Rest Easy, Factual’s Hotels Data Just Got Even Better

To me, the most fun thing in the world is working with big data. But the second most fun thing? That has to be road trips.

And luckily for me, I have one coming up this Summer that I’m really excited about, too. My girlfriend and I will be driving up to Sea Ranch, CA to attend one of our best friends’ wedding.

But that means we’ll have to find lodging, and that’s not such a fun thing. Figuring out where to stay is stressful and difficult: where are the nearest hotels on our route? Which will work best for us?

Fortunately, we’ve been cooking on a solution to that problem here at Factual: a brand-spanking-new update to our Hotels Extended Attributes set. This update to Hotels is a significant release: Hotels v3 has 145k hotels versus 98k in our previous Hotels release. Additionally, like our Restaurants and Doctors data, it is perfectly synchronized against our core US Places data. Which is all to say this release is great news for App Developers, Hotel Nerds, and Data Enthusiasts alike!

So: I’m looking for a Bed and Breakfast near Carmel, CA. That search is a total cinch with the Factual API:

http://api.v3.factual.com/t/hotels-v3?filters=
  {
    "$and":
    [
      {"locality":{"$eq":"Carmel"}},
      {"type":{"$includes":"B&B"}},
      {"region":{"$eq":"CA"}}
    ]
  }

Note: I’ve omitted URL-encoding for clarity. In practice, your query will look more like this. You can run me in Apigee.

And what if we want to treat ourselves to something fancy before we head out — a five star hotel with a rating above 4.0 in downtown Los Angeles. Well, that’s easy too:

http://api.v3.factual.com/t/hotels-v3?filters=
  {
    "$and":
    [
      {"locality":{"$eq":"los angeles"}},
      {"neighborhood":{"$includes":"Downtown"}},
      {"stars":{"$eq":5}},
      {"rating":{"$gt":4.0}}
    ]
  }

See me run!

Still, what I really want is a hotel with an outdoor pool in Ojai. And it better be pet-friendly, in case Nieco the dog wants in on this trip (this shouldn’t surprise you by now, but that’s easy, too):

http://api.v3.factual.com/t/hotels-v3?filters=
  {
    "$and":
    [
      {"locality":{"$eq":"Ojai"}},
      {"pool":{"$includes":"Outdoor"}},
      {"region":{"$eq":"CA"}},
      {"pets":{"$includes":true}}
    ]
  }

See me swim!

Starting, well, now, you can access the beta Hotels v3 data at /t/hotels-v3. To help you transition, we’re keeping our older hotel data available at /t/hotels-v2 and (during a transitional period) at the existing canonical endpoint of /t/hotels-us for the sake of existing apps. Starting in June, we’ll be pointing the canonical endpoint at the v3 data, so make sure you’ve transitioned to the new schema by then!

Yours in data,
Ben Coppersmith
Software Engineer

On the Road Again: Viewing American Business Travel through a Mobile Lens

We are a truly mobile society. In 2013, Americans traveled nearly 600 billion passenger miles domestically by air alone1. Wherever we go, we take our mobile devices with us. Factual’s Geopulse Audience uses location data from mobile devices to develop insight about users’ behavior. I analyzed data from our partner, Smaato, to examine the behavioral patterns of some of the most mobile people around: business travelers2. The map below shows MSAs that are frequently visited by US business travelers (the larger the circle, the more unique travelers visit that MSA).

map 1

Looking at the map, there are clear hot spots. In fact, 25% of these business travelers originate from 11 “Top Home MSAs3.” To get a more detailed view of the travel patterns for individuals hailing from these areas, click on any of them on the interactive map below4.

