The world of search engine optimization (SEO) is indeed ever-changing. From algorithm updates to new SERP features to more sophisticated search tools, we have seen a lot of developments and changes in the SEO field over the past recent years. These shifts in the industry have not only revolutionized the way people conduct search, but also changed the way companies optimize and improve their websites and related online sources.
As such, staying on top of the ever-changing SEO landscape is a strong must if a website needs maximum popularity and visibility. Not only an outdate SEO strategy can lead to poor-performing website, it can also lead to heavy penalties which can drag its listings down in the SERPs of Google. If the business heavily rely on its website to generate leads and sales, outdated SEO tactics can mean loss of business and brand recognition as well.
Keep up with the latest techniques and make sure that your strategy is in line with the ongoing trends in the SEO industry. Here are the key takeaways from the infographic below that you should consider if you want to make the most out of your SEO efforts this 2018:
- More SEO will need to optimize for digital assistants.
- Leveraging the potential of new SERP features.
- The impending debut of the mobile-first index.
- Site speed will become more critical as a ranking factor.
- More development in visual search.
- More SEO will try the effectiveness of ‘link-less’ backlinks.
As the competition to get on top of search engines gets tougher, the need to adapt to these shifts in SEO also increases. If you want to learn more, check this infographic from Digital Marketing Philippines, which discusses the top trends that you should know if you want to improve your SEO strategy this 2018.
Read more at https://www.business2community.com/infographics/6-seo-trends-watch-2018-infographic-01997984
The arrival of the Pinterest Lens and Google Lens has ignited a battle for visual search engine supremacy. Beyond opening up a new revenue stream for e-commerce stores, visual search could completely alter consumer habits and purchasing decisions.
In a world driven by instant gratification, visual search can open the door toward “snap and surf” purchasing, streamlining the search interface. This provides a promising outlook for e-commerce stores that develop their product listing ads (PLAs) and online catalogs for the visual web.
While still in its infancy, optimizing for visual search could greatly improve your website’s user experience, conversion rate and online traffic. Yet images are often given very little attention by SEO experts, who generally focus more on optimizing for speed than for alternative attributes and appeal.
While visual search won’t displace the use of keywords and the importance of text-based search, it could completely disrupt the SEO and SEM industry. I’d like to discuss some of the fundamentals of visual search and how it will affect our digital marketing strategy moving forward.
What is visual search?
There are currently three different visual search processes being employed by major search companies:
- Traditional image search that relies on textual queries.
- Reverse image search that relies on structured data to determine similar characteristics.
- Pixel-by-pixel image searches that enable “snap and search” by image or by parts of the image.
In this article, I’m focusing mainly on the third type, which allows consumers to discover information or products online by simply uploading or snapping a picture and focusing their query on the part of the image they’d like to research. It’s essentially the same as text search, just with an image representing the query that’s being matched to it.
TinEye provided the first visual search application, which is still in use today. This form of image search matched the image to other images on the web based on similar characteristics, such as shapes and colors. Unfortunately, TinEye provided a limited range of search applications by failing to map out the outlines of different objects in an image.
Today’s image recognition technology can actually recognize multiple shapes and outlines contained within a single image to allow users to match to different objects. For example, Microsoft’s image search technology allows users to search for specific items pictured within a larger image.
Microsoft is even working on detecting when the selected portion of the image has a shopping intent, showing “related products” in these instances. Unfortunately, Microsoft’s visual search is fairly limited to a few verticals, such as home appliances and travel.
Right now, this technology is limited. What companies like Pinterest, Microsoft and Google are investing in is a visual search application powered by machine learning technology and deep neural networks.
The idea is to get machines to recognize different shapes, sizes and colors in images the same way the human brain does. When we look at specific pictures, we do not see a sea of points and dotted lines. We immediately identify patterns and shapes based on past experiences. Unfortunately, we still barely understand how our minds interpret images, so programming this into a machine presents some obvious complications.
Visual search engines have come to rely on neural networks that utilize machine learning technology to improve upon its process. Companies like Google benefit from their wealth of information that allows its Lens application to constantly improve upon its search functionality. Google Lens is not only able to identify different objects within pictures but is also able to match them to locations near you, provide customer reviews and sort listings by the same principles that govern its own search algorithms.
Implications and future
So, what does this technology entail for users and businesses? Imagine being able to snap a picture of a restaurant and have a search engine tell you the name of the restaurant, the location, peak demand times and menu specials for the night. This technology could feasibly be used to snap a picture of a pair of shoes from a magazine or from a stranger and enable you to order them right there.
For e-commerce stores, visual search puts people very high in the funnel. With some unique images, product reviews and a good product description, you can entice buyers to make a purchasing decision on the spot.
This will also open up the field of competition a little bit. The Pinterest visual search engine is by far one of the most disruptive on the market. However, Pinterest’s search engine only redirects pinners to posts on Pinterest, meaning you’ll need to develop a presence on this platform to reach those audience members.
