If there is one constant in the ever-changing online search environment, it is Google's continual charge to test and innovate the search engine experience. With each feature update to the leading search engine, the way users interact with Google search results changes. Online marketers must understand how these changes to search results relate to their industry—whether it is financial services or consumer products and retail—and ensure their paid search and search engine optimization (SEO) strategies remain relevant and forward-looking. It is for this reason, to continually inform strategy and test the status quo, that Rosetta's Search & Media Innovation Lab Team conducted an eye tracking study, which evaluated how search behavior evolves with various iterations of Google's changes.
Utilizing Rosetta's advanced, in-house Usability Lab, Rosetta performed a qualitative eye tracking test over a 2-day period, aimed at evaluating how users interact with a set of recent Google search updates. The study revealed the following key insights:
Background: Google Instant launched in September of 2010, promising a faster and more user-friendly search experience. The feature provides results instantly as users enter their search query.
Findings: A significant majority of testers did not engage with Google Instant while entering their desired search query. The eye tracking results showed users either focused primarily on the search bar or did not engage with the screen at all by looking down at the keyboard. The minority of users who leveraged the Instant results seemed to do so when they could not recall the brand name they were searching for.
Impact & Implications: When Instant launched, a variety of predictions were made on how the new feature would impact SEO and paid search. In some instances it was predicted that a user may not complete a search query, if what the user was searching for appeared on the search engine results page (SERP) before the query was complete. For paid search, some were concerned about the impact on impressions, quality score and ultimately cost-per-click. Rosetta's test demonstrated that the lack of user engagement in the changing results neither shortens search queries nor threatens the budget of paid search campaigns. Based on these findings, Search Marketers' SEO and PPC strategies are not impacted by Instant. However, it should be noted one user did leverage the Instant results when he had trouble recalling the specific brand he was searching for. This emphasizes the importance of ranking well for brand and brand modifier terms/keywords in both organic and paid listings.
The above gaze plot image demonstrates how a tester interacted with Google Instant as they entered their search query. The larger the circle, the greater the amount of time the tester's eyes spent on that particular portion of the page. Lines between circles show how the eyes scanned the page.
Background*: In April 2011, Google launched Google Instant Preview. This feature shows a visual preview of search results. Users can now click on a magnifying glass – which appears next to each search result – to see a preview of the landing page of that particular result.
Findings: None of the users tested had used the Preview Pane before. A majority of users said they would use this feature now that they knew about it. A minority of users still did not fully understand what the Preview Pane did even after using it.
Impact & Implications: The results demonstrated that while feature adoption rate is still low, the benefit of the feature resonates with users. The findings reinforce the notion that a website must have a quality post-click experience to entice the user to stay and engage with the site. Previously, users only had the results position in organic search, the URL, and a few lines of text to determine if they should click. Now users have insight into the post-click experience, pre-click. Additionally, these results confirm the need for integration between SEO and user experience in website design to create an engaging experience for the user.
*Note: Since the completion of the Rosetta test, Google has since updated the Preview Pane feature to automatically pop up as users mouse over the results. This increases the importance of having a relevant landing page, so as not to lose users before they click.
The above gaze plot shows how a user engages with the Preview Pane. This particular image shows how a user engages with the preview of the post-click landing page and the importance of having an optimized and well-designed page for the post-click experience.
Background: As Google has continued to update the search engine results page (SERP), it has introduced video, images, products and news, among other feeds, to its search results page. This creates opportunities for companies to appear on the results page in a variety of ways. The introduction of these elements is commonly referred to as Universal Search Results.
Findings: Users reported that they prefer looking at results pages that include images, particularly those that appear in the shopping results portion of the results page. Although some of these users did not ultimately click on the image or shopping results, product image results did grab and hold the visual attention of the user.
Impact & Implications: With the advent of universal search results, companies have greater opportunities for related queries, as well as opportunities for taking up a larger portion of the search engine results page. These opportunities make it imperative to ensure strategic optimization efforts are implemented for all paid, earned, and owned marketing tactics (e.g., videos, images, and product feeds). While users in this study did not always click on the image results, the visual results still attracted significant attention. Additionally, not optimizing digital assets leaves room for competitors to occupy additional real estate on the results page. Retailers especially need to make product feed optimization a priority. Brand identification with product image through the shopping results image feeds creates an opportunity to both increase awareness as well as strengthen it.
The white area of the above focus map shows where users focused during the eye tracking test. Areas where users did not look are in black. The eye tracking test shows universal results are attracting users' attention even though they do not always click on them.
Background: Since its beta launch in 2004, Google Local has impacted the way users search. Users can now find information on local businesses within the search results instead of needing to leverage a phone book, Yellow Pages, or another source. Local listings are included as part of the universal search results but their impact is worthwhile to discuss separately.
Findings: During the test, when users entered search queries that triggered search engine results pages (SERPs) with local listings, rarely did they click on the location links in the primary SERPs even though the links corresponded to their placement in the map. However, most users stated that they do interact with the map when looking for a specific place. Participants are likely to use this feature when looking for a nearby store or branch of their bank close to their home. When asked to search for a new bank, several users mentioned they leverage the map to identify a bank that is local and accessible.
Impact & Implications: Local search results allow users to search for a business within their geographic region. Businesses can edit, create and manage their local business listings. For retailers, a strong local search presence allows their business to be accessible online and easily found when a customer is ready to find a store and make a purchase. Not having correct information, or simply not having a local presence, may prompt the customer to look elsewhere, potentially to a competing brand.
For a financial business, ensuring a bank's local branches are properly optimized creates the opportunity to be found by current customers as well as potential new-to-bank customers looking for a local, accessible bank.
The heat map above shows users' engagement with local results. Areas of dark red and orange represent sections of greater focus.
Background: Google Autocomplete, an update to Google Suggest, was introduced in October of 2010. This feature automatically offers search query recommendations that align to the query being typed by the user in the search box.
Findings: Of the features tested, Google Autocomplete was most widely used by all participants. Users leveraged this feature to correct misspellings as well as to hone in on a specific search query. Some users mentioned that Google suggests more relevant search terms than those the users created on their own.
Impact & Implications: At this time, companies are not able to impact key terms that appear in Autocomplete. It is important for companies to understand that customers are using this feature and to have insight into what terms are appearing in the Autocomplete to address potential relationship management concerns and identify keyword opportunities. The suggested queries should be used to help inform keyword research components of both paid search and SEO strategies by offering suggestions to broad or header terms not initially assumed or found in preliminary research. Keyword strategies should also be revisited frequently, given the influence Autocomplete has on consumers, and the ability for both consumers and Google to change preferences without notice.
The heat map above shows how intensely a user is looking at the suggestions in Autocomplete. Areas of dark red and orange represent sections of greater focus.
The qualitative eye tracking test involved 11 participants—with 9 providing eye tracking results, and ranging in age from 19 to 55—who use the Internet on a daily basis and have previously made online purchases. Participants were asked to complete three primary tasks:
Users were then also given static images of predetermined search results to gauge a baseline of the impact of new features in the search engine results page. Results were analyzed using eye gaze videos, heat maps, and focus maps. The testing structure was formulated to analyze results against a series of hypotheses, mapped to a set of Google Search features.