Geoanalytics, location intelligence, customer analytics, and mobility simulation projects for organizations that make data-driven decisions.
Our case studies
unica360 has delivered geoanalytics and location intelligence projects for leading organizations in retail (IKEA, Immochan, Coca-Cola), banking and insurance (CaixaBank, BNP Paribas), consumer goods, real estate, the public sector (MITMA, MITECO, ISTAC, Basque Government), and energy (Iberdrola). Our case studies cover site selection, customer segmentation with geodata, pedestrian mobility simulation, risk model enrichment, and urban planning across Europe and Latin America.
Case studies by sector
Retail / Franchise Network Expansion
Language school franchise expansion
Client: Kids&us (children's language education)
Problem
They needed to choose locations for their franchisees that would maximize both access to the target audience and the number of viable franchises.
Location scoring model based on micro-territorial indicators (child density, income, foot traffic), competition and cannibalization analysis, plus a geomarketing tool for expansion, marketing, and franchisee teams.
350
centers open in Spain
70
international centers
1 closure in Spain and 4 internationally
Retail / Fitness
Revenue prediction for new locations
Leading gym chain (400+ locations)
Problem
They wanted to reduce the proportion of new locations that opened without becoming profitable.
AI model that predicts revenue for each potential location based on 20 variables (residential and working population, fitness habits, competitive pressure, cannibalization), accessible to the business through a mapping application.
30
centrocenters opened in one year
12%
higher revenue per new center
28%
reduction in the rate of unprofitable new centers
Retail
Site selection and commercial network optimization
Analysis of historical listing data enriched with environmental data, which identified the key predictors of new housing supply: presence of European residents, population density, proximity to transport and amenities, and sociodemographic profile.
Model that detects areas up to 4 times more likely to generate listings than average
15
branches opened
10
closed based on this criterion
Real Estate
AVM, automated property descriptions, and lead qualification
They wanted to target retention campaigns at profitable customers with the highest churn risk, but their internal data wasn't enough to identify them accurately.
Customer enrichment with indicators not captured by internal data — income, mobility habits, housing type, presence of children, lifestyle — to improve the performance of churn prediction models.
Enriched models capture several percentage points more of actual churn than models based on internal data alone.
Across 1M policies worth €400 each, preventing churn among just 1% of profitable customers offsets the cost of enrichment 100 times over.
Banking & Fintech
Credit scoring and AVM enrichment with territorial variables. Referenceable clients
Enrichment of each pharmacy with environmental variables and a model that identifies what characterizes the most profitable ones (tourism, income, neighborhood type, centrality), scoring the potential of every possible customer while excluding existing ones.
1.100
new high-value customers
21%
revenue increase
26% higher margin, against only a 6% increase in logistics cost
E-commerce / Consumer Goods
Retention in online grocery
Leading gym chain (400+ locations)
Problem
They were losing many customers on their second and third orders and needed to increase repeat purchase rates.
Identification, using environmental data, of the household profile most likely to reorder — senior couples in single-family homes, in low-density, mid-to-high-income municipalities — redesign of sales territories around these areas, and a tool showing sales reps where to acquire customers.
De 48% a 69%
From 48% to 69% increase in repeat purchase rate among the new target audience.
E-commerce
Distribution network segmentation and campaign targeting
Agent-based mobility simulation: reconstruction of the real road network, generation of a synthetic population with schedules derived from time-use surveys, and simulation of millions of pedestrian and vehicle routes.
Pedestrian traffic map by segment, day, and hour:
r² = 0,72
very high correlation against manual counts at 35 points across the city.
Public Sector (Government)
Demand for sports facilities
Client: Barcelona and Bizkaia Provincial Councils
Problem
They needed to measure actual coverage of sports facilities across municipalities and estimate demand for new facilities.
Estimation of sports participation by micro-territory using surveys, machine learning, and spatial analysis, combined with a socioeconomic vulnerability model and an assessment of current coverage, with a mapping application and an environment report generator.
90%
reduction in time spent assessing new projects and responding to municipal requests.
Smart City & Public Sector
Mobility analysis and simulation for urban planning, sustainable urban mobility plans (SUMPs), pedestrianization, and digital twins
Enrichment of every application with territorial indicators — local income, tourist appeal, housing characteristics, commercial indices — with high predictive power for default risk.
32% reduction in the default rate among new customers
The highest-risk segments (low-income tourist areas) exceeded 10% default rates, versus under 1% in lower-risk segments.
Energy & Risk
Territorial optimization of sales network and customer acquisition. Referenceable clients
AI system that automatically classifies documents and determines when human review is needed, built on a cloud architecture that scales cost-effectively, with a dashboard to fine-tune precision and coverage.
85.6% of documents are classified by AI with 94.8% accuracy.
The remaining 14.4% is reviewed by the team with 98.4% accuracy.
Legaltech & Operations
Automated classification of legal notifications and entity extraction
