Google search is essentially the largest real-time, unbiased consumer panel that has ever existed, with “over 3.5 billion searches per day and 1.2 trillion searches per year worldwide.”
Oftentimes, when a brand is running a large media campaign, consumers will turn to search engines to learn more about the products they are exposed to on other media channels, such as television. A marketer can gain valuable insights by analyzing the correlations between media campaigns and the fluctuations in relevant search activity.
This article walks you through several examples of how to produce these types of analyses and the value they provide.
Companies such as Millward Brown and Nielsen tend to measure TV impact by GRPs (gross rating points = reach x frequency). GRPs are typically modeled by week and location/DMA (designated market area). Modeling often requires two or three years of data to ensure that seasonality and other statistical noise can be accounted for.
Because TV remains the largest area of investment, we are commonly asked by brands to associate search fluctuations with GRPs and consumer interest. To do this, we look at several things, including the general increase of interest and the incremental traffic absorbed by the brand’s digital properties.
First, let’s look at what it takes to get interest by week. Currently, Google only publicly provides monthly search volumes, not weekly. But with a little ingenuity, you can get free, fairly accurate weekly search volumes by using Google Keyword Planner and Google Trends. If you are completely new to Keyword Planner tool, visit here for a good summary of the basics.
Personally, I do all of this through Google AdWords & Trends API in KNIME, but it can be done manually with the other tools, as follows.
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