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Testing Google’s Semantic Search [Case Study]

Google’s new Knowledge Graph, also called “semantic search”, takes search beyond keywords optimization. In other words, it tries to understand the intent and meaning behind the search phrase and then provide a more relevant and complete picture to the user.

We recently conducted a few case studies on Semantic Search application with very promising short-term results.

Since the basis of Semantic Search technology is to provide relevant results, we reviewed and analyzed user sentiments across many review websites for particular hotels and their websites.

We then incorporated the top sentiments into the content of the website in a natural and very informative manner.

This was done for two websites: a hotel in New York and a hotel in Maui, both  are full service hotels with great amenities that were fully described on the websites. However, after a deep analysis of the user sentiment, it was discovered that people were also talking about about several other features of the properties in great depth, including:  the lounges, décor, outside ambience, large and inviting windows, etc

We then proceeded to weave the above findings within the content of the website – using similar key phrases that we found in the user sentiments. We also created new pages (where needed) to highlight more features and provide more information.

Short term results:

After two weeks of semantic search alignment, the New York hotel’s website revenue increased by 77% due to the further optimized, relevant pages. People coming to those pages

  • Spent more time on the site,
  • Viewed more pages,
  • And significant decrease in bounce rate.

For the Maui hotel’s website, we saw a similar increase in metrics. The traffic, page views and revenue increased by over 50% in the short period of two weeks.

Conclusion:

The key take away is Semantic Search definitely work! By making the content more relevant, we found that more people were coming to the website – driving enhanced website performance in search results. It’s evident that with the new Knowledge Graph, Google is attempting to correlate relationships between entities, just like an actual graph, and provide better results.

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Contributed by Manisha Kumar, Director of Strategies

 


4 Responses to “ Testing Google’s Semantic Search [Case Study] ”

Hi
thank you for sharing this experiment, I think in Italy content editor are still using word based on search and not sentiment or user generated content.
Do you think I can translate and post on a hotel travel web site to share your tip?

regards

damiano usala

Hi Damiano – Glad you found this useful. Please feel free to translate and share – we just ask that you list Milestone as the original source, and provide a link back to our article.

Thanks,
Mike Supple, Milestone Internet Marketing

The article is about key word optimization and not semantic search. What happened according to the article. They investigate how people talk between each other about hotels, collected their words and expressions, incorporated naturally their vocabulary into the web-site. The traffic increased because people make search queries in the language they talk between themselfs. Also people see on the site description in the language they are used to. This is good business solution and perfectly right but has nothing to do with semantic search.
The nature of semantic search is different, you can look at semanticsearchart.com for understanding concept.

Thanks for your comment. A good part of the concept behind semantic search is focusing on contextual meanings – which is what the article is based on. By layering in more contextual phrases into the content, it augmented the relevance factor and helped with the performance of the website. It can be done in several ways – one of the best ways for us was to incorporate user sentiment into the content – which helped add a more semantic relationship.

-Manisha Kumar


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