When Pinterest Lens launched in 2017, it was the latest – and boldest – step in Pinterest’s evolution from a visual social network into a powerful visual search tool.
Pinterest knew that there was great potential to blend its “inspiration”-focused online platform, full of enticing DIY, craft, beauty and recipe ideas, with the offline world to help its users make their ideas into reality. The goal was to offer a camera search that helps you discover online what you come across in the offline world.
The idea seemed ambitious, but Pinterest made it clear at the time that its Lens technology was still developing, encouraging users to help it build a powerful tool:
“Lens is still learning, and doesn’t always recognize exactly what you’re looking for.
Lens will stay in beta as it gets even better at recognizing all the things. And that’s where you come in!
If you get results that feel a little meh, tap the new + button to add feedback and help Lens get better at finding ideas inspired by whatever you just Lensed. As more and more people help teach Lens about more and more objects, soon it will earn its way out of the beta zone.”
A year on from this announcement, how has Pinterest’s visual discovery evolved – and what has the impact of Pinterest’s Lens tool been on the wider industry?
There are now twice as many Pinterest users who use Lens every day, compared to 6 months ago
People carry out more than 600 million visual searches with Lens every month, which marks an increase of 140% year-over-year
According to Pinterest, the more people searched, the better Lens got. Several new developments over the past year have also contributed to Lens’ growth:
Lens was moved to the front of Pinterest’s app and they have also createdshortcuts to facilitate the fast search
Pinterest introduced Pincodes, a QR-code-esque technology, to help users seamlessly switch between Pinterest and the offline world
Lens your Look has also been launched to “bring together text and image searches in one query”, and encourage people to use Pinterest for outfit inspiration
A partnership with Samsung brought the Lens to the latest smartphones worldwide, while Target activated visual search to their products
The visual search technology now understands more than five times as many things as it did a year ago. This means that you can now search for recipes, clothes, and countless objects for your home with increasing accuracy.
What’s next for Lens
Pinterest has announced that their next step includes an enhanced image search that also allows you to include it in your text search. Starting with iOS apps, people will be able to include an image to their text search to make their discoveries easier.
This will help users find exactly what they’re looking for by benefiting from all the elements of a consideration journey. They can start with an object they’ve come across in an actual shop, they use Pinterest’s Lens to discover it and if they are not able to purchase it directly through a pin, they can use the image to include text search and find more details about it.
This feature is also expected to roll out to Android users soon and it aims to make visual search even more useful. It is a clever way to include the benefits of visual and text search to help both the consumers, but also the retailers in strengthening their customer journey between the online and the offline world.
The future of visual search
The growth of Pinterest Lens shows how visual search is steadily gaining traction as a genuine tool and not just a novelty. Pinterest is also not the only player in this space: three months after the launch of Pinterest Lens, Google debuted its own version of the tool, Google Lens.
Soon afterwards, Bing released an update to its visual search capabilities which allowed users to search for a specific object within images – a noticeably Pinterest-like feature.
Pinterest is clearly blazing a trail in the visual search space which has left the other big players in search scrambling to catch up.
Above, Pinterest’s “search within image” feature, and below, Bing’s strikingly similar capability
Pinterest seems to be aware of its product’s value, and is heading in the right direction to make it profitable.
Pinterest already had a strong business proposition which capitalized on the fact that its users would come to its platform for inspiration on everything from fashion to design, food to furniture. With the introduction of Shoppable Pins, Pinterest was able to monetize this, allowing users to actually buy the components of their new dream house, garden or outfit.
Now, Pinterest Lens has made that possible in the offline world, too.
Business Insider has foreseen a bright future for mobile visual search technology, releasing a new report which cites “strong evidence that mobile visual search technology will take off in the near future, including growing access to technology, strong usage rates of camera-related apps, and early indication of potential revenue growth”.
By getting into the visual search space early and investing heavily in developing the technology, Pinterest has put itself in an excellent position to be the leader in visual search going forward.
While visual search has yet to truly cross over into the mainstream, the foundations have been laid, and the statistics shared on Lens’ one-year anniversary paint a positive picture for the future.
The human brain has evolved to instantly recognize images.
Visual identification is a natural ability made possible through a wonder of nerves, neurons, and synapses. We can look at a picture, and in 13 milliseconds or less, know exactly what we’re seeing.
But creating technology that can understand images as quickly and effectively as the human mind is a huge undertaking.
Visual search therefore requires machine learning tools that can quickly process images, but these tools must also be able to identify specific objects within the image, then generate visually similar results.
