Quizzes are often highly experiential in nature and building out quizzes with that experience in mind can be tricky before you are able to see it come to life to make sure it is just as you envisioned - until now. 

We’re excited to announce the release of our quiz preview experience so that merchandisers can get a sense of what the quiz they are building out will be like before it is rendered on their site. This will allow merchandisers to make edits and adjustments and validate them in real time directly in the dashboard. 

Preview can be found in the top right next to the “save” button.

Example generic preview experience.

Within the preview merchandisers be able to validate all content (including copy and images), the quiz flow through different combinations of questions and answers, and the results returned at the end of the quiz for a given flow in a generic preview experience. 

For more information about Quizzes, check out our product page, connect with your Customer Success Manager, or contact us through support@constructor.io.

We recently released the slotting Rule Performance page to measure how slotting rules affect add to carts (ATC), and now the analytics are even more detailed! The new summary statistics and time series view will help merchandisers make data informed decisions to optimize business KPIs and merchandising rules. Clicking on the more information arrow on specific rules will allow you to view the detailed statistics on rule performance.

Below the summary statistics is a time series chart showing the daily conversion totals from slotted and unslotted results. The chart below shows that once the product was slotted (represented by the blue dots), the performance dropped off significantly from past performance (represented by the gray dots) when the position was not slotted. 

These additional insights will help merchandisers measure the impact slotting rules have on business KPIs. For more information, please connect with your Customer Success Manager, contact us through support@constructor.io, or read our documentation on merchant intelligence.

Power ecommerce product search and product discovery with Constructor and integrate with Akeneo for automated product catalog data updates.

We make the process of building and maintaining integration with Constructor even easier for Akeneo PIM customers. Introducing Constructor Connect for Akeneo – the App on Akeneo App Store, that makes it easy to connect and upload your Akeneo product catalog to Constructor. 

Now you can integrate all product data from Akeneo to power Constructor solutions, identify optimization opportunities, and empower your ecommerce team in real-time:

• In just a few clicks, connect your Akeneo catalogs for ingestion to Constructor (categories, products, and variations included)
• Done-for-you integration: no need to rely on engineering resources or third-party apps
• Up and running: integrate your product data in as little as the same business day 
• View catalog ingestion status anytime on the Constructor dashboard

Use our visual dashboard to validate your product data within the Constructor platform.

For more information, please connect with your Customer Success Manager, view our documentation, or reach out at partners@constructor.io    

Overview

Constructor’s conversion optimization and discovery benefits are only as good as our uptime and performance. For this reason, we have a robust process of performance validation and monitoring. During the holiday season and the peak demand period of Black Friday and Cyber Monday, we increase our standards in all of these areas out of recognition that it is the most important selling period for many of our customers.

Survey of peak demand for 2021

In planning our preparations in the run-up to the 2022 holiday season, we looked back to daily and peak demand changes during the holiday season and also reviewed how our baseline traffic has increased in the time since then.

Last Black Friday our overall traffic increased 44% compared to Black Friday 2020, which was already 200% over daily baseline levels. Not only did we maintain our 100% uptime, but performance during the peak demand periods actually improved relative to equivalent periods (due to changes in traffic patterns). Since then the system has already scaled without interruption or degradation. For the past several  months our average daily traffic has been greater than last year’s Black Friday event.

Performance improvements over the past year

Over the past year we have worked continuously to drive even better performance and scalability, contributing to improved latencies and zero downtime. Some example projects and outcomes include:

• Decreased index update delivery times with incremental indices
• Rolled out new datacentre in Asia
• Continued to improve instance boot and data download time by a further ~50%
• Introduced parallel processing of requests
• Added more IP’s per service region
• Created independently scalable sub-services in each region
• Increased service dependency redundancy
• Improved our internal service monitoring platform
• Upgraded our operations and incident response platform
• Introduced IP based traffic prioritization

Scale-out performance testing 

We have tested scaling to 2000% of current average daily traffic volume, while validating the continued performance of the following:

• Database connections 
• Monitoring infrastructure
• Networking infrastructure
• Response latencies @ median, 90th percentile, 95th percentile, 99th percentile
• Response latencies for each customer, and each product used by each customer
• Data ingestion SLA times

Chaos and anti-fragility testing

We also use chaos testing to validate that catastrophic failure of the following supporting infrastructure does not impact critical features (primarily search, autosuggest, browse, recommendations, collections request/response times):

• Disabled MySQL
• Disabled index builders
• Disabled personalization queues
• Disabled supplemental ranking engines
• Availability zone and data center failures

All of the above is in addition to the rigorous performance test and rollout plan we use for every release:

• Full test suite on every pull request (incremental code change).
• Production traffic replay for all deployment builds (multiple times a week).
• Rolling, risk-adjusted deployment procedures across worldwide data centers.
• Canary deployment for deploys touching critical path request/response lifecycle.
• Automatic build failures if sensitive thresholds on result quality, latency, memory consumption, CPU consumption and more are breached at any of these levels. 