With the rise of voice search and natural language processing (NLP) accompanying this trend, this technology could help kick-start the trend of interface-free SEO. (Although I suspect that keywords and text-based search will still retain its importance, even for shopping and purchasing decisions.)
In terms of optimizing for visual search, some of the most fundamental SEO practices will still apply. Structured data remains incredibly important, especially for visual search algorithms like Microsoft’s that still rely on it to match characteristics.
It’s important that images are displayed clearly and free of clutter so that visual applications have an easier time processing them. Beyond this, you should stick to the basics of image-based search optimization:
- Add descriptive alt-text to images for indexation.
- Submit images to an image sitemap.
- Optimize image titles and alternative attributes with targeted keywords.
- Set up image badges and run them through a structured data test.
- Optimize for ideal image size and file type.
- Utilize appropriate schema markup for images and content pages.
- Optimize images to render on mobile and desktop displays.
Visual search will provide a new revenue stream for e-commerce stores and vastly improve the user’s shopping experience. This could have a major impact on SEO and paid media, bringing back a renewed focus on image optimization, which has long been ignored by SEO practitioners. This new frontier of search will only reinforce existing strategies for SEO and make the need to optimize for mobile search and your visual web presence more prescient.
The future of search is visual, whether it’s on Amazon, Pinterest, or Google. Learn what this shift means for SEO and how to adapt.
I want to tell you a story about a young Google algorithm.
He was born blind, in a world where a picture is worth a thousand searches. This little algorithm had one dream. To be able to see. So he got his friends to describe him images, but still he couldn’t see.
He built magical Google Goggles, but these didn’t work. Then one day, he built a learning machine and finally, after years of struggle, he could recognize images.
That little algorithm who could is named visual search and has taken on a job as the world’s personal shopper.
Image Searches Are Now Commonplace
Look at the two options below, which is more useful if you wanted to buy a handbag?
Slyce asked that question to consumers. 74 percent of them replied that text-based keyword searches are inefficient in helping to find the right product online.
A 2017 report by Jumpshot & Moz further supports that discovery through pictures is alive and well, with around 27 percent of all searches being for images. MozCast reports image blocks in around 11 percent of Google results. While Jumpshots’ data shows images earn 3 percent of all Google search clicks.
Image SEO: The Early Years
Let’s be honest, image optimization is the dinosaur of the SEO world. Sure you sayyou implement image SEO for additional ranking opportunities in Google image search, but in most cases, you don’t truly believe this will have a significant impact on your KPIs.
When is the last time you looked at the sessions from image search in Google Analytics? Did you even notice years ago the change from the referral path /imgres under google.com referral to a fully fledged source medium as images.google.com?
Most of the image SEO best practices are more for user experience than search engines rankings. Take a critical look at common image optimization tips:
Primary Reason Behind Common Image Optimization Tips
- Rankings OtherShy away from stock to use original, high-quality images
- Shy away from stock to use original, high-quality images
- Context is key, be relevant to surrounding text
- Appropriate file format so images are crisp
- Optimize image file size for web page load times
- Use standard image ratios
- Use image dimensions large enough to be clearly visible on any device
- Add descriptive captions for users who scan
- Descriptive image file names
- Descriptive alt text
- Descriptive image titles
- Submit an image sitemap
- Schema markup
- Open Graph tags
- Twitter cards
- Beware of copyright
And one can argue descriptive image file names, alt text, and image titles are used as an opportunity to add a keyword in order to rank the page, not necessarily the image itself.
Not to say the image optimization tips above are not valuable. You should still do these things.
The hard truth is SEO professionals often neglect image optimization as an afterthought to page-level optimization, if it’s considered at all. And this level of image optimization alone is not going to be enough to win users.
So why are you reading about it…
The Rise of Visual Search
In the past there was image search, where search engines took a text-based query and tried to find the best visual match.
In the present there is visual search, where search engines, social networks, ecommerce powerhouses, startups and many companies in between take an image as the query.
A change in consumer behavior is happening. In the words of Jeffrey Gitomer “people don’t like to be sold to, but they love to buy.”
When you see something you’re interested in, whether it’s online or offline, you want a fast an easy way to get more information.
For example, you see a pair of shoes in a magazine. With image recognition, you can take a photo and find similar item for sale online.
This see-snap-buy behavior is becoming commonplace and has opened up opportunities for companies to enter the purchase cycle with the photo as the search query. This places them higher in the conversion funnel than a text-based search query.
Visual search is fast becoming a staple of shopping apps. And with the impact on KPIs, it’s no surprise why.
BloomReach found that visual search is associated with 48 percent more product views. Consumers are 57 percent more likely to make a return visits and spend on average 9 percent more on mobile than those who do not use it.
Amazon, Pinterest, and many more have launched visual search capabilities on mobile. There is a battle of the brands to be your snap and shop app of choice.
At present, early adopters Amazon (turning the world into a hyperlink) and Pinterest (promoting on online discovery) are leading the pack. But Google isn’t taking this lying down.
Visual Search & Google
Google has been quietly adding machine learning and image recognition capabilities to mobile image search over the last years. Plotting the updates, you can see clear stepping stone technologies building on the theme of visual search.
