List of Algonomy RichRelevance Customers
Algonomy
49 Stevenson Street Suite 950,
San Francisco, 94105, CA,
United States
San Francisco, 94105, CA,
United States
1 415-956-1947
Professional Services
600
$65M
Since 2010, our global team of researchers has been studying Algonomy RichRelevance customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Algonomy RichRelevance for Personalization and Product Recommendations from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Algonomy RichRelevance for Personalization and Product Recommendations include: Costco, a United States based Retail organisation with 333000 employees and revenues of $254.45 billion, Samsung Electronics South Korea, a South Korea based Manufacturing organisation with 262647 employees and revenues of $206.82 billion, Samsung Electronics South Korea, a South Korea based Manufacturing organisation with 262647 employees and revenues of $206.41 billion, Samsung Electronics, a South Korea based Manufacturing organisation with 262647 employees and revenues of $203.54 billion, Samsung Semiconductor, a South Korea based Manufacturing organisation with 262647 employees and revenues of $66.52 billion and many others.
Contact us if you need a completed and verified list of companies using Algonomy RichRelevance, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The Algonomy RichRelevance customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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100 Black Men Of Savannah | Construction and Real Estate | 10 | $1M | United States | Algonomy | Algonomy RichRelevance | Personalization and Product Recommendations | 2019 | n/a |
In 2019, 100 Black Men Of Savannah deployed Algonomy RichRelevance on its public website, adopting Algonomy RichRelevance as the core personalization and recommendation engine. The deployment is focused on site-level experience, embedding the Algonomy RichRelevance runtime into web pages to surface personalized content and recommendation decisioning for visitors to the organization website.
The implementation centers on customer-facing recommendation widgets and personalization rule configuration, with implementation work proportionate to a small organization of roughly 10 employees. Integrations are limited to the public website surface, using client-side embedding and API-driven calls to Algonomy RichRelevance to request personalized content at page render, and operational ownership resides with the digital and marketing function that manages content and rule sets. Governance emphasizes lightweight rule management and staged configuration updates to control on-site behavior, and the implementation impacts digital engagement and membership outreach workflows for the organization.
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1STOPLighting | Distribution | 60 | $6M | United States | Algonomy | Algonomy RichRelevance | Personalization and Product Recommendations | 2015 | n/a |
In 2015, 1STOPLighting implemented Algonomy RichRelevance on its website. The deployment uses Algonomy RichRelevance and the Apps Category .
The implementation focused on core personalization and recommendation capabilities, including catalog feed ingestion, behavioral event capture, real time recommendation APIs, merchandising rule configuration, and onsite A/B testing workflows. Operational scope covered the customer facing e commerce site and supported merchandising and marketing functions for product discovery and cross sell orchestration. Governance centered on data mapping for product and event feeds, phased feature rollouts to merchandising users, and iterative tuning of recommendation models and merchandising rules by internal teams.
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Air Compressor Service | Professional Services | 10 | $1M | United States | Algonomy | Algonomy RichRelevance | Personalization and Product Recommendations | 2017 | n/a |
In 2017 Air Compressor Service implemented Algonomy RichRelevance on its customer-facing website. The deployment used Algonomy RichRelevance, and the Apps Category "" is used to deliver on-site product recommendations and personalization across merchandising touchpoints.
Implementation scope was website-led, focused on embedding Algonomy RichRelevance into product detail pages, category listings and search result pages to influence product discovery. Operational ownership was concentrated within marketing and e-commerce operations at the ten-person firm, with configuration work centered on recommendation logic, relevance tuning and front-end integration rather than enterprise back-office systems.
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Aldi UK | Retail | 44475 | $22.8B | United Kingdom | Algonomy | Algonomy RichRelevance | Personalization and Product Recommendations | 2018 | n/a |
In 2018, Aldi UK deployed Algonomy RichRelevance as the primary Personalization and Product Recommendations solution across its eCommerce website and mobile site. The implementation targeted Aldi's online catalogue, including products available in store and the retailer's weekly Specialbuys program, to surface more of the catalogue to shoppers while preserving relevance for both known and unknown visitors.
The deployment enabled a single-solution suite approach, using Algonomy Engage™ for personalised content and campaigns, Algonomy Personalisation Recommend™ for algorithmic product suggestions, Algonomy DeepRecs NLP to generate semantic recommendations for rapidly changing Specialbuys, and Algonomy Discover™ to personalise browse and navigation. Customer profiles were updated in real time as shoppers interacted with the site, and recommendation logic was configured to handle out-of-stock situations and present substitute items automatically, reducing manual merchandising effort.
