Quick: who do you know that’s ready to sell? We mean, really ready?

It’s not something most agents know off the top of their head. You probably have a list of people you’ve bucketed based on the information you know about them. And hopefully, you’re doing your best to stay in touch and stay valuable to those people.

But it still happens. That dreaded moment when you learn a person in your network recently listed… without you.

How can you keep that from happening?

Meet Seller Scores: your data science superpower.

If you're like most agents, you have a pretty sizeable list of people in your database. But do you have 214 million?

That’s how many individuals helped shape the predictive algorithm we use here at First, and that algorithm powers the Sellers Scores. By analyzing patterns across past movers, we can determine which factors indicate that someone is likely to sell their home.

When you import your contacts First connects your data to a vast database and determines if your contact is a homeowner, renter, or real estate agent.

We use each piece of contact information to match people to corresponding property data and profiles, which matches them to their Seller Score.

The more accurate the contact information, the better the matches.

‍

Sellers Scores give you an at-a-glance likelihood of who will list.

First uses data science to measure how likely homeowners are to sell.

The likelihood of each contact to sell is compared to the national average.

The average homeowner has about a 6% chance that they will sell their home this year. That’s not great odds.

Homeowners with a score of 2x or higher are at least twice as likely to list their home this year than the average homeowner.

But remember, your contacts don't know about the First platform. They certainly don't know what their Seller Score is.

First often knows that a person is likely to sell -- even before they do. That's the magic of data science. So when you see a contact is highly likely to sell, what do you do?

Real relationships – powered by data.

Instead of asking likely sellers if they want to list, send a text, setup a coffee appointment, or invite them to a ball game.

Studies show that sellers are primarily looking for someone trustworthy and responsive when selling their home.

If you connect with a likely seller at the right time, you'll build the rapport and trust needed to convince them to choose you as their agent – even if you never talk about their home.

If you see a contact who is likely to sell but you don’t know this person, we don’t recommend contacting them right away about listing.

Start by reviewing where the contact came from. Was it an online lead or is it someone you connected with on LinkedIn but never really talked to? Take a little time to establish the foundation and find a way to add value from there.

Generically reaching out to lend your professional assistance is good, but the more personal and specific you can make your outreach, the more effective it will be.

‍

We know WHO is likely to list. We know WHEN they are likely to list. But do we know WHY they will list?

There are so many personal reasons a homeowner would list. Life changes are the leading factor: their family is changing shape, or there is job change. But overall, individual factors don’t come anywhere close to the predictive power of a holistic model, because the underlying factors which drive someone to list a home are far more complex than a few data points.

Our algorithm is highly non-linear and based on thousands of decision trees to make predictions. And the trees themselves are based on historical observations about which households did or did not move.

In other words, selecting a few characteristics or clusters of people can get you part of the way there, but what drives our model's performance is the inter-relationship between hundreds of factors.

It's a difficult (if not misleading) exercise to boil down the rationale behind a household's move score to just a couple of factors (e.g. "this household is more likely to move because they have X income and live in a Y square foot house").

Many agents would like to know the "why" behind our predictions, but we try to caution that sometimes forcing a conversation based on this inferred context can lead to awkward interactions.

There are a handful of reasons for this, but an obvious one is that people get creeped out if you know "too much" about them (especially since we are using largely non-public data to inform our predictions).

“Hey, will you be moving because of that upcoming divorce?”

“How are you going to spend that big raise?!”

“Are you worried about your kids going to school in this district?”

All of these are nonstarters. You don’t want to be that agent.

Remember, you're cultivating and nurturing relationships – not "managing" leads. People do business with people. And these are the people who want you as a trusted advisor in real estate.

You know the right way to build valuable relationships with homeowners. We’ll help you know the right time.