ProspectNow Predictive Analytics Product Launch

Table of Contents

I normally don’t write blog posts for every new feature of ProspectNow since we are constantly adding and updating the capabilities of the application.  However, in this case I felt it necessary to discuss a new product that will have a huge effect on your marketing efforts as a CRE professional.
When I started the company, I was motivated to solve a core problem that I had as a CRE broker.  That problem was that I was spending a lot of time researching the contact info for commercial buildings. My goal was to market to them to see if they wanted to sell their building.  I think it’s fair to say ProspectNow has made it a lot easier to get to the key decision makers of a given building.  The challenge now is centered around marketing to the right building owners that actually have a need to sell or buy.  Prospecting for sellers of real estate is a numbers game and a lot like throwing darts.  If you talk to enough owners, eventually you will find someone that needs to sell.  But talking to owners that have no intention of selling is wasted effort.

What if you could filter out the properties with virtually no chance of selling?

In a perfect world, the goal of marketers is to read your mind and present to you the perfect product that you are in need of at the exact time you need it.  Just a few years ago this seemed like an impossibility, but now as the world of big-data grows…it’s becoming more and more possible.
Many of you who follow this blog may remember a post we did on a survey of CRE brokers as to why their most recent client sold his property.  I have re-posted the results below:
Investment Property Survey
What we learned from that is that there is a correlation between a property that sells and particular events and conditions.  About a year ago we set out to see if we could build a predictive algorithim that would take into account the way a property looked before it sold, and then apply these similar characteristics to properties that have yet to sell.  The goal is to filter out the non sellers.  For example, if a property was just purchased 10 days ago…it’s unlikely that the owner is going to sell it any time soon.  So why bother sending a post card to this owner or call the owner?  If you have been in real estate for a while, you know there are lots of different triggers as to why an individual might sell.  But, we wanted to stop guessing and actually prove it using hard data and analytics.
We decided to start running our model each week for a year.  After the model was trained, we then looked at a group of properties we tagged as “likely sellers”.  Then we continued running our model and updating scores on properties each week.  We did not want to launch a product we had not tested, so we wanted to see if the list of properties our model generated 10 months ago, actually resulted in a higher percentage of properties sold.
Sure enough we found that in some cases more than twice the number of properties sold in the properties we tagged as “likely sellers”.
The following graphic is a good analogy.  The top graphic is a normal market, and the bottom graphic is a group of properties tagged as likely sellers:
 
Average-Turnover

What does this mean for our customers?

If you focus your marketing efforts on the “likely sellers” group, it’s possible you will see a 100% increase in results.  This is a game changer for those looking to get more listings and represent more sellers.  As of this writing….if you are a ProspectNow customer, you have access to this data.  All you have to do is login, search and select the check box “likely sellers” in the search and you are on your way.  We are looking forward to your success!

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