adoption, and we can see that in terms of Sales Hub, adoption of AI features. But then there are, a whole set of customers who are either just getting out of experimenting or figuring out the first set of use cases and then getting value, and that is going to take time. So, our focus this year is all about driving repeat usage. From a product perspective, you’re focused on driving repeat usage. From a go-to-market perspective, we are focused on educating customers how their data is being used, where they can drive productivity benefits as well as growth benefits.