
Pryor Analytics builds practical forecasting tools powered by Bayesian modelling, helping businesses turn uncertainty into clear, confident decisions. By combining mathematical rigour with real-world operational insight, our models adapt to business data and deliver actionable forecasts that help cafés, restaurants, and other SMEs plan ahead with clarity.

An introduction to Pryor Analytics and our mission to make forecasting more practical, affordable and useful for small businesses — starting with BayesBlend, our café demand forecasting service.
BayesBlend uses Bayesian modelling to help cafés forecast demand more clearly, understand uncertainty, and make better day-to-day decisions.
With clear, readable forecasts, uncertainty ranges, and practical recommendations, BayesBlend helps owners and managers to plan more effectively around stock, staffing and preparation, without needing expensive software or a dedicated analytics team.
Key Benefits

Currently in development
A Bayesian forecasting engine built from the ground up for full-service restaurants. BayesTable will help you predict covers, manage kitchen load, and plan staffing with confidence — even on your busiest nights.
Planned Features
Upload your historical sales or POS exports — nothing complicated.
We capture patterns, uncertainty, and real-world variability.
Easy-to-interpret outputs that support planning, staffing, and ordering.
Because real businesses don't behave like spreadsheets.
Traditional forecasting assumes certainty and fixed patterns. But cafés and restaurants operate in the real world — where weather shifts, events happen, and demand fluctuates.
Bayesian models embrace uncertainty, adapt as new data arrives, and provide a more honest, flexible view of the future. The result is forecasting that's both rigorous and practical.
I studied Mathematics at the University of Exeter, with a particular interest in statistical theory and how statistical tools can be applied to real-world decision-making.
Before founding Pryor Analytics, I worked in hospitality, where I saw first-hand how difficult it can be to plan around uncertain demand. Staffing, stock control, preparation, waste, and profitability are all affected by not knowing exactly what is likely to happen next.
That experience led me to build Pryor Analytics: a business focused on turning data into clear, practical insight for owners and managers.
I'm especially interested in Bayesian statistics because it helps quantify uncertainty in forecasts, rather than reducing them to a single fixed estimate. This enables us to provide realistic forecast ranges, helping business owners and managers make operational decisions with greater confidence.
Pryor Analytics combines rigorous statistical training with real operational experience to create tools that are practical, readable, and genuinely useful for small businesses.
University of Exeter
BSc Mathematics
Hospitality Industry
Operational experience

We're looking for a small number of cafés to help test and shape BayesBlend, our forecasting service for café operators. The early adopter pilot is free of charge and includes clear demand forecasts, uncertainty ranges, and recommended actions around stock, staffing, preparation, and planning.
By submitting this form, you agree that Pryor Analytics may use your details to respond to your enquiry. We do not sell your data or share it with third parties for marketing purposes. See our Privacy Notice for more information.