Content & Product Recommendations

Personyze’s Recommendation Engine shows each visitor exactly what they are most likely to be interested in, using predictions gleaned from your data. Stay one step ahead by placing the right product or content in front of each visitor.

Combining personal & crowd wisdom

Personyze recommendations utilize each visitor’s individual interests, transaction history, demographics, as well as machine learning that harnesses crowd wisdom extracted from similar visitors, to generate personal recommendation.

Customizable Cross-Channel Widgets

Personyze’s of widgets includes wishlists so visitors can save products for later, and buy it together widgets, so visitors can check out with a few related products in one click. Code snippets to embed recommendations into emails or app.

A Recommendation for Every Scenario

Personyze’s recommendations include content and product algorithms for anonymous visitors, suggestions backed by past transactions for returning visitors, cross-sale for cart page, and email recommendations.

Provide the Most Personal User Experience Possible.

The recommendation engine builds a unit of recommendations for each visitor based on personal data combined with predictions based on other visitors, producing dynamic recommendations pushed in real time at every touchpoint to give the visitor the most relevant products/content at every moment.

A Personal, Unique Cross-Channel Visitor Journey.

Send personalized email drips with product/content recommendations, targeted content, and promotions directly from Personyze, or embed them into emails with your third-party provider. 

Build Workflow and Integrate Seamlessly Into Your Logic.

You can use built-in wishlists to let visitors save recommended products to a Personyze hosted wishlist, and then show it later on their cart page, or send it in a reminder email. Use Personyze’s smart forms to ask visitors to save their preferred sizes, or to send them a reminder of their cart content. Trigger recommendations right after a product is added to cart, with a list of items bought together. Leverage your customer expertise to fine-tune recommendations

Easy to Use, Integrates Into Your Site in Minutes.

After a 5-minute installatation, our step-by-step wizards guide you through the process of creating recommendations, and industry best practice responsive templates make the process even easier. 

Embed Recommendations on Your Website

Personyze can present both AI generated product or content recommendations on the site, using simple widgets embedded anywhere on your website

Add product recommendations to your existing email

Integrate your in seconds with your existing email provider and campaigns. Simply Add code snippet into your email template.

Send email drips with product/content recommendations

Send personalized email drips with product/content recommendations, targeted content, and promotions directly from Personyze.

Add Recommendations on your Mobile App

Add recommendations and targeted promotions for apps built on iOS and Android.

Add Recommendations on 3RD Party Applications

With Personyze, our teams around the globe can now deliver new targeted promotions and messages within hours instead of weeks. Moreover, our local marketing teams around the world are empowered to manage their own marketing campaigns without the involvement of our core development team!

Trey Ogier
Trey Ogier

We use Personzye for clients from the financial industry to deliver a personalized experience with content and calls to action which are aligned with visitors’ interest and location. The managed service team was very helpful in the implementation with some of our more complex use cases.

Kate Kotzea, Director of Marketing Technology at Click Rain
Kate Kotzea, Director of Marketing Technology at Click Rain

Leverage the Power of

AI Powered Recommendations & Personalization Engine

Imagine going to a store where the front shelves are stocked only with products that you like, or reading a newspaper where the stories you’re interested in move to the front page. This isn’t possible in the brick-and-mortar or print world, but with our powerful recommendations, this is easy to set up on your website.

E-Commerce Recommendations

E-Commerce Recommendations
See how Boomdeal uses interest-based product recommendations to create a personalized experience in their online store.

Content Recommendation

Content Recommendation
See how Global News Today personalizes their home page for a visitor’s known interests.

Recommendation for Online Booking site

Recommendation for Online Booking site
A visitor’s interest in Dubai and luxury travel is used by Personyze to serve targeted content on this airline site.

Works On Any Site

Whatever CMS or ecommerce platform you may be using, Personyze can simply plug into the back-end and completely personalize every aspect of your digital experience.

Industry Best Practice Templates

Personyze includes over 50 recommendation algorithms that are optimal for home page, cart page, category page, or emails, and fully customizable design templates.

Easy Integration of Your Data for Products & Users

Upload a file with your product list or CRM user data, or set a dynamic feed which can be synchronized automatically. Connect your CRM solution using out-of-the-box integration, or our API.

Visual Interface for Setup, No Coding Required

Personyze has a visual simulator interface for you to set up tracking of cart value, adding to cart, checkout, search box inputs, and more. Track virtually anything that appears during a visitor session, without writing a single line of code.

Campaign Simulator

Preview your recommendations’ before they go live, by impersonating different visitors with different characteristics, to see how your campaigns will behave for those segments.

A/B testing and rotations

Rotate recommendation algorithms or designs between different users for A/B testing, or rotate between pages to maximize exposure. Find the exact versions that get the most engagement and conversion. Pick the winner manually, or have it automatically deployed based on time or key metrics.

Delivering recommendations across channels

Personzye’s 360° costumer view makes it easy to merge data from different channels into one customer view, and display recommendations with simple widgets embedded on your site, apps, and in emails. Get code to embed recommendations in your existing outgoing emails. Use JSON API to run a URL with the user’s CRM ID or email, and get back a list of recommendations for them.

Get a Head Start by Uploading Past Transactions

Achieving maximum relevance takes time and data, but by uploading your past transactions, you can give the recommendation engine a head start.

Personalization Tags

Every custom field you create (user industry, account type, etc.) becomes a personalization tag. This means you can include visitor’s name in the title of their recommendations.

Campaign Performance Dashboard

Get a comprehensive campaign performance view, with metrics such as impressions, click through rate, bounce rate, conversion rate, recommendation revenue, time it took to buy from the first click, etc. Filter down to see detailed statistics by recommendation algorithms, list of products or content, and various user data parameters like demographic and location.

