March 25th, 2009

Lifestyle Listings Engine Web Service - New Property Search Version 0.9 Delivered

By Megan Murphy, Marketing Manager

 Onboard Informatics launched the second version of Lifestyle Listings Engine - Version 0.9 today.

Lifestyle Listings Engine, the first ever enterprise-class property search based on consumer lifestyle, was first announced earlier this year at Inman News Real Estate Connect in New York.  Since then we have been working diligently to launch the  Listings Web Service enabling consumers to search for a home based on school system ratings, amenities, neighborhoods, commute time, and more all at the same time.

The first Listings Web Service delivery in mid February, Version 0.8, focused on two primary search mechanisms - geographic and parametric. Scott Petronis, our Sr. Dri. Product Management, goes into the specific details of Geographic Search, and Lookup capabilities in the Listings Web Service, in his previous post, Lifestyle Listings Engine Web Serivce - New Property Search Version 0.8 Delivered.

In this release, Version 0.9,  there are three new keycapabilities :

1) Search based on school performance:

One of the most significant search criteria for one of the largest home buyer segments is school performance. To this end, we’re enabling search based on proximity to GreatSchools rated schools of a specific value. For example, “I want to find listings that have 3+ beds and 2+ baths for no more than $500,000 that are near a highly rated school.”

2) Search based on distance to amenities:

The next set of crucial criterion are the local amenities such as parks, restaurants, supermarkets and hospitals. We’re enabling search based on a pretty long list of amenities so a user can ask for “Homes within 5 miles of a golf course,” for example.

3) “Get content”:

Once a search is conducted, the next logical step is for the searcher to want to know more. So we’re introducing new calls to pull back specific content based on a specific listing or the geographic container the listing falls within. The first such call allows a developer to pull back all the amenity details associated to a listing so they may present this, for example, on a listing detail page.

Scott goes into much greater detail regarding Version 0.9 in his post from last week.

A few cool new things we’re just completing put the “lifestyle” in lifestyle search. And believe me, this is just the start. To start we’ve focused on exposing some key new search criteria and also added a new content retrieval concept into the Listings Web Service. The concept is simple: there are criteria people will use to “drive” their search and then there’s additional content one wishes to see to help better educate herself/himself on the area surrounding the listing. So we’re exposing easily understood and highly relevant criteria in the search web service. Then we’re exposing more detailed content that may be pulled for presentation on the listing detail page.

What’s Next?

Lifestyle Listings Version 0.9.1 & Version 0.10 — Currently in development and testing. Targeted for release early/mid-April

• Get School District Content:  This will allow the developer to pull back all the school district content associated with a specific listing. Using this, the developer can fill out additional content pages to go along with the listing details.
• Search by commute time / distance: This will allow a user to input a starting address, such as their work address, and a desired time (i.e., 45 minutes) or distance (i.e., 30 miles). The search will then determine the listings that fall within the drivable area. We’re already looking at ways to get public transit as well as to determine neighborhoods and other geos that fall within the commute time / distance.

Lifestyle Listings Engine  Version 0.11 &  Version 0.12 — Currently in planning and design.

• Lead profiling: We’ll be capturing the various search criteria used in order to enable presentation of search preferences for lead forms, analytics reports, CRM applications or other uses.
• Search by community demographics: We’re working on a set of key demographics including age focus, socioeconomic status and household status.
• Criteria weighting and ranking: Providing the ability to weight the importance of individual criteria in each search to ensure the most appropriate results are returned.
• Additional Get Content calls: Enabling the retrieval of additional content to help provide greater details and insight into the community surrounding a listing.

Lifestyle Listinges Engine Software Development Kit — Currently in planning and design.

• We’ll be providing a set of UI widgets, helper code and documentation to enable developers to more quickly integrate our search into their sites and to do so with much more confidence than writing code from scratch. Our goal is to help developers get these capabilities up and running in days or weeks vs. months.

Please contact our sales support team at 646.747.4273 or info@onboardinformatics.com with any enquires regarding Lifestyle Listings Engine.

Also, don’t forget to subscribe to Onblog to get the latest news and deliveries regarding Lifestyle Listings Engine and Onboard’s other products.

Tags: amenities, data, home sale records, IDX, inman, Inman Connect, Lifestyle, Lifestyle Listings Engine, lifestyle search, listings, LLE, MLS, neighborhoods, Onboard Informatics, Products, property search, Real Estate, schools, SEO.

February 9th, 2009

Weekly Data Updates & Add-ins: 2/2/09 - 2/6/09

By John Paul Murphy, Content Services Manager

At Onboard Informatics it is our goal to provide the most comprehensive and up to date data possible.  Please see below the latest data records regarding neighborhood coverage and sales transactions.

• Total number of neighborhoods that Onboard Informatics has coverage:   49,932
• Total number of places in the Onboard Universe (geo type = PL):  25,150
• New Weekly Sales Transaction Records:  192,522
• Total Number of Sales Transactions:  40,545,080 

For more information on all our data categories call 212-488-1550. 

