Knowledge Series: What is Google Trends Data Mining Using R Programming?

October 26, 2017
What is Google Trends Data Mining Using R Programing?

Mostly misunderstood as a keyword research tool, Google trends are much more than that. Google trends were not merely built to give a match to monthly keyword volume, Google trends were built with an advanced level of sophistication, to generate insights which are visual and dynamic in nature. Google trends are capable of presenting an entire life cycle of a keyword phrase, past, present and some kind of future as we may predict. So, what are Google trends exactly? It is essentially a service that brings together the relative frequency of Google searches over a period of time.

Google trends tool opens the possibilities to obtain incredible amounts of information from one of the world’s largest search engines. The google trends tool is derived from Google search data. ‘Trends’ to simply put it is numeric and also a historic representation of the search data. This feature differentiates google trends from google keyword planner, as in google trends, an index is created to represent the ‘trending’ instead of the definite volume. Therefore, the data presented by google trends can actually depict actionable insights which the keyword planner function cannot present.

Google trends thus adapt a multi-dimensional approach of comparing queries against required options. It is a fairly simple tool to use. To start one needs to put a search term in the query box, and then you can proceed to select from the various filtering options. Like…

  • Region – search definition can be Geo-specific
  • Time Frame – you can select a variety of predefined time frames. Like ‘last seven days’, ‘one month, etc…, you can go back in time up to the year 2004.
  • Categories – one can select and limit the terms and focus only on a certain category. This way you will be able to study specific trends with the possibility of discovering new searches or themes.
  • Engines– through this option you can choose between news, youtube, shopping search, thus offering increased flexibility and further allowing to choose focus on the right to intend.

All the results are presented as separate graphs,
(a) Interest over time, which offers a historical trending,
(b) Regional Behavior, offering on how localized behavior was during that time.

One can use ‘R’ to extract the data from google trends using ‘gtrends’. Using Google trends one can perform the simultaneous search on five terms, more than five terms are not possible, also it does not provide data in API format. These issues can be dodged using R especially by using ‘gtrends’ package. There are various functions in R that can be used to build automated solutions, which can be further applied to build end to end solutions.

Google trends thus become a powerful tool especially for a data scientist or even a marketing analyst’s inventory.
For the marketing department of any company or brand, google trends are like a goldmine of information that could perhaps supersede findings from focus groups, on other metrics like brand health by the region, or brand topics of discussion over a period of time. Once you understand what the consumers for a particular brand are searching for, you can start building your messages around those areas of opportunity and interest.

As with any data-driven insights, the flexibility and the opportunity that Google trend offers with tools like gtrendsR, the possibilities are fathomless. Learning the applicability of data mining using R on google trends will surely be very valuable in the long run.

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