eCommerce is one of the early adopters of technologies that seemed far fetched when they came into existence. Be it voice-enabled or chatbot assisted shopping; every innovation in eCommerce now-in-the-know is technology-driven.
In this blog, we will be looking at the top 5 technology-driven trends that are helping brands to improve customer experience visually and also understand their preferences better.
Video Analytics – Hyperpersonalizing with the power of AI
The video analytics market size is estimated to reach USD 4.23 Billion by 2021 – MarketsandMarkets
Brands like Netflix that heavily rely on tracking user behavior to improve its customer experience have pioneered in this segment. With an ocean of videos available, it is hard for monitoring systems to decide what users would be interested in watching.
For instance, Netflix’s ‘Artwork’ is a data-driven engagement idea where users get relevant content based on the character they like the most. Are you a fan of Chris Evans or Robert Downey Jr? If it is Downey Jr, suggestions for an Avengers movie will pop up in your feed with his picture. By hyper-personalizing the same content for individual users, Netflix aims at creating a visuals based approach that’s driven by users’ interest.
However, considering the number of videos that Netflix has, it is hard to design images for all videos manually. Thanks to AI and Machine Learning as these technologies help systems generate images. For brands like Netflix, whose business is entirely visual, such AI capabilities are sure to provide a great way to maximize engagement.
Image Recognition – Making sense out of visual contents using Machine Learning
Image Recognition technology aims at mimicking the way humans recognize images with the help of deep learning algorithms. Such algorithms, when fed with millions of objects, faces, people, and text, develop the ability to identify and categorize images accordingly.
‘Image retrieval process’ and ‘automatic image tagging’ are some of the examples of how Image Recognition technology could help. Automatic image tagging identifies images and tags them with appropriate text.
Advanced image recognition technologies apply deep learning through algorithms called Convolutional Neural Networks (CNN). CNNs understand data in images by mimicking the human brain, but the difference is they perceive images in the form of vectors.
Airbnb uses image recognition systems to identify photos of homes uploaded by users. Hosting over 5 million homes from 81,000+ cities in the world, the amount of user-generated photos is hundreds of millions. Users generally tend to add wrong captions for pictures that mislead a site visitor.
Source: https://medium.com/airbnb-engineering/categorizing-listing-photos-at-airbnb-f9483f3ab7e3
The challenge was to identify photos and put them at the right places on the website. Airbnb, with the use of TensorFlow machine learning algorithm, created a system named Bighead that identifies spaces inside the house. With BigHead, Airbnb is now able to classify images based on categories like ‘living room’ ‘bedroom’ and so on without human effort.
Source: https://medium.com/airbnb-engineering/categorizing-listing-photos-at-airbnb-f9483f3ab7e3
Visual Recommendation – Adding more visual relevance to product suggestions
Product recommendation engines that suggest products based on users’ search keywords, buying history, and so on have evolved to take even visuals as inputs.
Visual recommendation engines can recognize designs, patterns, style, texture, and color of the clothing chosen by the user and provide ‘visually similar’ suggestions like a sales representative would. By doing so, eCommerce brands can provide all the similar alternatives helping users in purchase decisions and increasing the chances of conversion.
Source: https://www.amazon.com/showroom
eCommerce brands selling fashion clothing and apparel can benefit from such recommendation engines. Another use case is brands can provide suggestions for even upselling and cross-selling. If users purchase clothing, recommendation engines can offer items that could go well with a purchased item like footwear, jackets, and so on.
Also, visual recommendation engines are smart enough to render results if users search based on attributes like color, design features, and style. From a commercial value, perspective, and customer experience perspective, visual recommendation engines are sure to benefit retailers in several ways.
Visual Search – Click, find, shop
Remember Pinterest’s ‘Shoppable Pins’ and the idea behind Google Lens? That’s visual search. The ability to click photos or scan objects through a camera and find what it is. Pinterest adopted AI to complement its concept of ‘Shoppable Pins, ’ which came to light in the year 2015.
Source: https://newsroom.pinterest.com/en/post/new-ways-to-shop-with-pinterest-0
Using AI, the visual search displays dots on the objects displayed in the camera/. Users can then tap on any specific dot to trigger a search and get recommendations for the same. Pinterest’s AI algorithm is also tuned to fetch similar items for the product detected. But that’s then.
Now, with the launch of Pinterest Lens, the game has gone to a whole new level. Pinterest is now integrating its shoppable pins with visual search, which means the shoppable pins will be showing in visual search results.
Source: https://newsroom.pinterest.com/en/post/new-ways-to-shop-with-pinterest-0
As people are more likely to buy after taking efforts to capture and visually search for a product they are looking for, this feature could be a game-changer for many eCommerce retailers.
Retailers who are already using computer vision (visual search) or recommendation engines, can benefit by ranking on top in Pinterest’s search results. And we have stats to back this statement.
– 80% of Pinterest users start with visual search when shopping
– 85% of users shopping for clothing or furniture look mainly for visual information than text information.
– 49% of users say they develop a better relationship with brands through visual search.
– 61% of consumers say visual search elevates their experience while in-store browsing.
Source: https://www.searchenginejournal.com
Shoppable pins, which means buyable products from Pinterest, directly lead to the checkout page, making it easy for users to buy quickly. As buying through visual search is getting a lot of popularity, investing in computer vision technologies is worth considering.
Product Visualization – Reimagining buying experience online and offline
Quality visuals of products not only attract but also help users make well-informed buying decisions. Unlike in-store buying, users don’t get to try products, which results in doubtful buying, and eventually leads to product returns. Augmented Reality can save the day under such scenarios.
63% of customers are sure that augmented reality may buff their shopping experience – Thinkmobiles.com
The Augmented reality market is estimated to grow from USD 10.7 billion in 2019 and projected to reach USD 72.7 billion by 2024 – Marketsandmarkets.com.
With AR, eCommerce retailers can redefine the way users experience products while buying. AR’s product visualization helps users to mount products into a real-world environment. For instance, a user can mount a couch into a living room space or corner and see how it fits before buying.
Furniture brands like IKEA are already into product visualization. AR 3D product scanning feature in Lacoste’s mobile app allows shoppers to place their foot in a designated AR area and view via their mobile phone to know how a shoe fits them. The app also provides additional product details.
Physical product catalogs can also be provided with 3D model rendering capabilities so that when users see the catalog with their smartphone, a 3D model with a 360-degree rotation feature pops up on their mobile screen.
With AR, retailers can provide multiple overlays which means, one or more products can be mounted into a real-world environment. Brands like Lenskart offer overlay options to users while buying eyewear so that users can check for size and aesthetics like colors, texture, and material.
Augmented Reality works for both brick and mortar stores and online retail players. With AR experiences, your customers will be able to judge based on facts to make strong buying decisions, which results in more conversions and fewer returns.
Final words
Visual experience has always been an important aspect to consider when it comes to enhancing customer experience. If you are into an industry like fashion, furniture, and home decors where visuals play a prominent role, you need to consider implementing the technologies discussed above.
Be among the few to adopt visual commerce technologies, stay ahead of the curve, and enjoy the early bird advantage.
