A Recommendation Algorithm for Every Situation
Personyze recommendations utilize a wide variety of algorithms to show visitors what they’re most likely to be interested in reading or buying, by combining crowd data with tracked individual visitor interests, as well as other user data such as demographic and location.
Visitor interests are derived from how each visitor has interacted with the content or products in your catalog/feed. Each time a visitor views, clicks, likes, comments upon, adds to cart, or purchases a product or piece of content, this feeds into Personyze’s data and contributes to recommendations that increase engagement across your website, email, and app.
Personyze recommendations and all other Personyze features work on ANY ecommerce/website platform, including WordPress, Shopify, WooCommerce, Magento, and every other platform in existence.
Note: This list does not include every algorithm that is available with Personyze, but rather those which are most popular with our clients. If there is an algorithm you are interested in that is not found here, feel free to contact us to inquire whether it’s available in our system.
Product Recommendations On Website
Content Recommendations On Website
Product Email Recommendations
Content Email Recommendations
Recommendation Algorithms FAQ
The more data your feed contains, the more rich and dynamic your product recommendations will be. The most essential things to include are:
- Product Title
- Product Listing URL
- Product Image URL
- Product Description
- Interest Categories for each product (click here to read more about interests)
- Product ID (SKU, or similar unique ID)
Some additional product data that are helpful to have are:
- Sale Price
- Cross-Sale SKUs
- Up-Sale SKUs
- Secondary Interest Categories
- Seasonal product associations (sells more in the Summer/Winter)
- Availability (In Stock or not)
For content, the requirements are fewer, and the key essentials are:
- Content Title
- Content Page URL
- Content Image URL
- Content Description
- Interest Categories for each article (click here to read more about interests)
- Content ID (SKU, or similar unique ID), if applicable
You’ll also need to tell Personyze which column corresponds to which value, in your Personyze product feed.
Yes, if your product inventory or content catalog exists in the form of any type of feed or spreadsheet, it’s possible to integrate it with Personyze. The default formats our system works best with are .CSV, RSS feed, .XLS, and similar.
Yes, most recommendation algorithms allow you to add additional filtering, based on any of the 70+ data points which Personyze has on visitors, including demographics, location, CRM attributes, and more.
Yes, you can show as many display widgets with as many designs and algorithms as you want, throughout your site, emails, and apps.
Yes, every recommendation widget can be targeted to individual audience segments, such as only returning visitors for Buy It Again recommendations.
This will depend on a few different factors, including your site traffic, volume of products or content, and whether or not Personyze is starting from scratch.
It’s possible to upload past interactions data, such as past ecommerce transactions of users, to give the algorithms a head-start, and if such data is available this is highly advisable. The Personyze team will help you with this process.