Release Summary - Aug 24, 2023

Enhance Social Proof Experience Campaigns with Importance Indicator

In this release, we have introduced a new enhancement to Social Proof, enabling users to assign Importance levels to their experiences. This empowers Digital Experience Optimizers to ensure that the most vital social proof messages are displayed when conflicts arise between multiple experiences.

Now, when configuring a Social Proof experience, you can specify its Importance level. The system will automatically prioritize experiences based on their Importance values, allowing for precise control over message display. This enhancement provides users with a powerful tool to optimize customer engagement strategies and ensure maximum impact.

Jira: ENG-26565

Display Interval Values for Each Message Type in Social Proof UI

In this release, we have enhanced Social Proof by allowing Digital Optimization Managers to conveniently view and adjust interval settings within the user interface for each message type, eliminating the need for JavaScript code modification.

Within the Social Proof campaign configuration, a dedicated section for interval settings is available for each message type. Here, you can set numerical values and units (Minutes, Hours, Days, or Weeks) for intervals, with default settings displayed as a reference.

This streamlines interval management, enabling you to optimize campaigns effortlessly. Please note that interval values are optional for specific message types, simplifying your campaign setup.

Jira: ENG-26577

Enhanced Social Proof by Displaying Dates Alongside Campaign Names

We have enhanced our Social Proof feature to provide clearer campaign management. You can now view campaign dates alongside the campaign name, both in view and edit modes. This update streamlines the editing process, making it easier for you to manage campaign date ranges with confidence.

Jira: ENG-26510

Composite Outfit UI - Enable to Select Category/Sub Category from Category Hierarchy

We have made it easier for merchandisers to select categories and subcategories within our Composite Outfit feature. With the addition of a category hierarchy view, you can now effortlessly choose categories for defining styles and include/exclude subcategories without needing to remember category IDs or names. This update streamlines the category selection process, enhancing your overall experience when creating outfits.

Jira: ENG-25811

Resolve CXP Portal Issue with UPS Category View

We have resolved an issue in CXP Portal UPS, where some users encountered excessive category views being displayed inaccurately.

Upon thorough investigation, we identified that all category views were mistakenly added to all sessionID-date sections, leading to an inaccurate representation of user activities. To rectify this, we have refined the categorization of category views, ensuring they are now accurately displayed only within the relevant sessionID-date sections.

Jira: ENG-26436

Add a diversify by attribute filter to Only Recommend rules

We've introduced a new feature that provides digital merchandisers with even greater control over recommendation diversity. Now, within the "Only Recommend" rules, merchandisers can apply diversity filters based on specific product attributes. This means you have the flexibility to precisely tailor diversity settings to meet your unique requirements.

For example, imagine you want to showcase product recommendations while ensuring that products with the same "product type" attribute are not overly repeated. With this feature, you can easily achieve this goal. You can specify the attribute name, set the maximum number of products per attribute value (e.g., limit each color to 3 products), and fine-tune your recommendations to provide more personalized and engaging shopping experiences.

This enhancement isn't limited to a single strategy type; it's adaptable across various strategy types, making it versatile and suitable for a wide range of merchandising needs.

Jira: ENG-26179

Enhance Configurable Strategies Best Offers Model with Personalization Seed Options

In this release, we have improved the Best Offers model within Configurable Strategies. Now, you can easily customize your top offer recommendations based on specific categories or brands.

Within the 'Strategy Composition,' you'll find Personalization Seed options that match those for Top Sellers, including User's History-based preferences like Category and Brand Affinity, as well as Context-based options like Category and Brand Context.

In the 'View Results' tab, input options align with your selected seed for straightforward configuration, supported by auto-complete functionality.

These enhancements offer you more flexibility and precision when configuring your Best Offers strategy.

Jira: ENG-26100 & ENG-25731 

Ability to Set TTL for Email Recommendation Cache (Early Access)

We have introduced the ability for merchandisers to define the time-to-live (TTL) for email recommendation caches at the site level. This enhancement allows merchandisers to have precise control over how long recommendation caches are maintained, offering a more tailored and dynamic shopping experience for your customers.

With this feature, you can configure the cache refresh rate to align with your specific needs. For example, you can set a cache TTL of 12 hours for one site, ensuring that recommendations are refreshed twice daily, while another site might benefit from a 6-hour TTL, delivering entirely different recommendations to shoppers who open their emails within that timeframe.

This level of customization empowers you to optimize your email marketing strategies by providing fresh, relevant product recommendations to your customers. Whether it's promoting new arrivals, showcasing trending products, or highlighting personalized suggestions, this feature allows you to fine-tune your email recommendation caching for maximum impact.

Jira: PLAT-3473

Catalog Enrichment data import for feed clients

In this release, we have introduced a streamlined integration for Catalog Enrichment data, enhancing the capabilities of our feed clients. This improvement enables seamless synchronization of approved Catalog Enrichment attributes with product IDs in the Primary catalog, ensuring your product recommendations are both accurate and effective.

Here's how it works: During the feed herder process, the system automatically collects accepted Catalog Enrichment attributes and synchronizes them with corresponding product IDs in the Primary catalog. This synchronization occurs each time the feed herder process runs, guaranteeing that your product catalog is consistently updated with the latest enrichment data.

To maintain data relevance, the process refreshes Catalog Enrichment attributes every 24 hours. This advancement not only simplifies your workflow but also empowers you to utilize these attributes for attribute top views, attribute top sellers, user affinity, rules, and guided selling filters.

Jira: PLAT-3527