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Understanding referrer clicks and how they can skew search engine market share

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As every search marketer knows, clicks are a key metric in measuring search traffic, yet counting clicks can be a complicated thing. All clicks are not the same. There are paid clicks. There are organic clicks. There are mobile clicks. And many times there are clicks that get quickly redirected in the blink of an eye without a user even realizing it. These redirected clicks can cause discrepancies and confusion in click reports.

Consider this: a recent post from StatCounter shows a search engine market share of Google 88.37% and Bing 6.07%. At the same time, other sites such as Statista, show Google at 62.5% with Microsoft sites (Bing) at 25%. And even another site, comScore, places U.S. Bing share at 36% on PC and 20% across all devices. Why such large discrepancies? What is driving the confusion? The answer requires an understanding of the mechanics of ad serving and web referrals.

Referrers are links that drive traffic to other websites, moving people around the internet. A referrer site is simply the site that a person was on right before they came to your page. But sometimes referrer sites get misrepresented. A click can get diverted to an ad server, then quickly redirected to your page. Take for example the retailer, Kohls. A person is surfing the Kohls website and clicks on a picture of a TAG Heuer watch:

From a user experience, this shopper goes directly from the Kohls website to TAG’s website. And yet on paper, the referrer click gets credited to Google. Why is this? Through Google’s AdSense program, the click from Kohl’s gets quickly redirected to Google’s ad server before going to tagheuer.com. The click referral is attributed to Google not Kohl’s. The clicks from ad servers can add up and skew market share, even though these are not direct search queries from a search engine.

It’s good to understand how sites such as StatCounter or JumpShot calculate their data by combining search engine referrals with ads from syndicated websites in their referrer metrics. Referrer can be rich with insightful information, but should be carefully analyzed and understood before making any optimization or business decisions. Search marketers should also stay vigilant for redirects on referrer click reports as often times there is more to a click than meets the eye.


Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.


About The Author

​Christi Olson is a Search Evangelist at Microsoft in Seattle, Washington. For over a decade Christi has been a student and practitioner of SEM. Prior to joining the Bing Ads team within Microsoft, Christi worked in marketing both in-house and at agencies at Point It, Expedia, Harry & David, and Microsoft (MSN, Bing, Windows). When she’s not geeking out about search and digital marketing she can be found with her husband at ACUO crossfit and running races across the PacificNW, brewing and trying to find the perfect beer, and going for lots of walks with their two schnauzers and pug.



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Google Search Console unparsable structured data report data issue

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Google has informed us that you may see a spike in errors in the unparsable structured data report within Google Search Console. This is a bug in the reporting system and you do not need to worry. The issue happened between January 13, 2020 and January 16, 2020.

The bug. Google wrote on the data anomalies page “Some users may see a spike in unparsable structured data errors. This was due to an internal misconfiguration that will be fixed soon, and can be ignored.” This was dated January 13, 2020 through January 16, 2020.

To be fixed. Google said they will fix the issue with the internal misconfiguration. It is, however, unclear if the data will be fixed or if you will see a spike in those errors between those date ranges.

Unparsable structured data report. The unparsable structured data report is accessible within Google Search Console by clicking here. The report aggregates structured data syntax errors. It puts all the parsing issues, including structured data syntax errors, that specifically prevented Google from identifying the feature type.

Why we care. The main thing here is that if you see a spike in errors in that report between January 13th and 16th, do not worry. It is a bug with the report and not an issue with your web site. Go back to the report in a few days and make sure that you do not see errors occurring after the 17th of January to be sure you have no technical issues.


About The Author

Barry Schwartz a Contributing Editor to Search Engine Land and a member of the programming team for SMX events. He owns RustyBrick, a NY based web consulting firm. He also runs Search Engine Roundtable, a popular search blog on very advanced SEM topics. Barry’s personal blog is named Cartoon Barry and he can be followed on Twitter here.



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Google rolls out organic ‘Popular Products’ listings in mobile search results

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Several years ago now, Google made the significant move to turn product search listings into an entirely paid product. Shopping campaigns, as they’re now called, have accounted for an increasing share of retail search budgets ever since. More recently, however, Google has been augmenting organic search results with product listings. It’s in a product search battle with Amazon, after all. On Thursday, the company announced the official rollout of “Popular Products” for apparel, shoe and similar searches in mobile results.