Yet thanks to the vast resources at the disposal of companies like Google, visual search is finally becoming viable. How, then, will SEO evolve as visual search develops?
Here’s a more interesting question: how soon until SEO companies have to master visual search optimization?
Visual search isn’t likely to replace text-based search engines altogether. For now, visual search is most useful in the world of sales and retail. However, the future of visual search could still disrupt the SEO industry as we know it.
What is visual search?
If you have more than partial vision, you’re able to look across a room and identify objects as you see them. For instance, at your desk you can identify your monitor, your keyboard, your pens, and the sandwich you forgot to put in the fridge. Your mind is able to identify these objects based on visual cues alone. Visual search does the same thing, but with a given image on a computer. However, it’s important to note that visual search is not the same as image search.
Image search is when a user inputs a word into a search engine and the search engine spits out related images. Even then, the search engine isn’t recognizing images, just the structured data associated with the image files.
Visual search uses an image as a query instead of text (reverse image search is a form of visual search). It identifies objects within the image and then searches for images related to those objects. For instance, based on an image of a desk, you’d be able to use visual search to shop for a desk identical or similar to the one in the image.
While this sounds incredible, the technology surrounding visual search is still limited at best. This is because machine learning must recreate the mind’s image processing before it can effectively produce a viable visual search application. It isn’t enough for the machine to identify an image. It must also be able to recognize a variety of colors, shapes, sizes, and patterns the way the human mind does.
The technology surrounding visual search is still limited at best
However, it’s difficult to recreate image processing in a machine when we barely understand our own image processing system. It’s for this reason that visual search programming is progressing so slowly.
Visual search as it stands: Where we are
Today’s engineers have been using machine learning technology to jumpstart the neural networks of visual search engines for improved image processing. One of the most recent examples of these developments is Google Lens.
Google Lens is an app that allows your smartphone to work as a visual search engine. Announced at Google’s 2017 I/O conference, the app works by analyzing the pictures that you take and giving you information about that image.
For instance, by taking a photo of an Abbey Road album your phone can tell you more about the Beatles and when the album came out. By taking a photo of an ice cream shop your phone can tell you its name, deliver reviews, and tell you if your friends have been there.
All of this information stems from Google’s vast stores of data, algorithms, and knowledge graphs, which are then incorporated into the the neural networks of the Lens product. However, the complexity of visual search involves more than just an understanding of the neural networks.
The mind’s image processing touches on more than just identification. It also draws conclusions that are incredibly complex. And it’s this complexity, known as the “black box problem”, that engineers struggle to recreate in visual search engines.
Rather than waiting explicitly on scientists to understand the human mind, DeepMind — a Google-owned company — has been taking steps toward programming the visual search engine based on cognitive psychology rather than relying solely on neural networks.
However, Google isn’t the only company with developing visual search technology. Pinterest launched its own Lens product in March 2017 to provide features such as Shop the Look and Pincodes. Those using Pinterest can take a photo of a person or place through the app and then have the photo analyzed for clothing or homeware options for shopping.
What makes Pinterest Lens and Google Lens different is that Pinterest offers more versatile options for users. Google is a search engine for users to gather information. Pinterest is a website and app for shopping, recipes, design ideas, and recreational searching.
Unlike Google, which has to operate on multiple fronts, Pinterest is able to focus solely on the development of its visual search engine. As a result, Pinterest could very well become the leading contender in visual search technology. Nevertheless, other retailers are beginning to catch on and pick up the pace with their own technology. The fashion retailer ASOS also released a visual search tool on its website in August 2017.
The use of visual search in retail helps reduce what’s been called the Discovery Problem. The Discovery Problem is when shoppers have so many options to choose from on a retailer’s website that they simply stop shopping. Visual search reduces the number of choices and helps shoppers find what they want more effectively.
The future of visual search: Where we’ll go from here
It’s safe to assume that the future of visual search engines will be retail-dominated. For now, it’s easier to search for information with words.
Users don’t need to take a photo of an Abbey Road album to learn more about the Beatles when they can use just as many keystrokes to type ‘Abbey Road’ into a search engine. However, users do need to take a photo of a specific pair of sneakers to convey to a search engine exactly what they’re looking to buy.
Searching for a pair of red shoes using Pinterest Lens
As a result, visual search engines are convenient, but they’re not ultimately necessary for every industry to succeed. Services, for instance, may be more likely to rely on textual search engines, whereas sales may be more likely to rely on visual search engines.
