Smart Recommender is an AI-powered personalization engine that automatically delivers the right products to the right users at scale. It works across multiple channels—including your website, mobile app, emails, and more—adapting in real time to user behavior, context, and preferences.
Whether your goal is to increase conversions, improve engagement, or boost average order value (AOV), Smart Recommender is designed to support and optimize your marketing objectives.
Why Smart Recommender is a Game-Changer
Smart Recommender transforms how you connect with shoppers by turning anonymous browsers into engaged, loyal buyers. Here’s what makes it valuable:
Boosts Conversion Rates
Recommends the most relevant products to each visitor, improving the likelihood of purchase.
Increases AOV
Surfaces complementary or higher-value items at the right moment in the journey.
Improves Engagement
Creates personalized and meaningful product discovery experiences that keep users exploring.
Adapts across Touchpoints
Works seamlessly across homepage banners, product detail pages, cart pages, mobile apps, and email campaigns.
Scales with your Growth
Leverages machine learning to handle large catalogs and high traffic, while continuously improving recommendations.
How Smart Recommender works
Smart Recommender combines real-time user behavior with your product catalog data to deliver personalized recommendations at scale. Here's a simplified breakdown:
1. Collect User Data
User interactions are tracked across web, mobile apps, and offline touchpoints—including product views, add-to-carts, purchases, and even in-store transactions.
2. Sync Product Catalog Data
Your catalog is continuously updated so the system knows exactly which products are available to recommend.
3. Match with Algorithms
Advanced algorithms connect users to products based on multiple factors:
Popularity (best-selling or trending items)
Context (e.g., the page a user is browsing)
Behavioral Similarity (patterns from similar users)
4. Design the Experience
Use the intuitive Web Smart Recommender editor to design recommendation widgets and product cards. Customize layout, styling, number of items, and titles—without any coding.
5. Customize by Channel
Tailor recommendations for each channel:
Web widgets embedded on product or homepage
App recommendations optimized for mobile UX
Email personalization for re-engagement and upselling
The Outcome
The result is intelligent, context-aware recommendations that adapt to where customers are in their journey—whether they’re exploring, comparing, or ready to check out
Where you can use Smart Recommender
Smart Recommender works across multiple channels and touchpoints, enabling you to personalize the entire customer journey.
Web & Mobile Web
Add personalized product carousels to key pages such as the homepage, category pages, product detail pages (PDPs), and cart pages.
Mobile App
Embed recommendation sections directly into your app with the Insider SDK, ensuring seamless in-app personalization.
Insert personalized recommendation widgets into email campaigns using drag-and-drop blocks to boost engagement and conversions.
Web Push
Deliver timely, personalized product recommendations via Web Push notifications, re-engaging users instantly.
InStory
Use swipeable, Instagram-style stories to showcase personalized product recommendations in an interactive, visual format.
Architect
Incorporate recommendations into Architect Journeys, stepping in with personalized suggestions at the right stage of the user’s discovery or purchase flow.
Smart Algorithms behind the scenes
Smart Recommender relies on multiple algorithm types, depending on your chosen strategy and setup:
Generic Algorithms: Recommend products based on overall performance, such as best-sellers or most-viewed items.
Contextual Algorithms: Adapt recommendations to the page the user is currently viewing, such as showing similar items on a product detail page.
Personalized Algorithms: Use real-time user behavior and past activity (views, clicks, purchases) to generate unique, user-specific recommendations.
Multi-Strategy Algorithms: Combine several algorithm types into a single recommendation campaign for more flexibility.
On top of algorithms, you have full control to shape recommendations:
Audience Segmentation: Decide which user segments see which recommendations (e.g., new visitors vs. loyal customers).
Trigger Rules: Define when campaigns appear (e.g., on exit intent or after 10 minutes of browsing).
Filters: Refine results to show products from a certain category, above a certain margin, or matching specific attributes.
Exclusions: Prevent already purchased or recently viewed items from appearing.
This combination of algorithms + business rules + customer context ensures recommendations are not just smart—they’re strategically aligned with your goals.
Who is it for?
Smart Recommender is ideal for any business with a product catalog and customer interactions, including but not limited to:
Ecommerce marketplaces
Fashion and cosmetics retailers
Consumer electronics stores
Online publishers
And more—if you have products to recommend and customers to engage, Smart Recommender can help.