Interactive Travel Map
Click on any MSA to see where its business travelers visit

msa map

From this view, it is evident that while many business travelers originate in the same set of MSAs, most of their actual travel is regional. For example, if you click on the Chicago map, you will see that most of the travel activity is scattered throughout the Midwest. To demonstrate this idea more clearly, I found the percent of visits from each of the top 11 home MSAs that were to one of the other top 11 (home MSA excluded), and the percent that were to any other MSAs. On average, just over 80% of visits from travelers from one of the top 11 home MSAs are not to another top 11 MSA.

table 1

Since it is somewhat difficult to think in terms of percent of visits (especially because most business travelers visit more than one destination), I broke down the percent of travelers who originate from each of the top 11 home MSAs and travel to the remaining ones.

table 1

A few trends stand out to me here. The first is that it appears that the percent of business travelers from elsewhere that tend to visit the New York MSA is much larger than that of travelers from New York who tend to visit elsewhere. This is most clearly demonstrated in the patterns of travel between Philadelphia-New York and Washington DC-New York. While 8.7% of business travelers from Philadelphia visit New York, only 3.4% of business travelers from New York visit Philadelphia. From Washington DC, 5.2% visit New York. From New York however, only 1.8% visit Washington DC.

table 1

In comparison, the portion of the Philadelphia business traveler population that visits Washington DC is pretty close to the portion of the DC population that visits Philadelphia (3.3% from Philadelphia visit DC and 3.7% the other way around).

table 1

This type of uneven travel exchange also exists with Los Angeles and San Francisco/Phoenix.

table 1

Some explanation for this lies in the relative size of New York and LA compared to the other 9 MSAs. The New York-Newark-Jersey City MSA was estimated to have nearly 20 million residents in 20135. Los Angeles-Long Beach-Anaheim was estimated at around 13 million, almost 40% more than the next most populous MSA. Being larger MSAs, in some cases they are likely to have larger offices than in other places. In that vein, in 2013 New York City was home to the headquarters of 43 Fortune 500 companies, far more the next city on the list (Houston at 24)6. Some portion of this may also be attributable to their role as major transit hubs, where it is likely that some travelers simply pass through on their way to other places (this trend is also apparent for Atlanta and Chicago, home to some of the busiest airports in the world, albeit on a smaller scale). While none of these factors independently describes the trends, combined they pose a reasonable argument.

When you look through the data what conclusions do you draw? Do you see your own commute, or perhaps that of a friend or colleague? Maybe you and your associates don’t travel for work. Take a minute and instead think about all of the places you do go with your mobile devices, and the story these places tell about you.

-Julie Levine, Marketing Associate

About Smaato
Smaato is the leading global mobile Real-Time Bidding ad exchange (SMX) and Supply Side Platform. Factual’s Geopulse Audience analyzes the location data running through Smaato’s RTB exchange and enhances Smaato’s mobile ad inventory by providing over 40 audience segments (such as “business traveler”) that advertisers can use to deliver more relevant advertising.

Notes:

1. http://www.transtats.bts.gov/Data_Elements.aspx?Data=3

2. Factual’s Geopulse Audience generates anonymous user profiles with geographic, demographic, and behavioral characteristics for mobile device users based on their location histories (provided by our partners, such as Smaato). “Business travelers” are users who display the behaviors typical of business travelers such as frequent short trips that start and end on weekdays.

3. The “Top MSAs” abbreviated in the charts in this post are: Atlanta-Sandy Springs-Marietta, GA; Chicago-Naperville-Joliet, IL-IN-WI; Dallas-Fort Worth-Arlington, TX;
Houston-Sugar Land-Baytown, TX; Los Angeles-Long Beach-Santa Ana, CA; Miami-Fort Lauderdale-Pompano Beach, FL; New York-Northern New Jersey-Long Island, NY-NJ-PA; Philadelphia-Camden-Wilmington, PA-NJ-DE-MD; Phoenix-Mesa-Scottsdale, AZ; San Francisco-Oakland-Fremont, CA; Washington-Arlington-Alexandria, DC-VA-MD-WV.

4. The maps for individual MSAs are all on the same scale. However, the main map is on a much larger scale, as so not of obfuscate the information. On individual MSA maps, the home MSA is ignored.