Standard on-call procedures                                                                                  

At all times we have multiple on-call schedules for the following teams:

• Front-end and client teams 
• Data science and result quality teams 
• Core platform and response performance teams 
• Each of these have multiple fallbacks and tiered escalation policies

Automated alerting

Alerting is automated across dozens of metrics to ensure we are aware of incidents within seconds. A few representatives:

• Queuing times
• Per-service latencies
• Memory and CPU consumption

Special holiday on-call procedures

In addition, we take special precautions during peak holiday shopping periods:

• We will over-provision all infrastructure above and beyond typical scale-out policy.
• We double on-call rotation utilizing the above-mentioned automatic notification and escalation policies.
• The entire account and product team will be monitoring throughout the Black Friday / Cyber Monday period, with elevated focus for other holiday periods (such as Boxing Day).

Code freeze during critical time periods

We will freeze all deployments except for the most critical fixes from Black Friday through to Cyber Monday.

Conclusion

At Constructor, we take uptime, performance, and service stability very seriously because the best conversion optimization and ML are moot if we don’t deliver fast and stable service consistently. The goal of this document is to provide our customers with a broad overview of our site reliability practices, as well as a specific view of our holiday readiness procedures. As always, please feel free to reach out to your Customer Success Manager if you have any further questions.

Building on top of our recent release of the quizzes builder within the dashboard, we’re already making improvements upon it to provide even greater flexibility in creating quiz experiences. 

Quizzes are often highly curated and immersive experiences which usually means including beautiful imagery to support the story telling that you are looking to achieve by incorporating a quizzes experience within your product discovery journey. This can look like having images that provide visual reference to the options you might be presenting, or a beautiful background image right at the start of your quiz to help set the mood and immerse a user within a quiz experience. 

Images to further convey the tasting note options within a guided coffee quiz experience. 

We’ve always supported images within our quiz experience, but now we’ve made it even easier by adding support for them directly in the dashboard on all question and option types. Any externally hosted asset (including images) can be added into a quiz, and can be adjusted at any time without needing to make changes to the rendering of the quiz. 

“Add an asset” for both the question and the option level on a multi-select question type.

Asset editor screen where you can reference in the hosted asset URL, alt text for accessibility and add a secondary asset if desired.

For more information about Quizzes, check out our product page, connect with your Customer Success Manager, or contact us through support@constructor.io.

Cognitive Embeddings Search (CES) analytics are now available in the opportunity analytics page for customers with CES turned on. A table view underneath the time series chart (see image below) allows merchandisers to toggle between top queries that triggered CES results and zero results.

Merchandisers track zero results analytics closely in the Constructor dashboard to make business decisions on how to handle the shopper experience when queries return no products. CES has greatly reduced the occurrence of zero results for shoppers, however, the need still remains for merchandisers to track where a search query would have led to zero results had CES not triggered. Low results (CES or zero results) analytics help merchandisers determine where to start stocking new products, place redirects for non-product searches, create synonyms, or perhaps introduce UI elements to help direct shopper queries. Stay tuned for further updates on CES analytics. 

For more information about CES, connect with your Customer Success Manager, or contact us through support@constructor.io.

Merchandisers have been relying on impressions and click-through rates (CTR) as a measure to determine the success of recommendation strategies, and while helpful, they necessitate additional metrics to make critical business decisions. Now, add-to-carts (ATC) and add-to-cart rates (ATCR) are available in recommendation analytics so merchandisers can more accurately measure performance. The ATC analytics are available on overall recommendations performance and on specific pods.

Add-to-cart analytics provides new insights and analysis not available before. For example, merchandisers can create two PDP pods, one using the complementary strategy and one using the alternative strategy. After allowing each one to run alongside each other or with split traffic, merchandisers can compare the impact on clicks and add-to-carts to determine which strategy performs better for their desired business KPI. These comparative and pre/post analyses drive additional insights for optimizing your recommendations implementation!

For more information on recommendations strategies, analytics, or any additional feedback, please connect with your Customer Success Manager or contact us through support@constructor.io. 

Today we’re expanding our suite of searchandizing capabilities and adding a brand new type of searchandizing rule to the set - content in search! 

Generic preview of content in search within the Searchandizing view.

