Search marketers move on from the keyword to secondary search signals
US internet users are conducting more and more searches that start and finish on different devices. As advertisers shift more of their search budgets to mobile, this multidevice behavior makes paid search targeting and accurate performance measurement more difficult. But there are some methods and best practices that marketers can adopt to improve their results, according to a new eMarketer report, “Cross-Device Search Marketing: As Search Goes Multidevice, Ad Targeting and Measurement Struggle to Keep Pace.”
Analyzing cross-device search user behavior is difficult, and marketers disagree about what will help effectively reach such users moving forward. For many, improved methods for targeting multidevice search users will be key. This will involve using secondary search signals such as the type of device along with user location and time of day to further inform bidding strategies.
Paid search marketing has long been a discipline focused on maximizing the value of keywords. But the evolution of search toward cross-device leads many to conclude that keywords may no longer be enough. “If you are a marketer, you’re building a marketing plan against an audience. You have a specific person you’re trying to reach, not a keyword,” said John Cosley, director of product marketing for the search advertising business group at Microsoft.
“Focusing just on keywords is like reading an email from someone where you don’t get as many contextual clues. You just have the text,” said Jeremy Hull, director of bought media at iProspect. “Looking at other information that the user passes when they search, such as device specifically, but also location ... that’s equivalent of being able to have a face-to-face conversation with someone where you can read their body language.”
To help solve this problem, marketers are increasingly using secondary data from CRM programs along with search cues like time of day, user location and device used to further targeting strategies for search. How this might work in practice is still up for debate, though a number of sources suggest marketers typically use this information to help decide on bid adjustments. For instance, a search user in a specific ZIP code might be worth more to an apparel company even if he or she doesn’t search for jackets. “It’s more context-based. For example, say [the user] lives in an area that gets a lot of rain,” said Brian Lee, market research analyst at Marin Software. “While they might not be looking at rain products at that moment, it’s related to their location and the audience more than it’s related to their current search topic.”
Other marketer surveys confirm that many are increasingly looking to customer data to improve targeting efforts. A February 2015 survey by Duke University’s Fuqua School of Business investigating US marketers’ usage of customer behavior data for targeting purposes implies that the practice is increasing. Although slightly less than half of US marketers in the survey currently used data for targeting, more than 90% said that their use of such data was increasing.