Operational coverage spanned digital merchandising, marketing, and eCommerce operations on web and mobile storefronts, with strategic advisory services from Algonomy used to define a phased rollout and a personalisation roadmap for business teams. The implementation focused on surfacing relevant content and products across category pages and campaign entry points, and was explicitly designed to personalise experiences for anonymous and first time shoppers as well as returning customers.
Results reported by Aldi UK from the Algonomy RichRelevance deployment include 46% higher revenue per visitor, 10% higher average order value, 20% attributable revenue, 2X higher engagement for Specialbuys, up to 6X higher click through rates for targeted categories, and 25x revenue per 1000 impressions (RPMI) from DeepRecs NLP for new launches.
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American Lighting Store | Retail | 11 | $3M | United States | Algonomy | Algonomy RichRelevance | Personalization and Product Recommendations | 2018 | n/a |
In 2018, American Lighting Store implemented Algonomy RichRelevance for Personalization and Product Recommendations on its public website. The deployment embedded Algonomy RichRelevance as the site-level personalization and product recommendation engine to support onsite merchandising and browsing experiences.
The implementation used client-side integration through site-mounted personalization tags and recommendation widgets, aligned to the retailer's product catalog feeds and storefront page templates. Functional modules configured included product recommendations, category-level merchandising, and onsite personalization rules, reflecting typical Personalization and Product Recommendations capabilities.
Operational scope was focused on the e-commerce storefront and merchandising workflows within the United States, suited to the retailer's small organizational footprint. Governance emphasized merchandising decision rules and content targeting, with configuration and rule management performed through the Algonomy RichRelevance management consoles and site-side configuration.
Algonomy RichRelevance drove contextual recommendations and personalized product placements across product detail and category pages on the American Lighting Store website. The implementation prioritized a lightweight, web-embedded personalization layer appropriate for a small retail site.
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Retail | 44481 | $4.8B | Brazil | Algonomy | Algonomy RichRelevance | Personalization and Product Recommendations | 2016 | n/a |
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Retail | 100 | $5M | Brazil | Algonomy | Algonomy RichRelevance | Personalization and Product Recommendations | 2016 | n/a |
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Professional Services | 500 | $16M | Hong Kong | Algonomy | Algonomy RichRelevance | Personalization and Product Recommendations | 2015 | n/a |
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Professional Services | 300 | $35M | Austria | Algonomy | Algonomy RichRelevance | Personalization and Product Recommendations | 2015 | n/a |
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Manufacturing | 1000 | $196M | Australia | Algonomy | Algonomy RichRelevance | Personalization and Product Recommendations | 2015 | n/a |
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Showing 1 to 10 of 259 entries
Buyer Intent: Companies Evaluating Algonomy RichRelevance
ARTW Buyer Intent uncovers actionable customer signals, identifying software buyers actively evaluating Algonomy RichRelevance. Gain ongoing access to real-time prospects and uncover hidden opportunities. Companies Actively Evaluating Algonomy RichRelevance for Personalization and Product Recommendations include:
- Publicis Groupe, a France based Media organization with 107273 Employees
- Hackajob, a United Kingdom based Professional Services company with 100 Employees
- ByteDance, a China based Professional Services organization with 150000 Employees
Discover Software Buyers actively Evaluating Enterprise Applications
| Logo | Company | Industry | Employees | Revenue | Country | Evaluated |
|---|---|---|---|---|---|---|
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Publicis Groupe | Media | 107273 | $18.8B | France | 2025-05-26 |
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Hackajob | Professional Services | 100 | $10M | United Kingdom | 2025-02-06 |
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ByteDance | Professional Services | 150000 | $120.0B | China | 2025-01-27 |
FAQ - APPS RUN THE WORLD Algonomy RichRelevance Coverage
Algonomy RichRelevance is a Personalization and Product Recommendations solution from Algonomy.
Companies worldwide use Algonomy RichRelevance, from small firms to large enterprises across 21+ industries.
Organizations such as Costco, Samsung Electronics South Korea, Samsung Electronics and Samsung Semiconductor are recorded users of
Algonomy RichRelevance for Personalization and Product Recommendations.
Companies using Algonomy RichRelevance are most concentrated in Retail and Manufacturing, with adoption spanning over 21 industries.
Companies using Algonomy RichRelevance are most concentrated in United States and South Korea, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of Algonomy RichRelevance across Americas, EMEA, and APAC.
Companies using Algonomy RichRelevance range from small businesses with 0-100 employees - 20.46%, to mid-sized firms with 101-1,000 employees - 30.5%, large organizations with 1,001-10,000 employees - 30.89%, and global enterprises with 10,000+ employees - 18.15%.
Customers of Algonomy RichRelevance 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 Algonomy RichRelevance 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.