Release Summary - Nov 14, 2024 (24.22)

The following key features and improvements, along with bug fixes, have been released in Algonomy CXP products in the release version 24.22.

Ensemble AI, Science

Ensemble AI: Region-Specific Ensemble Generation and Preview

Ensemble AI now enables clients to generate region-specific ensembles based on configurations set at the style level, ensuring outfits are created using only the catalog available for each shopper's region. Merchandisers can configure styles with a region parameter alongside the product seed, allowing for targeted, region-specific ensembles. Additionally, through a site configuration, non-regionalized products can be included in ensemble generation across all regions, allowing these universal products to seamlessly integrate with regional selections. This enhancement enriches the shopping experience by providing localized outfit recommendations while offering merchandisers flexible control over product inclusion.

Ensemble AI also introduces a region selection dropdown in the preview, allowing merchandisers to review region-specific outfits tailored to different locales. With "Use region as a seed" enabled, users can select a region from the dropdown to see the number of products per part and total possible combinations without altering the style definition. This feature provides accurate insights into regional product combinations, enhancing control over targeted regional displays.

Jira: ENG-28265, ENG-26579

Ensemble AI: Generate Transparent Images for Enhanced Product Overlays

Ensemble AI now supports transparent images, allowing merchandisers to create visually engaging product combinations that seamlessly overlap, providing shoppers with a realistic preview of how products look together.

Key Enhancements:

  • The Shopper API has been updated to include URLs for transparent images, either provided by clients or generated by the platform, for seamless integration with front-end displays.

  • The Portal API also provides URLs for transparent images, enabling merchandisers to toggle between standard and transparent views within the portal.

  • If transparent images aren’t available from either client or platform, the API handles this gracefully, ensuring front-end and portal compatibility.

Jira: ENG-28170

Ensemble AI: Including RCS in API Response for Consistent User Journey

The Ensemble AI API now includes the RCS (RichRelevance Client Session) parameter in its response, enhancing consistency for server-side clients and mobile apps in user journeys. Previously, RCS was unavailable on initial Ensemble API calls, which could disrupt seamless personalization. By integrating RCS directly into the API output, optimization managers can maintain consistent tracking and user experience across API interactions.

Jira: ENG-28516

Enterprise Dashboard

Multi-language Support in Guided Selling

Guided Selling now supports multi-language configurations, allowing merchandisers to create dynamic quizzes in multiple languages without duplicating experiences for each language. Users can manage translations by downloading a blank CSV from a new "Translations" tab, entering language-specific content for quiz elements, and uploading the file to apply translations across the experience. Translatable fields include start screen titles, descriptions, button labels, questions, and answers. This feature simplifies multilingual setup, enhancing accessibility for international audiences.

To aid in managing multi-language quizzes, a language dropdown has been added for previewing and editing translated content. Merchandisers can switch between languages during quiz editing, with any changes saved to the translations API. For consistency, adding screens or answers is restricted to the default language, and alerts appear when unsaved changes are detected or when deleting screens and answers that have translations. This comprehensive language support provides an efficient way to deliver localized Guided Selling experiences, ensuring accuracy and relevance for diverse user bases.

Jira: ENG-28721, ENG-28722

Guided Selling: Enhanced Naming, Quiz UI, and Styling Updates

Guided Selling now features unique default variation names (e.g., "Variation 1," "Variation 2") with validation to avoid duplicates when renaming. The "Restart Quiz" button is repositioned to prevent overlapping with the close button and features an updated icon.

Additional improvements include font adjustments and justifications in the Recommendations preview to ensure a cleaner look and alignment. For scenarios where no products are found, the message now appears in-line within the recommendation display instead of as a pop-up.

Jira: ENG-29165

Configuration Options for Seeds

The latest update introduces flexible configuration options for seed selection, enabling digital merchandisers to prioritize recent products from a shopper's view or purchase history. In Configurable Strategies, merchandisers can now specify the number of seed items and set a custom lookback period, allowing for more precise control over personalization. This replaces the previous "Use Multiple Items" checkbox with a refined interface where merchandisers can input specific values for seed item count and a date range for user history.

