Owner Data Offers Springboard for Predictive Analysis Niche

Wayne says brokers can’t get listings before knowing who owns every building in a respective market.

SAN FRANCISCO— Steve Wayne started out as a commercial real estate broker, pounding the pavement for leads, listings and most importantly, the ownership records for buildings in his market. This painstaking work was the spark behind founding the company, ProspectNow . Wayne shares his insight into the predictive analysis platform and why it is helping brokers who are now in his former shoes. GlobeSt.com: What was missing in the industry that prompted you to start ProspectNow? Steve Wayne: I spent the first year of my career as a CRE broker researching building ownership. My objective was to get listings and I ​was​ not​ able to​ get listings unless I knew who owned every building in my market. As most people know, commercial real estate is owned in LLCs, trusts and other entities, so it’s not a trivial task to get the key decision makers behind every building. It was a brutal process going to multiple database​s ​to obtain all of the information. I also noticed this research was being duplicated across my peers so there was an obvious inefficiency. Fast forward to today and ProspectNow has detailed information on millions of buildings and​ a portfolio of ​thousands of customers. GlobeSt.com: How has the product/vision evolved? Wayne: The vision has not changed. Our goal is to help our customers get more listings and close more deals. Getting the key decision makers for a property is the first step but the next evolution is using predictive analytics to guide our users to their most likely customer. We eliminate wasted marketing and maximize the productive marketing. In addition to providing information on all of the properties, we can also inform you about the properties where you should direct your marketing. GlobeSt.com: How does predictive marketing work? Wayne: Predictive marketing is the process of applying data science to determine the customers that are mostly likely to buy from you. In our case, our data science team profiles thousands of properties each week that have just sold. This profile can then be applied to properties that have not yet sold. The result is our customers can focus on a group of properties that will have a much higher probability of being listed than a random grouping of properties. Our predictive model is a “machine learning” model, so this means with each update, it gets smarter and more efficient. GlobeSt.com: Who benefits from this process? Wayne: Really everyone . . . the broker saves money by reducing wasted marketing efforts, the building owners who want to sell get access to a quality broker and the other building owners receive fewer unnecessary marketing communications. It’s a win for everyone. GlobeSt.com: Finally, what can we do to speed the adoption of tech in commercial real estate? Wayne: There are a ton of smart tech-savvy people in this industry. The challenge around the adoption of tech in CRE is not due to the people but rather the structure.  Specifically, each CRE broker is really like an independent business and as a result, the decision making is distributed across thousands of brokers.  It’s not uncommon to find lots of different tools for CRM, marketing, analysis, etc. in a single organization. The good news is both the larger and smaller firms are starting to see the advantages of adoption at scale. We have customers that have adopted our program for all their agents and the benefits are realized uniformly across the organization.  The industry is definitely going in the right direction. Read more about ProspectNow in a previous issue.