Last week, Google, Bing and Yahoo announced collaboration on a single standard for structured markup. Yes, I’m talking about Schema.org and utilizing Microdata for “Rich Snippets.”

Since then, many sites have posted about why Schema.org might be good, bad or otherwise for site owners; some balanced, some not. Personally, I think structured markup and machine-readable information is always good to have on your site, regardless of potential SEO benefits. I’ve had a love for structured markup (in the form of Microformats) since I first laid eyes on hCard several years ago. I could have written a whole post about why I think Schema.org is good for SEO, but instead I decided to implement it on a site of mine.

I co-own a book review site, and I’ve been meaning to implement the microformat hReview on it for over a year. I never got around to it because it involved creating custom post types in WordPress, and I knew that would be a time-consuming affair. I finally bit the bullet and sat down to do that on Sunday. That part took about 5 hours of my day.

Then, I started implementing microdata. From never having implemented microdata before in my life (like I said, I was a Microformats fan), I found out what markup I needed, added it to my template, and tested it in about an hour.

I started out by making a list of all of the attributes about books that we use in a review. Then I determined which item type (itemtype) it would be associated with – for my purposes, Book, Review , and Rating were all I needed. Then, I noted which item property (itemprop) I would use. Then it was simply a matter of adding the appropriate markup to my existing HTML and PHP.

There were a couple of attributes that were confusing – for example, do I use description or reviewBody from Review? Do I use aggregateRating from Review, or reviewRating from Rating? The examples on Schema.org were helpful to a degree, but I still felt like I was guessing at proper use. Time will tell if I’ve used the appropriate item properties. I also wasn’t sure if I had to upgrade the doctype to HTML5 or not, but I chose not to as only modern browsers support it and some of my users have older browsers.

To test that you’ve implemented microdata correctly, you can use Google’s Rich Snippet testing tool. However, it was throwing errors for things it should not have had a problem with (I suspect it was getting a lot of use over the last week as people rushed to add microdata to their sites), so I looked for an alternative. I found this Microdata Tool using jQuery to test that I had applied the code correctly; unfortunately it can’t show how Google might display this data in the SERPs.

One of the arguments the naysayers against Schema.org are using is that it will take too long/too many resources to implement, but clearly that is not the case. I’m going to continue to tinker with microdata and my review template, and monitor my organic search rankings and conversion rates to determine just what the effect of adding it will be over time.

When Google released their new Local search results format in October, 2010, SEOs quickly determined that the number of reviews and overall rating associated with a business were ranking factors. They also predicted that these would be quickly be gamed.

It was an easy ranking factor to launch the new integrated SERPs with, as they already had piles and piles of review data from their own properties as well as sites they’d partnered with. But Google’s algorithms are not static, and it couldn’t be too long before the Local algorithm included other ranking factors.

Now, it looks like they might be starting to think about other options. A paper submitted to the upcoming Very Large Data Bases conference, on Hyper-Local, Directions-Based ranking and written by two Googlers along with two other researchers, proposes a method for using direction queries…say, of the sort a user might enter into Google Maps…to determine interest in particular places that could possibly be used for ranking such places.

Greg Linden has a post summarizing the key points of the paper, and wrote, “the core idea is that, when people ask for directions from A to B, it shows that people are interested in B, especially if they happen to be at or near A.”

And of course, who happens to have piles and piles of data regarding direction queries?

I’m sure there are some people out there already thinking about how they could game this. But this got me thinking: what other sources of hyper-local, location-based, user-generated data is out here that could supplement direction queries?

GPS Trails on Android Devices

I’ve always believed that Google developed Android simply as a massive data mining engine. After the recent debacle where it was discovered Apple devices store GPS data, it was also uncovered that Android does too, which is not entirely unsurprising.

*removes tinfoil hat*

However, the paper addresses the main issue with GPS trails, in that “GPS datasets typically contain many positions for a few users,” and Greg points out that “just being in a location doesn’t make it clear that it is your endpoint or that you want to be there.”

All good points.

Location-Based Check-In Services

So what applications do people use when they want to be somewhere and want to tell people about it? Well, with increasing frequency, people are checking into location-based games like Foursquare, Gowalla, and Facebook Places.

Sure, this data would be heavily skewed to early adopters, owners of mobile devices, and geeks, but it could be another indicator of interest in places.

Twitter

Google already partners with Twitter to use their data. The Twitter API includes a portion for GPS coordinates, and many mobile Twitter apps and third-party supporting sites like Twitpic have a setting that allow users to embed their coordinates in their tweets. Rather convenient, considering the number of people who tweet frequently from doctor’s waiting rooms, restaurants, grocery store line-ups, etc.

