Hotspot Analysis — Getis-Ord Gi*
Find Statistically Significant Hot and Cold Spots
DynaCarto Hotspot Analysis helps identify where high or low values form statistically meaningful geographic concentrations. Using the Getis-Ord Gi* spatial statistic, DynaCarto goes beyond simply showing where data appears dense—it evaluates each location together with its surrounding neighbors to determine whether the observed spatial pattern is likely to be meaningful rather than random.
In practical terms, Hotspot Analysis helps answer questions such as:
Where are unusually strong concentrations of sales?
Which neighborhoods consistently show high incident levels?
Where are low-performing areas concentrated?
Which geographic patterns deserve immediate attention?
The results are displayed directly on an interactive mobile map, allowing users to quickly distinguish hot spots, cold spots, and areas without statistically significant clustering.
What Is Getis-Ord Gi*?
The Getis-Ord Gi* statistic is a widely used spatial-statistical method for detecting local concentrations of high and low values.
For every location, the analysis considers:
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the value at that location
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values at surrounding locations
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the spatial relationship between neighboring observations
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the overall distribution of values across the dataset
If a location with a high value is surrounded by other high values, it may form part of a statistically significant hot spot.
If a low-value location is surrounded by other low values, it may form part of a statistically significant cold spot.
An isolated high value, however, does not automatically become a hot spot.
That distinction makes Hotspot Analysis much more powerful than simply coloring the highest values on a map.
Hot Spots, Cold Spots and Statistical Significance
Hot Spots
Areas where high values are geographically surrounded by other high values.
These can reveal concentrations of:
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strong sales
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high demand
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incidents
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population characteristics
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transaction activity
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service requests
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property values
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network usage
Cold Spots
Areas where low values are surrounded by other low values.
Cold spots may reveal:
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weak demand
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low sales performance
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underserved areas
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lower property activity
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low service usage
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areas requiring additional investigation
Not Statistically Significant
Some locations may have high or low values but do not form a sufficiently strong spatial pattern with surrounding locations.
DynaCarto helps distinguish these locations from statistically meaningful clusters.
Why Is Statistical Significance Important?
A colorful map can suggest that a pattern exists.
Hotspot Analysis asks a more rigorous question:
“Is this geographic pattern strong enough that it is unlikely to be random?”
Getis-Ord Gi* produces statistical measures that help determine the strength of the spatial pattern.
Results can be interpreted using familiar confidence levels such as:
90% · 95% · 99%
Stronger statistical evidence provides greater confidence that the identified concentration represents a meaningful spatial pattern.
This gives decision-makers a stronger analytical foundation than visual interpretation alone.
Hotspot Analysis vs. Heatmap
These analyses may look similar visually, but they answer different questions.
Heatmap
A Heatmap asks:
“Where is activity concentrated?”
It is primarily a visualization of density or weighted intensity.
It is excellent for rapidly seeing patterns and concentrations.
Hotspot — Getis-Ord Gi*
Hotspot Analysis asks:
“Where are statistically significant concentrations of high or low values?”
It evaluates the spatial relationship between observations using statistical methods.
So:
Heatmap = Visual concentration
Hotspot = Statistical spatial significance
Both are useful, but for different purposes.
From Excel to Statistical Spatial Intelligence
A Hotspot Analysis can begin with a simple Excel dataset.
Your data may contain fields such as:
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ID
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Name
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Address
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Latitude / Longitude
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Sales
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Revenue
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Demand
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Incidents
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Transactions
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Population
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Complaints
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Service requests
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Any other numeric value
If geographic coordinates are not available, DynaCarto Smart AI Geocoding can help convert addresses into map-ready locations.
A typical workflow becomes:
Excel → Smart AI Geocoding → Map → Select Value → Getis-Ord Gi* → Hotspot Map → Decision
All directly from a mobile device.
What Can Hotspot Analysis Reveal?
High-Value Concentrations
Discover where important values consistently concentrate geographically.
For example:
Where are our highest-revenue customers concentrated?
Low-Value Concentrations
Identify geographic areas where low values repeatedly occur.
For example:
Which regions consistently show weak sales performance?
Spatial Inequality
Compare areas with substantially different geographic performance.
