Concert Hotels is a website dedicated to finding places to stay near music and sporting venues. With thousands of hotels listed, organic search traffic is a key part of their business.
Distilled has worked with Concert Hotels for a number of years, and they were one of the first companies to run tests on our ODN platform. The Distilled team designed and built a test to run over their roughly 20,000 location category pages that list hotels near specific locations.
Following keyword research focused on venue search volume and user intent, we changed the focus from "<<location>> hotels" to "hotels near <<location>>" on half of the category pages, while keeping the other half back to provide control data.
Specifically, we changed the titles of these pages:
|Title Before (Control)|
|<<Location>> Hotels, <<state>> | ConcertHotels.com|
|Title After (Variant)|
|Hotels near <<Location>>, <<sub-location>>, <<state>> | ConcertHotels.com|
We also change the H1 tags:
|H1 Before (Control)|
|H1 After (Variant)|
|Hotels near <<Location>>|
Our research found that the latter construction of search query had over double the searches per month
|Search Query Structure||Overall Search Volume|
Hotels near <
And we found that users often refined their search by including either the city, state or both within their search query, hence our focus on improving the long tail opportunity for these pages.
For years, my on page SEO strategy was essentially trial and error. I made changes to my website based on knowledge and ideas picked up from online resources such as Moz.com and Distilled, so there was always some method behind the decisions. However, there was no easy way for me to determine whether those changes specifically helped the growth of my website. DistilledODN has allowed for a more data-driven approach to my on page SEO strategy. Mike Kelly
Founder, Concert Hotels
The following graph shows the total additional organic search sessions to the pages we changed that came as a result of this improvement.
Based on our Bayesian statistical model, that uses the traffic to the unchanged control group pages to capture the uplift caused by our specific change, after a couple of weeks, we were 95% confident that this change was causing a sustained uplift. You can see this in the chart at the point where the pale blue area - which represents the confidence interval - passes the zero axis.
Following the successful completion of the test, we rolled the change out to 100% of pages to capture the uplift while the Concert Hotels team updated the site. If you're interested in more detail, you can check out the blog post we wrote at the time.