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List of QuarticOn Recommendation Engine Customers

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Logo Customer Industry Empl. Revenue Country Vendor Application Category When SI Insight
Agata Poland Retail 1200 $641M Poland QuarticOn QuarticOn Recommendation Engine Personalization and Product Recommendations 2017 n/a
In 2017, Agata Poland deployed the QuarticOn Recommendation Engine on its public e-commerce website. The QuarticOn Recommendation Engine, implemented for Personalization and Product Recommendations, was used to surface contextually relevant products and support online merchandising and product discovery for Agata Poland. The implementation focused on core product recommendation capabilities typical of the Personalization and Product Recommendations category, including on-site recommendation widgets, catalog feed ingestion, behavioral profiling, and real-time inference for session-based and cohort-based recommendations. Configuration work included mapping the Agata product catalog, defining category and cross-sell rules, and tuning algorithm parameters to align recommendation outputs with merchandising objectives. Technical integration centered on synchronizing the product catalog and session context between the website storefront and the QuarticOn recommendation layer, using site instrumentation and product feed updates to preserve catalog accuracy. Operational ownership was assigned to the e-commerce and online merchandising teams at Agata Poland, who maintained business rules, catalog mappings, and ongoing model tuning to align recommendations with product lifecycle and merchandising workflows.
Apart Poland Retail 3000 $300M Poland QuarticOn QuarticOn Recommendation Engine Personalization and Product Recommendations 2015 n/a
In 2015, Apart Poland deployed the QuarticOn Recommendation Engine on its public e-commerce site. The QuarticOn Recommendation Engine was configured to deliver Personalization and Product Recommendations across product detail pages, category listings, search result pages, and checkout adjacencies to support onsite product discovery and merchandising workflows. The implementation emphasized runtime recommendation scoring and storefront embedding to surface related products, cross-sell suggestions, and curated lists within the shopping journey. Deployment architecture was implemented as a site-embedded recommendation layer that served recommendation payloads to the storefront UI and commerce flows, with runtime decisioning performed by the QuarticOn Recommendation Engine. Operational scope covered online sales, e-commerce merchandising, and digital marketing teams who governed recommendation rules, creative variants, and catalog feed configuration. Functional capabilities implemented align with typical Personalization and Product Recommendations platforms, including collaborative and content-based recommendation patterns, category-aware ranking, and merchandising rule overrides to influence on-site product exposure.
Black Red White Poland Manufacturing 2700 $422M Poland QuarticOn QuarticOn Recommendation Engine Personalization and Product Recommendations 2017 n/a
In 2017, Black Red White Poland deployed QuarticOn Recommendation Engine for Personalization and Product Recommendations on its customer-facing website brw.pl. The QuarticOn Recommendation Engine was embedded into the public storefront to deliver product recommendations and personalized product ranking across browse pages and product detail pages. The deployment was implemented at the site level, ingesting catalog feeds and on-site interaction events to enable real-time recommendation scoring and delivery. Configuration emphasized category-aligned modules including session based recommendations, cross sell and upsell recommendation blocks, and algorithmic product sorting tailored to catalog structure and user behavior. Operational control was centralized with ecommerce and merchandising functions, using rule configuration and A/B testing to govern personalization rules and staged rollouts. The implementation relied on the QuarticOn Recommendation Engine for runtime scoring and widget rendering within the website presentation layer, with analytics instrumentation of page events to support iterative model tuning.
Retail 20 $15M United Kingdom QuarticOn QuarticOn Recommendation Engine Personalization and Product Recommendations 2019 n/a
Retail 153 $75M Poland QuarticOn QuarticOn Recommendation Engine Personalization and Product Recommendations 2016 n/a
Retail 220 $42M Czech Republic QuarticOn QuarticOn Recommendation Engine Personalization and Product Recommendations 2017 n/a
Leisure and Hospitality 300 $45M Poland QuarticOn QuarticOn Recommendation Engine Personalization and Product Recommendations 2015 n/a
Retail 2500 $160M Poland QuarticOn QuarticOn Recommendation Engine Personalization and Product Recommendations 2022 n/a
Media 1600 $531M Poland QuarticOn QuarticOn Recommendation Engine Personalization and Product Recommendations 2017 n/a
Retail 90 $15M Poland QuarticOn QuarticOn Recommendation Engine Personalization and Product Recommendations 2015 n/a
Showing 1 to 10 of 11 entries

Buyer Intent: Companies Evaluating QuarticOn Recommendation Engine

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FAQ - APPS RUN THE WORLD QuarticOn Recommendation Engine Coverage

QuarticOn Recommendation Engine is a Personalization and Product Recommendations solution from QuarticOn.

Companies worldwide use QuarticOn Recommendation Engine, from small firms to large enterprises across 21+ industries.

Organizations such as Agata Poland, Player Poland, Black Red White Poland, Apart Poland and Martes Sport Poland are recorded users of QuarticOn Recommendation Engine for Personalization and Product Recommendations.

Companies using QuarticOn Recommendation Engine are most concentrated in Retail, Media and Manufacturing, with adoption spanning over 21 industries.

Companies using QuarticOn Recommendation Engine are most concentrated in Poland, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of QuarticOn Recommendation Engine across Americas, EMEA, and APAC.

Companies using QuarticOn Recommendation Engine range from small businesses with 0-100 employees - 18.18%, to mid-sized firms with 101-1,000 employees - 36.36%, large organizations with 1,001-10,000 employees - 45.45%, and global enterprises with 10,000+ employees - 0%.

Customers of QuarticOn Recommendation Engine include firms across all revenue levels — from $0-100M, to $101M-$1B, $1B-$10B, and $10B+ global corporations.

Contact APPS RUN THE WORLD to access the full verified QuarticOn Recommendation Engine customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of Personalization and Product Recommendations.