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Posted by Casey_Meraz
Last week I wrote a post about the new Snack Pack, where three local results have become the new standard, and explored where users were clicking based on some preliminary data from UsabilityHub tests we ran. In our test, we measured 200 clicks on a heat map to see where users were clicking most.
In that example, organic results won, getting almost 40% of clicks. However, this test was based on a search result where there was one organic listing above the local results, as seen in the screenshot below:
Since the release of this study, we've been conducting many more tests that take into consideration other variables, such as the different types of results that display and the impact of reviews.
In this article, we're going to analyze some new click-through studies, conduct live interviews with potential searchers, and talk about the new best practices you should focus on to win the local search game. If you're not familiar with the major impact of this update, you can read this great post by Jennifer Slegg.
The biggest change to occur was the removal of the 7-pack and the addition of the new 3-pack. In the image below you can compare the changes:
In essence, this research is meant to be insightful, but not definitive. Our sample sizes may be small but the users are real, so I hope this inspires you to see which areas you can improve upon for your clients.
In a close second follows the organic listing. This means that many users skipped over the local listings entirely and opted for the traditional organic result. We can't say exactly why this is, but it could be that users are not yet used to this format. We may see a shift in this behavior over time, as users become more accustomed to the change.
Notice how the local pack got very few clicks overall, resulting in just 8% of clicks (or 22%, if you include the "more local results" option). Does this seem weird? It does to me, but there is a key difference between the screenshot we used for this test and that which we used for the last one. There are no review stars present in the screenshot for our current test. It appears that the results with reviews were clicked more often than those without.
However, another item of interest is that the listings with reviews got the clicks. The third listing, with no review stars, received zero clicks in the local 3-pack. Additionally, it's worth nothing that most of the local-centric clicks land on the business name itself. These clicks no longer lead straight to your website or even your old Google+ page, where you still controlled the information to some extent. These now take you to a map page, where other businesses are displayed and where users can read your reviews.
Essentially, just because you got a click to your listing in the local 3-pack doesn't mean you've earned a visit to your site or a phone call.
Heat map data is super cool and fun to look at visually, but I wanted to dive a bit deeper and see if I could collect more accurate search data. Since we don't have access to Google's actual data, we have to simulate click-through studies based on a certain amount of variables and find the means to test our hypothesis. In the past, we've used Mechanical Turk and UsabilityHub for the majority of these tests. The potential problem therein is that we don't get as much information on the users, and it doesn't involve the emotions present with someone who is more invested in the search.
To simulate this and explore whether the data correlated with real user behavior, my friends at Fox Airsoft allowed me to stop in for the day and interview their actual customers. To do this, I created a very specific scenario for each of the candidates and screen-captured their behavior with a short interview. Keep in mind that for this test we specifically explored desktop user behavior, as that format was affected by the new Snack Pack update.
The scenario I used to try to invoke an emotional response read like this:
"You are sitting in front of your computer and you get a frantic call from a loved one. They tell you that your father has been locked up in [city changed per user] and that he needs to be bailed out immediately."
From here, I informed them that they needed to find someone ASAP. I then turned the computer over to them and had them conduct their searches and make their clicks, interviewing them after the fact. Overall, we interviewed ten people, which is a small sample size but offers intriguing results. A few of the most insightful interviews are below:
Meet Leah, a 27-year-old female who lives in New York. Leah is employed and has a four-year college degree. Watch how she responds to the scenario below:
In this scenario, she used a laptop computer and performed the search from Google's home page.
She opted to use a geo modifier for the result, since we clarified that her loved one was locked up in Denver. The keyword she typed in was "Denver bail bonds."
What's interesting about her behavior is that she scrolled past both the paid ads and the local Snack Pack to view the top three organic results before clicking on the business in the first local results position. At first glance, I would have done the same thing. However, the reason she provides for her selection is loud and clear. "I skimmed past the ads at the top, and then I noticed that there were a few listed, and one of them said 'five-star rating'..."
1) Local results ultimately earned the click.
2) Reviews were the reason the first local click won the battle.
Would Leah's behavior change if the organic results featured rich snippets with reviews and a five-star rating?
This is Todd. Todd is a 53-year-old man who lives in Colorado Springs, Colorado. Todd has a high school education and is employed full-time. Watch how he responds to the scenario below:
In this test, Todd took his time and was thoughtful about his search. Like Leah, Todd used a geo modifier for his keyword, but added it following the keyword and including the state abbreviation. The keyword he chose was "Bails Bondsman Colorado Springs CO."
When the search results page loaded, he recognized some offline branding from the show "Dog the Bounty Hunter" and mentioned he knew of Bobby Brown Bail Bonds because of this. However, even though he knew the brand, he put more weight into the reviews before deciding to click through to the first local result's website.
As you can hear in the interview, the reviews also played a big part in his decision here.
1) Todd was most interested in the top two local results, both of which include review stars.
2) The first-position listing won the click in the end, though.
Kaitlin is a 25-year-old female who works in the airline industry full-time. Kaitlin was given the same scenario as the others.
Kaitlin started at Google and used a geo modifier in front of the keyword she chose: "Denver Bail Bondsman," selected by autocomplete. She looked at the results and scrolled past the top two local listings—likely because they did not have any review stars associated with them, unlike the third result in the Snack Pack.
Kaitlin clicked on the listing's business name, which brought up the new map-type view. Here she could read the reviews. Her behavior was different than our other samples because she said she would do multiple searches before making her final decision.
Kaitlin seemed to have more interest in looking at the best and worst reviews before making a decision. She also used Yelp to explore reviews.
1) Local results earned the first click on the business listing that brought her to the map view. Keep in mind that other local businesses are also listed here.
2) Reviews were the reason the first local click won the battle. Positive and negative reviews made the difference.
3) A result with zero reviews in a pack where others include them seems to be a negative factor for click-throughs.
Clayton is a 29-year-old male who lives in New York City. He has a full-time job and previously dabbled in blogging. He was given the same bail bonds scenario:
Clayton started his search in Google with a geo modifier of "Denver CO" at the end of his search. The overall keyword phrase he chose was "best bail bondsman denver co." He scrolled down long enough to look at the local results and the top two organic results.
Ultimately, he clicked on the business name for the first result in the Snack Pack, which took him to the map-like results page. He made his final decision because of the five-star results. As he stated, "If you're number one, but your reviews suck, I don't want to go there."
1) Local results earned the first click on the business listing that brought him to the map view.
2) Not to beat a dead horse, but the decision was made because there were review stars present.
With so many different variables out there to test and ways to launch bigger studies, we're interested to hear what you think. What type of tests would you like to see?
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