Osmos
AI-driven platform for retail media monetization.
What is Osmos?
Osmos is an AI-driven platform designed to help retailers and e-commerce businesses monetise their owned media inventory through advertising. The platform uses machine learning to optimise ad placement, targeting, and pricing across product pages, search results, and other publisher-owned channels, allowing retailers to generate additional revenue from existing website traffic. It automates the technical complexity of running an ad network: managing advertiser demand, optimising inventory allocation, and adjusting pricing to maximise fill rates and revenue. The platform serves retailers of all sizes, from independent sellers to larger e-commerce operations. Its freemium pricing makes it accessible for businesses starting their retail media programmes, with paid tiers offering advanced optimisation and advertiser features. Osmos provides real-time analytics so publishers can track ad performance, understand which inventory slots generate the highest revenue, and optimise their strategy accordingly.
Key Features
AI-powered ad targeting
Machine learning algorithms match ads to relevant shoppers based on behaviour and intent
Self-serve advertiser portal
Advertisers can create, manage, and monitor campaigns without publisher involvement
Dynamic price optimisation
AI adjusts ad pricing based on demand, inventory scarcity, and performance data
Real-time analytics
Track impressions, clicks, conversions, and revenue metrics across campaigns
Multiple ad formats
Support for display ads, sponsored product listings, native ads, and other advertising formats
Inventory management
Organise and allocate available ad slots across different placements and pages
Demand aggregation
Connect with multiple advertisers and automatically match them to relevant inventory slots
Pros & Cons
Advantages
- Generates additional revenue from existing website traffic without major infrastructure changes
- Freemium model lets smaller businesses test retail media without upfront investment
- AI automation reduces manual work in ad management, targeting, and price optimisation
- Real-time analytics provide actionable insights to improve revenue per impression
- Works with existing e-commerce platforms without requiring complete system rebuilds
- Handles both supply and demand sides, simplifying operations for publishers
Limitations
- Requires sufficient traffic and inventory to make an advertising programme worthwhile
- Success depends on attracting quality advertisers, which takes time and marketing effort
- Faces competition from established retail media networks with larger advertiser bases
- May need technical integration work depending on existing website or app architecture
- Revenue potential varies significantly based on audience relevance to advertisers
- Publisher policies and compliance requirements can limit which advertisers you accept
Use Cases
E-commerce marketplaces monetising search results and product listing pages
Online retailers creating new revenue streams beyond product sales
Publishers and content sites generating income from reader attention
B2B marketplaces offering sponsor visibility to suppliers and vendors
Niche online communities launching advertising programmes for relevant brands
Price comparison sites selling targeted ads to relevant product vendors