How can marketers optimize for Google's new "similar items" feature?
Google has announced that “Similar items” is now available globally in image search on mobile and in its Android app.
Similar items will suggest related products based on a user’s search query and their interactions with the resultant images.
At first, the feature will only be available for shoes, sunglasses, and handbags. Google does, however, expect to roll this out across a much wider set of products this year, starting with furniture, homeware, and potentially some other apparel categories.
Retailers of all stripes should keep a very close eye on this and start thinking about how to optimize for Similar items.
One essential step is to add Products Schema to any items you want to be eligible for this feature. Google provides some clear guidelines on this; but as a summary, the following elements should be tagged:
There is also the option to opt out of this altogether, should you wish to avoid having your images show up in Similar items.
Aside from these essential technical details, optimizing for Similar items does bring with it new questions for marketers.
Links between products can be based on their shape, style, color, or any one of a number of factors, as we can see in this diagram from TechCrunch outlining how the technology functions at a very high level:
Although not typically the domain of search marketing, we will need to be involved with the selection of imagery for client websites to maximize the opportunity to appear in these new results.
From a pay-per-click perspective, this is a product ripe for monetization.
Tellingly, Google ended its announcement of the new feature with:
“We’re excited to help users find your products on the web by showcasing buyable items. Thanks for partnering with us to make the web more shoppable!”
The long-term aim will, quite clearly, be to offer new targeting options to advertisers based on other items their current or prospective customers have perused.
As such, we should certainly expect a raft of new advertising options this year from Google. Pinterest has launched a (thus far) tentative foray into this market in tandem with Kenshoo, so Google will want to nip any progress in the bud on that front.
Google made the following statement as part of their announcement:
“The “Similar items” feature is designed to help users find products they love in photos that inspire them on Google Image Search. Using machine vision technology, the Similar items feature identifies products in lifestyle images and displays matching products to the user.”
A “Similar item to this” feature already exists over on Pinterest. We have written extensively in the past about Pinterest’s suite of visual discovery tools, most notably the new Lens tool, which allows Pinners to point-and-shoot with a smartphone camera. Pinterest then deciphers the image and suggests complementary items.
That does distinguish it from Google’s offering, but perhaps only temporarily. We can infer from a patent review on SEO by the Sea that Google has something very similar in production.
Of additional note within the Google statement above, from a business strategy perspective, is the use of the verb ‘inspire’, which has been a hallmark of Pinterest’s public communications over the past few months. There can be little doubt that Google is positioning itself to nudge Pinterest further to the fringes if it can.
A similar item (belonging to a more direct competitor) also exists on Amazon’s mobile app, powered by their FireFly technology.
Amazon’s app allows shoppers to search via images, with the e-commerce giant using this data to provide further shopping recommendations. We know that online shoppers are increasingly going to Amazon first, a trend that Google will be unlikely to tolerate without putting up a fight.
Probably not. Google still holds two very distinct advantages in this arena: a huge user base, and an intuitive, integrated, proven suite of advertising products.
Pinterest has yet to crack either of these, and it should be noted that they also cater to very different demographics in very different states of mind.
Amazon continues to go from strength to strength and is diversifying its portfolio of products is evermore interesting ways, but its paid advertising offering is not yet equipped to take on AdWords.
It has been known for quite some time that Google has been working tirelessly on its machine learning-based image search technology. Problems that a sentient being can deal with rather intuitively (distinguishing a sneaker from a loafer, for example) have historically been close to insoluble for machines.
Things have progressed markedly in the last decade, but issues still linger with machine vision technology.
This helps to explain why so many other Google products have been launched before this one. It is not because of its lack of importance, but rather the converse; Google is keen to get this one right, as it is a hitherto untapped revenue stream.
Ours is a visual culture largely mediated by images, so this is a natural step for any search engine or social network. There is not necessarily a cap on the amount of suggested products that can be provided either, so long as there is an ongoing increase in image-based searches.
We may see a decline in traditional text-based searches as this e-commerce mechanism takes hold, however, and that will require Google and its advertisers to change their way of working.
This is not the finished product from Google, of that we can be certain. Through the rest of this year, we should expect improvements in the technology, accompanied by a slew of new advertising options.
If it wasn’t already, image search should be one of our core considerations for any search strategy.