- Related images (April 2013): Click on a result to view visually similar images.
- Collections (November 2015): Allows users to save images directly from Google’s mobile image search into folders. Google’s answer to a Pinterest board.
- Product images in web results (October 2016): Product images begin to display next to website links in mobile search.
- Product details on images (December 2016): Click on an image result to display product price, availability, ratings, and other key information directly in the image search results.
- Similar items (10th April 2017): Google can identify products, even within lifestyle images, and showcases similar items you can buy online.
- Style ideas (April 17, 2017): The flip side to similar items. When browsing fashion product images on mobile, Google shows you outfit montages and inspirational lifestyle photos to highlight how the product can be worn in real life.
- Image badges (August 1, 2017): Label on the image indicate what other details are available, encouraging more users to click. For example, badges such as “recipe” or a timestamp for pages featuring videos. But the most significant badge is “product” – shown if the item is available for purchase online.
These developments highlight that Google is making a play to turn image search into shoppable product discovery. It’s easier to show than tell.
The new visual search capabilities are all algorithmically selected based on a combination of schema and image recognition. Google told TechCrunch:
“The images that appear in both the style ideas and similar items grids are also algorithmically ranked, and will prioritize those that focus on a particular product type or that appear as a complete look and are from authoritative sites.”
How To Get Your Brand’s Images Featured
1. Implement Schema Markup
Badges are simple enough to win:
- For the recipe badge, use recipe markup.
- For the video badge, use video markup.
- For the product badge, use product markup.
Getting into the Similar Items and Related Items sections are a touch more challenging. To do this, ensure you have product markup on the host page with the meta-data minimum requirement:
But the more quality detail, the better, as it will make your results more robust. How product markup elements are populated into Google image search is shown below.
2. Validate Your Implementation
Run a few URLs through Google’s Structured Data Testing Tool. Don’t simply scan if there are no errors and move on. Be sure to look at the information itself to ensure it’s user-friendly.
It can take up to one week for your site’s images to be crawled. Like all schema markup, how items display in search results is at Google’s discretion and not guaranteed. However, quality markup will “increase the chance” of your images showing up.
4. Do a Site:Yourdomain.Com Query
Why your own site? To confirm your images have been indexed. Be sure to do this image search on mobile web or in the Android Search app. It is a mobile-first world. Not all image search functionality is visible on desktop.
If you see no image results badges, you likely have an implementation issue. Go back to step two.
If you see badges, click a couple to ensure they show your ideal markup in the details. Once you confirm all is well, then you can begin to search for your targeted keywords to see how you rank and if you are eligible for Similar Items or Related Items.
Note: While Badges and Related Items are common, Similar Items only cover a limited number of products in fashion. Google says it will expand in the coming months.
The Next Steps for Visual Search
The future is “Lens” – using your smartphone to translate real world input to digital action. No more QR codes or snap tags.
Markerless image recognition is coming. A world where nothing needs to be done to an image or object to turn it into a visual trigger to cue digital content. The static world becomes digitally connected simply by pointing your phone at it.
Both Pinterest and Google have the functionality, but I’ll let Google CEO Sundar Pichai explain in more detail:
I can envision:
- Product packaging coming to life. You point your phone at the product and it displays recipe possibilities, maps to nearby stores with the item in stock or coupon for an online order.
- Billboards of celebrities endorsing products will naturally connect you to the store to buy the product, but may also provide the latest gossip on that celebrity.
- Stranger’s outfits become walking ads when I can snap a pic and literally buy the shirt off their back. This will be a world where you can spontaneously buy most items you can see.
That is the power of visual search.
So, what are you doing to make your brand more visually appealing?
Visual search is one of the most complex and fiercely competed sectors of our industry. Earlier this month, Bing announced their new visual search mode, hot on the heels of similar developments from Pinterest and Google.
Ours is a culture mediated by images, so it stands to reason that visual search has assumed such importance for the world’s largest technology companies. The pace of progress is certainly quickening; but there is no clear visual search ‘winner’ and nor will there be one soon.
The search industry has developed significantly over the past decade, through advances in personalization, natural language processing, and multimedia results. And yet, one could argue that the power of the image remains untapped.
This is not due to a lack of attention or investment. Quite the contrary, in fact. Cracking visual search will require a combination of technological nous, psychological insight, and neuroscientific know-how. This makes it a fascinating area of development, but also one that will not be mastered easily.
Therefore, in this article, we will begin with an outline of the visual search industry and the challenges it poses, before analyzing the recent progress made by Google, Microsoft and Pinterest.
What is visual search?
We all partake in visual search every day. Every time we need to locate our keys among a range of other items, for example, our brains are engaged in a visual search.
We learn to recognize certain targets and we can locate them within a busy landscape with increasing ease over time.
This is a trickier task for a computer, however.
Image search, in which a search engine takes a text-based query and tries to find the best visual match, is subtly distinct from modern visual search. Visual search can take an image as its ‘query’, rather than text. In order to perform an accurate visual search, search engines require much more sophisticated processes than they do for traditional image search.
