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Westpac NZ, an Infosys Finacle customer evaluated nCino Bank OS

Wayfair, a Korber HighJump WMS customer just evaluated Manhattan WMS

Swedbank, a Temenos T24 customer evaluated Oracle Flexcube

Citigroup, a VestmarkONE customer evaluated BlackRock Aladdin Wealth

Cantor Fitzgerald, a Kyriba Treasury customer evaluated GTreasury

Moog, an UKG AutoTime customer evaluated Workday Time and Attendance

Michelin, an e2open customer evaluated Oracle Transportation Management

List of FACT-Finder Customers

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Logo Customer Industry Empl. Revenue Country Vendor Application Category When SI Insight
Aceitera Martinez S A Consumer Packaged Goods 81 $10M Argentina FACT-Finder FACT-Finder Personalization and Product Recommendations 2022 n/a
In 2022, Aceitera Martinez S A implemented FACT-Finder to deliver Personalization and Product Recommendations on its ecommerce site. The deployment centered on standard category capabilities such as onsite search personalization, a product recommendation engine, relevance tuning and merchandising controls, and automated catalog feed ingestion to drive personalized product display and browse experiences. FACT-Finder was integrated with the company website hosted on GoDaddy at https://www.alsamar.com, implemented as embedded recommendation widgets and search enhancements that synchronize with the product catalog and analytics instrumentation. Operational ownership sits with e-commerce and marketing functions, with governance focused on relevance rule management, merchandising workflows and experimentation through A B testing and analytics, enabling Aceitera Martinez S A FACT-Finder Personalization and Product Recommendations to support its e-commerce merchandising and marketing business functions.
Armaturenwerk Hotensleben Manufacturing 260 $30M Germany FACT-Finder FACT-Finder Personalization and Product Recommendations 2021 n/a
In 2021, Armaturenwerk Hotensleben implemented FACT-Finder on their website to deliver Personalization and Product Recommendations. The deployment targeted the company ecommerce product discovery layer on awh.de and embedded the FACT-Finder application into the public storefront to surface context aware suggestions and improve search relevance. The implementation configured FACT-Finder search and recommendation modules, including relevance tuning, product ranking logic, and rule based merchandising to align results with the manufacturer's catalog taxonomy and SKU attributes. The FACT-Finder recommendation engine was applied across search results and product detail pages to enable category aware suggestions, cross sell and up sell product placements, and contextual product recommendations. Operational scope centered on the customer facing ecommerce and online merchandising functions, requiring catalog mapping, attribute normalization, and ongoing relevance governance by the ecommerce team. Governance routines included administrative configuration within FACT-Finder and iterative tuning of merchandising rules and recommendation strategies using the application's analytics and relevance tools.
B+B Thermo-Technik Manufacturing 100 $20M Germany FACT-Finder FACT-Finder Personalization and Product Recommendations 2021 n/a
In 2021, B+B Thermo-Technik implemented FACT-Finder as a site-level solution to improve online product discovery. FACT-Finder was deployed as the company’s Personalization and Product Recommendations application on its public website, supporting search-driven product discovery and on-site recommendation workflows for the online product catalog. The implementation embedded FACT-Finder search and recommendation components into the website front end and relied on a product data feed and administrative console for relevance tuning and merchandising controls. Operational ownership and day to day configuration work is oriented to e-commerce and marketing functions, with governance focused on search relevance, recommendation rules, and catalog merchandising to steer onsite navigation and purchase guidance.
Retail 500 $100M Germany FACT-Finder FACT-Finder Personalization and Product Recommendations 2014 n/a
Retail 120 $40M Germany FACT-Finder FACT-Finder Personalization and Product Recommendations 2013 n/a
Manufacturing 2700 $422M Poland FACT-Finder FACT-Finder Personalization and Product Recommendations 2017 n/a
Retail 11096 $1.6B Germany FACT-Finder FACT-Finder Personalization and Product Recommendations 2021 n/a
Retail 21 $7M Netherlands FACT-Finder FACT-Finder Personalization and Product Recommendations 2021 n/a
Retail 62 $7M Germany FACT-Finder FACT-Finder Personalization and Product Recommendations 2022 n/a
Retail 180 $20M Germany FACT-Finder FACT-Finder Personalization and Product Recommendations 2016 n/a
Showing 1 to 10 of 52 entries

Buyer Intent: Companies Evaluating FACT-Finder

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FAQ - APPS RUN THE WORLD FACT-Finder Coverage

FACT-Finder is a Personalization and Product Recommendations solution from FACT-Finder.

Companies worldwide use FACT-Finder, from small firms to large enterprises across 21+ industries.

Organizations such as Sick AG, Bofrost, HELLWEG, Snipes and Cyberport GmbH are recorded users of FACT-Finder for Personalization and Product Recommendations.

Companies using FACT-Finder are most concentrated in Manufacturing, Retail and Professional Services, with adoption spanning over 21 industries.

Companies using FACT-Finder are most concentrated in Germany, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of FACT-Finder across Americas, EMEA, and APAC.

Companies using FACT-Finder range from small businesses with 0-100 employees - 40.38%, to mid-sized firms with 101-1,000 employees - 28.85%, large organizations with 1,001-10,000 employees - 26.92%, and global enterprises with 10,000+ employees - 3.85%.

Customers of FACT-Finder 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 FACT-Finder 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.