That being said, with 69% of young consumers showing an interest in making purchases based on visual-oriented searches alone, the future of visual search engines is most likely to be a shopper’s paradise in the right retailer’s hands.
What visual search means for SEO
Search engines are already capable of indexing images and videos and ranking them accordingly. Video SEO and image SEO have been around for years, ever since video and image content became popular with websites like YouTube and Facebook. Yet despite this surge in video and image content, SEO still meets the needs of those looking to rank higher on search engines. Factors such as creating SEO-friendly alt text, image sitemaps, SEO-friendly image titles, and original image content can put your website’s images a step above the competition. However, the see-snap-buy behavior of visual search can make image SEO more of a challenge. This is because the user no longer has to type, but can instead take a photo of a product and then search for the product on a retailer’s website. Currently, SEO has been functioning alongside visual search via alt-tagging, image optimization, schema markup, and metadata. Schema markup and metadata are especially important for SEO in visual search. This is because, with such minimal text used in the future of visual search, this data may be one of the only sources of textual information for search engines to crawl.
Meticulously cataloging images with microdata may be tedious, but the enhanced description that microdata provides when paired with an optimized image should help that image rank higher in visual search.
Metadata is just as important. In both text-based searches and visual-based searches, metadata strengthens the marketer’s ability to drive online traffic to their website and products. Metadata hides in the HTML of both web pages and images, but it’s what search engines use to find relevant information.
Marking up your images with relevant metadata is essential for image SEO
For this reason, to optimize for image search, it’s essential to use metadata for your website’s images and not just the website itself.
Both microdata and metadata will continue to play an important role in the SEO industry even as visual search engines develop and revolutionize the online experience. However, additional existing SEO techniques will need to advance and improve to adapt to the future of visual search.
The future of SEO and visual search
To assume visual search engines are unlikely to change the future of the SEO industry is to be short-sighted. Yet it’s just as unlikely that text-based search will be made obsolete and replaced by a world of visual-based technology. However, just because text-based search engines won’t be going anywhere doesn’t mean they won’t be made to share the spotlight. As visual search engines develop and improve, they’ll likely become just as popular and used as text-based engines. It’s for this reason that existing SEO techniques will need to be fine-tuned for the industry to remain up-to-date and relevant.
But how can SEO stay relevant as see-snap-buy behavior becomes not just something used on retail websites, but in most places online? As mentioned before, SEO companies can still utilize image-based SEO techniques to keep up with visual search engines.
Like text-based search engines, visual search relies on algorithms to match content for online users. The SEO industry can use this to its advantage and focus on structured data and optimization to make images easier to process for visual applications.
Additional techniques can help impove image indexing by visual search engines. Some of these techniques include:
Setting up image badges to run through structured data tests
Creating alternative attributes for images with target keywords
Submitting images to image sitemaps
Optimizing images for mobile use
Visual search engines are bound to revolutionize the retail industry and the way we use technology. However, text-based search engines will continue to have an established place in industries that are better suited to them.
The future of SEO is undoubtedly set for rapid change. The only question is which existing strategies will be reinforced in the visual search revolution and which will be outdated.
Pinterest has announced its long-awaited move into the self-serve paid search space, after a period of trial campaigns with select partners. With innovative visual search technology and an ambition to corner the ‘discovery’ phase of search, this could prove an enticing complement to AdWords for many brands.
So, how does Pinterest PPC work, how does it differ from other paid search options, and how can advertisers get started?
Pinterest Ads Manager is now open to all businesses who have opened an account and uploaded at least one Pin. In what is a fiercely competitive space, Pinterest is hoping that its offering can both provide something new and still deliver on the core performance metrics marketers have come to expect from Google AdWords.
This announcement comes at the end of a lengthy campaign to get the product right, with early partners including eBay, Target, and bid management platform Kenshoo. The newly released self-serve paid search platform provides the same experience these early partners have enjoyed, without the need to go through Pinterest or a third party to get started. The Ads Manager allows brands to create and optimize their promoted Pins and will also track and report on campaign performance.
Pinterest has been clear in its desire to monetize the discovery phase of search, when a user does not yet have a defined product in mind but is open to suggestions. The uniquely visual nature of this social network makes it ripe for this approach, but it brings with a host of accompanying challenges.
As a result, Pinterest has invested heavily in image recognition and object detection technologies, culminating in the launch of the impressive Pinterest Lens visual search tool.
Feedback on their advertising offering has been positive so far, but this will be put to a much more rigorous test now that advertisers can launch and optimize their own campaigns through the Ads Manager.