Google Analytics Integration

By default, Personyze reports campaign performance in real-time to Google Analytics.

Product Recommendations for Ecommerce

Best Sellers & most popular

This category of algorithms involves showing visitors what is most popular (according to views, adds to cart, likes, comments, purchases, etc.), based on an item that the visitor is currently viewing, a category that they are known to like, or other options.

You may like based on similar users

This recommendation shows products that the visitor may like, because other visitors with similar characteristics viewed, added to cart, or purchased them often. 

Popular in your neighborhood

This recommendation shows items that are popular among other visitors from the same geographic region, or from the same referrer(s). 

Hot sales from items you viewed/left in cart, or interest

This recommendation shows popular items which have recently lowered in price, based on the visitor’s ranked interests from past browsing. 

New on the site from category you purchased in the past

This shows the visitor the newest items from categories they have viewed or purchased from in the past. 

Buy It Again (Re-supply for Perishables)

This type of recommendation is to remind a visitor to purchase perishable items again, after a certain period of time. 

Inspired by your last purchase

This recommendation shows items that were popular among visitors who purchased the same item as the visitor’s most recent purchase. 

those who bought the same also bought
Most recommended for you

This recommendation uses machine learning to find patterns in the crowd data, and shows each visitor what they are most likely to be interested in based on these detected patterns. 

Bought/Viewed together on product page

This recommendation will show the visitor other products that were frequently bought together with the product currently being viewed. 

Up-sell for product you are viewing

This recommendation will show the visitor products which have an up-sell association in the product catalog with the product that is currently being viewed. 

Save to Wishlist

This functionality allows the visitor to add one or more products to their wishlist, to be purchased at a later time, and used in remarketing emails or wishlist recommendations on the site. 

Popular with those who bought from this category

This recommendation shows products that were popular among those who bought and viewed items in the category of the item currently being viewed. 

Content Recommendation for Publishers

You may like based on your interest

This recommendation shows the visitor what they are most likely to be interested in, based on their ranked set of interests derived from previous content interactions.

Those who read this also read this

Shows visitors on a content page what other posts have been most popular among other visitors who read the current post. 

Most popular/commented from this category

Shows the visitor the most viewed, commented, favorited etc. content from the same category as the content currently being viewed. 

Inspired by you recent reading

This recommendation will show a list of most popular content based on those categories most recently read by the visitor. 

Trending now content

This recommendation will show the content that is most popular recently. 

New content from author/interest/category

This type of recommendation will show the newest content from the same author, interest, or category as the content currently being viewed. 

Good for Anonymous Visitors (Location, Referrer, etc.)

You can show recommendations that are popular for users from the same geographic region, which is especially useful for new/anonymous visitors.

Demographic from Facebook or CRM

When you have demographic information on visitors, such as gender or age, you can show items that were popular among their similar demographics. Demographic/CRM variables can be any custom variable you have on your visitors.

Continue Reading/Read It Again (Cross-Device)

Show visitors items which they previously read but did not scroll to the bottom of the page, across devices. 

Most Popular from This Topic

Show the visitor the most clicked, viewed, commented etc. content which has the same topic tag as the content currently being viewed, good for content pages. 

Those Who Read This Bought These Products

This recommendation is good for guide and info pages, and shows products frequently bought by visitors who read the same content currently being read. 

Most Popular Content from Visitor’s Favorite Author

This will show the visitor the most viewed/commented/liked content from their most read author on the site. 

Recommendations for Ecommerce Emails

Now on sale from past interests/left in cart

This recommendation shows the visitor items that have recently changed in price, based on what they previously interacted with or left in their cart. 

Cart abandonment email drip

This type of email recommendation reminds the visitor of items they left in their cart, as well as recommends similar items, in emails sent at intervals determined by you.

time to resupply

This recommendation type reminds the visitor to re-stock perishable items, and can be sent only at certain intervals determined by you.

those who bought these also bought

This email recommendation suggests items based on a previous purchase, using what other visitors who purchased the same product also bought. 

Most recommended for you

This email recommendation uses machine learning to detect patterns in the crowd data, and based on the visitor’s characteristics will show them what they are most likely to be interested in. 

Cross-sale with your past purchase

This email recommendation suggests items which other visitors who made the same purchase as this visitor’s most recent purchase also bought, or items which have a cross-sale association in the catalog with the visitor’s most recent purchase. 

Newly listed items/accessories for you

This email recommendation will suggest items to the visitor that have been newly added, which go together with items previously purchased. 

Send my cart to email button

This button on the site allows the visitor to opt-in for their cart to be sent to their email, as a reminder. If their email is not known yet, it can trigger an email form to be launched in the form of a popup, which can then be used for other remarketing emails, as well.

Content Recommendations Emails

inspired by your past reading

This recommendation type shows visitors the most popular content based on the visitor’s ranked interests from previous content interactions. 

Your weekly updates

The most commented or read content from the past weeks, based on the visitor’s ranked interests. 

Most read/commented/liked content

This recommendation show the overall most popular content on the site. 

those who read what you have also read

This recommendation takes all of the visitor’s past reading, and recommends the most popular content that was also read by those who read all this past content. 

Most recommended for you

This algorithm utilizes machine learning to determine what the visitor is most likely to be interested in, by finding patterns in crowd data. 

New content from your favorite author(s)

This recommendation type shows the visitor the newest content from their most frequently read author(s). 

Popular content based on your profile

This recommendation shows the visitor content that is most popular among other visitors with similar data profiles, such as similar location, referrer, etc.