Celeste Starchild is part of the leadership team at Move, Inc., that oversees the development of professional software tools and services. Senior Vice President of Professional Software, she has a successful track record in technology services, product development, sales and marketing, business development, and data security, and is the recipient of the 2015 Inman Innovator Award.

  • Predictive analytics will help consumers find the right house and help agents know when people are going to sell and buy.
  • Agents have more context and understanding of consumers with data analytics.
  • Countless opportunities with artificial intelligence will come to market soon.
  • The broker owns the listing data, but there are nuances about ownership when you have a collection of data.
A headshot of Celeste Starchild

Celeste Starchild

Celeste Starchild is part of the leadership team at Move, Inc., that oversees the development of professional software tools and services. Senior Vice President of Professional Software, she has a successful track record in technology services, product development, sales and marketing, business development, and data security, and is the recipient of the 2015 Inman Innovator Award.

She has created products that increase brokerage efficiency, such as online transaction management software (SettlementRoom, Inc.), and security products that protect real estate data (Clareity Security).

Most recently as general manager of ListHub, Starchild has been instrumental in leading ListHub growth. ListHub is a listing management platform that has been widely adopted for listing distribution and syndication. Starchild joined the executive management team at ListHub in 2006.

Hello, Inman News readers and listeners. I am super excited today to have with us a software guru, a data guru, a leader of the industry, Celeste Starchild, who has a big title. She’s Senior Vice President of Professional Software. Welcome, Celeste.

Hi Brad, thank you for having me. Great to be here.

When did you get that new title? You got promoted within this big News Corp. organization recently?

A few months ago, yes.

Good — well, congrats. So we’ll ask you about that, what it means to have that title and what you gotta do every day. But first, I’m just curious. Tell me about your last name, where does that come from?

Nobody’s ever asked me this question before!

Well, I’m gonna ask you.

Well, apparently you can make up whatever name you want, if you have a child — if anybody’s listening or thinking about naming a child. You can get as creative as you please and just write whatever you want on the birth certificate. That’s what my parents did. And it stuck, so…

I love it.

Most people ask if my parents are hippies and I usually say no, they were American Indian, and then that usually makes people pause for a second. And I think the truth is that they were probably hippies.

Yeah, that’s cool. I just watched a documentary about San Francisco in the late ’60s. I kinda miss that period in San Francisco. Now all the nerds have taken over.

But anyway, let’s get down to business. So I wrote you this esoteric first question.
 
I just reread it and I thought, my gosh, why did I write that or why would I ask Celeste this, but I think I’ll ask it anyway.

I say, “I feel like real estate data, particularly listing data, is like a multi-faceted stone. It represents power, control and influence.

 
People seem to be afraid of losing it, but also do not know how to keep it or use it. What is it with data that’s suddenly entered the picture even though MLS data has been around well over a hundred years? There’s certainly a new infatuation and there’s lot of politics around it.

 
What’s going on? Can you give us a thumbnail sketch of what’s going on with MLS data?”

Sure. So anybody who wants to create tools, software or technology or innovate around technology to serve and support the real estate industry needs data. So it’s like the gas that powers all tech, it’s the gas that powers all insight. So from the perspective of somebody who’s trying to drive economic insights or who is trying to drive any kind of predictive insights around consumer behavior, around the real estate market, it’s simply for research purposes.

 
It’s the fuel that powers all technologies.

If you think about what real estate is, real estate, in its kind of most distilled form, is the interaction between properties and people. And so, the properties is half of the equation, whether those people are engaged in a transaction or they own a home or they’re shopping for their dream home or whatever stage of a cycle they might be in.

 
It’s that intermix of property and people, so you need the listing content for a great search experience. It has to be complete.

And so everybody wants it and everyone wants to use it which accounts for all these little fisticuffs going on in the industry. Let me ask you this — predictive analytics. That’s what I’m really excited about and I think everyone is. Give us an example of a data insight that would explain in an act or a story or a piece of data what you’re talking about, predictive analytics.

Well, so if you think about what marketing really tries to accomplish, it’s a matter of bringing together the right person or consumer with the right product, at the right price, at the right time, right?

