Google, Researchers Seek To Develop Brand Search As A Metric

Could Google Trend Data replace brand tracking studies? New research from Drexel University, Brigham Young University, and Google suggest the data could at least supplement traditional methods to lower costs and develop brand search as a metric.

Researchers set out to analyze the relationship between brand attitudes and search engine queries. They wanted to determine whether customers who hold positive attitudes toward a brand are more likely to search for the brand, and if so, which brand attitudes are most closely associated with brand search.

Jeffrey P. Dotson, associate professor of marketing and global supply chain at Brigham Young University; Elea McDonnell Feit, assistant professor of marketing at Drexel University; and Ruixue Rachel Fan, Jeffrey D. Oldham and Yi-Hsin Yeh of Google studied more than 1,500 Google users who opted in to have their searches related to smartphones and desktops tracked for eight weeks and then linked their responses to a traditional brand attitude survey.



Dotson explains that those participating in the study opted in to monitor a select set of keywords through their Google ID. They also agreed to take surveys that allowed researchers to study their attitudes and the connection with the types of searches for branded keywords.   

The attitudes considered include measure of favorability, awareness, consideration, and purchase intent. For example, consumers who only recognize a smartphone brand and hold no other positive attitudes were only 1.22 times more likely to search for a brand than those who do not recognize the brand, per the findings.

Some categories will always drive more searches before a purchase such as furniture, appliances, financial services, autos and smartphones. An increase in brand attitude for these categories could lead to increases in search queries for the brand. For other product categories, searches prior to purchase may not apply, but that doesn't mean that purchases are minimal. Coca-Cola, for example, may not have a high search volume in queries, but has a high volume of sales, according to the research. 

One challenge, Dotson acknowledges, resides in branded search when it comes to positive or negative associations with the brand and the motivation behind the search. Machine-learning technologies will help engines like Google identify intent when it comes to branded searches, he says.

Marketers interpreting total brand search volume from tools like Google Trends data should expect to see a higher amount of searches for brands with more owners, regardless of consumers' attitudes toward the brand, per the study.

The next step in developing brand search as a metrics is to distinguish shopping-related brand search from the other sources of brand search such as troubleshooting or searching for homonyms to the brand, according to the study. Researchers recommend some ad-hoc ways to narrow Google Trends data to queries that are shopping related such as discounting queries with terms that are related to product use or troubleshooting. 

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