On having a #1 app in the iPad App Store

Posted by shane on March 3, 2012 No comments

Time to brag.

On Monday at work at autoTRADER.ca, we released a new autoTRADER.ca iOS app. This new app is a complete rewrite of our existing app for the iPhone. I had the fun opportunity to push the release button in iTunes connect in front of our office to much applause and excitement. Since then we have been watching all the metrics very closely and so far it has wildly exceeded our expectations.

We partnered with our friends at Auto Trader UK and expanded on their successful iPhone and iPad apps. We setup a new dev team late last year that quickly worked on upgrading and enhancing it to make it our own. Our new app is a universal app, with two distinct UIs optimized for iPhone and iPad. For the iPad, we reached #1 in the Lifestyles category in just over three days and for the iPhone we are currently at #2.

So far, the iPad version has hit #11 across all categories with the iPhone at #54.

Not bad for our first release from our new mobile dev team!

autoTRADER.ca iPad #1 in the Lifestyle category

Google Profiles to Google Plus migration stats

Posted by shane on July 17, 2011 No comments

Last week Google provided some initial numbers for their new social network, Google+. Better yet, Larry Page posted them on Google+ during their quarterly call – so far they’ve had ten million users sign-up to the service. Personally, I really like the service and was excited and invited many fellow Facebook users to join.

Even before Google released the initial numbers, I was curious as to how many users had joined the site. I realized that many users already had a Google Profile before they moved to Google Plus. Would it be possible to know how many users had migrated to Google Plus? I decided to do some poking around for fun.

Digging up Google Profile users

Google publishes sitemap files for Google Profiles but the index file appears to be out of date – the last change being March 16. The URL for the sitemap index can be found at profiles.google.com/robots.txt:

As you can see, Google doesn’t prohibit spiders from crawling user’s profiles. If you dig further into the sitemap index file you’ll find the following:

The sitemap files are numbered and only go to 999. The sitemap specification allows for 50,000 URLs per file thus requiring multiple files for a large website. This appeared odd to me since 50,000 x 999 would only equal 49,950,000 profiles. I dug further into a few example files and found that the number of URLs per file was actually much lower – most only had 2500 URLs per file. This would mean only 2,497,500 profiles – too low to be credible.

Since Google decided to name each sitemap file with an incremental number I decided to dig in further and see how high they went. The result was 7,102 site map files or, in theory, 17,755,000 profiles. Next up – how could I determine how many of them had migrated?

Turning the tables: crawling Google

The first thing I did was write a quick app to download each sitemap file and store the individual profile URLs into a database. I did this as politely as possible including waiting three seconds between requests. The result was 17,717,154 profile URLs. That’s a big number, although perhaps not the complete list of profiles but it’s the best I could come up with.

Next up – how to determine if the user had migrated? What I found was that if the user had migrated to Google Plus then the server would return a redirect to their new Google Plus URL. Also, I found that a certain number of URLs returned a 404 error – presumably for users who had deleted their profile since the sitemap files had last been updated.

I didn’t want to download all 17m+ profiles – for a couple of reasons. First, I didn’t want to pull in all that personal user information for no reason. People have enough trouble with privacy without worrying about some curious geek in Canada. Secondly, given that I decided up front to not hit the services very hard (with my three second waits between requests) that it would take forever to pull in all of the URLs.

The results are in

What I settled on was to simply issue an HTTP HEAD request for the profile URLs and do it only for a credible sample number of users. A HEAD request doesn’t actually pull down the web page you are requesting – only the headers which was good enough for my purpose. I estimated that I would need to pull in 10,000 URLs for a reasonable sample. In addition, I excluded the small number of deleted profiles that my spider found (<200). Here are the results:

Users who migrated to Google Plus: 1,047
Users who still have a Google Profile: 8,953

This shows that, so far, only 10.47% of Google Profile users in my sample have migrated to Google Plus.

What does it mean?

To me, it means that Google has a ready set of users who have profiles that can easily be migrated to Google Plus. I’m sure they have a plan for that. But it also means that only a small number of users have already migrated. Given that users who had profiles seemed to be relatively limited (early adopters?) perhaps that’s worrying. But we won’t really know if this is important until open sign-ups become the norm with the service.

In other words: it was a fun exercise and I’ll leave it to the reader to decide how valuable this data is and what it could mean this early for Google’s new service.

PS: Follow me on Google Plus here.

 

 

 

 

 

 

 

 

 

How to prepare for Facebook’s upcoming location services

Posted by shane on May 10, 2010 No comments

The news today out of Techcrunch is confirming the rumors about a location product/service from Facebook. For site owners perhaps a way to prepare for this can be found in the recent Open Graph documentation that launched with the new “Like” feature. Under “Recommended Meta Data” it includes specifics on embedding location information into your page:

This is useful if your pages is a business profile or about anything else with a real-world location. You can specify location via latitude and longitude, a full address, or both.

Facebook provides an example snippet for this location data as well:

<meta property="og:latitude" content="37.416343"/>
<meta property="og:longitude" content="-122.153013"/>
<meta property="og:street-address" content="1601 S California Ave"/>
<meta property="og:locality" content="Palo Alto"/>
<meta property="og:region" content="CA"/>
<meta property="og:postal-code" content="94304"/>
<meta property="og:country-name" content="USA"/>

For sites that expose real world entities, such as a business’ home page, directories or similar, these tags could be essential for either a Facebook powered location product (like Foursquare) or even just to suggest relevant local pages for a user. Taking a quick look at some sites that have implemented the “Like” feature I have yet to find one that is using these tags but I have not performed an exhaustive search.

Another side of SEO: Optimizing CTR from Google

Posted by shane on May 8, 2010 3 comments
Google Webmaster Tools Queries Report

Google recently updated the Webmaster Tools’ Search Queries report with some new features. If you haven’t used this tool before you’ll immediately be amazed with a key statistic that it exposes: the click through rate of your site’s pages on the Google search results page. Traditionally some people involved with search engine optimization have focused on three main things:

  1. Increasing the amount of content indexed using flat paths, XML Sitemaps, etc.
  2. Using techniques to increase the quality of that content from the spider’s perspective (keyword-rich page titles/urls, alt tags, etc.)
  3. Measuring the traffic that results from these SEO efforts

Looking at this report you start to see the importance of another dimension in optimization: improving what is actually presented to users on the Google site in order to increase clicks to your site. Here is a pretty stark example – it shows that although Google is driving good traffic to the site there is a huge amount of headroom available to improve:

Google Webmaster Tools Queries Report

This graph is showing that the site has a 7.36% overall click through rate. This means that you were successful in getting your content in front of Google users, but for over 92% of them it wasn’t enough to get them to visit. However, this example is based on all Google search types and for all countries. In this example the site’s main content is photos – if we narrow this down to image searches only we get a better result:

Now we see that image conversions are at 10.94% – still a lot of room for growth. Using this as a starting point, you can go further by focusing first on specific countries and then all the way down to specific keywords/URLs and their associated ranking positions. For your site, optimization could mean testing various page title formats, the position of keywords within your content in order to provide a more appealing text snippet on Google’s results page and even how you tag and organize your image content.

This is just a small example of the power of this new tool – every serious site optimizer can immediately benefit by digging into the metrics it provides.

Another empty blog

Posted by shane on April 4, 2010 No comments

See above.