And so, the idea around predictive analytics is that effectively, artificial intelligence can be employed to, in effect, kind of narrow the focus of what’s likely to happen.

 
So if you think about a consumer who’s searching for real estate related information through the vast internet and all the information that’s out there, trying to personalize an experience for an individual consumer that really speaks to what that consumer is interested in and what their needs are to a very tailored degree.

 
That’s something predictive analytics can solve.

Let’s look at business-to-business. Forever and an age, listing agents — agents generally — would love to be able to predict when Celeste Starchild’s gonna sell her home in Malibu — or I guess you’re not in Malibu — Washington D.C.

 
Or when Brad Inman’s gonna sell his house in West Hollywood. Have we gotten to a point where all this machine learning and algorithms and AI (artificial intelligence) and predictive analytics that you can predict when I’m gonna do that?

I think there’s absolutely directional information that can be obtained using predictive analytics, so there are probably lots of factors involved in that and it’s not a crystal ball.

To draw a distinction, predictive analytics is more of a likelihood, sort of narrowing down the likelihood approach.

 
And being able to apply it to a B2B application like you’re describing would — say for example, take an agent CRM (customer relationship management) database with their thousands of contacts that they’ve been working, of prospects and past clients, etc. And really deriving a decision on a daily basis around what that agent should be responding to, which contacts should be at the top of the list, which contacts may want specific types of content to be delivered to them at a certain point in time. So it’s really about that and making that process more efficient.

So they might at least, let’s say there’s a hundred houses in my neighborhood. Predictive analytics might be able to narrow the number of people that are likely to sell over the course of the next year down to like 20. So if I was an agent and I was inclined to knock on doors, instead of knocking on 100, I might knock on those 20.

 
 Is that an example?

Absolutely, that’s an example. And even more importantly than that, on top of that, the agent should have a more informed notion about how to engage with that consumer based on more context. As opposed to, “Hey there, it’s Sally or it’s Joe and just thought we would touch base,” right?

Gotcha, anything else on the horizon? I just saw the Google AI — I don’t know if you heard about this, but they have an algorithm on writing sentences. And they poured in, I think, several hundred thousand pieces of literature, whole books from that huge Google library.

 
And their little AI guy or girl, whatever they call that person at Google, wrote a poem, and they gave them a beginning sentence and an end sentence and they filled in the blanks.

I guess that makes me think — and part of our focus at Connect this summer is, how far will AI penetrate into the real estate transaction, where bots or robots would be serving as escrow officers or other things.

 
What do you see with data and AI coming into real estate?

Well, I think that there are countless opportunities to employ AI in this space. I think it’s going to be interesting to see as some companies look to really leverage the technology. Use their powers for the forces of good versus the powers or the forces of evil.

What I mean by that is I think there are going to be companies that really try to replace aspects of that interaction between the real estate agent and the consumer.

 
And there are going to be other companies, and I would say that our company is sort of squarely positioned. And it really defines our company that our mission is to capture and leverage these technologies and put them in the hands of real estate agents and empower them to be more effective with consumers.

What you were just talking about reminded me of SwiftKey, it’s an interesting application that uses machine learning to predict personalized messaging. So effectively, SwiftKey could learn how Brad writes and what he’s likely to say, how he phrases things, the cadence of his writing, right? And would effectively be able to predict what Brad might say in response to any given email, etc.

When I first read about it, it sounded a terrible lot like autocorrect, but it’s actually a lot more sophisticated than that. And has interesting implications in this space as we’re looking for time-saving devices, ways to communicate on the go or on the fly. And I think it would be interesting for agents.

Yeah, I mean, I could use some autocorrect for sure. Particularly in voice.

Let’s look at the politics of data — and you were smack dab in the middle of it with Move and Zillow and all that.

 
Do you feel like the industry is coming together on a standard, on a process? We’ve got Upstream maybe bringing some certainty to the whole thing and then others say no, no Upstream.

But are we in the middle of the fray? Are we coming through the knothole and see the light at the end of the tunnel?

 
How’s that for about six mixed metaphors? Anyway, any thoughts?

