AI is rapidly becoming a gamechanger for marketplaces. In a world where everything is about balancing supply and demand, AI can play a crucial role. The digital first mindset of marketplace and e-commerce parties often creates perfect breeding grounds to leverage data & AI.
For Start-ups
Knowing that AI can be a game-changer for your marketplace or e-comm platform, start early on with understanding which AI use cases can bring future business value. Base your data collection strategy on this and blueprint a data stack that balances between costs and scalability.
AI audit; understanding your marketplace dynamics to determine AI use cases
Blueprinting and development of modern data & AI architecture
Customized AI use cases: forecasting, dynamic pricing and ranking
For Scale-ups
Mature marketplace and e-commerce platforms typically have vast data amounts. Developing large scale and customized AI solutions for key company processes like forecasting or pricing becomes a serious investment opportunity. A mature MLOps ensures that you have a short time to market for AI use cases.
Blueprinting MLOps and large scale AI systems
Act as an accelerator for in-house data & AI teams
Development of complex AI use cases like recommendation systems
Customer Cases
P2P Marketplaces
On peer-to-peer marketplaces, effective matching between buyers and sellers is crucial to maximize revenue and customer satisfaction. Enjins assists companies to achieve optimal matching.
Ranking: Providing the right supply to potential customers
Dynamic pricing: Advising sellers on the right price to set for a listing
Find out more about the Wunderflats & SnappCar case here.
B2C Platforms
When a big managed supply is available for an involved customer base, recommenders become key. Enjins develops customized recommendation engines to improve conversion rates and platform satisfaction.
Recommendation engine: boosting platform conversion
Segmentation: clustering customers to provide the right service
Find out more about the JustWatch case here.
E-Commerce
The number of relevant AI use cases for E-Commerce businesses is limitless, but forecasting is often key to balance between waste and out of stock.
Forecasting engine: Predicting demand to avoid waste & out of stock
Purchasing engine: Leverage your forecast in the buyers process
Find out more about the Crisp case here.