Merchants can define a lookback period, such as “0 to 30 days ago,” and adjust the number of seeds, ensuring that the most relevant products are prioritized. These settings are applied in both the preview and saved configurations, providing enhanced control and granularity in strategy personalization.

Jia: ENG-28713, ENG-26113

Roll-up Category Affinities to Parent Categories

This new feature enables digital marketers to leverage higher-level category affinities when targeting content, enhancing the precision of content delivery in Engage. Previously, category affinities were only calculated for leaf categories, such as Skinny Jeans in a hierarchy like Women's Clothing > Jeans > Skinny Jeans. With this update, affinities now roll up to parent categories, so if a user shows interest in Skinny Jeans, their affinity will also extend to broader categories like Jeans and Women's Clothing. This allows marketers to target users based on higher-level category interests.

The User Affinity Configurations now include default weights for category tiers (from Tier 1 to Tier 5) with a customizable range up to 100. The UI has been updated to enable marketers to set these weights and view category tiers. When category tiers are displayed, a note clarifies that they specifically apply to Engage content. Additionally, charts for category tiers are hidden when their weight is set to zero, ensuring a cleaner and more focused visualization.

Jira: ENG-29176, ENG-29258

Advanced Merchandising Strategy: Exclusive Use in Specific Placements

This update allows Advanced Merchandising strategies to operate exclusively in selected placements. Previously, if no Advanced Merchandising rule was found, other strategies were triggered, requiring additional Rec Restriction rules and increasing response times. Now, when AdvancedMerchandisingStrategy is applied in a strategy rule with the "use only these" option enabled, only the Advanced Merchandising strategy is evaluated. If there’s no applicable AdvMerch rule for the seed product, no recommendations are returned, eliminating the need for restrictive Rec Restriction rules.

Jira: ENG-29152

Ingredient Cross-Sell Strategy: Expanded Product Model Limit

The Ingredient Cross-Sell strategy has been updated to increase the maximum number of products from 50 to 300, allowing for a broader product selection. Additionally, this strategy now correctly includes previously purchased items, aligning with its purpose of showcasing relevant past purchases in cross-sell recommendations.

Jira: ENG-28179

Find Reporting Enhancement: Filter by Wildcard Searches

Find Reporting has been enhanced to include a filtering option that allows digital optimization managers to view metrics solely for actual search queries, excluding broader Find requests. This addresses the need to differentiate true search activity from general Find usage, which often includes wildcard queries (e.g., query=*) used for navigation or listing purposes. With this enhancement, metrics more accurately reflect targeted searches with defined terms.

By default, the report now excludes wildcard searches, but users can opt to include them by selecting the "Include wildcard searches" checkbox.

Jira: ENG-28923

Data Engineering

Dynamic Experiences Report: Aggregated and De-aggregated Views

The Dynamic Experiences Report now offers merchandisers the ability to view data aggregated and de-aggregated by experience, allowing for a comprehensive report across multiple experiences, including those segmented by region. This enhanced report includes a multi-select experience selector, with the option to select or deselect all experiences, making it easier to analyze performance across various experiences in a single view.

Users can now toggle between aggregated and de-aggregated views for both graph and table visualizations. In de-aggregated mode, the report provides individual experience details for each variation, complete with a new "Experience" column for a clearer, more summarized view.

Jira: ENG-27735

MVT Reporting: Download Visit Data for Concurrent Tests

Merchandisers can now download visit data for concurrent tests, allowing for deeper analysis when unexpected test results occur. This feature enables users to obtain visit data specific to a chosen test, filtering out treatments from other concurrent tests to maintain focus on the relevant data.

This enhancement, initially restricted to internal users, is now available for external users conducting concurrent tests, providing them with streamlined access to test-specific insights.

Jira: ENG-28979

Display External Region IDs in Reports

To improve report clarity for clients, all analytics reports have been updated to display external region IDs in place of internal region IDs. Previously, internal region IDs were shown, which held limited relevance for client teams. With this enhancement, reports across the analytics suite now present external region IDs, offering more meaningful insights.