I really don’t know. I think that the value of data is really in effect wherever it exists in sort of a, in an aggregate or in a usable fashion. So, there are few places where that shows up in the industry today.

We’ll see where it all goes, but I think there will always be a need out there for companies that are really looking to kind of serve the industry.

 
Whether it’s from a marketing perspective or productivity tools and software, or other things. To be able to come in and access information under terms that make sense, that are equitable to the industry to be able to fulfill on those opportunities.

As an average agent, can I get my hands on some of the Move data to use in my business? And how do I go about that, do you have some sort of data program or can I plug in and use your market or your MLS data or at ListHub or Move?

 
Is that one of your tools or offerings to agents?

So our ListHub business has some tools for firms to be able to access their own listing content within the MLS. And then, be able to put that into, whether that’s marketing websites or software tools. Things like that, for example, if you’re using a virtual tour company of your choice and you’d like to send all your listings to that virtual tour company.

 
So those virtual tours can be created, that’s a service that we would provide.

Most of the companies that the ListHub business serves are these companies that really need a wide breadth of data nationwide. So as an example, Fannie Mae operates first of all a website called homepath.com. But more importantly, all the agents all across the country that are listing and selling Fannie Mae-owned properties have some requirements.

 
 They have to actually put the listings in Fannie Mae’s database, they actually have to use Fannie Mae’s offer management system, it’s a really sophisticated system.

And so, these agents need a method for kind of synchronizing their listing data that happens to be in the MLS with all of Fannie Mae’s back offices.

 So that works, mainly because from Fannie Mae’s perspective, they can have an efficient way to work with all the agents that operate and sell their properties across the country.

So you collaborate with Fannie Mae on that, to extend it to the agents? Well, that’s great. So where would my readers go to find that? Do they call up Fannie Mae on a landline? That would be difficult. How would they get a hold, how do they find out about those kinds of things?

 
 Is there some place on your website where people find that stuff?

Yes, the ListHub website has a pretty comprehensive list of the different parties that we work with from a data perspective. So we call them publishers, and somewhere sort of midway down the homepage, there’s access to a link that will take an agent or a broker to one of those pages.

 
So it’s a pretty broad array.

I think your original question was more about providing agents or providing brokers back with the data directly to them. And we do that, too, through a series of products that we call “connector” products. And the whole essence of a connector product is — if your company, your brokerage, your franchise firm has a database or a back office system,

 or anywhere where you’re trying to collect all your listing content for whatever you need it for, usually to run accounting systems or marketing programs or whatever it might be, then we would be able to provide a connector to be able to feed that data to you.

So we do this today for a number of the Realogy brands,
 Keller Williams, Re/Max Integra in the Northeast, and others across the country. So really, it’s a pretty simple type of technology, but today, it’s very useful for especially the bigger firms that cross multiple MLS markets.

Let’s end with a question: Who owns the data? Who owns the listing data?

Well, I’m not a lawyer…

Yeah, but you’re smart, you know data. What do you think?

Fundamentally, we believe that the brokerage is the owner of the listing data. It sort of is part of what a consumer signs up with a brokerage for. And you look at the listing agreement, it’s pretty clear that the listing brokerage is that rightful owner.

I think that there nuances when you start to refer to a collection of data or an aggregate of data that’s been aggregated by MLS typically, and so that becomes in some respects a different work than the individual listing content itself.

 
And so, I know that there are numerous perspectives around that data in aggregate and then who owns it and what rights they have.

Some new information coming out from the NAR (National Association of Realtors) too about that topic and specifically as it relates to listing content.

Tricky stuff, isn’t it? It feels like this debate’s been going on 20 years and it has been going on 20 years. I always thought one of these things would weave its way into the courts. Like who owns the data? I’m the homeowner, I own the data.

 
 And who knows, you own the data. You have the collection or Zillow has the collection or the MLS has the collection. It’s tough stuff.

Hey, Celeste, keep up the good work. We love having you at Connect, you’re a great speaker. You always make a great contribution — and thanks for doing this interview.

Great, well, thanks for the visit this afternoon and looking forward to the next event.

Email Brad Inman

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