Organic product listings. Google has been experimenting with ways to surface product listings in organic search results, including Popular Products, which has been spotted for several months now. The section is powered by those organic feeds. Google says it identifies popular products from merchants to show them in a single spot, allowing users to filter by style, department and size type. The listings link to the retailers’ websites.

Popular Products is now live in Google mobile search results.

Why we care. This is part of a broader effort by Google to enhance product search experiences as it faces increasing competition from Amazon and other marketplaces as well as social platforms. Earlier this week, Google announced it has acquired Pointy, a hardware solution for capturing product and inventory data from small local merchants that can then be used in search results (and ads).

In the past few years, Google has also prompted retailers to adopt product schema markup on their sites by adding support for it in Search and Image search results. Then last spring, Google opened up Merchant Center to all retailers, regardless if they were running Shopping campaigns. Any retailer can submit their feed in real-time to Google to make their products eligible in search results.

Ad revenue was certainly at the heart of the shift to paid product listings, but prior to the move, product search on Google was often a terrible user experience with search listings often not matching what was on the landing page, from availability to pricing to even the very product. The move to a paid solution imposed quality standards that forced merchants to clean up their product data and provide it to Google in a structured manner in the form of product feeds through Google Merchant Center.


About The Author

Ginny Marvin is Third Door Media’s Editor-in-Chief, running the day to day editorial operations across all publications and overseeing paid media coverage. Ginny Marvin writes about paid digital advertising and analytics news and trends for Search Engine Land, Marketing Land and MarTech Today. With more than 15 years of marketing experience, Ginny has held both in-house and agency management positions. She can be found on Twitter as @ginnymarvin.



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Google buys Pointy to bring SMB store inventory online

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Google is acquiring Irish startup Pointy, the companies announced Tuesday. Pointy has solved a problem that vexed startups for more than a decade: how to bring small, independent retailer inventory online.

The terms of the deal were not disclosed, but Pointy had raised less than $20 million so it probably wasn’t an expensive buy for Google. But it could have a significant impact for the future of product search.

Complements local inventory feeds. This acquisition will help Google offer more local inventory data in Google My Business (GMB) listings, knowledge panels and ads especially. It complements Google Shopping Campaigns’ local inventory ads, which are largely utilized by enterprise merchants and first launched in 2013.

Numerous companies over the last decade tried to solve the challenge of how to bring small business product inventory online. However, most failed because the majority of SMB retailers lack sophisticated inventory management systems that can generate product feeds and integrate with APIs.

Pointy POS hardware

Source: Pointy

How Pointy works. The company created a simple way to get local store inventory online and then showcase that inventory in organic search results or paid search ads. It utilizes a low-cost hardware device that attaches to a point-of-sale barcode scanner (see image above). It’s compatible with multiple other POS systems, including Square.

Once the device is installed, it captures every product sold by the merchant and then creates a digital record of products, which can be pushed out in paid or organic results. (The company also helps small retailers set up local inventory ads using the data.) Pointy also creates local inventory pages for each store and product, which are optimized and can rank for product searches.

Pointy doesn’t actually understand real-time inventory. Cleverly, however, it uses machine learning algorithms to estimate this by measuring product purchase frequency. The system assumes local retailers are going to stock frequently purchased items. That’s an oversimplification, but is essentially how it works.

Pointy said it a blog post that it “serve[s] local retailers in almost every city and every town in the U.S. and throughout Ireland.”

Why we care. The Pointy acquisition will likely help Google in at least three ways:

  • Provide more structured, local inventory data for consumers to find in Search.
  • Generate more advertising revenue over time from independent retailers.
  • Help Google more effectively compete with Amazon in product search.

Notwithstanding the fact that e-commerce outperformed traditional retail over the holidays, most people spend the bulk of their shopping budgets offline and prefer to shop locally. Indeed, Generation Z prefers to shop in stores, according to an A.T. Kearney survey.

One of the reasons that people shop at Amazon is because they can find products they’re looking for. They often don’t know where to find a particular product locally. But if more inventory data becomes available, the more people may opt to buy from local stores instead.


About The Author

Greg Sterling is a Contributing Editor at Search Engine Land. He writes about the connections between digital and offline commerce. He previously held leadership roles at LSA, The Kelsey Group and TechTV. Follow him Twitter or find him on LinkedIn.



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