Why should advertisers take notice of Pinterest PPC?
Although some will be keen to trial Pinterest paid search in the hope of gaining the early adopter’s advantage, others may require some convincing before they view this social network as a genuine platform for selling their products. Nonetheless, Facebook faced the same resistance and ultimately, the numbers will do the talking.
For now, Pinterest is understandably touting some statistics to try and get advertisers excited. We covered many of these benefits in our visual guide to Pinterest advertising, but some of the key points are:
97% of Pinterest searches are non-branded
There are now over 200 million Pinterest users (up from 150 million in 2016)
More than 2 billion searches take place on Pinterest each month
75% of all Pins saved by users come from businesses
In an era of ad blockers and decreasing consumer trust in brands, Pinterest aims to offer a native feel to its promoted Pins. Through highly targeted ads that fit both aesthetically and conceptually alongside organic posts, brands can potentially attract much higher engagement rates.
In fact, the official announcement of self-serve Pinterest ads promises more sophisticated targeting than the competition, both in terms of its keyword options and the granularity of its audience data.
Moreover, it is not a significant enough departure from AdWords to require a completely new set of skills to get the most out of Pinterest PPC campaigns. That may entice some advertisers to trial the platform, which will give Pinterest the opportunity to prove its worth.
Some ideas borrowed from AdWords
The tech giants are not shy about borrowing each other’s ideas, and it would be fair to say that Google’s own image search interface has become more Pinterest-esque this year.
It is therefore not surprising that Pinterest’s move into PPC advertising involves some familiar concepts from AdWords. Google has mastered the art and science of delivering a great search experience and making a lot of money from the data, so AdWords is an obvious reference point for a new entry to the PPC market.
For example, the keyword targeting options are broad match, phrase match, and exact match. Advertisers can define their list of negative keywords that they do not want to be shown against, and can download a search query report to see how they have performed on a keyword level. This approach has served Google very well, so perhaps we should not expect a smaller player to waste resources by trying to improve on it.
It is also possible to move a keyword-based account structure from other PPC platforms directly into Pinterest Ads Manager, although the social network does not advise this due to the different nature of user search behavior on the platform.
The new features announced last week include an autotargeting option, which will automatically place ads for relevant keywords, even if they are not within the brand’s keyword target list. Imagine AdWords’ Dynamic Search Ads on Pinterest and you’ve pretty much got the gist of it. Autotargeting is driven by the Taste Graph, which contains over 100 billion Pins and employs machine learning technologies to identify patterns and trends, which in turn help improve the accuracy of search results.
Pinterest will be hoping its proprietary features and the unique nature of its database will suffice to differentiate it from Google’s advertising behemoth.
What will make Pinterest paid search successful?
Pinterest is in an enviable position, in some senses. The paid search market is mature enough now to provide plentiful data on consumers and the competition. By hiring two senior engineers from the Google image search team, as Pinterest did last year, they have also been able to tap into some of the most extensive knowledge the industry has to offer.
In addition, Pinterest can approach the market with a challenger mindset. Google and Facebook can almost be viewed as victims of their own success, with advertisers craving new options for their digital budgets.
Simply mimicking these two giants would reap little reward, so Pinterest is sticking to its inherent USPs. As a social network, it functions rather differently to Facebook and, as a search engine, it is distinct from Google. The combination of a new slant on the saturated social network space and the technology to capitalize on such a vast quantity of search data could be a winning one.
Pinterest Lens sits at the heart of this strategy. The visual search technology turns a user’s smartphone into a discovery tool, identifying objects and serving related search results. In our recent comparison of the best visual search technologies out there right now, Pinterest emerged the clear winner.
Conversely, Pinterest is late to the party, and the onus will be on them to prove that the platform can deliver a positive return on ad spend. Creating a self-serve product with similarities to AdWords may ease the transition for new users, but it also sets their expectations at a high level. AdWords, after all, remains unsurpassed as a means of generating online revenue.
Pinterest ads require a blend of creativity and analytical nous, which will demand collaboration between paid search and social media teams to make the most of the opportunity. People use this platform differently; advertisers need to tailor both their creative assets and their targeting strategies to reflect this.
There is a fine line to be trod here, of course, and there are few guarantees of success.
However, if Pinterest can deliver on the twin promises of creating a new, sophisticated form of PPC advertising and delivering great results against essential metrics like cost-per-acquisition, it could allow advertisers to capitalize on a previously untapped stage of the search purchase journey.
It will be fascinating to see the early results now that the self-serve platform is open to all marketers.