Jira: ENG-27496

Other Feature Enhancements

The following feature enhancements and upgrades have been made in the release version 24.22.

Jira #

Module/Title

Summary

General Availability

ENG-29102

Ensemble AI, Science:

Customizable Complimentary Color Mapping

Ensemble AI now supports customizable complimentary color mapping, allowing clients to define specific color combinations for ensembles through the model build configuration. Clients can use the model options API to view and adjust default color pairings, enabling brand-aligned color coordination. For instance, clients can configure the model to avoid certain pairings, like red with black, enhancing brand consistency in outfit recommendations.

14-Nov-24

ENG-29268

Ensemble AI, Science:

Ensemble AI API Call Count Reporting

Ensemble AI now offers API call count reporting, allowing merchandisers to track daily usage via TS visualizations for greater billing transparency. API calls are logged through Avro logs, capturing metrics like Site ID, Site Name, Method, Date, and Total Call Count. This enables teams to monitor API activity effectively. The reporting is viewable through TS visualizations, similar to the Find API reporting, with the dashboard update pending.

14-Nov-24

ENG-29090

Ensemble AI, MVT, Science:

Ensemble AI: MVT Site Configuration

This update enables Digital Optimization Managers to export Dynamic Experience and Social Proof reports, allowing for easy sharing of detailed report insights with stakeholders. Available in both CSV and Excel formats, the export includes all metrics along with lift and confidence values, and provides an option to download visualizations.

14-Nov-24

ENG-27761

Data Engineering:

Co-occurrence Report: Customizable Co-Purchase Category Selection

The Co-occurrence Report now enables merchandisers to customize their view by selecting specific co-purchase categories to include in the report. This feature allows users to filter the co-purchase data based on categories of interest.

Merchandisers can select one or multiple categories, including higher-level categories, with all associated subcategories automatically included. A primary category flag is also added to the rollup data, streamlining category management and ensuring reports reflect only the most relevant co-purchase relationships.

14-Nov-24

ENG-29098

Data Engineering, Find:

Find Reports - Enhanced Reporting with findCallType and Response Style

Find Reports now include the parameters findCallType and response style within the visit logs, enabling more granular reporting from the find API calls.

Notably, findCallType entries tagged as "overlay" are excluded from reporting if they don't involve a search tracking URL click. Similarly, reports will exclude entries where the response type is "facet only," ensuring that the metrics reflect only meaningful search interactions. 

14-Nov-24

ENG-28081

Data Engineering, MVT:

New Social Proof A/B Testing Support

Merchandisers can now conduct A/B testing specifically for social proof configurations through a newly added SOCIAL_PROOF test type. This functionality allows users to enable or disable the social proof feature for a specified percentage of traffic, providing insight into social proof impact on engagement and conversions.

The new setup also supports the includeMVTDetailedData parameter for both the productEventMetrics and spMessages APIs, along with the mvt_ftr preview feature, enhancing control over test previews and data accuracy. 

14-Nov-24

ENG-25994

Enterprise Dashboard:

Export/Download Dynamic Experience and Social Proof Reports

Export Dynamic Experience and Social Proof Reports

Digital Optimization Managers can now export the Dynamic Experience and Social Proof reports in CSV or Excel formats, making it easier to share insights with external stakeholders. The export includes all metrics, along with lift and confidence values, and supports downloading visualizations.

14-Nov-24

ENG-29386

Find:

New Find Stack: Enhanced Index Matching in Find Deployer

The Find Deployer on the new Find stack now includes a check to match indexProperties.numFound before activating the alias, ensuring data accuracy prior to deployment.

14-Nov-24

ENG-29385

Find:

Include numFound and JavaBin Properties in Batch Index Zip

The batch index zip now contains additional properties, including index.numFound and javabin.totalNumFound, in the indexProperties file. This enhancement allows for more accurate tracking of document counts in index downloads, aiding in comprehensive data validation for all job types.

