Embrace Data Science

Your marketplace is a valuable source of data, which is why our platform collects and tracks every click and bid.

Evolve your platform. Every day.

Our machine learning capability ensures that your platform is continuously improving.
Step 1

Understand what’shappening in the market

Key features:

Business intelligence
Performance metrics
Price indices
Step 2

Predict future trends and performance

Key features:

Price forecast
Inventory forecasting
Step 3

Optimise marketplace performance

Key features:

Feature one
Recommendation engine
Buyer & seller matching

Understand what’s happening in the market

Understanding who is doing what on a multi-sided trading platform is hard.

We help our clients understand what marketplace information is most instructive for their specific markets. Measuringmarketplace performance to ensure that all segments of the market are thick (attracts optimal number of both sell-side and buy-side participants) and functioning optimally is key to growth, long-term sustainability and value optimisation.

Diagram that explains how NovaFori applies data science to understand what's happening in the market.

Predict future trends and performance

We help you predict your market's direction of travel by calculating probabilities and forecasting if the market will be ‘trending-up’ or ‘trending down’. Providing this information to buyers and sellers guides them in their pricing decisions.

We also use this information to match buyers and sellers depending on the market’s current state.

Diagram that explains how NovaFori applies data science to predict future trends and performance.

Optimise marketplace performance

Price discovery

We use all of our capabilities to suggest buyers, sellers and inventory to optimise transaction prices and volumes.

Recommendation engine

We embed auction theory in our recommendation engine to maximise price. Preference is given to recommended listings for highest possible bids. The objective is to maximise revenue across the entire marketplace and not just for a minority of listings.

Buyer and seller matching

We use three methods to optimise segmentation:

Micro - the activity and behaviour of bidders in the current period;

Mining - the most similar metadata attributes (e.g. reserve price);

Macro - significant bid behaviour patterns in all available historical auction data.