By Rex Yuxing Du, McCombs School of Business, University of Texas at Austin, USA, email@example.com | Tsung-Yiou Hsieh, D’Amore McKim School of Business, Northeastern University, USA, firstname.lastname@example.org
Every year billions of users around the world submit trillions of queries through online search engines such as Google, Bing, Baidu, and Yandex. Over the years, aggregated and anonymized search volume data on keywords contained in all these queries have formed an epic database of human intentions that continues to expand every day. Thanks to platforms such as Google Trends, Google Ads Keyword Planner, Microsoft Advertising Keyword Planner, Baidu Index, and Yandex Wordstat, advertisers can readily assess search engine users’ collective interests over time and across geographic areas to optimize their search engine marketing efforts. In this monograph, we illustrate how online search volume data, indexed or otherwise, can be leveraged as a powerful source of marketing insights for purposes beyond search engine marketing. We do so by offering a brief tutorial on Google Trends and Google Ads Keyword Planner, two popular (and free) platforms for gathering online search trend and volume data, respectively. We review prior studies that have examined the use of aggregate online search data as (1) predictors for nowcasting and forecasting, (2) dependent variables in market response modeling, and (3) proxies for otherwise hard-to-measure constructs. In each of these three areas, we provide specific examples of applications to illustrate the power and versatility of online search data. We conclude by offering several ideas for future research where we see the full potential of online search data is still to be uncovered.
Leveraging Online Search Data as a Source of Marketing Insights is written with two main audiences in mind. For practitioners, it offers a guide on how best to utilize platforms such as Google Trends and extract actionable insights for a wide array of business decisions illustrated with real-world example applications. For academics, it provides a literature review and a framework that integrates the various avenues through which online search data can be leveraged in scientific research.
The monograph starts with a brief tutorial of Google Trends and Google Ads Keyword Planner, two popular platforms for gathering online search trends and volume data, respectively. It also briefly discusses Baidu Index as an alternative to Google Trends for insights about the Chinese market, where Baidu is the dominant search engine. The next section offers a review of the literature that has utilized online search data. First, it surveys research that has treated aggregate online search interests as either concurrent or leading indicators of real-world phenomena. Second, it examines research that has treated online search data as response variables that can help measure and improve marketing effectiveness in terms of both immediate and longer-term impacts. Third, it reviews research that has treated patterns of online searches as unvarnished reflections of the public psyche, uncovering what people really think, feel, and intend to do, insights that may otherwise be difficult to ascertain based on what people post on social media or tell market researchers in surveys. The authors conclude by highlighting several promising areas for future research where online search data can serve as a big-data supplement to traditional market research.