14-Nov-24

ENG-29406

Find:

New Error Bucket for MAX_BOOLEAN_CLAUSE Solr Exception

A new error bucket has been added to handle MAX_BOOLEAN_CLAUSE exceptions in the search service on J11. This categorization allows for better tracking and resolution of errors related to Boolean clause limits in Solr queries.

14-Nov-24

ENG-29341

Find:

Offmenu Plugin Performance Improvement

Performance improvements have been implemented for the offmenu plugin, enhancing its efficiency.

14-Nov-24

ENG-29101

Recommend:

Update to Configurable Strategies with UPS Seed Options

Existing configurable strategies using UPS seed options have been updated to maintain prior functionality. For strategies where seedStrategy is set to ACCUMULATE, the seedLimit is now set to 5. For strategies where seedStrategy is set to FIRST_VALID, the seedLimit is set to 1.

14-Nov-24

ENG-29255

Engage:

Dashboard Support for Enhanced Tags Syntax

Digital marketers can now add Enhanced Tags directly via the dashboard, enabling content sorting by affinity. Tags added in the expected syntax (brand:, category:, or attribute:) will be treated as Enhanced Tags, aligning them with specific brands, categories, or attribute key-value pairs. When the Content Model is rebuilt, these tags will automatically assign the content to the designated brand, category, or attribute, providing seamless tag integration and improved content organization.

14-Nov-24

PLAT-3840

UPS:

Wishlist Items Now Stored in User Profile Service (UPS)

To enhance personalization, our platform now stores wishlist items in UPS, allowing finer adjustments based on products customers add to their wishlists. Each product’s ID, brand, category, SKU, price, and quantity will be stored in a dedicated "Wishlist" section within UPS, supporting up to 20 items by default. Wishlist changes, such as adding or removing items, are captured in real-time through front-end instrumentation and API updates, ensuring that UPS accurately reflects the latest customer preferences.

14-Nov-24

PLAT-3871

UPS:

Tracking "Remove from Cart" Events in UPS

To improve recommendation accuracy, the platform now captures "Remove from Cart" events directly from RRserver, logging each product removal in UPS. This enables merchandisers to generate recommendations that reflect the most current items in a shopper’s cart, even if the shopper hasn’t revisited the cart page. Through enhanced front-end instrumentation and API updates, detailed product information—such as ID, brand, category, SKU, price, and quantity—is tracked for each removal event.

14-Nov-24

ENG-29374

Data Engineering, Data Reporting:

Addition of include_star Attribute to ThoughtSpot Configuration

The include_star attribute has been successfully integrated into the thoughtspot.properties file in production. This attribute, relevant to the find report, is now configured and fully operational within the ThoughtSpot environment for enhanced reporting accuracy.

14-Nov-24

ENG-29329

Data Engineering, Social Message:

Logging of User and Channel Information in SP-API

The SP-API now logs User ID, Session ID, and Channel information in the API call log when these details are provided in the request. This enhancement ensures that User ID (u or userId), Session ID (s or sessionId), and Channel (cak or apiClientKey) are captured in HDFS, providing more comprehensive logging and tracking of API calls.

14-Nov-24

ENG-29356

Data Engineering, Data Reporting, Social Message:

Log Social Proof API Calls for Server-Side Integrated Clients

The Social Proof API now logs all server-side API calls ("spMessages") for enhanced reporting and tracking. This logging is added to avro logs to monitor daily usage by each site, capturing details such as Site ID, Site Name, Method, Date, and Total Call Count. These insights are visualized in TS reports, similar to existing Find API reporting, providing merchandisers with a clear view of API call volumes for better usage analysis and billing transparency.

14-Nov-24

ENG-29335

Enterprise Dashboard, Find:

Log Social Proof API Calls for Server-Side Integrated Clients

The Social Proof API now logs all server-side API calls ("spMessages") for enhanced reporting and tracking. This logging is added to avro logs to monitor daily usage by each site, capturing details such as Site ID, Site Name, Method, Date, and Total Call Count. These insights are visualized in TS reports, similar to existing Find API reporting, providing merchandisers with a clear view of API call volumes for better usage analysis and billing transparency.

 

Bug and Support Fixes

The following issues have been fixed in the release version 24.22.