With this new rule type merchandisers will be able to add all kinds of contextually relevant content to their search experiences to help provide their site visitors with the best possible experience, especially in instances where some additional content around a new product launch, a promotion, or key information about shopping for a given type of product aids in the overarching experience. 

While content in search is meant to be open-ended for many creative uses, here are some ways this capability could be used: 

In-cart Discounts -

For example, maybe you have an in-cart discount on Samsung dishwashers and are looking for ways to communicate this in your product listing. Adding a banner to this experience that communicates that Samsung products are further discounted in-cart is immensely helpful information to a shopper who knows they want a new dishwasher, but hasn’t decided on a brand yet and this information would influence what products they went on to look at deeper in the funnel. 

Special Messaging - 

Maybe you have keen shoppers searching for the next rumored hot product release before you have it up on your site but you want to let them know that you’ll be carrying it and maybe even when to check back to snag it. Being able to communicate this helps let your shoppers know that you understand their intent and that you are the right destination for what they’re looking for. 

Content in Search is available as a new rule type within Searchandizing and includes a variety of commonly needed fields for this type of content. All fields are optional meaning that you can mix and match for exactly what you need. 

New rule type for Content added to Searchandizing options. 

All rendering logic will be handled on your site so you will be able to control the ultimate look and feel of any experience you build - ensuring a seamless experience for your users.. 

Right now this capability is available for query level Search Searchandizing rules, with plans to add Browse Searchandizing rules on categories and collections in the future.

For more information about this capability, check out our documentation here, connect with your Customer Success Manager or contact us through support@constructor.io.

Interact has long been a powerful tool to preview experiences, see how the results change with different ranking factors and engage with facets to see how the results change in various scenarios that your site visitors may experience. Although the feature has always had high usage, we’ve gotten feedback from our users over the last few months that they want to be able to use it to emulate the experience when searching within an individual store, or brand, or account within a bigger index. This has been especially appealing for our customers who use Constructor to power BOPIS and B2B.

You asked, we listened. Now, we’re taking that a step further by making Hidden Facets available in Interact within the Dashboard as well. This can be handy in instances where you are doing query-level filtering for attributes like store ID, or item availability by location or B2B account where you want your visitors to experience different results powered by hidden facets. 

Now dashboard users will be able to see what the experience would look like for a user after they’ve selected their preferred store, or they can see what products are returning with facets that aren’t shown to users on their site.  

Within Interact, this is now available below the Shown Facets in the bottom of the left-hand panel.

For more information, questions or feedback please connect with your Customer Success Manager or contact us through support@constructor.io.

Merchandisers create rules within the Constructor dashboard to adjust the product discovery results in search and browse, however, there hasn’t been easy access to data showing the effects of those rules on business KPIs. Now, within a day of creating a searchandizing rule, the rules that under or over perform historical expectations will be flagged, sorted for review, and action can be taken to remove under performing rules or continue rules that outperform. With this sorted list, merchandisers can focus their attention on the most critical rules to restore conversions or continue rules that are providing positive results.  

There are two ways to see the alerts, the first is the Rule Performance dashboard in Analytics. This page sorts by add-to-cart gains or losses and allows users to determine if the rule is still meeting its purpose or if it's time to change the rule. Lost or gained add-to-carts are calculated by multiplying the viewers who saw the slotted product by the difference in conversion rates from the time period the product was slotted versus when it was not slotted, giving a prioritized estimate on total rule impact. 

Rule performance alerts are also available in the review icons on the Searchandizing rule creation page. Once the rule is opened in edit view, the product cards will now display over and under performance badges with details on conversion rate differences. In the example below, the performance badge shows the item in position one is converting at 2.24%, while the typical conversion rate for position one in this query when not slotted is 15%. This rule may have an alternative purpose beside KPI optimization, i.e. new product promotion, vendor agreements, visual appeal of results, or others, but now conversion data is easily available when making decisions on slotting rules.  

Many rules merchandisers create also lead to positive results. The rule performance dashboard can also be viewed from most add-to-cart gains and any item that outperforms the position average will have a green high conversion badge. Merchandisers can learn from successful slotting campaigns to see what hypotheses were correct and what types of rules to continue in the future. 

For more information, please connect with your Customer Success Manager or contact us through support@constructor.io. Stay tuned for more announcements to come on rule performance and reference this documentation to learn more about the metrics.

This is a beta release of new data available from our merchant intelligence product to help merchandisers make data driven decisions within our product discovery platform. Stay tuned over the next couple weeks as we add additional data views to give merchandisers more context on rule performance including time series data on conversion performance and other detailed views.