Search Engines and Brand Lift

By Anders Rosenquist | Feb 24, 2010 3:50:07 PM

Adweek recently published the results of a new study conducted by ZAAZ, Wunderman, BrandAsset® Valuator, and Compete that explores the relationship between the search engine that consumers use to find a brand’s website and the consumer’s perception of that brand. The study found that loyal users of Bing, Yahoo!, and Google have distinct characteristics that benefit some brands more than others.

“This research demonstrates that marketers have a real choice to make when formulating search strategies,” said Shane Atchison, CEO of ZAAZ. “The search engine acts as a kind of ‘train’ on the Internet. Each train provides a different set of unique results or ‘destinations.’ Consumer preference for a specific train demonstrates a unique demographic and psychographic profile.” That preference, the study found, can have enormous impact on any brand a consumer searches for.
 
ZAAZ led the analysis portion of this pioneering research study, which combined attitudinal and behavioral data to draw a more complete picture of consumer search behavior.  In this two-part post, we’ll first discuss our methodology;   in the second post, we’ll discuss the findings and how marketers could put these findings to use.  (Note: this research was independently conducted, and was not funded by any of our clients.  You can view a version of the results presentation here: Search Engine Research (pdf, 850 kb)
 
Our team combined two extensive databases from BrandAsset Valuator (BAV) and Compete. Both BAV and Compete own the largest databases in their areas of expertise.
 
BAV’s databases contain a range of attitudinal information – focusing on 72 brand metrics – and use the world's most comprehensive database of brands. Its BrandAsset Valuator model has measured brands since 1993; today, over 35,000 brands have been evaluated, and over 600,000 respondents in over 50 countries have been surveyed. To find out more about BAV data, try comparing a few of your favorite brands using the ZAAZ-built interactive tool: http://thebrandbubble.com/explore/.
 
We also used behavioral data provided by Compete. Compete combines site and search analytics and surveys on a diverse sample of more than 2 million users in the U.S. to understand what people are clicking on and why. Compete manages the largest pool of online consumer behavior data in the industry.
 
The datasets from BAV and Compete  both contained information on the same brands across verticals including retail, travel, wireless, and automotive.  Additionally, both data sets contained a field with information on a consumer’s primary search engine. Taken independently, each data set provides insights into search engine use.  However, when ZAAZ combined and mined the data sets, we found a much more powerful and complete story.
 
At ZAAZ, we live in a world of disparate data sources; we have data for Web analytics, social media, usability, optimization testing, surveys, and more.  Almost always, this data is supplied through different tools and in different formats.  Most online marketers will be familiar with this scenario: too much data, too few connections, limited insights and action.  We’re constantly looking for new and innovative ways to combine data and tell a true 360-degree story of the customer.
 
The research published by AdWeek is certainly not the first time we’ve been through this process.
 
Working with Ford we’ve joined attitudinal survey data to behavioral Web analytics data, and analyzed this data by unique user.  With this combined approach, we are able to map how different user journeys affect customer’s brand perception and likelihood to purchase a Ford vehicle.  As a result, we have quantitatively identified what areas of the Ford site and types of content are most effective at driving sales – an insight we never could have gained by analyzing the data sets in isolation.  Ford has used this data to channel media, redesign site architecture, and run a data-driven optimization program.
 
Working with Dell, we combined site optimization testing with in-person usability testing to understand why a particular creative treatment won. For a particular campaign, we found from our optimization tests which page variants generated the greatest interaction with the page. In addition, our analytics data showed that there were several key places in the purchase path where users were abandoning at an alarming rate. To gain insight into why this was happening, we conducted usability tests in our Seattle lab with Dell consumers, having them step through the purchase path and describe their process. We were able to uncover how participants’ attitudes toward the site and the brand changed through the process, why parts of the site became annoying, and why they decided to jump out of the purchase path—either to find a different product, or to go  a competitor’s site.  The insights gleaned from combining optimization and usability test data helped generate  site changes focused on improving user attitude and increasing conversion.
 
With the search engine research, the objective was to understand the relationship between a customer choice of search engine and the brand perception of products being searched.  Once we had the data sets combined we set to work looking for trends.  Using a series of aggregations, drilldowns, and data visualizations, we were able to observe trends in the data common across attitudinal and behavioral data sets. Once the trends in the data were clear, we pulled together stakeholders from BAV and Compete to build consensus on the interpretation of the data as well as actionable strategies.
 
Next week we’ll discuss some of the findings from the research and how to take action on these findings...

By Erik Koto and Anders Rosenquist

Ligers- At Home in the Optimization Department

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