<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-07-08T08:44:08Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/6C48A850-B410-46DC-99B3-AD2375C73524" ns1:id="6C48A850-B410-46DC-99B3-AD2375C73524"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/C8BFAA45-D512-4ECA-BE29-966C62DFBFDF" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/B3CC0348-0402-4477-8511-5E16F3BB8300" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/B3CC0348-0402-4477-8511-5E16F3BB8300" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2022-02-28T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/DE6C743A-0E84-49BC-85D2-C5578DD27EE9" ns1:rel="FUND" ns1:start="2020-11-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">72975</ns2:identifier></ns2:identifiers><ns2:title>The Store Analysis Machine Project (SAM)</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Study</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Successful Quick Service Restaurant (QSR) performance is based on a clear understanding of location, footfall, and its customers. We were approached by a global QSR business to capture store and contextual level data and intelligently use the data to promote menu items. Two other QSR chains concurred that this is a genuine need.

Store Analysis Machine (SAM) collects data, analyses it and promotes on in-store digital menus in real-time the right product based on current context and feedback from previous promotions.

SAM monitors and links current data in-restaurant and additional customer centric data including demographic, footfall, weather, events etc. Using business rules and machine learning, SAM promotes through in-restaurant and digital channels to increase revenue and reduce waste.

This project creates a unique machine learning engine that works with SAM to provide real-time restaurant-level demand-based promotion in-restaurant and on other digital channels.</ns2:abstractText></ns2:project>