GlobeOSS
Geospatial Data Science

Site selection can be used for opening, closing, repurposing, or relocating sites. Using spatial data science techniques, GlobeOSS can help our customers to effectively carry out market analysis to drive decisions. We use the existing internal data sets and external data sets. 

OOH analytics can be used by OOH companies & agencies to turn location analytics to pinpoint audiences to have better ROI. Some of the potential uses cases will campaign audience identification, ROI increase for brands, and micro segmentation for hypertargeting.

Geospatial Data Science can help in understanding of the spatial context of fraudulent insurance claims or financial transactions by identifying and predicting patterns. Some use cases will be to identify anomalies faster, data streams overlay to identify fraud etc.

Geospatial analytics can ingest sensor data from cities, such as waste management, street lighting, public transport etc. This will improve the citizen’s experience.

Geospatial analytics will enable our customers to optimize the field sales & service performance – designing and balancing the sales territories with sales representative productivity, reduce field cost and fleet operational cost.

Geo-marketing can be used for planning and measuring the effectiveness of Out of Home (OOH) or Mobile Advertising campaigns. This is done using offline data to understand the consumer behavior. Customer segmentation is also possible with this technique – identify your audiences on the map that will shape your marketing strategies – right message, right audience, right time and right place.

This model can be used by insurers used for climate related data streams to effective use of their capital – from managing disaster assessment to maximizing control over policy selection in their services portfolio.

Geospatial data science can be used for disease prevention and clinic site selection. Example use case will be healthcare factor analysis, medical site selection and disease surveillance & prediction.

Geospatial enables better infrastructure decisions to reduce traffic congestions and speed up incident response for the city, through location driven solutions. Example use case is like reducing traffic congestion, better insights on commuting patterns and faster incident response.

Geospatial Data Science can help in reducing cost and improving the visibility. Spatially optimized supply chain solutions and routing optimization is fundamental to fulfill today’s increasing expectation of sophisticated consumers. Example use cases are Route Optimization, Last-Mile Logistics dan Demand Modeling.

Data monetization is an alternative source of income for many companies. Some example use cases will be retail location insights, mobile events data monetization etc.

Indoor location intelligence can be used to accelerate revenue, boost operational efficiency and improve customer experience, using data source from WIFI, beacon and GPS data.

Geospatial data science helps in optimizing telco and utility networks, overlaying with the right mix of products and services. Some use case will be network operations and maintenance, engineering planning and marketing & sales.