I joined Crunchbase as Chief Product Officer about a year ago, just six months after ChatGPT stunned the world. It was an uncertain time for startups — generative AI presented both an opportunity for innovation and an existential threat, and rising interest rates and fears of a recession were forcing many companies to slash their SaaS budgets.
In this new world, one thing was clear: customers wanted generative AI to help them do their jobs. For Crunchbase, this presented a compelling challenge. We already had proprietary data people trusted and loved. We also had a foundation of machine learning and artificial intelligence in our product. Now, the task was to harness the latest generative AI technology and apply it to our unique data to exceed customer expectations.
I’m excited to share what we’re doing on the product side with the help of AI, and why Crunchbase is uniquely positioned to create something truly remarkable. I’m also going to explain why we’re implementing these developments, and how these changes will help the people who rely on Crunchbase every day.
Learning from our customers
Our customers, ultimately, are the guiding force behind our product decisions. My team knew we wanted to combine the strength of our unique data with powerful AI, but we wanted to do it in a way that addressed our users’ needs. We met with our customers to ask them one key question: How can we help you succeed in your daily work?
Several shared that they loved our proprietary data, but wanted Crunchbase to do the analysis for them. They wanted to know if going after a particular company was worth their time — whether it was on a path toward growth, for instance, or whether it was about to go out of business. Could we tell them which companies were worth prioritizing so they’d know where to put their resources?
We came away from these conversations empowered and emboldened to act on our customers’ suggestions and deliver a product of deeper value. We wanted to create something that met the needs of all users making decisions based on company data, whether they were looking to invest in startups, source their next deal, or gain intelligence about the market.
Crunchbase data meets AI
Taking our customers’ feedback to heart, the next evolution of our product will offer more than our unique data; it will also tell stories about companies based on that data.
We’ll share insights and predictions about company health, strategic moves, and trends and forecasts in the private market. Crunchbase is uniquely positioned to do this because we already have a treasure trove of historical context that we’ve gathered by tracking millions of startups from their initial ideas through seed funding, IPOs, and exits. In other words, we have great, hard-to-replicate, proprietary data — the core of any successful AI platform.
We’re still focusing on the proprietary data that makes Crunchbase indispensable, but we’re taking it a step further. We’re analyzing and extrapolating this data with our AI model to offer intelligent, personalized guidance and answer important questions for our users, like Should I invest or partner with this company? Who should I target for funding, and when? Is this company likely to buy my product right now?
We’re not just a repository of data, but we’re also helping users make the right business decisions by synthesizing that data into actionable insights and predictions that are scaled with AI.
A peek at our product roadmap
Customers can already find new insights across a wide range of company profiles. We’re still in the early stages, but our conversations with customers are leading us to build more robust profiles that guide our users’ decision-making and help them stay ahead of the market.
We’re going to proactively deliver this information and answer our users’ underlying questions — sharing insights and predictions about company health, the market landscape, and risks — without making people dig for that information themselves. You’ll see a complete overhaul of how our users interact with company data, starting with profiles and going all the way into how they make their business decisions.
On top of that, we rolled out a beta version of our AI search assistant, powered by natural language processing, as the first step in interactive, personalized engagement on the platform. This allows users to conduct searches in plain language — for instance, typing, “Show me companies that recently raised funding,” without navigating any filters. Our aim is to simplify interactions, making them as intuitive as chatting with a personal assistant. This is just the beginning of how we’re taking the gains from the generative AI boom and applying them to our unique data and distribution advantage.
Finally, we want to make sure that Crunchbase continues to meet the needs of different types of users. Some people still want comprehensive, unfiltered data, while others prefer quick, simplified access to that information. To serve such a diverse user base, we are doubling down on our API and refining our core data models. This ensures that organizations can access our unique private company datasets to create world-class decision models, while others can enjoy easy, personalized access to the specific data they need.
Our goal is to cut through the noise and align with what users expect and appreciate — simplicity, efficiency, and personalization in digital platforms. By providing direct answers, reducing friction, and sharing tailored guidance, we’re improving the value and user-friendliness of Crunchbase and unlocking more ways to access and use our proprietary data.
We’re going to be more than a data platform; we’ll be a guiding source of truth for our users when it comes to business decision-making. My team couldn’t be more excited about what we’re building next. Keep an eye on Crunchbase in the coming months.
