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Speaker 1: I'm Charlie Pellott. Stocks lower for a second day, the
Speaker 1: dollar weekend to an eight month low. Treasuries advanced as
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Speaker 1: James Comey. There's also the ECB policy decision. Along with
Speaker 1: the UK election. SMP down six to twenty nine, down
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Speaker 1: seconds at yield two point one four percent. I'm Charlie Pellot.
Speaker 1: That's a Bloomberg Business Flash. This is your Bloomberg real
Speaker 1: estate report. I'm Denise Pelgueni. Single family home prices in
Speaker 1: the Bay Area are showing signs of weakening. San Francisco,
Speaker 1: which was which has been booming in terms of home prices,
Speaker 1: suddenly when negative in the first quarter. Brashanco Paul Is
Speaker 1: reported for Bloomberg News. He says unaffordability is weighing on
Speaker 1: the housing market after prices surged. You know, San Francisco
Speaker 1: is overpriced. You know, not everybody has a tech salary
Speaker 1: out there, which is I think everyone assumes everybody's working
Speaker 1: in tech and Starrsisco. That's not really true. Paul says.
Speaker 1: That has some people wishing for the worst. I think
Speaker 1: many San Francisco residents are hoping for a crash. You know,
Speaker 1: there are many people who want to get into the
Speaker 1: the market and they feel like they're not going to
Speaker 1: get in anytime soon. But Copaul says not all tech
Speaker 1: related metos are seeing a similar problem. Take Boston, for example,
Speaker 1: where tech jobs are increasing in single family home prices
Speaker 1: gained six percent in April from a year ago, but
Speaker 1: are still seen as relatively affordable. And that's your Bloomberg
Speaker 1: real estate report. I'm Denise Pelgueni. You're listening to Bloomberg
Speaker 1: Markets with Carol Messer and Corey Johnson on Bloomberg Radio.
Speaker 1: Data Fox is the competence Thateo joins right now best
Speaker 1: and john and George Joins has been here in our
Speaker 1: am My sixty studios. But to see you, I haven't
Speaker 1: seen him a couple of years. Maybe yeah, I could
Speaker 1: see um, uh explain what data Fox is and maybe
Speaker 1: how it's changed over the last few years. Definitely, Yeah,
Speaker 1: it's been quite an evolution. Data Fox is a CRM
Speaker 1: orchestration platform, which I'm gonna have to explain what that
Speaker 1: is to you. Where this all came from was myself
Speaker 1: and my co founders. We used to work in banking
Speaker 1: and finance and we came out of that and uh,
Speaker 1: I thought that there ought to be a better way
Speaker 1: to collect all of the world's business information on privately
Speaker 1: held businesses to basically on earth growth trends among those
Speaker 1: amongst those companies to help inform better investment decisions, better
Speaker 1: lending decisions. And that proved to be proved to be there,
Speaker 1: proved indeed to be that neat. But what really was
Speaker 1: interesting was when we found that there's a similar I
Speaker 1: would feel like that's like a donea bread Streets, even
Speaker 1: a Bloomberg for private companies. That's essentially how we how
Speaker 1: we started exactly exactly, and then what we found was
Speaker 1: that in the enterprise landscape, people working in sales, marketing,
Speaker 1: business development, commercial, real estate, anybody, everybody has needs just
Speaker 1: like that, and so the business evolves into what we now.
Speaker 1: We do two things. So part of what we do
Speaker 1: is we collect proprietary intelligence on companies, information about the
Speaker 1: people who work, their growth trends in that business, where
Speaker 1: they're expanding, the products they're launching. And then the second
Speaker 1: pieces orchestrating all of that information with a company's internal
Speaker 1: customer data. Every company has a CRM or some some
Speaker 1: sort of database of their customers, but that data is
Speaker 1: very siloed. It's difficult to actually keep all that information
Speaker 1: up to date, and so we do that for them
Speaker 1: so they can unearth the best opportunities for them to
Speaker 1: go after. Talk to us little bit about clients that
Speaker 1: you're signing up, the growth and revenues, what kind of
Speaker 1: you know, growth and profitability. Talked to us a little
Speaker 1: bit about that, Yeah, definitely. So it's been an exciting year.
Speaker 1: We've grown revenue hundred year over year and that's on
Speaker 1: the back largely of growth selling into large companies. UM.
Speaker 1: An example I love is we work with ups and
Speaker 1: what we've helped them figure out is that one of
Speaker 1: the best signals for their sales team to reach out
Speaker 1: to a business is when that business expands its geographic footprint.
Speaker 1: Kind of obvious, right when they open a new office
Speaker 1: or a new location. Turns out, it's it's very difficult
Speaker 1: for ups actually know when that happens, but we keep
Speaker 1: track of those signals and surface those opportunities. UM. Another
Speaker 1: example I like is there's a a cleaning service in
Speaker 1: UH in New York. Sounds old school, but it's actually
Speaker 1: a tech company called Managed by Q. They provide office
Speaker 1: management services, and similarly, they're interested when businesses are are
Speaker 1: growing quickly. That's when they ought to reach out to
Speaker 1: a business and say, hey, we can really help you
Speaker 1: take control of your office management services. So this isn't
Speaker 1: just like cr leads where you're sort of saying, here's
Speaker 1: the name of the person that's in purchasing this is
Speaker 1: here's a business and an event that's happening that's going
Speaker 1: to trigger a potential sale for you. Exactly. There's a
Speaker 1: fundamental shift that we're hoping to pioneer away from dumb
Speaker 1: leads in a way, it's just you know, buying lists
Speaker 1: of potential leads to call into towards a lot of
Speaker 1: intelligence that actually helps a company figure out what their
Speaker 1: ideal customer looks like and where they can find more folks.
