In the late 1990s, a particular online retail brand introduced a new type of technology that served as a major sales catalyst. Though it was completely new then, it is now used by almost every successful retailer.
This simple solution helped the e-commerce platform boost its ROI by enhancing customer engagement and driving more purchases. It did it through algorithms that analyze shoppers’ browsing/purchasing history and other data points (like demographics and preferences) to provide the products that the shoppers actually want to buy.
The technology in question is real-time personalization/recommendation systems, and the famous brand is, of course, Amazon.
From a “Small” Add-On to a Strategic Necessity
According to McKinsey, around 35% of Amazon’s revenue has been driven by their recommendation algorithms after implementing these systems. They also reported a 29% increase in sales (from $9.9 billion to $12.83 billion) during the same year.
Once other online retailers realized that Amazon’s recommendation engines were bringing in more than a third of its product sales, they knew this technology was no longer only useful but a strategic necessity.
Businesses that recognized the need to use recommendation engines thrived, while those that didn’t quickly reached the end of their e-commerce journey.
Today, the evolution of machine learning, data analytics, and AI-powered tools continues to improve recommendation systems, making them essential to anyone who wants to stay competitive.
Direct Benefits of Visual AI Product Discovery Tools
Better Shopping Experience
AI-powered Product Discovery Tools utilize sophisticated search features driven by natural language processing (NLP) and ML algorithms. This empowers customers to effortlessly locate products, even if their keywords are inaccurate.
Competitive Advantage and Brand Differentiation
I know this may sound like a ChatGPT-generated sentence, but today’s e-commerce landscape is so hyper-competitive that online stores must find a way to stand out. With most e-commerce stores, no matter the niche, offering similar product listings, your platform must provide:
- Superior customer experience
- Improved personalized recommendations
- Highly intuitive navigation and product discovery
Only then will your e-commerce platform gain the much-desired competitive edge.
Increased Conversion Rates
Visual AI product discovery tools are currently changing the e-commerce game by offering personalized product suggestions and allowing shoppers to have a Pinterest-like shopping experience.
When your website visitor gets only the items that closely match their desire, style and preferences, almost all the obstacles in the buying process are removed, leading to increased conversion rates and better ROI.
AI Product Discovery Tools are not just another fancy addition to the e-commerce toolkit but a strategic imperative for every online store. By empowering both shoppers and e-commerce store owners with personalized experiences, actionable insights, and improved shopping experiences, visual AI product discovery is reshaping the future of online retail as we speak.
But don’t take just my word for it. Here’s a recent graph from Statista showing areas in which AI will help e-commerce businesses according to decision-makers in North America and Europe:
As you can see, implementing these innovations is no longer optional – it’s a strategic necessity for survival and success in the crowded online retail market.
Secure a Winning E-Commerce Strategy With Miros.ai
Traditional search methods that rely only on text-based queries and search filters are slow, inefficient, and not user-friendly. They make it almost impossible for a shopper to quickly and in a minimal number of steps find the exact item they want.
Luckily, new AI-based visual search and product discovery technologies are now solving these problems and changing the online retail industry forever. One such groundbreaking tool leading the charge is Miros.ai.
How Miros Works
Miros technology uses state-of-the-art visual AI to analyze and interpret product images to deliver highly relevant items to the shopper.
When a user uploads an image or selects one from the web, the platform’s algorithms go to work, identifying key features, colors, patterns, and shapes within the image. This process allows this product discovery tool to accurately understand the visual characteristics of the desired product.
It typically works like this:
- The shopper inputs one keyword-based search
- Taps on a couple of products that resemble the one they have in mind
- Miros.ai then accurately reads the product images and delivers results that closely match their search intent
- The shopper makes a purchase because they quickly found the item they wanted
The short video below shows this simple process and perhaps best illustrates how Miros improves e-commerce search accuracy and product discovery:
Semantic Search for Ultimate Understanding
Miros also takes it a step further by incorporating semantic understanding into its analysis. It puts visual features in context to get a much deeper understanding of what the shopper is looking for.
It’s like mind-reading.
It understands the customer’s style, preferences, and intentions, then provides more relevant and personalized product recommendations custom-tailored to each shopper and their unique tastes and requirements.
Product Matching and Recommendation
Once it does its magic for image analysis and semantic understanding of the search intent, Miros matches these characteristics with products from your e-commerce database listings to deliver the desired items.
Through AI and ML, it ranks and presents the most relevant product recommendations to the shopper. It continuously learns from these interactions, refining its recommendations over time to better align with individual preferences and boost customer satisfaction.
Quick and Simple Integration
Miros seamlessly integrates with existing e-commerce platforms (with the API option available as well), allowing your customers to effortlessly discover and buy products from their favorite online retailers.
Whether browsing through fashion items, home decor, stock images, footwear, or any other category, your shoppers can rely on Miros.ai search to always have the best shopping experience, one that resembles the fun of TikTok or Pinterest browsing.
The Impact of Miros.ai Shown in Tangible Numbers
Miros clients experience immediate KPI increase. Momox, for example, improved its GMV by 19%, AOV by 11%, and ARPU by 10%. Swap, also Miros’ client, reported similar KPI boosts, with our numbers showing that shoppers who buy via Miros bring in 2.6x more revenue per customer than the control group.
I hope this showcases why visual AI product discovery technologies are a strategic necessity for any online retail store that wants to stay competitive. Book a quick demo here and see how Miros can help you embrace the future of search engines.