Typically, as part of this process, deep neural networks are put through their paces in tests like the one below, with the hope that they will mimic the functioning of the human brain in identifying targets:
The decisions (or inherent ‘biases’, as they are known) that allow us to make sense of these patterns are more difficult to integrate into a machine. When processing an image, should a machine prioritize shape, color, or size? How does a person do this? Do we even know for sure, or do we only know the output?
As such, search engines still struggle to process images in the way we expect them to. We simply don’t understand our own biases well enough to be able to reproduce them in another system.
There has been a lot of progress in this field, nonetheless. Google image search has improved drastically in response to text queries and other options, like Tineye, also allow us to use reverse image search. This is a useful feature, but its limits are self-evident.
For years, Facebook has been able to identify individuals in photos, in the same way a person would immediately recognize a friend’s face. This example is a closer approximation of the holy grail for visual search; however, it still falls short. In this instance, Facebook has set up its networks to search for faces, giving them a clear target.
At its zenith, online visual search allows us to use an image as an input and receive another, related image as an output. This would mean that we could take a picture with a smartphone of a chair, for example, and have the technology return pictures of suitable rugs to accompany the style of the chair.
The typically ‘human’ process in the middle, where we would decipher the component parts of an image and decide what it is about, then conceptualize and categorize related items, is undertaken by deep neural networks. These networks are ‘unsupervised’, meaning that there is no human intervention as they alter their functioning based on feedback signals and work to deliver the desired output.
The result can be mesmerising, as in the below interpretations of an image of Georges Seurat’s ‘A Sunday Afternoon on the Island of La Grand Jatte’ by Google’s neural networks:
This is just one approach to answering a delicate question, however.
There are no right or wrong answers in this field as it stands; simply more or less effective ones in a given context.
We should therefore assess the progress of a few technology giants to observe the significant strides they have made thus far, but also the obstacles left to overcome before visual search is truly mastered.
Bing visual search
In early June at TechCrunch 50, Microsoft announced that it would now allow users to “search by picture.”
This is notable for a number of reasons. First of all, although Bing image search has been present for quite some time, Microsoft actually removed its original visual search product in 2012. People simply weren’t using it since its 2009 launch, as it wasn’t accurate enough.
Furthermore, it would be fair to say that Microsoft is running a little behind in this race. Rival search engines and social media platforms have provided visual search functions for some time now.
As a result, it seems reasonable to surmise that Microsoft must have something compelling if they have chosen to re-enter the fray with such a public announcement. While it is not quite revolutionary, the new Bing visual search is still a useful tool that builds significantly on their image search product.
A Bing search for “kitchen decor ideas” which showcases Bing’s new visual search capabilities
What sets Bing visual search apart is the ability to search within images and then expand this out to related objects that might complement the user’s selection.
A user can select specific objects, hone in on them, and purchase similar items if they desire. The opportunities for retailers are both obvious and plentiful.
It’s worth mentioning that Pinterest’s visual search has been able to do this for some time. But the important difference between Pinterest’s capability and Bing’s in this regard is that Pinterest can only redirect users to Pins that businesses have made available on Pinterest – and not all of them might be shoppable. Bing, on the other hand, can index a retailer’s website and use visual search to direct the user to it, with no extra effort required on the part of either party.
Powered by Silverlight technology, this should lead to a much more refined approach to searching through images. Microsoft provided the following visualisation of how their query processing system works for this product:
Microsoft combines this system with the structured data it owns to provide a much richer, more informative search experience. Although restricted to a few search categories, such as homeware, travel, and sports, we should expect to see this rolled out to more areas through this year.
The next step will be to automate parts of this process, so that the user no longer needs to draw a box to select objects. It is still some distance from delivering on the promise of perfect, visual search, but these updates should at least see Microsoft eke out a few more sellable searches via Bing.
Google recently announced its Lens product at the 2017 I/O conference in May. The aim of Lens is really to turn your smartphone into a visual search engine.
Take a picture of anything out there and Google will tell you what the object is about, along with any related entities. Point your smartphone at a restaurant, for example, and Google will tell you its name, whether your friends have visited it before, and highlight reviews for the restaurant too.
This is supplemented by Google’s envious inventory of data, both from its own knowledge graph and the consumer data it holds.
All of this data can fuel and refine Google’s deep neural networks, which are central to the effective functioning of its Lens product.
Google-owned company DeepMind is at the forefront of visual search innovation. As such, DeepMind is also particularly familiar with just how challenging this technology is to master.
The challenge is no longer necessarily in just creating neural networks that can understand an image as effectively as a human. The bigger challenge (known as the ‘black box problem’ in this field) is that the processes involved in arriving at conclusions are so complex, obscured, and multi-faceted that even Google’s engineers struggle to keep track.
This points to a rather poignant paradox at the heart of visual search and, more broadly, the use of deep neural networks. The aim is to mimic the functioning of the human brain; however, we still don’t really understand how the human brain works.