Visual search engines will be at the center of the next phase of evolution for the search industry, with Pinterest, Google, and Bing all announcing major developments recently.
How do they stack up today, and who looks best placed to offer the best visual search experience?
Historically, the input-output relationship in search has been dominated by text. Even as the outputs have become more varied (video and image results, for example), the inputs have been text-based. This has restricted and shaped the potential of search engines, as they try to extract more contextual meaning from a relatively static data set of keywords.
Visual search engines are redefining the limits of our language, opening up a new avenue of communication between people and computers. If we view language as a fluid system of signs and symbols, rather than fixed set of spoken or written words, we arrive at a much more compelling and profound picture of the future of search.
Our culture is visual, a fact that visual search engines are all too eager to capitalize on.
Already, specific ecommerce visual search technologies abound: Amazon, Walmart, and ASOS are all in on the act. These companies’ apps turn a user’s smartphone camera into a visual discovery tool, searching for similar items based on whatever is in frame. This is just one use case, however, and the potential for visual search is much greater than just direct ecommerce transactions.
After a lot of trial and error, this technology is coming of age. We are on the cusp of accurate, real-time visual search, which will open a raft of new opportunities for marketers.
Below, we review the progress made by three key players in visual search: Pinterest, Google, and Bing.
Pinterest’s visual search technology is aimed at carving out a position as the go-to place for discovery searches. Their stated aim echoes the opening quote from this article: “To help you find things when you don’t have the words to describe them.”
Rather than tackle Google directly, Pinterest has decided to offer up something subtly different to users – and advertisers. People go to Pinterest to discover new ideas, to create mood boards, to be inspired. Pinterest therefore urges its 200 million users to “search outside the box”, in what could be deciphered as a gentle jibe at Google’s ever-present search bar.
All of this is driven by Pinterest Lens, a sophisticated visual search tool that uses a smartphone camera to scan the physical world, identify objects, and return related results. It is available via the smartphone app, but Pinterest’s visual search functionality can be used on desktop through the Google Chrome extension too.
Pinterest’s vast data set of over 100 billion Pins provides the perfect training material for machine learning applications. As a result, new connections are forged between the physical and digital worlds, using graphics processing units (GPUs) to accelerate the process.
In practice, Pinterest Lens works very well and is getting noticeably better with time. The image detection is impressively accurate and the suggestions for related Pins are relevant.
Below, the same object has been selected for a search using Pinterest and also Samsung visual search:
The differences in the results are telling.
On the left, Pinterest recognizes the object’s shape, its material, its purpose, but also the defining features of the design. This allows for results that go deeper than a direct search for another black mug. Pinterest knows that the less tangible, stylistic details are what really interest its users. As such, we see results for mugs in different colors, but that are of a similar style.
On the right, Samsung’s Bixby assistant recognizes the object, its color, and its purpose. Samsung’s results are powered by Amazon, and they are a lot less inspiring than the options served up by Pinterest. The image is turned into a keyword search for [black coffee mugs], which renders the visual search element a little redundant.
Visual search engines work best when they express something for us that we would struggle to say in words. Pinterest understands and delivers on this promise better than most.
Pinterest visual search: The key facts
Over 200 million monthly users
Focuses on the ‘discovery’ phase of search
Pinterest Lens is the central visual search technology
Great platform for retailers, with obvious monetization possibilities
Paid search advertising is a core growth area for the company
Increasingly effective visual search results, particularly on the deeper level of aesthetics
Google made early waves in visual search with the launch of Google Goggles. This Android app was launched in 2010 and allowed users to search using their smartphone camera. It works well on famous landmarks, for example, but it has not been updated significantly in quite some time.
It seemed unlikely that Google would remain silent on visual search for long, and this year’s I/O development revealed what the search giant has been working on in the background.
Google Lens, which will be available via the Photos app and Google Assistant, will be a significant overhaul of the earlier Google Goggles initiative.
Any nomenclative similarities to Pinterest’s product may be more than coincidental. Google has stealthily upgraded its image and visual search engines of late, ushering in results that resemble Pinterest’s format:
Google’s ‘similar items’ product was another move to cash in on the discovery phase of search, showcasing related results that might further pique a consumer’s curiosity.
Google Lens will provide the object detection technology to link all of this together in a powerful visual search engine. In its BETA format, Lens offers the following categories for visual searches:
Some developers have been given the chance to try an early version of Lens, with many reporting mixed results:
Looks like Google doesn’t recognize its own Home smart hub… (Source: XDA Developers)
These are very early days for Google Lens, so we can expect this technology to improve significantly as it learns from its mistakes and successes.