5. http://en.wikipedia.org/wiki/List_of_Metropolitan_Statistical_Areas

6. http://www.metroatlantachamber.com/docs/staff-bios/fortune-500-1000-headquarters.pdf?sfvrsn=0

Keeping Up with the Times – Quarterly Changes in Factual’s Global Places Data

At Factual, we’re obsessed with data quality. The real world is constantly changing, so we continually update our Global Places data to ensure that it is the most accurate representation of reality possible. That means adding new businesses that pop up, removing ones that have closed, and updating attributes of those that have changed (like a new telephone number or address). There isn’t a places dataset in the world that’s perfect, but we’re working hard to ensure ours is the best.

To give you an idea of how much underlying change there is to the data, we’ve pulled some metrics to summarize the evolution of our US Places data over Q1 2014. We made updates to at least one field in about 9.5 million records1. Furthermore, we deleted 7.1 million records and added 3.2 million.

The chart below breaks down the relative number of updates to each field2.

It’s a challenge to keep up with constantly changing landscape of world places, but rest assured that we’re on top of keeping our data fresh for you.

- Julie Levine, Marketing Associate

Factual’s Global Places data contains over 65 million business listings and points of interest worldwide. To access our Global Places data, either use your existing API key (or get one here) or request a download.

Notes:

1. Fields include: address, address extended, category id, category label, country, email, fax, locality, name, neighborhood, po box, postcode, region, tel, website.

2. Note that some records had updates to more than one field, thus the number of updates is larger than the number of updated records.

Factual Featured Partner: Shopular

We’re always impressed with the amazing things our partners are doing with location data, so we’ve decided to start showing them off. This month, our featured partner is Shopular.

Shopular is a visual, mobile shopping companion that helps millions of users discover deals at nearby stores. Shopular automatically pushes personally relevant deals to their users as soon as they walk into their favorite retailer or mall. Check out their company profile and a short Q&A below.

Company Name: Shopular
Located: Redwood City, CA
Factual Partner Since: 2014
Website: www.shopular.com
Facebook: www.facebook.com/shopular
Twitter: @ShopularApp
App Store Listings: Google Play, iTunes

Q: Why is location data important for Shopular?
A: Location data enables us to best serve our users by showing them the most pertinent nearby deals.

Q: What was the inspiration for Shopular? How did you get started?
A: We were driving by a mall and thought, “wouldn’t it be awesome if we knew about all the deals going on right now?” We looked for an app that did this and couldn’t find one, that’s how Shopular was born.

Q: What’s a fun fact about Shopular that most people don’t know?
A: Our app can detect our users at over 40,000 retail locations and auto prompt them with relevant deals!

Q: What’s a great feature about Shopular that most people aren’t taking advantage of?
A: We share great deals, shopping tips and tricks, run contests, and schmooze with our users on our Facebook page. We’d love to see more folks taking advantage of this channel!

Q: What’s the best part of working at Shopular?
A: Other than our awesome electric sit/stand desk, I’d have to say we’re building a great team. We truly enjoy working alongside some really smart, nice, fun people on a daily basis.

Q: What’s the biggest lesson you’ve learned since starting Shopular?
A: There are never enough hours in the day! There is always more to do here at Shopular but we also recognize that a healthy balance between work, fun, family and friends keeps us sane, productive and creative.

Q: What advice do you have for developers looking to launch their own apps?
A: Always develop with the user in mind. At Shopular we are obsessed with our users. We interact with them daily, respond to every inquiry, and continue to shape our product based on their feedback.

Q: What is your favorite app featuring location today (that isn’t your own)? Why do you love it?
A: With summer around the corner, our entire office seems to be on a workout kick so the apps that help us workout better like RunKeeper and MapMyWalk are some favorites at the moment.

Q: What location-focused app or technology do you wish existed that’s not available today?
A: RFID tags on all inventory would be really cool. This would enable us to tell our users not only which promotions are going on but also be able to alert them of item inventory at their favorite stores.

“The Mobile Revolution and Opportunities for Big Data” – Gil Elbaz at Startup Grind 2014 [Video]

Factual founder and CEO Gil Elbaz spoke at Startup Grind in Mountain View, CA this past February. Listen to his talk about the great possibilities that arise from today’s influx of new data from mobile.