Unilever · Consumer goods (marketing content production) · Global (Beauty and Wellbeing brands)
Unilever: product digital twins for marketing imagery with Omniverse and OpenUSD
Unilever builds photoreal 3D twins of its products with NVIDIA Omniverse and OpenUSD, working with creative technology partner Collective World, and renders marketing images from them instead of running repeated photo shoots. Unilever and NVIDIA report imagery made twice as fast at half the cost.
- Status
- In production
- Status as of
- 18 Mar 2025
- NVIDIA technologies
- NVIDIA Omniverse
The challenge
One product line can need thousands of individual images once every variant, size, language and channel is counted. NVIDIA's case study says that without a unified digital asset system Unilever had to reshoot products repeatedly, which was costly and slowed its content work.1
What was implemented
Unilever and its creative technology partner Collective World build a 3D twin of each product with OpenUSD (an open scene standard that originated at Pixar and is developed through the Alliance for OpenUSD) and NVIDIA Omniverse, including Omniverse Nucleus services for shared work on the same files. Each twin holds product variants, labels, language versions, lighting setups, camera angles and approved effects, so teams pull images for TV, e-commerce and social channels from one approved source.
Marketing Dive reports that brands in the Beauty and Wellbeing segment (TRESemme, Dove, Vaseline and Clear) were the first to use the approach, and that Unilever's chief growth and marketing officer presented it at NVIDIA GTC in March 2025. NVIDIA mentions integration with NVIDIA Blueprints as groundwork for future generative AI work; Unilever's release does not mention Blueprints.
Unilever's own release of 18 March 2025 gives the same speed, cost and duplication figures, names Omniverse and OpenUSD, and says Beauty and Wellbeing piloted the approach first and has since built it into its wider content workflow.1234
Reported outcomes
Product imagery produced twice as fast as with traditional shoots123
2x faster
MeasuredProduction cost of product imagery cut in half123
-50% cost
MeasuredContent duplication reduced by an average ratio of 5:113
5:1 reduction
Measured
Each outcome links to its source; the label there says whether the company, NVIDIA or a third party reported it.
What others can learn, and the limits
What others can learn: a single approved 3D master per product, with variants and languages inside one file, removes repeat shoots and keeps packaging consistent across markets. The approach suits brands with many variants and channels. Limits: this is a marketing content case, not a factory or supply chain twin. The figures are Unilever and NVIDIA statements without a published method, and press reports give different numbers for different brands and markets, so treat them as indicative. Building accurate twins needs 3D product data and a specialist partner (here, Collective World). Brands with few products or few formats may do better with conventional 3D rendering or photography.
Explore a similar project
Use the Digital Twin Opportunity Lab with your own assumptions. Results are independent of this case.
Sources
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