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Harnessing Visual AI to Boost E-Commerce Sales

Each person interprets an image in countless subjective ways, based on individual biases. However, when searching for a product on the Internet, most people prefer accuracy over multiple interpretations of a single object.

Putting the appropriate tags on images ensures better searchability for users. Doing this manually, though, can be inefficient and prone to errors. With visual AI, you not only can tag your images automatically, but also save on costs.

What Is Visual AI?

Artificial intelligence, or AI, is the ability of a machine to learn and understand things similar to the way humans do. Through the use of machine learning algorithms, computers can be programmed to think objectively and make decisions.

Visual AI combines artificial intelligence with computer vision software. It intelligently recognizes photos and can extract useful information from them using image processing and deep learning techniques. Machines with visual AI capabilities can do tasks like portrait segmentation, face identification, depth estimation and overexposure detection.

The benefits of visual AI technology also are evident in its application in areas like security, healthcare, banking and industrial maintenance, to name just a few examples. Visual AI also is utilized to boost social media usage and improve image searches.

Perhaps one of the biggest ways that visual AI is being used is to enhance the e-commerce shopping experience.

E-Commerce and Visual AI

Although visual AI is fairly new compared to other machine learning technologies, large retail businesses like eBay and Amazon have been harnessing its benefits in order to make the e-commerce shopping experience more convenient to users.

Here are some of the ways visual AI can boost your e-commerce site:

1. Make searches more relevant with visual AI.

Entering keywords rarely delivers the exact product customers look for, unless they also enter a lot of information about the item.

For example, a user likes an outfit shown in a poster and wants to have the same one. The user has trouble finding it online without having information on the brand, the size, the color, and other details about the outfit to narrow the search.

Obviously, if they can just take a photo of the poster and do an image search with accurate results, their search will be much simpler. This is precisely how visual AI technology helps boost e-commerce sales.

Using visual AI technology, retailers enable customers to find items such as clothing, accessories, or even furniture using an uploaded photo.

Curious about the bag or pair of shoes a passerby is wearing? Fancy the lamp or light fixture you saw in a hotel? How about the watch your favorite actor was wearing in a movie?

With visual AI, users just need to take a snapshot of the item they want and search an e-commerce website for similar products. With the astoundingly accurate results that current algorithms are able to give, it is easier for customers to browse the selection and choose the item that fit their budget and preference.

Perhaps you’ve already used Google’s ‘search by image’ feature at least once to find the name of a place, an item, or even a personality. The search engine returns images that look similar to the provided photo, facilitating your search for a name or other details.

The same concept can be used to search for thousands of items on an e-commerce site, but with better accuracy since the database is narrowed down to a more specific selection.

Pinterest has perfected the use of visual AI technology.

People mainly use Pinterest to look for items to buy. Others use the platform to get fresh ideas on just about anything: car modification, books to read, food to cook, financial tips, home decoration, places to visit, and a whole bunch of inspiring content.

Using the platform’s ability to search its database with an image, you gain access to an endless number of related posts. The photos are nothing short of stunning, and this is where Pinterest seamlessly integrates ads, making it easier for customers to purchase the items they see on the pictures.

eBay and Target leverage the same technology Pinterest uses to boost their sales. Even if users don’t know how to describe the item they’re looking for, they can just take a photo of it and let visual AI do its work.

Early adopters of visual AI in the e-commerce industry may see a 30 percent increase in revenue by 2021.

Mobile users will continue to dominate the market, and searching the Internet using images is the most convenient way to look for merchandise to buy. An e-commerce website that utilizes this technology while it’s still in its early years can gain a huge advantage over competing brands that are just picking up on SEO content optimization.

2. Tag images automatically.

Keyword searching is still the most popular method for finding items on the Internet, and adding effective tags can enable a more efficient selling process on sites like eBay.

When buyers search, images are returned in search results by using the tags that describe them. This means that if you’re selling pants on your e-commerce website but you forgot to tag them as such, chances are they won’t show up in the search results.

It’s a must for your business to tag every item you’re selling with the appropriate description to make it easier for the website’s search function to pull them up. If a user searches for the word “stapler,” “wedding dress,” or “car muffler,” your website easily can match the keywords with the images, and display them on the results page.

Image tagging can be done manually, but it would be a waste of resources and time. Instead you can use visual AI to place appropriate tags automatically on each image processed, which is way faster than manual tagging.

3. Keep Tabs on Your Competitors

Visual AI also can serve as a competitive intelligence tool. It can be trained to read and analyze the competition’s social media marketing efforts.

For example, Brand A can post photos of models showcasing its new collection. Through machine learning and predictive analytics, visual AI can be taught to recognize patterns on the image output. By sorting through mountains of photos, visual AI can determine which consumer trends work and which don’t.

Photos are not created the same, and there are certain colors, angles and moods that consumers prefer to view. The system can be programmed to sift through all the images and identify which of them receives the highest customer engagement. The trending images then can be grouped, revealing certain similarities and patterns.

Knowing which kinds of images generate the most views, you can take photos of your merchandise using the deduced criteria. After all, It’s easier to adjust your business strategy when you know the kind of content customers prefer to consume.

While probing your competition’s postings with visual AI, you also can discover new trends that might not be on your radar. Comparing posts from different brands will reveal which kinds of images they release on a regular basis.

Not everything competitors do fit will fit a company’s branding. Highly engaging content from one website may not do well on others. Still, knowing what doesn’t work can be an advantage, since you won’t have to waste time working on something highly likely to fail. Knowledge of your brand and your competitors’ capabilities will make your e-commerce business more competitive.

Search Revolution

Now is the time to incorporate AI tech into your e-commerce business and make browsing your e-commerce website more flexible to consumers. Visual AI programs get smarter the more data that is fed into them, meaning they continuously deliver more accurate results for consumers.

Visual search is revolutionizing the way customers look for products, so it’s best to leverage the technology and present your merchandise through visual AI.

Jeffrey Goldsmith is vice president of marketing at Chooch, which provides a machine learning and visual recognition solution with both Cloud and Edge deployments. Goldsmith has written for many publications in the past, and he authored the classic Wired piece from 1994, "This Is Your Brain on Tetris."

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