When it does, Google is uniquely placed to make visual search a powerful tool for users and advertisers alike. The opportunities for online retailers via paid search are self-evident, but there is also huge potential for brick-and-mortar retailers to capitalize on hyper-local searches.
For all its impressive advances, Pinterest does not possess the ecosystem to permeate all aspects of a user’s life in the way Google can. With a new Pixel smartphone in the works, Google can use visual search alongside voice search to unite its software and hardware. For advertisers using DoubleClick to manage their search and display ads, that presents a very appealing prospect.
We should also anticipate that Google will take this visual search technology further in the near future.
Google is set to open its ARCore product up to all developers, which will bring with it endless possibilities for augmented reality. ARCore is a direct rival to Apple’s ARKit and it could provide the key to unlock the full potential of visual search. We should also not rule out another move into the wearables market, potentially through a new version of Google Glass.
Google visual search: The key facts
Google Goggles launched in 2010 as an early entrant to the visual search market
Goggles still functions well on some landmarks, but struggles to isolate objects in crowded frames
Google Lens scheduled to launch later this year (Date TBA) as a complete overhaul of Goggles
Lens will link visual search to Google search and Google Maps
Object detection is not perfected, but the product is in BETA
Google is best placed to create an advertising product around its visual search engine, once the technology increases in accuracy
Microsoft had been very quiet on this front since sunsetting its Bing visual search product in 2012. It never really took off and perhaps the appetite wasn’t quite there yet among a mass public for a visual search engine.
Recently, Bing made an interesting re-entry to the fray with the announcement of a completely revamped visual search engine:
This change of tack has been directed by advances in artificial intelligence that can automatically scan images and isolate items.
The early versions of this search functionality required input from users to draw boxes around certain areas of an image for further inspection. Bing announced recently that this will no longer be needed, as the technology has developed to automate this process.
The layout of visual search results on Bing is eerily similar to Pinterest. If imitation is the sincerest form of flattery, Pinterest should be overwhelmed with flattery by now.
The visual search technology can hone in on objects within most images, and then suggests further items that may be of interest to the user. This is only available on Desktop for the moment, but Mobile support will be added soon.
The results are patchy in places, but when an object is detected relevant suggestions are made. In the example below, a search made using an image of a suit leads to topical, shoppable links:
It does not, however, take into account the shirt or tie – the only searchable aspect is the suit.
Things get patchier still for searches made using crowded images. A search for living room decor ideas made using an image will bring up some relevant results, but will not always hone in on specific items.
As with all machine learning technologies, this product will continue to improve and for now, Bing is a step ahead of Google in this aspect. Nonetheless, Microsoft lacks the user base and the mobile hardware to launch a real assault on the visual search market in the long run.
Visual search thrives on data; in this regard, both Google and Pinterest have stolen a march on Bing.
Bing visual search: The key facts
Originally launched in 2009, but removed in 2012 due to lack of uptake
Relaunched in July 2017, underpinned by AI to identify and analyze objects
Advertisers can use Bing visual search to place shoppable images
The technology is in its infancy, but the object recognition is quite accurate
Desktop only for now, but mobile will follow soon
So, who has the best visual search engine?
For now, Pinterest. With billions of data points and some seasoned image search professionals driving the technology, it provides the smoothest and most accurate experience. It also does something unique by grasping the stylistic features of objects, rather than just their shape or color. As such, it alters the language at our disposal and extends the limits of what is possible in search marketing.
Bing has made massive strides in this arena of late, but it lacks the killer application that would make it stand out enough to draw searchers from Google. Bing visual search is accurate and functional, but does not create connections to related items in the way that Pinterest can.
The launch of Google Lens will surely shake up this market altogether, too. If Google can nail down automated object recognition (which it undoubtedly will), Google Lens could be the product that links traditional search to augmented reality. The resources and the product suite at Google’s disposal make it the likely winner in the long run.
Since the early 2010s, visual search has been offering users a novel alternative to keyword-based search results.
But with the sophistication of visual search tools increasing, and tech giants like Google and Microsoft investing heavily in the space, what commercial opportunities does it offer brands today?
Visual search 101
There are two types of visual search. The first compares metadata keywords for similarities (such as when searching an image database like Shutterstock).
The second is known as ‘content-based image retrieval’. This takes the colour, shape and texture of the image and compares it to a database, displaying entries according to similarity.
From a user perspective, this massively simplifies the process of finding products they like the look of. Instead of trying to find the words to describe the object, users can simply take a photo and see relevant results.
