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Utilizing Freebase for Keyword Research, Keyword research has always been vital task for digital marketers, yet our research process hasn’t really changed in the past few years. We identify new terms thorough keyword research using basic keyword tools to help sites rank well not just for main terms but also for long tail queries. The biggest problem with keyword research is that it is a repetitive, lengthy process. This got me thinking- could we speed up the process without sacrificing quality?

Cue Freebase, a community-curated database of almost everything.

Snapped up in a deal by Google back in 2010, the catalog currently plays a major part in helping power Google’s Knowledge Graph. It also offers fantastic keyword mining opportunity for marketers. Using Freebase to find new keywords is a quick way to get access to lists of information that are constantly updated.

As Freebase’s archives become more integrated into the fabric of Google’s algorithm, it makes sense for digital marketers and SEOs to mine it for keywords.  Not only for the volume of data, but also because of potential of finding new prevalent searches.

How to run queries on Freebase

There are a few ways to access data on Freebase, depending on your technical level. The first and most simple is to search for the parent term and copy/paste the information you need.

For example, if you are looking for a list of all the local governmental areas of Wales, you navigate to the Wales page and grab the list provided.

For those of you that are a little more adventurous, try using the Freebase Query Editor. The tool allows you to input basic MQL (Metaweb Query Language) queries and return formatted data ready to be added to a keyword list.

To put it into context, the above “Wales” example is attained through a simple query:

[{   "name": "Wales",   "/location/country/first_level_divisions": [{     "name": null,     }]   }]

The Query Editor is capable of complicated queries allowing you to gather hundreds of items in one go, perfect for creating variables for keyword lists.

We can also use more advanced queries to capture multiple variations and add filters to our data. Below is an example of a request for all Renault cars and their Freebase ID (for further information), as well as the models that came before and after to give us an extended look at which keywords might be searched for when looking for new versions of the vehicle.

[{   "/automotive/make/parent_company": [{     "name": "Renault"   }],   "/automotive/make/model_s": [{     "name": null,     "id":   null,     "/automotive/model/predecessor": [{       "name": null     }],     "/automotive/model/successor": [{       "name": null     }]   }] }]  

The MQL language is really simple to understand and you can get your head around it in a few hours. Considering the time you will save searching for keywords, it is well worth the investment. For more information on MQL, there is a great video by Jamie Taylor which will give you some idea of how it works and what can be done.

As you can see the Freebase database can be extremely powerful for finding new terms, but will you bring it into your keyword research process?