Tags: data, data update, Home Sales Transactions, neighborhoods, Onboard Informatics, Sales Transaction records.

December 3rd, 2008

On Hyperlocal Targeting

By Robert Hahn - VP, Marketing

If you are interested in real estate and marketing, then you need to check out Real Estate Relativity. The author is an expert in matters of database marketing, social media, and real estate — and it shows.

In one of his recent posts, Mr. Relativity (I’ll let him reveal his identity himself… but he knows of which he speaks) wrote about hyper-targeting of enhanced listings:

Trulia partnered with 1020 Placecast to provide targeted ad services.

Once users input a location they want to learn more about on Trulia, Placecast will access that data and apply it as a key component along with common demographic data points like psychographic information to provide more targeted ads.

This process makes sense especially at the zip code level (see previous posts on zip code optimization) because demo/psychographic differences exist between zip codes–even contiguous zip codes. Accordingly, if I’m looking in a zip code that trends more affluent, Trulia can now serve ads that appeal to an affluent consumer (Jaguar advertisement). Alternatively, if I’m searching in a zip code that trends more middle of the road, Trulia can now serve an ad that appeals to a bargain shopper (Toyota Corolla advertisement).

I think this is right on, but I feel it would be appropriate here for us to once again preach the gospel of the Human Touch.  The only gloss I would put on what Relativity wrote is to point out that human beings typically do not think in terms of zip codes.  They think terms of neighborhoods, or towns, or real places.

Fact is, demo/psychographic differences exist intra-zip code as well, depending on whether there are multiple neighborhoods within a single zip code.  But beyond that, when thinking about targeting ads, the geographic limitation imposed by arbitrary zip codes is pretty significant.  Far more effective, we feel, to use neighborhood boundaries (which are themselves psychological in nature) or real places, such as towns.

But the real insight comes from Relativity’s next thought:

For real estate, I’d like to see a twist on this process: somehow also deduce from where a consumer searches so as to better deploy advertising resources with respect to select properties. For instance, let’s assume you’re a firm situated in a Utah ski resort community, and that you know based on previous dealings with out-of-market buyers that your to primary “feeder” markets are Chicago and Orlando, and that these primary markets are generally interested in purchasing luxury-oriented rental income properties.

It’d be a great service to be able choose which of your top properties to “enhance” that exist in a specific zip code and display the “enhanced” versions of these properties only when a consumer from either Chicago or Orlando conducts a search in the targeted zip code. Employing a scheme like this, one makes an ad buy based on a “known” marketing attribute (i.e., based on personal experience) along with hyper-targeting, which should translate into higher quality clicks to the “enhanced” properties and, thus, increase the potential ROI on those ad buys.  (Emphasis added)

I have two thoughts about this.

First, consumer searches in real estate today cannot deduce anything at all.  The reason is that today’s search — no matter how slick and how sophisticated — is still property-centric.  It’s all about the property, its location, its features, and its price.  The standard “zip, bed/bath, price” model is how a computer database stores information and processes queries.  It has no relationship to how an actual human being goes about thinking through a search.

What is required then is a new model of search: a human-centric search that starts with the person doing the search, rather than the properties that are the targets of that search.  We will have more to say on this topic.

If you start out with the focus on the person doing the search, then all of the requirements/factors above fall into place rather quickly.  Rather than knowing from “previous experience” that the feeder markets of out-of-market buyers are Chicago and Orlando, the firm would know from the actual search trail that this particular consumer is hailing from Chicago.  The firm would also know that this particular consumer’s search parameters dealt with skiing, horseback riding, and snowmobiling, because the search itself begins with a concern for the consumer’s preferences, rather than the “zip, bed/bath, price” paradigm.

Second, the process is inherently iterative.  Because human beings do not search with “requirement X, Y, and Z” in mind.  They start broad, then narrow down.  They might start off thinking, “You know, I really want a chalet right on the mountain.”  Then once they see the prices of such chalets, quickly change their minds to, “Nevermind — within 15 minutes driving distance is good enough.”  Once confronted with a large range of choices, they could then refine their thinking even more: “It’d be great though to have a fireplace….”  And so on.

The good news is that there is technology already available that does exactly this sort of iterative profiling of consumers.  One such company is X+1, whose product, Site+1, is precisely this iterative consumer profiling mixed with psychographic data.  [Full Disclosure: X+1 is not a client, not a partner, hasn't paid us, or me, and we have no business relationship with them whatsoever.  But I do have a friend who works there, which is how I know about them.]  While this technology is relatively expensive, and is currently used mostly by Fortune 500 companies, we know that it is possible.

What that means, then, is that hyperlocal targeting is not a one-and-done tactic, but a continuous, iterative thing for a website that is built to do it.  Profile your $15m condo, together with two others that are more modestly priced.  Depending on the consumer’s next move, you can showcase a whole new set of enhanced listings.  Then based on the next input, showcase something else to boot.

This level of control is possible today.  It remains for someone in real estate to put it all together.

