Location Intelligence is known as the use of spatial reference for the improvement of Data Visualization, Analysis, and Event Forecast. Through the connection of alphanumeric and spatial data an additional and intuitive view is created, which makes it possible to recognize spatial patterns, trends and potentials. Through the consideration of spatial conditions, Location Intelligence creates an optimized entrepreneurial decision-making base in Business Intelligence Solutions, and an improved customer interaction, as well as integrating a higher process quality in business processes.
If one is searching the Internet for notions such as Location Intelligence (hereinafter called “LI”), Location Analytics, GeoMapping or other catchwords, one will find a variety of interpretations and definitions. However, there is no clear representation of the necessary elements that determine Location Intelligence. In principle it is possible to describe in a closed loop with the 3 memorable words LOCALIZE-ANALYZE-ACT; WHAT one wishes to reach with LI. However, the question remains of HOW one can usefully establish LI in a company. Basically there are 3 cores to differentiate:
1. Location Discovery (Data Warehouse “Tuning“):
Ideally in B2C companies an integrated information source (Data Warehouse, hereinafter called “DWH”) exists in which relevant data from different sources for the corporate management are brought together in a uniform format. If it is a customer centered DWH, i.e. a dataset which describes processes between businesses and customers, then data or key performance indicators like turnover, customer profitability, customer rankings, site performance, sales, sales performance and customer satisfaction will usually be stored within it.
Traditional BI solutions give simplified answers to the questions “Who, What and How much”. The question of “Where” is however often neither asked nor answered. Yet the “Where” controls often the “When, Who and How much” and then makes possible an objective assessment where all important factors including the spatial references are taken into account.
If one looks more attentively at a customer centered DWH, one discovers that spatial data is already available, such as customer addresses, branch locations, sales areas, marketing target areas, risk areas, supply chain relationships, routes and competitive structures for example. Due to inadequate technology, however, the visualization and analysis in traditional BI solutions are not available.
Location Discovery begins with the so-called Geocoding. Every object with spatial reference will have one or more coordinates (x/y, or Lat/Long) assigned in the database and will thus be made available on a geographic map for the subsequent spatial representations and analysis. This event takes place in the DWH every time a spatial data changes or a new one is added. Once the WHERE is known, once something is located, it is possible through simple intersection of spatial information for every point, every line or surface to inherit attributes (like product-related purchasing power, product affinities, socio-demographic indicators, risk class, area affiliations, etc.). This process is well described and identified as “Data Refining”.
The value and ROI of a dataset in a customer centered DWH is thereby significantly increased. The DWH turns from “single point of truth” to “single point of business value”. Location Intelligence begins therefore with the back end environment and not at the front end.
This post by Olivia Sedant originally appeared on Galigeo Blog