Introducing Related Categories for Search—a feature designed to help your users find their way to the right product sections when search results aren’t enough.

When users search for broad or unclear terms like “storage” or “gaming,” our system now suggests high-value categories like “Closet Organisers,” “Hard Drives,” or “Gaming Accessories,” helping users shortcut into curated experiences.

Benefits include:

• Better orientation and navigation from search pages
  
  
• Increased exposure for priority categories
  
  
• Higher engagement on discovery-based queries

By guiding users toward relevant categories, this feature reduces friction and significantly improves product discovery. Industry research shows 12–25% improvement in product exploration when users are guided via category-based cues.

To activate Related Categories, please connect with your Customer Success Manager or contact us through support@constructor.io.

At Constructor, we know that merchandisers need visibility into which products are resonating most with shoppers—not just across the site, but on specific pages and over specific timeframes. To make this easier and more actionable, we’re introducing a new Item Analytics table within Page Analytics for search query pages, categories, facet pages, and collections.

Here’s what’s new:

• A new table in Page Analytics that shows top clicked, added-to-cart, and purchased items from that particular page.
• Support for custom date ranges so merchandisers can analyze trends over any relevant time window.
• CSV export to share and collaborate on performance data.
• By clicking on an item, merchandisers can proceed to its dedicated analytics page and see performance across the entire site.

This enhancement addresses a key challenge many merchandisers face: understanding which specific products are performing well within particular discovery contexts. Until now, performance visibility was limited to the last 30 days in the Interact section of the dashboard. With this update, merchandisers can analyze top performers across any time period, having greater flexibility to evaluate seasonal trends, campaign effectiveness, and long-term product performance. With a focused view of what’s working at the page level, merchandisers can double down on high-performing products, fine-tune product placements, and make smarter merchandising decisions faster.

Where to find it: go to Analytics → Search or Browse → Select any page from the tables below the charts → Scroll to the Item Analytics table under the charts.

If you have any questions or feedback on analytics in the dashboard, please connect with your Customer Success Manager or contact us through support@constructor.io.

Constructor is always looking for new ways to enhance the shopping experience for our customers’ shoppers. Our latest facet group sorting algorithm update introduces machine learning to predict the most relevant order for facet groups based on multiple dynamic features.

What is it?

A new machine learning-based approach to facet group sorting that incorporates more data-driven factors, such as coverage and facet type. Instead of using a hard-coded formula, the algorithm uses a trained machine learning model to predict the optimal order of facets for each search or browse query in real-time.

How does it work?

The machine learning model considers the following features:

• Popularity: How often each facet is used by shoppers over a recent period.
• Relevance Attractiveness: The appeal of top items within each facet.
• Diversity: The distribution of items within each facet.
• Coverage: The percentage of products that have the facet.
• Facet Type: The type of facet being displayed.
  
  

These features are processed in real-time by a model trained on historical data. Using this data, the model predicts a final score for each facet, which is then used to dynamically rank the facets during search and browse queries

What problem does it solve?

The new model-based approach enhances the responsiveness and accuracy of facet sorting. It allows for real-time adjustments based on current usage and shopper preferences, ensuring that shoppers always see the most relevant and attractive facets first, leading to a better shopping experience.

Availability:

The feature is rolling out to all customers, replacing the old method of facet relevance sorting with this machine learning-powered approach.

For more information, please contact your Customer Success Manager or reach out to us at support@constructor.io 

What’s new?

With Searchandising Campaigns, merchandisers can now define a single strategy and deploy it across multiple search, category, and facet contexts without creating individual rules for each one. This new feature makes it simple to:

• Group together related queries, category pages, and facet pages into one cohesive campaign.
• Create boost, bury, and slotting rules that apply to all selected contexts at once.
• Save time with bulk actions like Select all and Show subcategories to include every relevant touchpoint with just a few clicks.

Why it matters:

Managing promotional strategies across fragmented contexts used to be time-consuming and error-prone. Searchandising Campaigns fix that by:

• Allowing merchandisers to align their strategy across the entire site so a summer polo shirt promotion appears everywhere from “men’s shirts” to “brand=Ralph Lauren.”
• Reducing repetitive work with intuitive controls like context editing and dynamic subcategory visibility.
• Ensuring better control and consistency with centralised rule management and in-context previews of how changes impact shopper experiences.

Now, whether you’re spotlighting a new product launch or fine-tuning category-specific performance, you can do it all in one place, with precision, scale, and speed.

Learn more in the documentation.

Questions or feedback? Reach out to your Customer Success Manager or contact us at support@constructor.io.

Constructor’s facet group sorting algorithm uses multiple factors to determine which facets are most attractive to shoppers to optimize for e-commerce sales. Yet, there may be instances where merchandisers need to step in and strategically curate the facet experience—hide or change the order of facet groups and/or options within those groups—on certain pages.

That's why we’re excited to expand the dashboard capabilities to merchandise facets to search query pages. Previously, this control was only available on category and collection pages.

This added flexibility allows for smarter, more contextual merchandising. For example:

• During promotional periods, slot 'On Sale' facet group at the top for related search queries.
• Increase visibility of the private-label in the list of brands for key search queries. 
• Hide irrelevant facet groups or options that may appear due to catalog data inconsistencies — such as hiding the 'Gender' facet for 'diaper' searches.

Whether you’re running a campaign, optimizing a product line, or removing noise from the shopper journey, this update gives you more precise control over product discovery experience.

You can find more examples and step-by-step instructions on how to use the feature in Constructor Documentation Guides.

If you have any questions or feedback on Constructor dashboard, please connect with your Customer Success Manager or contact us through support@constructor.io.