Of course, we’re not there yet. This paper is to be presented at VLDB in August, so it’s not even being implemented by Google yet.  And by the time something like this is anywhere nearing integration into the Local algorithm, Foursquare and the like may not even exist. But with more users adopting mobile devices faster than desktop computers, and everyone under the sun trying to develop a location-based app, the opportunity is certainly there.

Photo: 23am.com/Flickr

After the latest local changes Google made to the search results we had a lot of updates to do with regards to how we process the local results. Those updates are now live and have been for a few days. Here’s an overview on how we parse each kind of local search result we’re getting served. We’re currently getting served three different types: the old style, the newest integrated style, and another style similar to the old style only the text that preceeds that pack starts with “Places for…”.

We’ve had a few questions on exactly how we plan on calculating rankings with these new results and why. Basically we try and make the “rank” reflect where that site would actually be located within a traditional search results page.

Click on each image to see the full serp.

Integrated Local Results

Places for Results

Fully Integrated Results

Here at AuthorityLabs, we really like to play with data. Whether it’s checking website rankings or tracking indexed pages, we’re crunching a ton of data all day, every day. Recently, we’ve started playing with some features in Google Spreadsheets that seem to have an almost endless possibility for collecting and manipulating data. Using the functions for external data, we’ve put together a list with a few ways to help speed up common tasks related to SEO. While it’s not a new feature, I think it’s probably underused.

The ideas below make use of XPath. If you’re not familiar with XPath, here’s a good resource to pick up a basic understanding and here’s a Firefox plugin to help finding the XPath for elements in a document.

Check SERPs

While we think we have the best tool around for checking search results, Google Spreadsheets can provide a quick and free way to see how a site is performing. For the results below, we’ve entered the following into the first cell of the spreadsheet:

=importXML("http://www.google.com/search?q=digital+cameras&hl=en&gl=US", "//a[@class='l']/@href")

Let’s break that down a little bit.

=importXML() – This is the function that Google uses to import the document at the specified URL.

http://www.google.com/search?q=digital+cameras&hl=en&gl=US – This is the URL of the search results page for [digital cameras] at US based (gl=US) English (hl=en) results at Google.com. You can add &num=100 to the end of this URL to expand the results to 100. Note that these results may include more than just the standard organic listings, so keep that in mind when figuring out how a site is performing.

//a[@class='l']/@href – This is the XPath query that is used to parse out the data we are looking for. In this case, we are looking for the href attribute of links with a css class of l.

Compare International SERPs

Looking for an easy way to compare site performance in different countries? If you’re looking for English results, just change gl=US in the above example to whichever two character country code Google is using. For the example below, we have used the following to get UK and Australia results -

=importXML("http://www.google.com/search?q=digital+cameras&hl=en&gl=UK", "//a[@class='l']/@href")

=importXML("http://www.google.com/search?q=digital+cameras&hl=en&gl=AU", "//a[@class='l']/@href")

Analyze a Page’s Links

Sometimes a situation comes up where you really need to look at a list of all links on a page and what anchor text those links are using. Google spreadsheets makes it easy to get these links into a spreadsheet for your searching and sorting pleasure. Drop the following ImportXML() functions into cells that are side by side in your spreadsheet and let Google do the work for you.

=importXML("http://www.yourpageurl.com", "//a")

=importXML("http://www.yourpageurl.com", "//a/@href")

The following is an example of the end result. Can anyone clue me in on why SEOmoz recommends using absolute links but uses relative links all over the place?

Other Ideas

Reputation Monitoring and Reporting – Get creative with Twitter’s advanced search, del.icio.us’ popular lists and tags, and Google’s blog search to document and report on a client’s reputation or recent mentions.

Importing Data From a Feed – The ImportFeed() function lets you quickly populate a spreadsheet with data from an rss or similar feed. This method doesn’t even need any XPath knowledge to make it work. The downside is that it appears to be limited to importing 20 feed items at a time and sometimes doesn’t work as expected.

Keep in mind that if you want to take the most advantage of the data you’re grabbing, there is a good chance you will need to export the spreadsheets for use in Excel or as a CSV. It appears that there isn’t an easy way to sort and manipulate the data that results from these functions due to the way that everything is referenced in the cells of the spreadsheets. I’d be interested in hearing how others are using these features. Maybe there are easier ways of doing some of the above items, but paired with a little creativity, someone who has no idea about writing code can create their own system for scraping and analyzing data.

Ha … Google’s changed their logo to a barcode! I fired up the Barcode Scanner app on my G1 to decrypt it and guess what, it’s Google in barcode.

I’d been making some updates to the blog and loaded up Google (because it’s my default page). It’s hard to miss, but there Turns out the original barcode patent was filed October 7th, 1952 by Wallace Flint.