List of UpSellit Customers
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Since 2010, our global team of researchers has been studying UpSellit 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 UpSellit 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 UpSellit for Personalization and Product Recommendations include: Total Wireless United States, a United States based Communications organisation with 2000 employees and revenues of $1.20 billion, Shutterstock, a United States based Professional Services organisation with 1715 employees and revenues of $935.0 million, Oneplus India, a India based Retail organisation with 1100 employees and revenues of $500.0 million, Beachbody, a United States based Leisure and Hospitality organisation with 355 employees and revenues of $419.0 million, Ravensburger Germany, a Germany based Manufacturing organisation with 745 employees and revenues of $256.0 million and many others.
Contact us if you need a completed and verified list of companies using UpSellit, 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 UpSellit 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 | Insight Source |
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Beachbody | Leisure and Hospitality | 355 | $419M | United States | UpSellit | UpSellit | Personalization and Product Recommendations | 2024 | n/a | In 2024, Beachbody deployed UpSellit for Personalization and Product Recommendations on its public website to deliver personalized product discovery and on-site merchandising. The implementation places UpSellit within Beachbody.com page flows to surface recommendations and targeted offers in product detail areas and cart-level interactions, leveraging standard recommendation widgets, session-based behavioral rules, and creative templates common to the Personalization and Product Recommendations category. Beachbody configured UpSellit to support ecommerce merchandising and digital marketing workflows, with governance led by commerce and marketing stakeholders who manage recommendation rules, creative variants, and staged site rollouts. UpSellit integrates at the front-end site layer and operates alongside Beachbody.com commerce flows to centralize recommendation logic and experimental A/B controls, enabling the digital team to iterate on commodity-level personalization and product recommendation strategies. | |
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Cigars International | Retail | 370 | $115M | United States | UpSellit | UpSellit | Personalization and Product Recommendations | 2023 | n/a | ||
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Cluey Learning Australia | Education | 100 | $16M | Australia | UpSellit | UpSellit | Personalization and Product Recommendations | 2025 | n/a | In 2025 Cluey Learning Australia implemented UpSellit to add on-site personalization capabilities and tailored product recommendations on its public website. UpSellit is deployed as a solution in the Personalization and Product Recommendations category to deliver dynamic content and recommendation workflows tied to visitor behavior. The implementation leverages core UpSellit capabilities including real-time recommendation widgets, behavioral targeting engines, rule-based merchandising controls, and an experimentation A/B testing console. Configuration emphasized catalog-driven recommendations and session-based personalization, with templated placements on homepage, category pages, and course detail pages, and an administrative interface for tuning algorithms and merchandising rules. Integration is focused on the website front-end, using standard tag-based deployment and a product or course feed to populate recommendation slots, while analytics events are collected to refine models and support experimentation. Operational ownership is aligned to digital marketing and customer experience teams, with staged rollouts and experiment governance to manage personalization rules, content variants, and ongoing model adjustments. | |
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Retail | 65 | $35M | United States | UpSellit | UpSellit | Personalization and Product Recommendations | 2025 | n/a |
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Consumer Packaged Goods | 460 | $232M | Italy | UpSellit | UpSellit | Personalization and Product Recommendations | 2025 | n/a |
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Retail | 25 | $10M | United States | UpSellit | UpSellit | Personalization and Product Recommendations | 2022 | n/a |
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Retail | 200 | $75M | United States | UpSellit | UpSellit | Personalization and Product Recommendations | 2021 | n/a |
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Professional Services | 150 | $12M | United States | UpSellit | UpSellit | Personalization and Product Recommendations | 2021 | n/a |
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Consumer Packaged Goods | 30 | $2M | United States | UpSellit | UpSellit | Personalization and Product Recommendations | 2022 | n/a |
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Retail | 25 | $10M | United States | UpSellit | UpSellit | Personalization and Product Recommendations | 2025 | n/a |
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Buyer Intent: Companies Evaluating UpSellit
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| Logo | Company | Industry | Employees | Revenue | Country | Evaluated | ||
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