As a result, DeepMind have started to explore new methods. In a fascinating blog post they summarized the findings from a recent paper, within which they applied the inductive reasoning evident in human perception of images.
Drawing on the rich history of cognitive psychology (rich, at least, in comparison with the nascent field of neural networks), scientists were able to apply within their technology the same biases we apply as people when we classify items.
DeepMind use the following prompt to illuminate their thinking:
“A field linguist has gone to visit a culture whose language is entirely different from our own. The linguist is trying to learn some words from a helpful native speaker, when a rabbit scurries by. The native speaker declares “gavagai”, and the linguist is left to infer the meaning of this new word. The linguist is faced with an abundance of possible inferences, including that “gavagai” refers to rabbits, animals, white things, that specific rabbit, or “undetached parts of rabbits”. There is an infinity of possible inferences to be made. How are people able to choose the correct one?”
Experiments in cognitive psychology have shown that we have a ‘shape bias’; that is to say, we give prominence to the fact that this is a rabbit, rather than focusing on its color or its broader classification as an animal. We are aware of all of these factors, but we choose shape as the most important criterion.
“Gavagai” Credit: Misha Shiyanov/Shutterstock
DeepMind is one of the most essential components of Google’s development into an ‘AI-first’ company, so we can expect findings like the above to be incorporated into visual search in the near future. When they do, we shouldn’t rule out the launch of Google Glass 2.0 or something similar.
Pinterest aims to establish itself as the go-to search engine when you don’t have the words to describe what you are looking for.
The launch of its Lens product in March this year was a real statement of intent and Pinterest has made a number of senior hires from Google’s image search teams to fuel development.
In combination with its establishment of a paid search product and features like ‘Shop the Look’, there is a growing consensus that Pinterest could become a real marketing contender. Along with Amazon, it should benefit from advertisers’ thirst for more options beyond Google and Facebook.
Pinterest president Tim Kendall noted recently at TechCrunch Disrupt: “We’re starting to be able to segue into differentiation and build things that other people can’t. Or they could build it, but because of the nature of the products, this would make less sense.”
This drives at the heart of the matter. Pinterest users come to the site for something different, which allows Pinterest to build different products for them. While Google fights war on numerous fronts, Pinterest can focus on improving its visual search offering.
Admittedly, it remains a work in progress, but Pinterest Lens is the most advanced visual search tool available at the moment. Using a smartphone, a Pinner (as the site’s users are known) can take a picture within the app and have it processed with a high degree of accuracy by Pinterest’s technology.
The results are quite effective for items of clothing and homeware, although there is still a long way to go before we use Pinterest as our personal stylist. As a tantalising glimpse of the future, however, Pinterest Lens is a welcome and impressive development.
The next step is to monetize this, which is exactly what Pinterest plans to do. Visual search will become part of its paid advertising package, a fact that will no doubt appeal to retailers keen to move beyond keyword targeting and social media prospecting.
We may still be years from declaring a winner in the battle for visual search supremacy, but it is clear to see that the victor will claim significant spoils.
10 Pinterest SEO Tips That Will Set You up for Success
Pinterest has slowly developed into a profitable social media channel for savvy marketers. It boasts an engaged base of more than 150 million monthly usersand provides a refreshing alternative to Google, Facebook, and Amazon.
However, it still represents something of an untapped opportunity for many of us in the SEO industry. As a social media platform, Pinterest seems to sit apart from our Google-focused efforts.
We should embrace this difference. Pinterest provides ample room for creativity and storytelling, while it also prides itself on being a “discovery” platform where Pinners can find new ideas. These are terms that should be familiar to the multi-skilled modern SEO professional.
Pinterest also offers a lot of value as an alternative search marketing channel. Did you know:
- 97 percent of Pinterest searches in 2016 were non-branded.
- 80 percent of Pinterest’s traffic is mobile.
- More than 2 billion searches take place on Pinterest each month.
- Visual search accounts for more than 250 million of the monthly searches on Pinterest.
All of this is underpinned by a search engine. It differs from Google or Bing, but many of our time-honored tactics still hold true. Where there is a search engine, there will be an opportunity for optimization.
The ranking factors on Pinterest relate more to engagement metrics and social shares than backlinks and technical SEO, but these are natural byproducts of great content. Again, we in the SEO industry should know all about that.
There are some important distinctions on Pinterest too, as we would expect. Without understanding the way search results are ranked and what exactly constitutes “great content,” you will struggle to succeed in Pinterest SEO.
With that in mind, below are 10 tips to set your Pinterest profile up for SEO success.
1. Get the Basics Right
Before we get into the more exciting aspects of Pinterest, some housekeeping. You’ll need to ensure the following aspects are in place before you can start posting:
- Create a business account. (You can simply convert your personal account if that makes the most sense.) This will give you access to analytics and the Pinterest ads manager.
- Choose an SEO friendly username. Your username will be included in your profile’s URL, so it’s worth considering what your consumers might be searching for.
- Optimize your profile. Fill in the “about you” section with relevant details and include a high-resolution company logo. This will make it easier for people to locate and save your Pins.
