Content and Product Recommendations

Personyze’s Recommendation Engine harnesses the power of AI to show each visitor exactly what they are most likely to be interested in, using predictions gleaned from your data. Keep your users clicking through until they find what they’re looking for.

Combining personal and 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 highly personal recommendations.

A recommendation for every scenario​

Set product and content algorithms for anonymous visitors, suggestions backed by past transactions for returning visitors, cross-sales for cart pages, and algorithms designed specifically for remarketing emails. We have an algorithm for just about every conceivable need.

Customizable widgets for all channels

Display widgets in Personyze are completely customizable, and come with a variety of responsive templates for vertical and horizontal displays. They can be embedded anywhere in the site, shown as popups, or embedded in emails and apps.

Easy integration of your data

Synchronize your product/content data automatically using our site content crawler, or use spreadsheet URL, API, or SFTP. Mapping the feed can also be automated, with our contextual algorithm that reads your content, and identifies and ranks interests/topics.

Increase sales with personalized product recommendations

The recommendation engine analyzes the unique browsing and buying behavior of every visitor to your store and then builds a unit of recommendations for each visitor, based on individual ranked visitor interests and demographics, as well as crowd wisdom extracted from other traffic on your shop. The result is dynamic recommendations pushed in real time at every touch-point, to give the visitor the most relevant products at each exact moment, which means more repeat visits, higher order sizes and, most importantly, more sales.

Product recommendation algorithms are specifically designed for various pages and scenarios, with a variety of algorithms for the homepage, product pages, cart page, and more.

Recommended for you
This machine learning-based algorithm uses the totality of user data to find patterns in how users of various types interacted with all of the items in your catalog.

Frequently bought together:
Recommend cross-sale items that were bought together often with the product they’re currently viewing, have in their cart, or have recently purchased.

Show those who viewed this also viewed/bought:
Suggesting the right alternatives, based on similarity or crowd data, will increase the number of products viewed and time spent in a convenient shopping flow.

Those who bought from this category also bought:
Recommend items frequently bought from other categories by customers who bought from the category they are viewing or just purchased from.

New in stock
Help customers stay up-to-date on items that are new on your shelves, with the option to fine-tune for items added to the site in the last 7 days, before the last visior, or based on visitor’s interests.

View it again/buy it again
Show the items they recently viewed or bought, so they can pick up where they left, or items they bought in the past so they can easily resupply. 

Further, fine-tune your recommendations with filters:

  • Discount = greater or less than X%
  • Product feed attributes, such as interest, color, brand, or price. 
  • Within X miles of distributions center’s location, offer free shipping
  • Visitor’s gender, age, client type, industry, etc.
  • Less than X units in stock

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.


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-Sell Based on Last 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.

Display widgets for recommendations are simple HTML and can be any design you like, but Personyze comes with a variety of responsive templates for horizontal and vertical displays by default, with an editor to change all aspects of the design to match your site.

All recommendations are responsive and can be displayed as popups, embedded into pages, emails, or apps with any HTML/CSS design you like for just the right look and feel.

Improve readership with content recommendations

Personyze’s dynamic content recommendations engine utilizes  visitors’ personal data combined with contextual recommendations and predictions based on crowd data from other visitors, producing dynamic content recommendations pushed in real time at every touchpoint, giving the visitor the most relevant content at every moment. The end result is higher engagement and return visits.

Content recommendation algorithms are specifically designed for various pages and scenarios, with a variety of algorithms for the homepage, article pages, search page, and more.

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 or Topic
Shows the visitor the most viewed, commented, favorited etc. content from the same category or topic 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.

Demographic or CRM
When you have demographic information on visitors, such as gender or age, you can show items that were popular among their similar demographic. Demographic/CRM variables can be any custom variable you have on your visitors.
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/Topic
This will show the visitor the most viewed/commented/liked content from their most read author/topic on the site.

Display widgets for recommendations are simple HTML and can be any design you like, but Personyze comes with a variety of responsive templates for horizontal and vertical displays by default, with an editor to change all aspects of the design to match your site.

All recommendations are responsive and can be displayed as popups, embedded into pages, emails, or apps with any HTML/CSS design you like for just the right look and feel.

A uniquely personal 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. Create a seamless experience as the personalization flows from your emails to your site, partly based on the email they arrived from.

Personyze can present AI generated product or content recommendations on the site, using simple widgets embedded anywhere on your website, as well as in emails or apps.

Integrate recommendations with your existing email provider and campaigns in seconds, by simply adding a code snippet into your email templates.

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

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

You can also use  JSON API to run a URL with the user’s CRM ID or email, and get back a list of recommendations for them.

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. Use the data collected to provide further recommendations or auto-fill product fields like size.

Recommendations widgets can include an add to cart button that add the items to their cart directly from the widget

API and Integerations

Works on any website, regardless of platform, all channels, and has full rest API available.

Even easier plug-and-play integrations with popular platforms, such as Segment, WordPress, Shopify, Magento, Salesforce, Hubspot, and more.

Content Widgets

Add any type of content to your site and emails, with many templates to get you started.

Personyze comes with many responsive templates for popups, sliders, countdowns, banners, recommendation displays, forms, and more.