Visual search engines: A (very) brief history
The first product to really make use of this technology was ‘Google Goggles’. Released in 2010, it offered some fairly basic image-recognition capabilities. It could register unique objects like books, barcodes, art and landmarks, and provide additional information about them.
It also had the ability to understand and store text in an image – such as a photo of a business card. However, it couldn’t recognize general instances of objects, like trees, animals or items of clothing.
CamFind took the next step, offering an app where users could take photos of any object and see additional information alongside shopping results. My tests (featuring our beautiful office plant) yielded impressively accurate related images and web results.
More importantly for brands, it offers advertising based on the content of the image. However, despite the early offering, the app has yet to achieve widespread adoption.
So what do people use Pinterest for? Ben Silbermann, its CEO and co-founder, summed it up in a recent blog post:
“As a Pinner once said to me, “Pinterest is for yourself, not your selfies”—I love that. Pinterest is more of a personal tool than a social one. People don’t come to see what their friends are doing. (There are lots of other great places out there for that!) Instead, they come to Pinterest to find ideas to try, figure out which ones they love, and learn a little bit about themselves in the process.”
In other words, Pinterest is designed for discovery. Users are there to look for products and ideas, not to socialize. Which makes it inherently brand-friendly. In fact, 93% of Pinners said they use Pinterest to plan for purchases, and 87% said they’d bought something because of interest. Adverts are therefore less disruptive in this context than platforms like Facebook and Twitter, where users are focused on socializing, not searching.
Pinterest took their search functionality to the next level in February 2017 with an update offering users three new features:
Shop the Look allowed users to pick just one part of an image they were interested in to explore – like a hat or a pair of shoes.
Related Ideas gives users the ability to explore a tangent based on a single pin. For example, if I were interested in hideously garish jackets, I might click ‘more’ and see a collection of equally tasteless items.
Pinterest Lens was the heavyweight feature of this release. Linking to the functionality displayed in Shop the Look, it allowed users to take photos on their smartphone and see Pins that looked similar to the object displayed.
In practice, this meant a user might see a chair they were interested in purchasing, take a photo, and find similar styles – in exactly the same way as CamFind.
Pinterest Lens today
What does it mean for ecommerce brands?
Visual search engines have the potential to offer a butter-smooth customer journey – with just a few taps between snapping a picture of something and having it in a basket and checking out. Pinterest took a big step towards that in May this year, announcing they would be connecting their visual search functionality to Promoted Pins – allowing advertisers to get in front of users searching visually by surfacing adverts in the ‘Instant Ideas’ and the ‘More like this’ sections.
For retail brands with established Pinterest strategies like Target, Nordstrom, Walgreens and Lululemon, this is welcome news, as it presents a novel opportunity for brands to connect with users looking to purchase products.
Product images can be featured in visual search results
Nearly 2 million people Pin product-rich pins every day. The platform even offers the ability to include prices and other data on pins, which helps drive further engagement. Furthermore, it has the highest average order value of any major social platform at $50, and caters heavily to users on mobile (orders from mobile devices increased from 67% to 80% between 2013-2015).
But while Pinterest may have led the way in terms of visual search, it isn’t alone. Google and Bing have both jumped on the trend with Lens-equivalent products in the last year. Both Google Lens and Bing Visual Search (really, Microsoft? That’s the best you have?) function in an almost identical way to Pinterest Lens. Examples from Bing’s blog post on the product even show it being applied in the same contexts – picking out elements of a domestic scene and displaying shopping results.
One interesting question for ecommerce brands to answer will be how to optimize product images for these kinds of results.
Google Lens, announced at Google’s I/O conference in May to much furore, pitches itself as a tool to help users understand the world. By accessing Google’s vast knowledge base, the app can do things like identify objects, and connect to your WiFi automatically by snapping the code on the box.
Of course, this has a commercial application as well. One of the use cases highlighted by Google CEO Sundar Pichai was photographing a business storefront and having the Google Local result pop up, replete with reviews, menus and contact details.
The key feature here is the ability to connecting a picture taken with an action. It doesn’t take too much to imagine how brands might be able to use this functionality in interesting and engaging ways – for example, booking event tickets directly from an advert, as demonstrated at I/O:
Many marketers think we’re on the brink of a revolution when it comes to search. The growing popularity of voice search is arguably an indicator that consumers are moving away from keyword-based search and towards more intuitive methods.
