Need help?
Hi! Can I help you? Choose a quick question below or type your message. 🙂
After demographic data, SES (socio-economic status), as well as retail and trade data have been successfully imported, the next crucial step is to visualize the data so it can be easily interpreted and used for decision-making. Raw data is often difficult to understand if not presented properly—this is where Smart Styling plays a key role.
In this video, you will learn how to apply smart styling in GEO MAPID to transform data layers into informative visuals, complete with classification, color schemes, and legends. As a result, you can quickly identify high-potential areas for business analysis needs, such as branch location selection or market evaluation.
v1/mapidlearning.non-spatial.smart_styling.leasons_1.text_1
v1/mapidlearning.non-spatial.smart_styling.leasons_2.text_2
v1/mapidlearning.non-spatial.smart_styling.next_leason.text
An introduction to the basic concepts of spatial thinking in a business context, including how location and spatial data support branch expansion, location-based marketing strategies, and outlet performance measurement.
An introduction to the GEO MAPID user interface.
Digitization of infrastructure data, such as industrial areas with multiple parcels, covering three types of geometries.
A case study on importing demographic data (age groups, income levels) and population density to analyze potential markets for new branch locations.
Applying and continuing data styling on imported and displayed datasets.
Preliminary survey using Area, Isochrone, and Buffer tools to calculate how many supermarkets are located within a 5 km radius.
SNJ use case for outlet expansion.
Market survey form for KJPP.