In the competitive landscape of commercial real estate (CRE) business development, data management and categorization have become pivotal. At the forefront of this transformation is the data team of Biscred, steered by Alex Grob, its director of data. Since joining in 2021, Alex has been instrumental in shaping Biscred's approach to database taxonomy. This article delves into Biscred’s unique methodology, combining machine learning, artificial intelligence, and human expertise, to revolutionize the way CRE data is collected, analyzed, and utilized for prospecting. With a focus on data quality and taxonomy, Biscred is redefining standards in CRE data services, blending technology and human insight to provide unparalleled accuracy and relevance.
To understand what Alex and his team does, let’s compare the Biscred operation to a self-serve cafeteria. The data are all the ingredients that the team uses to prepare their courses. The data classifications are like the dish types (entrées, sides, desserts, plus flavors like Southwest, vegan, etc.). The data operations team are comprised of all the people who slice and dice the ingredients, get rid of bad ingredients, find and create new recipes, get feedback from customers, and prepare delicious dishes. But this self-serve cafeteria is no ordinary one: All dishes are fortified with a secret sauce that makes them better and healthier than any other cafeteria!
How does Biscred approach database taxonomy?
The Biscred approach to database taxonomy has followed a philosophy of, “we start slow so we can move fast.” What does that mean? The team uses a combination of machine learning, artificial intelligence, and human brain power to collect, analyze, test, categorize and test again the quality and efficiency in their data.
With commercial real estate, formulating a list of classifications is complicated. In addition to the people who design, build and invest in commercial properties, you have the people and businesses that service the properties — HVAC, landscaping, property management, interior design — and the people and companies that operate the assets — property managers, leasing agents, and proptech firms, to list a few. How do you build a prospecting tool that serves all of those businesses, which have their own different goals, budgets, specialties and needs?
Alex explains that the question wasn’t whether they had enough data to fill a CRE platform, but how would they categorize it so that an end user could easily find exactly what they needed.
“We couldn’t just bundle owners, operators and developers together, for instance,” Alex said.
Their goal was to build a data platform where business development professionals could drill down to the most relevant prospects and filter out irrelevant data. An architectural firm that specializes in industrial design doesn’t need the same information as a commercial security company that wants to expand into the life sciences sector, or a CRE developer for mixed-use properties, or a solar sales company based in the Southwest.
What sets Biscred apart from other CRE data providers?
Alex lists two things that differentiate Biscred from other CRE providers: data quality and taxonomy.
“Our research team is in the data around the clock, every day, and we have checks in place and several layers of leadership that the data goes through to ensure the quality is top tier,” Alex says.
Data quality
One of the most valuable components of any database is the accuracy and contact-ability of the people who are in it. Without giving away their “secret sauce” approach to data management, Alex says his team uses a combination of automation and manual validation to ensure that the people listed as working at Company Z actually work at Company Z. They have checks in place to ensure that they find out when email addresses go stale before their clients do.
If you think that sounds tedious, you’re right … to a point. Their approach is to spend as much time as they need in discovery and manual processes, so they can learn from those steps and automate it in the future.
“Our model is we start slow so we can go faster,” he says. “We’re trying to replicate what a researcher might discover and fix it, then learn from that so they can automate it in the future.”
Database taxonomy
Biscred’s taxonomy reflects the way people in commercial real estate think about the industry. The filtering abilities go beyond asset class specification at the contact level, for example. Biscred’s users can filter at company, individual, industry, asset experience and location levels; additionally, they can filter based on seniority, job titles and company size. As Alex explains, they want to put only the most relevant information in front of their clients.
“Being able to go to the asset class specialization at the contact level on our platform is very valuable,” Alex offers as an example. “Other platforms don’t offer that type of filtering.”
Another area where Biscred’s taxonomy shines is with large organizations that have five, six or more specializations and finding the individuals who work in the specialty that their clients are most interested in. Where a purchased lead list might include a company name and a list of contacts that work there, the prospecting database goes much deeper.
“We do the heavy lifting for our clients, and they see it in the quality side of the data,” he says.
Will AI and machine learning replace humans in data validation?
Last year saw AI go mainstream, but, as Alex says, “We’re just scratching the surface. The nature of our work is going to change, no doubt about it, but I believe there’s always going to be a human in the loop.”
AI technology is far from perfect when it comes to reading a website and determining what type of business the site is in. Alex gives the example of real estate investment firms and private equity firms, which use similar language and vocabularies. Owner-operators and property managers also use similar languages. AI, at least as of now, doesn’t easily distinguish between the types of firms. That’s something that humans excel at because we can see images, words, colors, fonts and other characteristics and infer meaning.
Biscred is leveraging technology and working with technology partners in some interesting ways. They had the benefit of starting with a well-established brand (Bisnow), which had, at the time, about 14 years of data from commercial real estate companies and businesses ancillary to CRE.
“We’re not just relying on humans, and we’re not just relying on machines,” Alex says. “We’re blending them both so we can have the best of both worlds.”
What Does 2024 Look Like for Biscred’s Data Team?
“I think 2024 is going to be the most accelerated year for us, not without growing pains, of course, but I think, this is where we really hit our stride,” Alex says. “I'm excited for the clients who've already come on board with us realizing the value that they're going to see, and I’m excited to showcase the product to new clients this year.”
Ready to be one of those new clients? Click here to https://www.biscred.com/demo of the Biscred platform and learn how our data can help you smash your growth targets.
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