Named after the Norse God for Crops and Fishing, our prediction algorithms encompass multiple aspects of the retail spectrum. From shopping basket abandonment through to measuring footfall, our retail algorithms have already been tested by the likes of John Lewis and Marks and Spencers.
The prediction model is accessed through a RESTful JSON API. Location data is uploaded through an API.
Our footfall prediction software was part of the JLAB (John Lewis Lab) 2017 cohort and accurately gave hourly footfall figures for any popular location without the need for expensive people counting hardware.
There are many anonymised sources of footfall data available, from Facebook to Foursquare, to anonymised cell phone data - all can give a real time picture of how busy a retail location is, coupled with our unsupervised machine learning gives accurate predictions in the future.