Do you know how only your closest friends dare to tell you that a particular pair of pants doesn’t look good on you? It doesn’t feel too good, but those are the friends that actually wish you good.
They are also the ones who will recommend what’s best for you.
Now imagine that every search system within any website is your closest friend.
This is the future of online shopping and smart merchandising – only possible through the power of website search that uses AI recommendation systems.
Ecommerce recommendations, primarily when powered by AI and ML, can do wonders for your Average Order Value and increase Conversion Rates by up to 216%.
What is an AI Recommendation System?
An AI recommendation system analyzes customer behavior and preferences to suggest products or content they will likely purchase. It analyzes the following:
- Past Purchases
- Search History
- Demographic Information…
and so on.
The software then uses algorithms and data-driven insights to make personalized recommendations. This improves the shopping experience for the customers and increases sales and conversions for the ecommerce website.
And even the AI feels better for a job well done—a true win-win-win scenario.
Types of AI Recommendation Systems
There are three main types of AI recommendation systems:
- Collaborative filtering
- Content-based
- Hybrid
Collaborative Filtering – suggests products based on the choices of similar shoppers. For example, if Person A and Person B both liked/bought similar products, the AI recommendation system will put the products liked by Person A to Person B, and vice versa.
Content-Based– focuses on product attributes, recommending items similar in characteristics to those the shopper has shown interest in.
Hybrid– combines elements of the previous two. For example, it is widely used by platforms like Netflix and Spotify, which blend user behavior and content attributes.
How AI Recommendation System Helps Ecommerce
In 3 key ways:
- Better Personalization
- Increased Engagement
- Maximizing Revenue
Better Personalization
By using AI ecommerce recommendation systems and AI-powered search, ecommerce businesses improve personalization and make their shoppers feel understood and valued, increasing trust and loyalty.
A McKinsey study shows that companies speed up growth and improve revenue by 40% when they use personalization strategies.
Increased Engagement
Relevant product suggestions keep shoppers engaged, reducing bounce rates and increasing time spent on the platform. This engagement leads to higher conversion rates and, ultimately:
Maximized Revenue
The potential impact of AI-powered search and recommendations is huge. It can bring an additional $660 billion a year, according to McKinsey & Company.
Try Boosting Your Ecommerce With Miros
Miros.ai is a visual AI and photo search tool that reads what’s in product photos and uses this data to put only relevant products in front of online shoppers.
It provides a TikTok or Pinterest-like shopping experience that is extremely enjoyable for website visitors. Through a couple of clicks and scrolls, they can get exactly the items they are looking for – in 60 seconds or less.
No need for cookies, metadata, filters, or other annoying aspects of online shopping that are slowing down this industry.
Text-based search is slow and complicated. Miros uses wordless search to boost your e-commerce strategy by offering three key benefits:
1. Quick product discovery
2. Streamlined ecommerce operations
3. Increased revenue
Let’s schedule a demo with the Miros team and see how your shoppers can get a quick and immersive TikTok-like shopping experience.
