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Writer's pictureFahad H

What’s Google’s Biggest Fear? Native Search

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Historically, consumers have used Google for research in every step of the purchasing process, all the way up the sales funnel — starting with lifestyle search terms like [grass stains] to product consideration terms like [Tide reviews] and purchase decision terms like [where to buy Tide online].

In recent years, however, we have observed some interesting changes in customer behavior — one of the main ones being that consumers are starting to favor native search over Google search for lower-funnel terms. This is something retailers can take advantage of during the upcoming holiday shopping season — and, indeed, year-round.

Note: These insights are based on my observations of changes in consumer behavior and Google’s actions — I have no inside knowledge that confirms this is actually Google’s biggest fear, but I do believe it’s up there fairly high among its concerns. ;)

So what exactly is native search? Native search is the search functionality inside the different platforms or websites. Simply put, it’s the search box on e-retail sites like Amazon, Walmart and CVS, or in category sites like Edmunds and Newegg.

walmart native search box

amazon native search box

Based on our research, consumers are still starting their search for lifestyle and general interest terms like [best laundry detergent for grass stains] or [best off-road car] within Google; but, once they identify a product or category, they now move more often into the e-retail and category sites to delve further and refine their search there.

Why is this happening? While there is no concrete survey data, I believe it’s due in part to these four factors:

1. Better Search/Filtering

With ever-evolving technology in the search sector, the search engines that power sites like Amazon (A9) are now more advanced when it comes to category-level product research. They provide the ability to filter by very specific features like size, weight, and many more.

Although Amazon is clearly leading from a technology perspective, other retailers are following suit. In recent years, companies like Walmart have invested heavily in their search technology, as demonstrated by the 2012 release of Walmart’s semantic engine. By leveraging the Social Genome project, Walmart was able to get a semantic understanding of queries and understand that when someone searches for denim, they are also interested in results matching jeans.

2. Comparison Shopping

One of the big features we know consumers are still missing in Google is the ability to easily compare results (products) by various criteria such as price, features, or reviews. The ease of use provided by sites like Amazon for the purpose of comparison and refinements is just not possible within search engines today.

We have seen Google try to make up for this with the integration of product details into the search results pages through the implementation of schema markup. While this added some of the information (reviews, price, etc.) it is generally only available for a few results, and far from extensive.

Google Result:

google listing for tide detergent

Amazon Result:

amazon listing for tide detergent

3. Shopping Carts

Consumers like to add products to their consideration set by adding them to their basket and then making a final decision upon checkout. That functionality, coupled with the ability to return later and complete their decisions and purchase, makes the “add to basket” functionality a lifesaver.

4. Purchase Intent

Personally, this is one of the primary reasons why I use native search in the final stages of my purchasing decisions. While Google is great on answering questions like [how to remove grass stains], it has yet to present a useful answer to queries such as [buy Tide laundry detergent online]. It generally brings you to the brand site, some lifestyle article or the e-retailers instead of satisfying my purchase intent.

So, What Does This Mean To Brands?

Marketers already know and understand the importance of their products’ shelf placement in brick-and-mortar retail. But the digital shelf is becoming increasingly significant — and it is crucial for brands to treat their virtual shelf placement as importantly as they do in traditional environments.

Brands need to make sure that they adjust their existing search strategy to match the consumers’ behavior in native search, or they will be left behind at the virtual checkout line.

Without sounding like an advertorial, I will say that we (the agency I work for) started adjusting our search mindset a few years ago in this direction. In essence, we have started to treat e-retail destinations like Amazon the same way we would treat Google.

It means we also treat brand-controlled assets (such as product listings/SKUs inside the e-retailers) very similarly to how we would treat brand-owned web pages. Simply put, we create keyphrase/search strategies; we monitor rankings and share of digital shelf space in these sites; and then we optimize the product descriptions, names, images, etc., to win against these terms — just like we would do with traditional SEO.

In order to get you started on winning in native search, I put together four simple steps you can take tomorrow.

1. Conduct Native Keyphrase Research

Make sure you get a clear understanding of how your consumers search in those native search boxes. You can always use your traditional keyphrase research as a seed list, and remove searches that are not likely to occur in those sites (for example, almost nobody would search for  “how to remove grass stains” in Amazon).

amazon native search keywords

Then you can  add in additional information via the data from platform features like “autosuggest” or “related searches.” Once you start to dig deeper into the site, you can generally get a good idea of the search behavior.

2. Constantly Monitor Search Rankings

Just as you monitor rankings in traditional search engines, you should monitor your rankings on the different native platforms. By monitoring the rankings and results, you will learn how their algorithms work and be able to effectively “manipulate” their rankings through optimization and content creation — and believe me, none of these platforms have an algorithm as complex as Google’s!

3. Understand The Landscape

Collecting and categorizing the ranking data on a recurring basis will enable you to get a much better understanding of the opportunities and gaps in your visibility. Below is a sample report of what we are currently delivering to one of our oral care clients.


competitive-landscape

(Click to enlarge.)


4. Optimize Your Product Listings (SKUs)

Just as your search agency would optimize your page content against search terms, you should be optimizing your SKUs and other brand-owned assets against those search terms.

Sticking with our laundry detergent example, we have seen some product listings that were talking about “fresh scent” and “bright colors,” but did not contain keyphrases such as “grass stains” or “stain removal.” How could they rank well for these terms if they aren’t part of the product description? Again, it’s just like ranking in Google — if your page is not mentioning a specific topic, it’s less likely you’ll rank for it.

Measurement Challenge

One interesting challenge we have not discussed today — but that is certainly worth thinking about — is the challenge of measurement.

While the product awareness and consideration was definitely driven in these examples by the research conducted in Google, the eventual sale was not attributed to the search activity, but rather by native search. Although Google has made some progress in the field of omni-channel measurement, I believe there is still a lot of room for integration and growth.

With the continuous innovation driven by companies like Amazon and Walmart, the move to native search will continue to grow and slowly eat away at the lower funnel search in Google. I am very interested in seeing what Google’s next move will be; maybe it’s finally including a “buy now” button inside the SERP or the ability to compare products based on Knowledge Graph data. Whatever it is, I think we have an exciting chapter ahead of us.

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