Speaker 1: Just like that lastion, I've got kind of blockchain on
Speaker 1: my brain because we did I did an event here
Speaker 1: at Bloomberg last night and just talking about kind of
Speaker 1: the potential for blockchain, especially in kind of some boring
Speaker 1: on sexy ways, whether it's back office operations, paperwork. Certainly
Speaker 1: for the financial community this makes a lot of sense,
Speaker 1: but also elsewhere. And I'm just curious as you look
Speaker 1: at the unfolding technologies, whether it's artificial intelligence blockchain, does
Speaker 1: it have a role in you do? I think it does?
Speaker 1: That is that is a good question, you know, taking
Speaker 1: a step back, what what fascinates me is that as consumers,
Speaker 1: we all experience a lot of AI in our day
Speaker 1: to day already, right, and I think we know that
Speaker 1: it's it's interests artificial intelligence. When Google Maps tells you, hey,
Speaker 1: if you want to get to your meeting on time,
Speaker 1: you need to hit the road, Now we know that's
Speaker 1: AI and and and it helps us when with a
Speaker 1: quick search and one click, you've ordered a product from
Speaker 1: Amazon and you know it's going to arrive in two days.
Speaker 1: You know there's a lot of smart data stuff going
Speaker 1: on behind the scenes, but in our in our jobs,
Speaker 1: we haven't felt that quite the same way. We're we're
Speaker 1: all still filling out reports and and entering data into systems,
Speaker 1: and we're all wasting a lot of time, it seems
Speaker 1: on some of that manual labor and grunt work. So
Speaker 1: is it safe to say that you guys are exploring
Speaker 1: it or spending R and D or looking into it.
Speaker 1: It's Uh, it's a massive area of investment for us.
Speaker 1: We're we're scaling our engineering team, our data science team. Um.
Speaker 1: I mean, we've seen the effect that it can have.
Speaker 1: Our customers are telling us that just by us coming
Speaker 1: in and helping a business to prioritize which customers or
Speaker 1: future customers to focus on, and it can lead to
Speaker 1: an almost overnight increase in revenues just by focusing your
Speaker 1: sales team and your marketing team on the right opportunity.
Speaker 1: Tolos Business Analytics. But what is it is fundamentally different,
Speaker 1: which which what's happened with AI now and the business
Speaker 1: analytics are old. I think there's just so many companies
Speaker 1: use so many disparate systems now that um, what's needed
Speaker 1: is something that ties that all together. That's why you
Speaker 1: see companies actually hiring their own data science teams. Right,
Speaker 1: you've seen the proliferation of new job titles like biz
Speaker 1: ops and sales ops and marketing ops. Those weren't roles
Speaker 1: that really existed five ten years ago. It's because companies
Speaker 1: have so much internal data to manage, but it's all
Speaker 1: sitting in different silos and it takes a lot of
Speaker 1: work to tie that all all together. What kind of
Speaker 1: standards there are going to we need? Like I do
Speaker 1: you think about all of these about to say something?
Speaker 1: I think whether microphone you might say something, my microphone
Speaker 1: is on, We're gonna in either way. Um, as you
Speaker 1: guys do develop this business, what have you found for
Speaker 1: your own business? And what queues you need about when
Speaker 1: you should be making sales calls? Yeah, it's interesting. We obviously,
Speaker 1: uh we dog food right as people like calling it
Speaker 1: here in the Silicon Valley. We use our own product
Speaker 1: UM and it it's helped a lot. UM. I think
Speaker 1: it's been interesting to see that the artificial intelligence component
Speaker 1: to what we do can be incredibly powerful. And uh,
Speaker 1: you put yourself in a in a young sales reps
Speaker 1: shoes right there, joining a team of people who are
Speaker 1: um you know, have a number of years on them,
Speaker 1: have a lot of experience, and how do you if
Speaker 1: if we can help get that sales rep up to
Speaker 1: speed quickly, help them hit the hit the ground running
Speaker 1: by when they walk in into into work in the morning,
Speaker 1: offering them a um an overview of the key accounts
Speaker 1: that they should be hitting. And two, we're really helping
Speaker 1: them do their do their jobs. But it's also back
Speaker 1: to ridding the world of gruntwork and manual labor. It's
Speaker 1: just so much time that's spent every day doing manual
Speaker 1: data entry. So if we can remove that for people
Speaker 1: to cool stuff past and gentlemen, the company's called Data Fox.
Speaker 1: Check it out. He's a CEO. Thanks coming back for sure.
Speaker 1: Listen to bloomber Markets on Bloomberg Rady on Corey Johnson.
Speaker 1: She is Carol Master. This is Bloomberg