At Constructor, we are constantly looking for ways to make it easier for merchandisers to manage their e-commerce business and drive results. However, multi-index customers with operations in different regions and languages face the challenge of ensuring consistency in their merchandising strategy across all of their indexes. Recreating the same rules is cumbersome and time-consuming. That's why we have the Granular Rule Copying feature, and today, we are updating it to support copying rules to different search query pages in the target index. 

Previously, if the query spelling in the target index was different from the source index — which often happens in the case of different languages— merchandisers were unable to copy rules between queries. This meant they often had to manually adjust rules for each region, leading to inefficiencies and missed opportunities for a unified merchandising strategy.

With this update, merchandisers can now copy manual and/or automatic rules from one query in a source index to a different query in a target index, even if the spelling of the queries differs. This helps you maintain a consistent merchandising strategy across multiple regions without the need to manually replicate rules in different languages.

Here are the steps to access the feature:

1. Select Workspace in the side menu of the Constructor dashboard, then select Searchandising.
2. Choose Search & Autosuggest at the top of the listing page.
3. Locate the rule, then select the three-dot icon on the far right of the rule row.
4. Select the copy (middle) icon from the options displayed.
5. On the pop-up, specify new query, rule types, and target index(es).
6. Select Continue in the bottom-right corner of the pop-up.
7. Review the target indexes listed on the following page, then select Start in the bottom-right corner of the pop-up.

If you have any questions or feedback on Constructor dashboard, please connect with your Customer Success Manager or contact us through support@constructor.io.

What’s new?

Faceted Slotting is here to give merchandisers the power to slot items within filtered (faceted) shopping contexts on Browse and Collection pages. With this new capability, you can now:

• Pin items to specific positions after shoppers apply filters like Gender=Mens, Brand=Brembo, or Style=Contemporary.
• Easily navigate and manage slotting rules for refined experiences from a centralized facet searchandising view.
• Drag and drop items or add them manually to the exact spot you want in a filtered results set.

Why it matters:

Until now, item slotting was limited to root-level pages—great for general visibility, but not ideal for targeted merchandising strategies. With Faceted Slotting, you can:

• Showcase the right items in the right context—like highlighting men's t-shirts only when Gender=Mens is selected, or promoting specific coffee blends when users filter by roast.
• Deliver highly personalized and performant shopping experiences by tailoring product placement based on user intent.
• Save time with a streamlined, intuitive UI for managing slotting across multiple filtered views.

📌 Note: Currently available for Browse and Collection pages only. Support for Search, Campaigns, and additional rule types is on the roadmap.

Learn more in the documentation.

Questions or feedback? Reach out to your Customer Success Manager or contact us at support@constructor.io.

We’re excited to announce a new feature in Interact that brings unprecedented clarity and transparency to your product ranking experience.

What’s New?

• More transparent Ranking Explanations – get a detailed breakdown of the factors influencing the ranking of products on your PLPs. Understand why items appear in a specific order, whether due to item attractiveness, product popularity, personalisation, or other signals.
• Updated Recall Reasons –  we’ve refined the recall reasons to provide more actionable insights into why certain products are surfaced.
• New Ranking Insights – discover the most impactful factors driving your rankings, whether it’s a group of signals or specific searchandising rules.
• Explanation tooltips – always be able to understand the ranking factors at play 

Understanding the "why" behind product rankings and recall is critical for effective merchandising. With this update, you’ll gain the insights needed to trust and optimize the retrieval and ranking process, ensuring your best products are always front and center.

Check more details about this update in our documentation.

If you have any questions or feedback on the updated feature, please connect with your Customer Success Manager or contact us through support@constructor.io.

At Constructor, we know that merchandisers are always looking for ways to maximize the visibility and performance of newly launched products, especially in fast-changing verticals like apparel. Merchandisers often pay extra attention to ensure that these new items get the right visibility in product discovery, allowing algorithms to catch up and rank them accordingly. To make this process even easier, we’re excited to introduce a new report that gives merchandisers insights into how newly added items are performing after they’re launched.

Here’s what’s new:

1. A new table within the Conversions section of Analytics, which focuses specifically on items added to the catalog within a selected time period and features metrics such as clicks, add-to-carts, and purchased items.
2. A new Insights block on the homepage of the dashboard, featuring the number of items added to the catalog in the past 7/30 days, the total number of items purchased, and the top five performing items.

This update allows merchandisers to see up-to-date performance data and take timely actions based on how new items are performing. By regularly checking this data, merchandisers can ensure new products get the visibility they deserve and are aligned with the overall business goals.

If you have any questions or feedback on analytics in the dashboard, please connect with your Customer Success Manager or contact us through support@constructor.io.

We constantly strive to provide merchandisers with a holistic view of performance across all stages of the product discovery journey. To deepen this understanding, we are excited to announce a significant update to Recommendations analytics.

With this latest release, merchandisers can now track key business metrics, such as purchases and revenue, for specific recommendation pods. While we've always used this data in our machine-learning algorithms, we want to give merchandisers greater visibility into it. After all, these are the critical metrics for making informed business decisions.

When viewing a specific pod's analytics, purchases and revenue—alongside familiar metrics such as sessions, views, clicks, and add-to-carts—are now available for tracking over a selected period of time and segmentation by platform (Desktop, Android, iOS, etc.). Together, they provide a comprehensive view of recommendations performance, from a pod's appearance in the shopping journey to the completion of a purchase.

There are two ways to find these analytics. You can navigate to Analytics > Recommendations, scroll to the table below the charts, and select a pod. Or, you can also find a pod through Workspace > Recommendations and click the analytics icon next to a certain pod.

If you have any questions or feedback on analytics in the dashboard, please connect with your Customer Success Manager or contact us through support@constructor.io.