Does InsideView have a global dataset?

Explore InsideView’s global database of over 17 million companies and 50,000 decision makers worldwide.

Key Takeaways:

  • InsideView has a global dataset that provides B2B data on every public company and over 17 million private companies 
  • InsideView aggregates and triangulates data from multiple sources to provide more accurate data at scale
  • InsideView sources signals or real-time news from English content

View the Transcript

John Kosturos:
This is a kind of a double question in terms of where you target: Are you targeting companies that are primarily in the United States? Do you have a global customer base? And then, do you also have data that covers both North America and globally?

Heidi Tucker:
Yes. We’re a global data set. We have about 17 million companies in our database around the world. It’s every public company, which is about 50,000, and then all of the rest of those millions are private companies. We have about 50 million contacts or decision maker contacts in our database. And, we’re on a path to get to a hundred million contacts by the end of this year, while at the same time, maintaining our data quality and data accuracy. As you can imagine in the middle of a pandemic, with everybody changing jobs, that’s a very difficult thing to do. The only reason we’re really confident in our ability to do it, let’s just say, better than everybody else, is because we use various sophisticated, AI-based technology to aggregate and triangulate, which means try to find the same data in multiple places. We then validate things like email addresses through third-party email validation. The only way you can achieve the accuracy at scale is to have multiple sources of data and triangulate it.

To get back to your original question about geography, about half of our database is in North America and about the other half is spread across other regions of the world. Because we’re looking to triangulate data off of multiple sources, we tend to have more data in places where companies are more digitally visible. So we would have more information about tech companies or about financial services companies, then we might about a dry cleaner, for example, and in markets where there is more data available, we can validate the data more easily. So in markets like China, even in some regions of South America, it’s a little bit harder to obtain data to validate. So we tend to be more strong in North America and in Western Europe and English speaking companies around the world.

John Kosturos:
Okay. That’s pretty amazing. I have a specific question about languages. What if it’s a digital culture, but the language is not an English speaking character. Can you also find verified data places where other languages are used as the primary language for writing?

Heidi Tucker:
Yeah, so it depends what data you’re talking about. We do have hundreds of thousands, if not millions of companies, in markets where English is not the first language. We categorize news based on natural language processing to associate mergers and acquisitions, leadership change, funding events, or bankruptcies. That type of categorized news in our world only works with the natural language processing of English content. So we may have companies listed in China. We have lots of them. In fact, we work with some of the larger supply chains, companies, but we’re only able to present the signals or the real time news on English content.