- Set up at least one board. We will go through this in more detail later, but to get started you will need at least one board. You can’t add Pins without having a board, so it’s a pretty important first step.
2. Prepare Your Website
As with most other social media platforms, you can take data from your website to feed more targeted Pinterest campaigns. You can also send people through to your website to make a transaction, so it’s essential to link these two assets together.
This requires a few simple but fundamental steps. Get all of these in place if you want to report accurately on your Pinterest SEO efforts.
- Add the Save button. This one requires just a short piece of HTML code and will allow you to increase the reach of your campaigns beyond Pinterest. Once installed, users can save images on your site or app to their boards. There are two options: The button can appear automatically or when users hover over the top-left section of an image. Choose wisely. There is also a Pinterest Chrome extension that will allow visitors on your site to convert your images into Pins.
- Verify your site: A few easy steps will verify your website, which will add your profile picture to all of your Pins. Again, this only requires the addition of a few lines of HTML code.
3. Set Appropriate Goals for Your Business
Lead times on Pinterest can be much longer than you’re used to on Google or even Facebook.
The image below, taken from a Pinterest study, demonstrates just how valuable this social network can be as a lead generation tool, however.
Therefore, although it entails a different type of user engagement, Pinterest also fills a gap in the purchase journey.
The most important element of this planning is to understand what Pinterest means for your business and set appropriate goals. You will get a sense of this from looking at your historical data, so use this to formulate a plan you can stick to. From here, you can decide which aspects are most suitably covered by organic search efforts.
You can use the Pinterest tag to set up a wide variety of conversion events on your site, too. I would advise starting with metrics like traffic and re-Pins within a Pinterest SEO campaign, before layering conversion goals on top of this activity.
Wait to start pushing overtly commercial messages until you’ve earned the trust of both Pinterest and your audience.
4. Do Your (Keyword) Research
Albeit through a slightly different lens, there is still a lot of validity in carrying out keyword research on Pinterest. In fact, as Google continues to aggregate and obscure keyword-level search volumes, there’s an argument that we should use Pinterest as a data source for all keyword research tasks. It provides a broader view of semantically related concepts and is driven by a deep understanding of how visual our culture is in the 21st century.
The following tips should help you discover the right topics for your Pins and boards:
- Use guided search. Guided search on Pinterest helps users narrow their focus and find more relevant results. Using the initial search query as a stimulus, Pinterest automatically suggests semantically related modifiers. These are a pretty good indicator of the most popular search queries for each topic. You can then copy and paste these suggestions into another document.
- Engage with Promoted Pins. The logic here is similar (identical, in fact) to that which leads us to use AdWords to trial specific keywords to see how they perform before launching a long-term SEO campaign. If you have any hesitations about the right topics to target, you can take your best-performing keywords on Google and use Promoted Pins to see if they follow suit on Pinterest.
- Explore topics. Pinterest does a lot of the legwork for us here, with topics already neatly categorized and sub-categorized in most areas. You should explore all topics relevant to your business to see how ideas are categorized, but also to see how your competitors are targeting specific queries.
5. Organize and Optimize Boards
Your keyword and consumer research for Pinterest should be a core consideration when you start to create boards. They provide a great opportunity to tell Pinterest’s search engine how you categorize your products, which will only aid visibility. They are also the first thing users will see when they come to your profile, so it is worth thinking this through.
Nordstrom is often cited as the market leader in this sense. Their boards cover pretty much every interaction one could reasonably expect a consumer to have with their brand.
This consumer insight is combined with a subtle nod to keyword search trends, with board titles including ‘Style Under $100’, ‘Winter Fashion’, and ‘Beach Wedding Ideas’. They steer clear of disrupting the user experience and still manage to include popular keywords.
This approach should be seen as the blueprint for creating and optimizing Pinterest boards. However, boards need to be populated with high-quality Pins if they are to gain popularity.
6. Get to Know the Anatomy of a Pin
There is art and science to the creation of a perfect Pin. Although there will always be an instinctual creative drive behind the best campaigns, there are still some clear rules of thumb that we should all follow.
- Get your proportions right. The optimal aspect ratio for a Pin is 2:3 (600 px wide by 900 px high). This is particularly important on mobile, but Pinterest prefers to display longer images on desktop too.
- Use multiple colors. Images with multiple dominant colors get re-pinned 3.25 times more than their monochrome counterparts.
- Have a purpose. We need to understand the purpose of each Pin. Users create mood boards that they will return to multiple times, after all. Think about how you can be of repeat value to someone, rather than just pushing commercial messages. Step-by-step guides and tutorials work well in this regard.
7. Be Descriptive
It’s important to get descriptions right for SEO on Pinterest. For all of its significant merits as a visual discovery platform, text still matters. Don’t be afraid to include detail, as this will help Pinterest locate and serve your images for relevant searches.
A great way to do this is to use the description space to add to your image, rather than just repeating what it says via text. Tell your audience how the product will benefit them, how they can use it, or an interesting fact about the product they wouldn’t otherwise know.