It’s too soon to write off the medium entirely, of course – keywords are still by the far the easiest way to access most information. But visual search, along with voice, are certainly still useful additions to the roster of tools we might use to access information on the internet.
Ecommerce brands would be wise to keep close tabs on the progress of visual search tools; those that are prepared will have a significant competitive advance over those that aren’t.
This post was originally published on our sister site, ClickZ, and has been reproduced here for the enjoyment of our audience on Search Engine Watch.
There are millions of people on Pinterest, searching, pinning, and sharing – so it’s important to recognize its potential for building awareness and filling the top of the funnel, particularly for ecommerce companies.
This blog will discuss a couple of recommended targeting types within Pinterest to help fill the top of the funnel and essentially build up your audience. From there, once your audience is built out, we’ll run through how to actually capitalize on these new users to drive sales.
Let’s jump in.
Use Pinterest to fill the funnel
Pinterest has some specific features that are highly effective for building your audience. These include:
You can leverage user intent by targeting specific keywords that users are searching within Pinterest.
For example, if you are a trendy clothing brand that sells sweaters, you may want to target “trendy sweaters” and have your ad (in Pinterest lingo, your promoted pin) show up in the search results and related pins.
Pinterest will determine a user’s interest based on the pins they have engaged with and saved. Your ad (promoted pin) will show up in the user’s home feed or relevant topics feed.
A Promoted Pin on Pinterest
This is similar to Facebook’s lookalike targeting; you can upload a customer list and Pinterest will target audiences similar in behaviors, traits, and characteristics as that customer list. Our recommendation is to start off with your top customers – for example, your highest-LTV or AOV audiences.
I would initially recommend prioritizing the Actalike and keyword targeting as they tend to be more effective at getting in front of highly relevant audiences. But by leveraging any or all of the targeting options, you’re discovering and engaging with new, relevant audiences and driving them to your site.
That said, make sure your expectations are aligned. You should not expect to see Pinterest as a lever for immediate purchases, but more as a longer-term play where you’re developing an awareness and building your audience to hit later via a few different methods below to actually drive the sale.
That said, let’s talk about how to…
Convert Pinterest engagement into sales
Now that you’ve engaged with your audiences via Pinterest, you should be capturing those audiences for remarketing purposes.
First, to be smart with your remarketing efforts and truly understand the value of Pinterest, you should make sure every link on your Pinterest ads include a tag that labels it as Pinterest. You can use UTM parameters or anything else, but essentially you want to make sure that you can identify these audiences that have come through from Pinterest and segment them out.
You can then create specific audiences within both Google and Facebook (for example) that have come in through Pinterest. (E.g. url contains ‘utm_source=pinterest). Now you can separate out these audiences, and as you use them in your retargeting strategies, you can understand if the Pinterest audiences you have built are actually converting into sales.
Speaking of converting, I’d recommend the following methods:
RLSA (remarketing for search ads)
Layer your Pinterest audiences onto existing search campaigns and add a higher bid modifier. These audiences have already visited your site and developed a familiarity with your brand. If they end up searching for your product, you want to make sure your ad appears high in the search results to remind them of your brand, pull them to your site, and entice them to convert.
One RLSA strategy I’d recommend is to create a separate “broad” RLSA campaign where you can bid on head terms, and broader but still relevant terms that you normally wouldn’t be able to afford.
For example, you typically may not bid on a term like “womens clothing” because it is so generic and has heavy competition, but given the user has already visited your site, you can create an RLSA campaign, layer your Pinterest audiences, and bid on the term.
The thought behind this is that by serving your ad on this more generic keyword, you are reminding them that you sell women’s clothing. Since the users have been to your site, they’ll have a sense of if it’s worth visiting. Essentially, this is way of getting in front of relevant eyes without doing significant harm to overall efficiency.
You can do this on both Facebook and GDN where ads include the product the user has visited on the site (as well as other relevant products). The usual segmentation caveats apply; you want to make sure you’re segmenting by time lapsed since the visit and depth of site pages reached and bid accordingly.
Remarketing for shopping
Make use of your audience list by layering it onto your shopping campaigns. Again, the goal here is to bid more aggressively so you can ensure your ad shows up for the audiences who have engaged with your Pinterest ad, visited the site, and developed familiarity with the brand. You’ll typically see higher CVRs for these types of audiences.
The main takeaway here: if you’re not investing in Pinterest, you’re missing out on engaging a robust, potentially high-ROI audience. The platform itself has come a long way in adding marketing-friendly features and reporting capabilities to position itself as a long-term player. Get on board now; the traffic’s not getting any cheaper.