In the late 2000s, an Amazon customer who had recently lost his wife started getting spot-on book recommendations from Amazon. It appeared to him that this online retailer somehow knew about his wife passing away, and he was astonished by the accuracy of the product suggestions he received.
The books recommended to him were all about dealing with grief and were extremely helpful to the customer during this difficult time. He wrote to Amazon to thank them and to ask how their search engine knew which books to recommend.
Amazon replied that they were using AI technology to tailor product recommendations.
This moving yet informative anecdote showcases how AI not only drives sales but also adds genuine value to online shoppers through a personalized customer experience and search solutions tailored to their unique needs.AI Visual Search: A Game-Changer for E-CommerceAccording to a McKinsey survey from the early 2010s, Amazon reported that approximately 35% of its sales were generated by its AI-based algorithms and recommendation engine.This was a significant increase from earlier years and highlighted the effectiveness of AI-powered recommendations in product discovery and driving better customer experience.Their item-to-item collaborative filtering technology is what made this happen. Unlike other filtering methods focusing on finding similar consumers, Amazon’s item-to-item filtering focuses on finding similar items, forever changing how e-commerce platforms approach personalization.The same revolution in product discovery is happening now with AI visual search tools.
From Text to Visual Image Search: A New Way to Shop
AI-powered visual search technology is now revolutionizing online shopping and product discovery. Instead of typing 10+ vague keywords to find the product they want, online shoppers can now search for products using images.
This AI-powered tool makes shopping faster and more fun for shoppers and online retailers.
The impact of this AI technology is substantial:
- It improves customer experience
- It speeds up shopping journeys
- It enables better personalization and product discovery
- It boosts e-commerce sales and conversions
- It strengths customer relationships
With almost every soul on this planet using smartphones daily, people clearly prefer images over text, enabling image search to overcome the typical challenges associated with text-based search methods.
Challenges of Traditional Text-Based Search
The imminent shift from conventional text-based search to AI image search is taking place as we speak, signifying a notable change in how shoppers locate and buy products online.
Traditional text-based search and product discovery methods are slow and ineffective.
Searching for products only with keywords is difficult because the search engine relies on text and metadata to provide accurate and relevant results. This method is ineffective as the product metadata doesn’t always match the keywords the shopper uses and can’t recognize the unique user needs and style.
Main problems with text-based search:
- Keyword Limitations: Shoppers rarely predict and use the exact keywords and terminology an online store uses while tagging their products, resulting in unsuccessful customer experience and loss of sales.
- Lack of Contextual Understanding: Non-AI text-based searches cannot get the full context or customer intention, leading to low search relevance and loss of sales.
- Descriptive Challenges: Numerous items are extremely challenging to describe effectively in words, making the metadata game very complex for e-commerce businesses.
These challenges have been slowing down the industry for ages. But, luckily, those times are ending.
Enter AI visual search.
How AI Visual Search Solves Product Discovery Pain Points
Visual search technology simplifies the shopping experience by converting complex text-based searches into user-friendly and simple AI image search technology, directly solving major challenges shoppers face during online shopping.
1. Speed: Visual search significantly cuts down product search time, delivering immediate results that align with the customer’s input.
2. Accuracy and Relevance: Unlike text-based searches that often bring a broad range of unrelated results, AI visual search methods deliver more targeted and relevant products to the shopper, closely mirroring the initial search intent.
3. Simplicity: This technology eliminates the need to manually input dozens of text-based keywords to find the desired product. Instead, it provides a Pinterest- or TikTok-like shopping journey.
How Does AI Visual Search Work?
AI Understands and Analyzes Images
The AI-driven search identifies objects, colors, styles, and brands in images, improving search accuracy and efficiency.
- Pattern Identification: Recognizes textures, shapes, and forms.
- Machine Learning: Enhances accuracy through exposure to image datasets.
- Contextual Assessment: Understands relationships between objects.
Accurate element detection bridges the gap between visual inspiration and product discovery, making searches more streamlined and personal and ensuring that each shopper’s journey is as unique as their tastes.
AI connects user intent with similar products, enriching the shopping journey through customization, speed, and a broader selection of options. It ensures suggestions align with individual tastes, reduces search time, and offers diverse choices, transforming shopping into a personalized, immersive experience.
Benefits for Businesses: Increased Sales and Engagement
Visual search technology not only improves the shopping experience for consumers but also provides substantial benefits for businesses, leading to higher sales and more customer engagement.
Reach a Wider Audience
1. Access for All: Users from various cultural backgrounds can easily locate your products through images, overcoming language barriers.
2. Improved User Interaction: Visual searches make the browsing and shopping experience easier and more fun.
3. Broader Visibility for Products: Goods are exposed to an international market, breaking geographic and language limitations.
Boost Your ROI
1. Higher Conversion Rates: Better and faster product discovery leads to greater interaction, steering users toward products they are more likely to buy.
2. Improved Customer Satisfaction: Making products easier to find and improving recommendations specific to customers’ interests makes them feel recognized and valued, resulting in better customer retention.
3. Optimized Marketing Costs: Automated product tagging and visual search will cut your marketing costs and enhance ROI.
Boost Your E-Commerce With Miros.ai Visual Search
As AI tech keeps advancing and the way we shop changes, visual search is becoming a must-have product discovery feature for both stores and shoppers.
AI visual search tools use machine learning to learn the intent behind your search queries. It’s like having a personal shopping assistant who knows you well and gets your preferences, style, and mood.
By recognizing objects in product photos, our tool returns only relevant results, even if you can’t find the words to describe what you’re looking for.
Through a couple of taps on the products they like, shoppers get precisely the product they want to buy in 60 seconds, and they’ll end up browsing for at least 60 minutes more.
Here’s how it works:
Imagine a shopping experience that mirrors the addictive and playful engagement of social media platforms like TikTok or Pinterest.
Miros.ai’s clients experience a quick boost in conversion rate (4.7% in this case), their AOV increases, and their GMV jumps (19% in this case), while the consumers who have their buying journey curated by Miros bring in 2.6x more revenue per shopper compared to the control group.
Want to grow your e-commerce business faster? Book a quick demo here.