You can include up to 500 characters, which can all be viewed when a user clicks to see your Pin. There is typically no need to go to that upper limit, however. A couple of sentences of around 100 characters in total is sufficient to provide some good detail.
Avoid using hashtags in your descriptions. These tend to be distracting and don’t add anything in the way of ranking value.
8. Aim for Engagement
User engagement is of paramount importance on Pinterest. The following tips can improve your engagement metrics and increase your search visibility:
- Link your Pinterest account to your other social media accounts. This will increase awareness within your existing followers on other platforms.
- Invite relevant Pinterest influencers to collaborate on a board to grow your own following.
- Include text as an overlay on your images. As we can see for a search like [summer cocktails], Pins with a text overlay tend to rank well:
- Use a website like Canva to create mosaics and multi-image Pins. This allows a bit more freedom for creativity and room to include more within Pinterest’s vertical image format.
- Pin frequently. This study from Buffer found that you should aim for at least five Pins per day. These Pins can be scheduled ahead of time.
- Follow relevant boards. This will start to build up a network in relation to your profile.
- Measure your performance. Pinterest analytics will give you a lot of insight into how your profile is performing in organic search, and integrated dashboards like Datorama can now pull in Pinterest data.
9. Consider Visual Search and ‘Related Items’
Pinterest’s Lens technology is a market leader in visual search. By pointing a smartphone camera at a household item or piece of clothing, Pinterest can identify the object and suggest thematically related Pins.
Lens is a fascinating piece of technology that will reward content creators who put the time and effort into image optimization. This involves the SEO basics, but it extends beyond this into collaboration with photographers and designers.
Going back to a screenshot I used earlier in this article, I also uploaded this image to Pinterest to see how the platform evaluates content. Of interest here is the visual similarity between the image I posted and the Related Pins below (apart from the paid ad for bed linen on the right-hand side).
Pinterest is getting a lot better at understanding the component parts of an image. Its image recognition technology has identified the pie charts in my screenshot and suggested other popular pie chart-based posts. I made no reference to the shapes within my description, so Pinterest has had to figure this one out on its own.
This is important to note. If SEO comprises anything that helps content rank organically, on Pinterest we need to be thinking about aesthetics in tandem with keywords.
10. Don’t Forget About Google
Pinterest takes SEO seriously. They know that it is a cost-effective way to drive traffic, but they also know it takes a lot of work. This fascinating post on Medium from 2015 details exactly how fanatical Pinterest are about finding the right SEO formula.
They rank for a lot of keywords, as a result.
The screenshot below is taken from Searchmetrics and shows the significant improvement Pinterest has seen over the past 5 years.
We can make great use of Pinterest as a platform for our own SEO efforts.
By identifying the relevant keywords that Pinterest ranks for, we can optimize for the most profitable queries with our Pins and boards. If Pinterest deems you relevant enough to rank for that keyword via its own search algorithms, your organic Pinterest traffic will increase significantly.
This will allow you to prioritize your Pinterest SEO efforts, as you can target the keywords that will drive most value from both Pinterest search and Google search.
Visual search might never replace text-based search, but in an industry that relies on images to appeal to its audience, it’s a trend to watch out for.
Earlier this year, Nemanja Darijevic, Creative and Development Director of Pixel Road Designs, joined SEJ ThinkTank to talk about the future of visual marketing. In his talk, Darijevic gave us a powerful reminder of just how important great visuals are to SEO and e-commerce in 2016, with facts such as:
- Our brains process images 60,000x faster than text.
- After three days, customers still retain 65% of visual stimuli versus just 10% of auditory stimuli.
- Consumers are 80% more willing to engage with content that includesrelevant images.
- Content with relevant images earn 94% more views than content without images.
- Images are the most important deciding factor when making a purchase, according to 93% of consumers.
Of course, marketing experts have known for a long time that compelling images are necessary to increase conversions. This isn’t news. And Google continues to prove how important great images are to SEO by re-emphasizing its image searching and reverse image searching features year after year.
However, one problem continues to plague consumers and e-commerce retailers—it’s exceedingly difficult to find specific products using a text query. This is especially true when users lack certain information or don’t know how to describe a certain product. Keywords only take you so far when descriptors like “black dress shoes” apply to hundreds, if not thousands, of products.
Enter visual search, which aims to change the way we find products online. Unlike image search (which returns images for a text-based query) or reverse image search (which often relies on metadata to matching results), visual search uses pixel-by-pixel comparisons to return results with similar brands, styles, and colors.
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As Linda Bustos says in her GetElastic post, “Visual search ‘reads’ images to identify color, shape, size and proportions, even text to identify brand and product names. This offers an advantage over keyword-matched search, in which results are only as good as the searcher’s ability to describe them.”
Visual Search on Pinterest
Visual search isn’t new. Google bought Like.com back in 2010, and even before that the technology was being used by Zappos. But one platform that’s quickly become a favorite haunt of e-commerce sites didn’t adopt visual search technology until late 2015. Naturally, I’m talking about Pinterest.