I love that Real Estate Relativity is discussing issues like this, because it really opens the door to what consumer benefits — as well as increasing ROI — is possible leveraging the power of data and technology.  My view is that the more the real estate web focuses on becoming more and more humanized, the better it will be for consumers and service providers alike.

-rsh

Tags: hyperlocal, neighborhoods, psychographics, X+1.

October 1st, 2008

Congrats to Toledo Blade!

By Colleen McKeating, Product Manager

Onboard Informatics would like to congratulate Toledo Blade on being the first to implement the newest version of Neighborhood Navigator, the most powerful local neighborhood search tool on the market, maps and charts to their website, taledoblade.com.

Toledo Blade, a daily newspaper covering general news in Toledo, Ohio, was first published in 1835 and is now one of the top 100 USA newspapers. With so much growth they realized they needed to ramp up their real estate section and reached out to us for advice on how to gain the neighborhood and community expertise they needed.

We had just launched our latest version of Neighborhood Navigator, with a new user interface, maps and charts; they needed community data for their area…the timing was perfect. They were up and running in less than a week with community and school information, nearby establishments and local amenities . They also took advantage of our customization options, allowing them to provide the information they needed without losing any brand recognition. They used their own header, icons and fonts colors, providing a consistent look and feel throughout the site.

Part of Onboard’s team, Mike Demetriou, Relationship Specialist; Tahisha George, Product Support Specialist; Colleen McKeading, Product Manager, worked closely with Toledo Blade in successfully getting this up and running as fast and hassle free as possible.

Tags: community data, data, navigator, neighborhoods, toledo blade.

September 26th, 2008

The New Neighborhood Navigator!

By Colleen McKeating, Product Manager

For existing clients the switch will be seamless. The only difference is a slight change to the URL. Our Relationship Management and Product Support teams are already working to provide the pre-customized sites for those clients who previously customized their sites. Onboard is looking at the colors and images that clients previously used and are transferring these to the new version. The new user interface has a much cleaner look and feel, and as a result all those who previously provided Onboard with a Style Sheet will find that their new site will be that much sharper. Every client will be able to view these changes before actually putting the new URL into production. We will also send out the customizable images and the CSS template in case there are any additional changes that the client wants to make.

In order to take advantage of the new changes clients should look to make the switch as soon as possible. Our Product Support team will work with them on any issues that may arise.

At Onboard, we are very excited about this recent launch. The whole team here has worked very hard to ensure a successful product launch. This is a first step of many more improvements to come! Please stay tuned for more Neighborhood Navigator updates and tips! 

Check out a screenshot of the new design!

Tags: community_data, hosted_solution, navigator, neighborhoods, new_products, onboard, onboard_Products, Recent_home_sales, updates.

September 10th, 2008

Data Updates & Add-ins: Week of 9/1/08

By John Paul Murphy, Content Services Manager

Current Neighborhood & Markets Coverage:

• New Neighborhoods: 8,784
• Markets Added: 219
• Neighborhoods Added to New Markets: 4,716
• Neighborhoods Added to Existing Markets: 4,068
• Total Neighborhoods: 45,218
• Total Markets: 1,435

Top 5 New Neighborhoods Markets:

• Steamboat Springs, CO: 382 New Neighborhoods
• Crested Butte, CO: 297 New Neighborhoods
• Durango, CO: 208 New Neighborhoods
• Haines City, FL: 194 New Neighborhoods
• Auburndale, FL: 158 New Neighborhoods

Current Schools Data:

• 404 Schools were added to the profile package
• 1,325 reviews added for 325 new schools
• 6,014 new reviews added in August (may include some overlap with the aforementioned 1,325 new school reviews)
• Current Total Number of Schools: 131759
• Current Total Number of School Reviews: 369084

Tags: data, neighborhoods, Onboard Informatics, school information, update.

August 14th, 2008

Picture This

By Ira Monko, Product Manager

Imagine being able to walk the streets of a neighborhood from virtually anywhere. You get to see what it looks like. You see who lives, works, and plays there. Yet you haven’t even taken a step in its direction. You are viewing all of this from 1,000 miles away.

The ultimate experience may still be science fiction but photo blogging gets us closer than ever before. Photo blogging simply combines two things; blogging and photos. Blogging being the ability to quickly post content to the internet. And photos being the content most often posted.

Applied to the real estate market this could be especially useful in conveying the look and feel of an area to prospective home buyers. A scenario I could envision would be a website, or section of your website, devoted to a geographic area (neighborhood, subdivision, community). A group of trusted users, agents and home sellers, would be able to quickly and easily add photos, videos, and other content about that area.

ShutterFly launched, Share Sites, which makes this possible.

Although it suffers from some of the issues with free services (lack of customization, external links) it does provide a model for allowing mainstream users an easy way to

share content. The New York Times also points out that they intend to expand their service offering by enabling users to upload video and embed the content into any blog or social network.

To illustrate my point, take a 20 minute walk around our office at 90 Broad St.

Tags: neighborhoods, photo blogging.