The evolution of Pinterest Lens and Google Lens has sparked a competition for visual search engine dominance. In addition to creating a new income stream for e-commerce retailers, visual search has the potential to radically transform consumer behaviors and purchase choices based on SEO Malaysia.
In a society where rapid satisfaction is the norm, visual search may facilitate “snap and surf” purchase by simplifying the search experience. This bodes well for e-commerce retailers who optimize their product listing advertising (PLAs) and online catalogues for the visual web.
While visual search is still in its infancy, preparing your website for visual search might significantly increase the user experience, conversion rate, and internet traffic. However, SEO specialists often pay little attention to photos, since they typically priorities optimizing for speed above other qualities and aesthetics.
While visual search will not replace the usage of keywords and the significance of text-based search, it has the potential to totally upset the SEO and SEM industries. I would want to explore the foundations of visual search and how it will impact our future digital marketing approach.
What exactly is visual search?
There are now three distinct visual search methods used by major search engines:
Text-based picture search is the conventional method.
Reverse image search that utilizes structured data to identify related attributes.
Pixel-by-pixel image searches that allow “snap and search” by picture or by image segments.
This article focuses mostly on the third kind, which enables users to find information or items online by uploading or taking a photo and focusing their query on the desired portion of the image. It is largely identical to text search, except that a picture represents the query being matched to it.
TinEye created the first programme for visual search, which is still in use today. This kind of image search compared the picture to other images on the web with comparable attributes, such as forms and colors. TinEye provides a restricted range of search applications because to its inability to trace the outlines of various visual objects.
The image recognition technology of today can distinguish many forms and contours inside a single picture, allowing users to match to various things. Microsoft’s image search technology, for instance, enables users to search for particular objects inside a bigger image.
Microsoft is also working on determining whether a piece of a picture has a purchasing intent and displaying “similar items” in these circumstances. Unfortunately, Microsoft’s visual search is confined to a small number of sectors, like home appliances and tourism.
Currently, this technique has limitations. The visual search application that Pinterest, Microsoft, and Google are investing in is driven by machine learning and deep neural networks.
The goal is for robots to detect forms, sizes, and colors in pictures similarly to how the human brain does. When we see individual images, we do not observe a sea of dots and points. We recognize patterns and forms instantaneously based on our prior experiences. Unfortunately, we scarcely understand how the human mind interprets visuals, so encoding this into a computer raises obvious challenges.
Visual search engines have grown to depend on neural networks that use machine learning technologies in order to optimize their operation. Companies such as Google gain from their amount of data, which enables the Lens programme to continuously enhance its search capabilities. Google Lens is not only capable of identifying various things inside images, but also of matching them to nearby places, providing user reviews, and sorting results according to the same principles that control Google’s own search engines.
Implications and prospective
What are the implications of this technology for consumers and businesses? Imagine being able to photograph a restaurant and having a search engine provide the restaurant’s name, location, high demand periods, and specials for the evening. This technology might perhaps be used to take a photo of a pair of shoes from a magazine or a stranger and purchase them immediately.
For e-commerce sites, visual search places customers at the top of the sales funnel. With some distinctive photographs, product reviews, and a detailed product description, you may persuade shoppers to make an immediate purchase.
This will also expand the competitive landscape somewhat. Pinterest is by far the most disruptive visual search engine on the market. However, Pinterest’s search engine only links pinners to content on Pinterest, so you’ll need to establish a presence on this platform in order to access this audience.
With the increase of voice search and natural language processing (NLP) accompanying this trend, this technology might assist launch the interface-free SEO trend. (However, I anticipate that keywords and text-based search will continue to play a significant role in buying and purchase choices.)
Potential strategies
Some of the most basic SEO techniques will continue to apply when optimizing for visual search. Structured data is still vital, particularly for visual search engines like Microsoft’s that depend on it to match traits.
It is essential that pictures be shown clearly and without clutter so that visual applications can process them more efficiently. Beyond this, keep to the fundamentals of image-based search engine optimization:
Add alternative text to photos for indexing purposes.
Submit photos to a sitemap of images.
Optimize the names and alternate properties of images using relevant keywords.
Create picture badges and validate their structured data.
Optimize for optimal picture file size and type.
Use the correct schema markup for pictures and content pages.
Optimize photos for mobile and desktop rendering.
Conclusion
Visual search will give e-commerce companies with a new income stream and dramatically enhance the consumer purchasing experience. This might have a significant influence on SEO and paid media, refocusing SEO practitioners on image optimization for the first time in years. This new frontier of search will only strengthen current SEO methods and increase the need to optimize for mobile search and your visual online presence.
