AI Impact on Visual Shopping
Visual shopping is a relatively new, but interesting concept. It’s tied to advancements in video and photo technology and is being embraced by millennial shoppers around the world. So what is visual shopping and how is AI making it easier?
What Is Visual Shopping
To answer these questions it’s best to explain what visual shopping is. This is where shoppers search for an item with a photo or image rather than a keyword or specific description of what their item does. Customers can actually take or find a photo of what they are looking for, upload it into a database or search engine, oftentimes using Google or Pinterest, and find the item or similar items to buy. In recent years private companies have even begun to create apps to capitalize on this idea to help their customers narrow in on only their brands.
The reason it is becoming popular over traditional methods is that for most people it’s a quicker route than going through pages of items and keywords, it can be done at home or in a store, and it gives a quicker more tech-savvy customer experience. AI comes into play often using machine learning, the concept that AI improves automatically through experience, allowing businesses to better match customers to products, and enhancing both the search capabilities of visual shopping and customer service aspects.
Visual shopping is unique in the sense that it can provide customers with a truly personalized shopping experience. It was stated by Ross Simmonds, a digital marketing strategist that, “one of the most important trends in marketing is personalization. The ability to arm your customers in a retail setting with visual search is an opportunity to take personalization to the next level.” Right now the best way for companies to embrace Simmonds’s visual shopping idea is through AI.
Most AI that is being used for visual shopping is using a form of machine learning, but for visual shopping’s personalized touch it’s a little more specialized. This type of AI uses the visual metadata of past uploaded images to make accurate personal predictions of what a customer wants. This metadata is found by looking for similar product shapes and sizes, reoccurring colour templates, and reoccurring details both big and small across different products and services.
It then learns from the pattern of the user and begins to look for not just visually similar items to what has been uploaded into its search function, but images of products that match the new item plus the history of past items. An example of this is the synthetic’s Style Intelligence Agent or SIA for short. The AI was designed by Adobe Sensei and is a service provided by Discovery that, “uses artificial intelligence to help the user complete their outfits of clothing and discover many possibilities that might complement a single image.”
The app is not just limited to personalized clothing, but products across different departments even recommending home decor items based on how a person dresses. It was explained by its creators that customers, “just upload a photo, choose the desired filters and the robot will do the analysis for you.” This shows a level of customer personalization that would be difficult for any retail worker, but easy for an AI because of its ability to know every item the company has and every possible pattern that particular customer would want.
Making It Easier To Use
Not only is AI giving visual shopping a personalized touch but it is also making it easier to use. Lihi Pinto Fryman, co-founder, and chief marketing officer for visual AI software-as-a-service company Stye has advocated for the ease of visual shopping due to AI. She mentions that users don’t have to explain every detail of an item they want. That, “all they need to do is upload an image and find their inspiration.” She explains that companies use AI-powered visual technology to scan product images and provide end users with results closest to the screenshots or photos they sent to the retailer making everything easy for customers to get what they want.
She has even spoken with the tech website PYMNTS that AI can make it easier for companies to allow their customers to use visual shopping. She has said that her company Stye has provided businesses with AI technology that enable them to properly move away from text based shopping into the newer visual shopping market. That AI is removing the limit of terms and filters, customers just have to upload or tag a photo and wait for the AI to go through the data to find them what they want. AI is really making visual shopping that easy to use.
One example of this is the Luxury department store Neiman Marcus using AI to make it easier for customers to find items on their visual shopping company app called The Snapp Find Shop. Their app uses machine learning AI to let users upload pictures of items they see while out and about. The AI then searches Neiman Marcus inventory to find the same or a similar item. It was explained by Forbes that Neiman Marcus is AI is making it easier for customers, “instead of using vague search terms to find an item, the photos can usually find a very similar match.” This all means less hassle for both buyers and sellers.
In a study done by Businesswire, it found, “that 62 percent of millennials prefer visual search over other search methods.” If visual searching is preferred by millennials, and visual shopping heavily uses visual searching then there’s a good chance that visual shopping isn’t going anywhere. In fact, because of the integral advancements of AI, it’s only going to advance further. Right now AI is making visual shopping easy for businesses and customers while making the whole thing personable. This new way of shopping is only going to get more mainstream, and AI will be there every step of the way.