Problem: e-commerce platforms using traditional search models provide suboptimal customer experience, resulting in low conversions.
Solution: semantic search and visual AI-powered search tools improve shopping experience, allowing shoppers to quickly find exactly what they want.
Something happened in 2012 that completely changed AI-powered search and product discovery. It was all thanks to CNN, but not the famous news channel of a dying medium. In this case, we’re talking about Convolutional Neural Networks.
Convolutional neural networks, or CNNs, are a type of deep learning that recognizes image patterns by mimicking how the human brain processes visual information.
CNNs got propelled into the spotlight at the ImageNet Large Scale Visual Recognition Challenge (ILSVRC) back in 2012. In this competition, a CNN model called AlexNet significantly improved image classification accuracy compared to previous methods, completely changing image recognition technology and visual AI-powered search.
This wouldn’t be possible without the concept of semantic search.
It’s because the CNN technology relies on semantic understanding, feature extraction, and continuous improvement to help AI truly understand what’s in the image it analyzes. This technology has now become key for e-commerce businesses.
To find out how and why, we must first understand semantic search.
Semantic search, powered by Natural Language Processing (NLP) and visual AI, understands the meaning of phrases by analyzing sentence structure, grammar, and context.
It recognizes entities like product names, brands, colors, and sizes within queries. Rather than just matching exact keywords, it finds relevant content and products by understanding user intent
Instead of just looking for exact keyword matches, they look for products or content that contain information related to the user's query, even if the exact words aren't present. Content and products are then ranked and recommended by relevance, considering factors like user intent, source authority, and SEO.
Continuous improvement is achieved through user feedback loops, refining understanding, and search accuracy.
Integrating semantic search in e-commerce is crucial for understanding consumer behavior and catering to their nuanced needs and user intent.
Unlike traditional search algorithms that rely on exact keyword matches, semantic search interprets the user intent and contextual meaning behind search queries, striving to improve product discoverability.
By leveraging sophisticated natural language processing techniques and machine learning models, it can significantly enhance the relevance of search results, providing a more intuitive and satisfying shopping experience for users.
So why is this important for product discovery?
According to Statista, 70% of e-commerce decision-makers in North America and Europe believe AI-driven technology can help their business improve personalization, while 54% said it can help with their site search.
Another relevant study by Statista shows that 44% of company leaders state that AI-driven personalization boosts the speed of real-time data and customer retention or repeat purchases.
As businesses strive to meet the demands of an increasingly demanding customer base, adopting semantic search becomes a strategic imperative.
Product discovery and search benefits of this technology go well beyond simple functionality, vastly improving user engagement, retention, and the overall success of e-commerce platforms.
Semantic search in e-commerce makes it easier for consumers to find what they want. 41% of consumers say that AI-driven search improves product discovery and search relevancy, with this number likely to grow in the near future.
This is because semantic search in e-commerce does wonders to improve product discoverability.
Instead of just giving them the products that include the words they searched for, AI-powered semantic search tools understand user intent and optimize search experience to provide results that match what they really want.
Here's a simple comparison:
Looks for exact keyword matches → Provides basic/not-personalized results → Doesn’t improve.
Semantic AI-Powered Search
Understands user intent → Provides products you actually want → Adjusts to user preferences.
The secret behind smart AI-driven e-commerce search is that it understands how people naturally ask for things and gets the meaning and user intent, not just blindly focusing on specific words the shoppers use to search for items.
It's like when you're talking to a friend, and they know what you mean, even if you don't say it perfectly. This helps an online store suggest the right products to shoppers.
By doing this, an online store is more likely to show shoppers the things they actually want to buy. When people find what they're looking for easily, they're happier and more likely to come back.
Here's why this is great for online shopping experience from the customer standpoint:
• Better Shopping Journey: The search gets what you're looking for, so you feel like the store gets you.
• Stick Around Longer: You'll find other exciting products that keep you browsing, making you less likely to leave without buying anything.
• You Might Buy More: You're more tempted to buy when suggestions hit the mark.
• Come Back for More: Stores that keep showing you items you like make you want to return.
• Smart Decisions for Stores: Online shops can stock up on what people like and plan better strategies.
Semantic search and visual AI-powered search is a smart way for online stores to quickly increase their revenue through better engagement.
tools can easily keep their shoppers interested and more likely to buy something.
Here are the main search benefits:
• Searches Just for You: The search results get better the more you shop, as they start to understand what you like. This makes you want to come back and shop more.
• Easy-to-Use Searches: You can search like you talk, so finding what you're looking for is less of a hassle.
• Quick Finds: You get to see items that match what you want faster, which means you can buy it quicker.
• Smart Suggestions: The search understands what you mean, offering better choices that make sense to you.
• Matching What You Want: The items you see fit with what you're looking for, so you're more likely to trust the store and stick with it.
With semantic search, finding and buying things online is a breeze. It's all about making shopping online as easy and natural as talking to a friend.
E-commerce text search simply isn’t working anymore. Words are powerless to accurately describe a particular personal style.
Miros.ai brings a big change to online shopping by making product discovery search:
Imagine typing what you want into a store's search bar, tapping on a couple of images, and getting back exactly what you're looking for.
That's what Miros.ai does.
It helps online stores understand user intent, even if they don't use the “right” words - just talking to a helpful salesperson.
Here’s a quick example:
As you can see, Miros.ai solves the problem of inaccurate test-based searches and provides your shoppers with a fun TikTok or Pinterest-like shopping experience. And it’s not just about improved customer experience - it’s about boosting your e-commerce KPIs.
Let’s take Swap.com, one of Miros’ biggest clients, as an example. Once they started using Miros.ai, their GMV quickly improved by 10% and AOV by 8%, with their conversions going up by almost 5%. You can read the full case study here.
Let’s quickly and easily boost your own e-commerce KPIs and sales.Book a demo
The first 60 seconds mirror exactly what they’re looking to buy. The next 60 minutes they browse for stuff they never knew they wanted.
See how your store can inspire them better than Pinterest or Tiktok ever could.
Just like the name suggests:
Buying visually complex items like fashion, clothes, footwear, furniture, art, design pieces, decor… is a function of style and beauty, not features. So why do we keep making our shoppers buy these like they’re buying a book or a laptop?
Wordless Search is an AI technology that relies on shopper behavior. It recognizes browsing patterns based on which it mirrors the buying intent your shopper has, without them having to input a single word. It gives off the impression that their minds are being read.
Give your shoppers the experience they were always willing to pay a premium for. Book a demo to see how.