For many online retailers, Pinterest is a home away from home. With more than 100 million monthly active users, a built-in “Buy” button, and its “promoted pins” advertising unit, Pinterest has expanded the reach of numerous brands and introduced them to an entirely new audience.
Now Pinterest has also implemented a visual search feature: “Sometimes you spot something you really love on Pinterest, but you don’t know how to find it in real life, or what it’s even called… Well, now we’ve got a new tool that lets you find all those things you don’t have the words to describe.”
This new search method allows users to click on the visual search icon at the top of their screen and then click on any object in an image. Pinterest then automatically filters through similar pins, showing users where they can purchase products related to the one that caught their eye.
As Kate Ahl says in her Q&A Friday Podcast, “For those who sell products, this is [a] great way for you not only to be encouraged to pin your product pictures, but pin your products in a lifestyle picture as well. Imagine these boots on someone with a pair of jeans and a really cute jacket. I could hover over the boots in the picture and Pinterest would pull up matching related searches for those boots.”
Showing customers examples of what to wear, how to decorate a room, or otherwise use your products will help them envision life after making a purchase. These images are also useful for cross-merchandizing other products that complement your main offering.
Visual search has plenty of benefits for e-commerce sites outside of Pinterest as well. Here are three big advantages that visual search has over text-based search when it comes to on-page and off-page SEO:
1. Reduce Extra Steps
The checkout process is one of the biggest killers of e-commerce conversions. The typical checkout process asks customers to do a variety of things, such as sign-in or create an account, fill in personal information, fill in payment information, and make choices regarding gift wrap, coupons, etc.
KISSmetrics warns that most online shoppers don’t make it past your checkout, because “[each] option creates an unnecessary disconnect between the user and their goal—buying the product.”
The same is true for the buying process. The more hoops a customer has to jump through to find the product they want, the less likely they are to click the “Checkout” button at the end of the process. Visual search eliminates the tedious querying by bringing users straight to the products that match their image.
Visual search also aids users who are “spear fishing,” i.e. searching for one specific product. Visual search general yields more targeted results that appeal to these highly qualified leads.
In the end, visual search translates to better usability. Assuming that your visual search results are accurate, your users will enjoy a more positive experience on your website. Eliminating unnecessary steps for your customers should be an integral part of your usability testing.
2. Refine On-Site Search
Qualified leads looking for specific products usually want more control over their search parameters. Visual search technology allows users to refine their searches beyond keywords, by recommending products based on visual similarity, complementary styles, and other items that customers have viewed.
There are multiple benefits to refining your on-site search functionality, including:
- Increased customer satisfaction: Make browsing your site painless and easy.
- Increased engagement: Customers intuitively narrow their searches to find the perfect fit.
- Simplified buying process: Customers spend less time searching through menus.
- Higher conversion rates: Customers hit fewer dead ends on their path to your checkout.
- More sales: Cross-promote products by suggesting complementary pairings.
3. Eliminate Dead Ends
There are two dead ends that customers might face when searching for your products.
The first dead end happens off-page, and it can occur long before customers ever find your website. For example, on websites like Pinterest, users can see your products without ever visiting your home page.
Visual search solves this problem, by allowing users to find items that visually fit and continue searching for products that match their selection. According to Ahl, “The great part about [visual search] is that this prevents the dead links that we all dread—when we click on an item and we click through and we can’t find it.”
The second dead end occurs on-page, when users can’t find what the product they’re looking for, so they leave your website. While you might not have an exact match in stock, a cleverly implemented visual search program might show customers a suitable replacement for their query. By matching their style, color, and size preferences, you can ensure that your users always find something they like.
How to Get Started With Visual Search
If you want to add visual search to your e-commerce site, there are numerous options available, such as Slyce , Visenze, and Cortexica. You can also find more niche offerings, such as Snap Fashion, which focuses exclusively on clothing, but has its own app and marketplace featuring more than 16,000 brands.
However, as with all applications designed to improve user experience or augment your SEO, there’s no point to these changes if you don’t measure your results and continue tweaking. After you’ve implemented visual search on your e-commerce website, make sure you monitor:
- Conversion rates
- Click through rates
- Abandoned shopping carts
- Product views
- Bounce rates
- Inbound links
Pay close attention to how your customers find you, e.g. Pinterest, Google, or your other paid channels. The end goal is conversion, but visual search and an amazing user experience won’t help you if customers can’t find your website in the first place. Using a tool such as LinkAssistant (disclaimer: my tool) will help you improve your outreach and chase down high-quality link opportunities.
Will Visual Search Replace Text-Based Search?
Text keywords remain an important part of how search engines find and catalogue your images, so it should go without saying that even if you implement visual search, you’ll still need rich keywords and detailed metadata. That said, the basis of a truly great visual search platform is compelling images.
As David Amerland says, “As a marketer or a business owner, you should be building your identity on the visual web with the same care and attention that you are building it in the more conventional text-driven one.”
Visual search will probably never replace text-based search, but in an industry that’s already wholly reliant on beautiful images to appeal to its audience, it’s certainly a trend to watch out for.