Jira #

Module/Title

Summary

General Availability

ENG-29339

Recommend:

Log Social Proof API Calls for Server-Side Integrated Clients

The Social Proof API now logs all server-side API calls ("spMessages") for enhanced reporting and tracking. This logging is added to avro logs to monitor daily usage by each site, capturing details such as Site ID, Site Name, Method, Date, and Total Call Count. These insights are visualized in TS reports, similar to existing Find API reporting, providing merchandisers with a clear view of API call volumes.

14-Nov-24

ENG-29379

Engage :

Engage Content Affinity Ordering Issue Resolved

An issue was identified in Engage where content ordering by affinity was not functioning as expected, resulting in a seemingly random order of prioritized content. For example, "Carbonated drinks" content was intended to consistently appear before "Yogurt" based on affinity but was occasionally displayed in random order.

This issue has now been resolved, ensuring that content is ordered correctly by affinity,

14-Nov-24

ENG-29299

Enterprise Dashboard:

Set a Max Width/Height on Images in User Affinity Configuration

Images on the User Affinity Configuration page now display within a fixed box of 150x150 pixels, ensuring consistent sizing during preview.

14-Nov-24

ENG-29307

Enterprise Dashboard:

Category Recs Image Not Displaying on Recs Test Drive

An issue was identified where category recommendation images were not displayed correctly in the Recs Test Drive due to encoded URL values. The system now decodes these URLs, allowing images to be rendered as expected. This fix ensures category images display accurately for a seamless user experience in the Recs Test Drive. The issue has been resolved.

14-Nov-24

ENG-29219

 

Enterprise Dashboard:

Guided Selling - Duplicate Experience Created

An issue was identified in Guided Selling where creating a new experience resulted in the unintended creation of two instances—one with a variation and one without. Similarly, adding a new variation to an existing experience sometimes generated duplicate variations. This fix ensures only a single experience or variation is created as intended. The issue has been resolved.

14-Nov-24

ENG-28987

Enterprise Dashboard:

Fixes to Product Comparison UI

Updates to the Product Comparison UI now improve clarity and functionality. The "Product Attribute" label has been renamed to "Attribute Blacklist" with a tooltip noting that blacklisted attributes won’t appear in Product Comparison placements. When creating new rules, blacklisted attributes are automatically excluded.

14-Nov-24

ENG-29168

Enterprise Dashboard:

Search Term Expansion - Export Hover Issue Fixed

Previously, hovering over the Export button on the Search Term Expansion page incorrectly logged user activity as an export action. This issue has been corrected, ensuring activity logs only capture actual exports rather than hover actions. The issue has been resolved.

14-Nov-24

ENG-29411

DSW rrDatameshJob Docker Container Exit Issue and Log Improvements

The rrDatameshJob docker container was not exiting after completing its task, causing it to run continuously. This issue has been resolved to ensure the container exits properly post-task, along with improvements to log clarity.

14-Nov-24

ENG-29424

Enterprise Dashboard:

Guided Selling: Unable to Enter Price Range in Activity-Based Quiz

In the Guided Selling quiz flow on the REI site, users were unable to input values for minimum and maximum price ranges on Screen kay-3, limiting their ability to filter quiz results based on price. This bug has been resolved.

14-Nov-24

ENG-29317

Enterprise Dashboard, Find:

Boost/Deboost Search Rules: Unable to Set Negative Value with Arrows

In the Boost/Deboost search rules interface, users faced an issue where they could not set a negative boost value using the arrow keys, as the field would stop at zero and generate an error. This issue has been resolved, allowing users to adjust boost values into the negative range smoothly using the arrows.

14-Nov-24

ENG-29316

Enterprise Dashboard, Find:

Boost/Deboost Rules: Attribute Lookup Issue Fixed

An issue was identified where attributes were not appearing as options when adding a boost/deboost rule, preventing users from selecting desired attributes. The system was not performing attribute lookups as expected, which caused the list to appear incomplete. This issue has been resolved, and all available attributes now display correctly during rule configuration.

14-Nov-24