Personalized Recommendations

Today’s consumers expect their favorite brands to anticipate their needs with engaging experiences. Delivering personalized recommendations delights customers, increases consumption, and increases orders.

Real Results

3X

Add-to-basket Rate

2X

Product Coverage Rate

3 Months

From Start to Production

Product Capabilities

The foundation of relevant and personalized experiences is data. Syntasa has deep expertise in using advertising, digital behavior, and enterprise data sources to find the most relevant products, content, and services for your customers.
Combined first-party behavioral and enterprise data

Quickly and easily ingest first-party behavioral data from adtech and martech systems and combine with your customer data at the individual level.

Create customized recommender models with machine learning

Customizing your algorithms will enable you to fill your experiences with the most relevant content for each individual; our customizations enable you to make adjustments based on business priorities.

Activate across all channels

Make your experiences seamless by offering the same recommendations across all channels — whether they are 1:1 platforms like websites and apps, or audience based like ads, emails, and app notifications.

Ensure privacy and security in your private cloud

The scale and complexity of first-party behavioral data requires the power of cloud services; the more of your sensitive customer data you include, the more important the security of your private cloud becomes

Recommender Types

As you design your search and browse experiences, you need to think about how to deliver the most personalized and relevant content. Our recommenders give you the flexibility and options that you need.

You May Like These
You May Like These

Products (or content) a visitor is expected to interact with, purchase, or consume next.

Best Sellers For You
Best Sellers For You

Best seller products (or content) that are personalized based on user’s prior viewing, purchasing, or consumption history.

Bought Together
Bought Together

Products (or content) that are frequently bought together with one or more reference products.

Recommended Categories
Recommended Categories

Best seller products (or content) that are personalized based on user’s prior viewing, purchasing, or consumption history.

Similar Products
Similar Products

Products (or content) based on their feature similarity with a reference product.

Recently Viewed
Recently Viewed

Most recent products (or content) that were viewed by the customer.

Recently Purchased
Recently Purchased

Most recent products that were purchased by the customer.

Most Popular
Most Popular

Top products ranked based on purchases, consumption, revenue or views.

Get Started Quickly

Dixons Carphone used our award-winning method of AI to offer personalized recommendations that launched within 3 months for Black Friday.
Dixons Carphone Kicked off the project in August and pushed to production in November. To build the personalized recommendations, they were utilizing data pipelines, custom recommenders, visitor recommendations, automatic data refresh, and the real-time updates. This setup has led them to win "Best Use of AI in eCommerce" award.

Recognized by Leading Voices

Syntasa is a new breed of personalization and our approach is getting noticed.
451 Research
Named a Cool Vendor for Personalization by Gartner®
Ecommerce Award
Paula

"Syntasa has been really invaluable in speeding up our time to value by architecting our Adobe Analytics data and productionizing data science and machine learning at scale, and in a way that we can confidently pass that into production systems to drive user experience."
Paula
Head of Online Performance – Dixons Carphone

Personalized Recommendations in Action

Watch our webinar to learn how to create more personalized and relevant experiences.
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