AI Buyer Insights:

Cantor Fitzgerald, a Kyriba Treasury customer evaluated GTreasury

Citigroup, a VestmarkONE customer evaluated BlackRock Aladdin Wealth

Michelin, an e2open customer evaluated Oracle Transportation Management

Westpac NZ, an Infosys Finacle customer evaluated nCino Bank OS

Moog, an UKG AutoTime customer evaluated Workday Time and Attendance

Wayfair, a Korber HighJump WMS customer just evaluated Manhattan WMS

Swedbank, a Temenos T24 customer evaluated Oracle Flexcube

Cantor Fitzgerald, a Kyriba Treasury customer evaluated GTreasury

Citigroup, a VestmarkONE customer evaluated BlackRock Aladdin Wealth

Michelin, an e2open customer evaluated Oracle Transportation Management

Westpac NZ, an Infosys Finacle customer evaluated nCino Bank OS

Moog, an UKG AutoTime customer evaluated Workday Time and Attendance

Wayfair, a Korber HighJump WMS customer just evaluated Manhattan WMS

Swedbank, a Temenos T24 customer evaluated Oracle Flexcube

List of Optimizely Recommendations Customers

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Logo Customer Industry Empl. Revenue Country Vendor Application Category When SI Insight
313@somerset Consumer Packaged Goods 10 $2M Singapore Optimizely Optimizely Recommendations Personalization and Product Recommendations 2022 n/a
In 2022, 313@somerset implemented Optimizely Recommendations to add an on-site personalization layer, aligning the deployment with the Personalization and Product Recommendations category. The Optimizely Recommendations deployment is focused on web storefront product discovery and merchandising workflows for the retailer's public website. Configuration centered on catalog-driven recommenders, model-driven suggestion slots, and business rule controls for merchandising priority. The implementation included setup of recommendation widgets on product detail pages and category pages, tuning of recommendation logic for product affinity, and readiness for A/B testing of recommendation placements. Integrations were limited to embedding Optimizely Recommendations into the ecommerce storefront, connecting to the product catalog feed, and streaming click and conversion events into onsite analytics for monitoring. Operational ownership sits with merchandising and marketing functions, with governance processes established for rule approvals, content review, and merchandising overrides to control recommendation behavior.
Adage Technologies Professional Services 100 $10M United States Optimizely Optimizely Recommendations Personalization and Product Recommendations 2023 n/a
In 2023, Adage Technologies implemented Optimizely Recommendations on its public website. The deployment uses Optimizely Recommendations in the Personalization and Product Recommendations category to deliver algorithmic product suggestions and configurable merchandising controls for site merchandising and digital marketing functions. The implementation follows a cloud SaaS pattern, with client side instrumentation embedding Optimizely Recommendations into product detail and listing pages, combining algorithmic recommendation models with manual rule sets and merchandising overrides. Operational ownership is centered in digital marketing and merchandising teams, and the rollout was staged across site zones with editorial governance applied to recommendation taxonomies and rule configuration. Telemetry from Optimizely Recommendations is used to monitor placement performance and tune model and rule parameters over time.
ADM Brazil Consumer Packaged Goods 5000 $4.0B Brazil Optimizely Optimizely Recommendations Personalization and Product Recommendations 2022 n/a
In 2022, ADM Brazil deployed Optimizely Recommendations on its public website. Optimizely Recommendations is implemented as the Personalization and Product Recommendations layer to surface product suggestions and personalized merchandising across ADM Brazil’s digital storefront. The deployment uses a cloud delivered recommendation service embedded in site pages and driven by API decisioning, enabling product recommendation rails, context aware suggestions, and rule based merchandising controls typical for the category. The Optimizely Recommendations implementation exposes console based configuration for merchandising and content teams, supporting catalog driven recommendation strategies and segmentation oriented targeting. Operational responsibility is concentrated in e-commerce, digital marketing, and merchandising functions on the ADM Brazil website, with those teams using the Optimizely Recommendations management interfaces to configure rules, targeting, and creative placements. Governance is centered on ongoing configuration and editorial control rather than platform integration work, aligning the Personalization and Product Recommendations capability to site level commerce and marketing workflows.
Consumer Packaged Goods 300 $600M Switzerland Optimizely Optimizely Recommendations Personalization and Product Recommendations 2022 n/a
Consumer Packaged Goods 120 $10M Mexico Optimizely Optimizely Recommendations Personalization and Product Recommendations 2022 n/a
Consumer Packaged Goods 200 $25M Netherlands Optimizely Optimizely Recommendations Personalization and Product Recommendations 2022 n/a
Healthcare 38 $5M United States Optimizely Optimizely Recommendations Personalization and Product Recommendations 2022 n/a
Banking and Financial Services 10 $1M United States Optimizely Optimizely Recommendations Personalization and Product Recommendations 2022 n/a
Life Sciences 1300 $358M Australia Optimizely Optimizely Recommendations Personalization and Product Recommendations 2021 n/a
Manufacturing 600 $80M Brazil Optimizely Optimizely Recommendations Personalization and Product Recommendations 2022 n/a
Showing 1 to 10 of 380 entries

Buyer Intent: Companies Evaluating Optimizely Recommendations

ARTW Buyer Intent uncovers actionable customer signals, identifying software buyers actively evaluating Optimizely Recommendations. Gain ongoing access to real-time prospects and uncover hidden opportunities. Companies Actively Evaluating Optimizely Recommendations for Personalization and Product Recommendations include:

  1. Hg Capital US, a United States based Banking and Financial Services organization with 280 Employees

Discover Software Buyers actively Evaluating Enterprise Applications

Logo Company Industry Employees Revenue Country Evaluated
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FAQ - APPS RUN THE WORLD Optimizely Recommendations Coverage

Optimizely Recommendations is a Personalization and Product Recommendations solution from Optimizely.

Companies worldwide use Optimizely Recommendations, from small firms to large enterprises across 21+ industries.

Organizations such as lyondellbasell US, Takeda, Vattenfall, Novartis United States and Arla Foods are recorded users of Optimizely Recommendations for Personalization and Product Recommendations.

Companies using Optimizely Recommendations are most concentrated in Oil, Gas and Chemicals, Life Sciences and Utilities, with adoption spanning over 21 industries.

Companies using Optimizely Recommendations are most concentrated in United States, Japan and Sweden, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of Optimizely Recommendations across Americas, EMEA, and APAC.

Companies using Optimizely Recommendations range from small businesses with 0-100 employees - 46.58%, to mid-sized firms with 101-1,000 employees - 36.05%, large organizations with 1,001-10,000 employees - 14.74%, and global enterprises with 10,000+ employees - 2.63%.

Customers of Optimizely Recommendations 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 Optimizely Recommendations 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.