Emerging Priority Areas
Recognize concentrations that may require investment, intervention, expansion, or closer investigation.
Hidden Spatial Patterns
Patterns that are difficult to detect in spreadsheets can become immediately visible when spatial relationships are analyzed.
Key Business Benefits
Move Beyond Visual Guesswork
Statistical analysis provides stronger evidence that geographic concentrations are meaningful.
Prioritize Resources
Direct investment, staff, marketing, infrastructure, or services toward areas where patterns are strongest.
Discover Opportunities
Identify geographic concentrations of demand, customers, transactions, or other valuable activity.
Detect Problem Areas
Reveal statistically significant concentrations of incidents, complaints, failures, or poor performance.
Compare Geographic Performance
Understand how different areas behave relative to the broader market or service network.
Support Evidence-Based Decisions
Replace assumptions with measurable spatial evidence.
Communicate Results Clearly
Color-coded maps make complex statistical findings easier for managers and teams to understand.
Retail & Store Network Planning
Retailers can analyze:
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sales
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customer spending
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transaction volume
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demand
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store performance
Hotspot Analysis can reveal areas where strong commercial activity forms statistically significant geographic concentrations.
It can help answer:
Where are our strongest demand hot spots?
Where are low-performing markets concentrated?
Where should expansion be investigated?
Combined with Suitability, Proximity & Coverage, and Location Allocation, these patterns can support new-store planning.
Marketing & Customer Intelligence
Customer attributes can be analyzed geographically to identify significant market concentrations.
Examples include:
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revenue per customer
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purchase frequency
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customer lifetime value
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campaign response
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product adoption
Organizations can investigate:
Where are high-value customers concentrated?
Which areas show consistently strong response rates?
Where are low-engagement customer clusters located?
This allows campaigns and resources to be targeted geographically.
Healthcare Planning
Healthcare organizations can analyze:
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patient demand
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disease incidence
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emergency events
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healthcare utilization
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service requests
Hotspot Analysis can reveal statistically significant concentrations that may justify closer investigation or additional resources.
For example:
“Where are unusually high concentrations of emergency incidents occurring?”
Results can support healthcare resource planning, prevention programs, and facility analysis.
Public Safety & Emergency Services
Police, fire departments, emergency services, and public-safety organizations can investigate spatial concentrations of:
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incidents
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accidents
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emergency calls
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fires
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service requests
Instead of simply displaying incidents, Getis-Ord Gi* can help determine whether high incident values form meaningful geographic clusters.
This helps prioritize prevention, patrol, response, and resource allocation.
Real Estate & Property Markets
Hotspot Analysis can identify geographic concentrations of:
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property values
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transaction volumes
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rental activity
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development
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price growth
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investment activity
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Investors and developers can identify areas where strong market activity forms persistent spatial patterns.
Find where the market is heating up—not just where one expensive property exists.
Banking & Financial Services
Financial organizations can analyze:
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customer value
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deposits
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transactions
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loan activity
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commercial activity
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branch performance
Hotspot Analysis can reveal important geographic concentrations of financial activity and help support:
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branch planning
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ATM strategy
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market expansion
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customer intelligence
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service-network analysis
Telecommunications
Telecommunications organizations can analyze:
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subscriber demand
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network usage
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complaints
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service requests
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traffic volumes
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performance indicators
Hotspots may identify areas with unusually strong network demand, while other patterns can reveal locations requiring infrastructure attention.
This can support network investment and capacity planning.
Logistics & Distribution
Hotspot Analysis can reveal concentrations of:
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orders
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deliveries
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service requests
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freight activity
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customer demand
Logistics organizations can identify geographic areas producing disproportionately high operational demand and prioritize capacity accordingly.
Urban Planning & Public Sector
Governments and municipalities can analyze:
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population demand
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complaints
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infrastructure requests
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traffic incidents
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public-service usage
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socioeconomic indicators
Hotspot Analysis can reveal where public needs or problems are geographically concentrated.
This supports more targeted and transparent resource allocation.
Example: Retail Sales Hotspots
Imagine a retailer has 2,000 customer locations with annual sales values.
Looking at the spreadsheet reveals the largest customers—but it does not reveal the broader geographic structure.
DynaCarto analyzes each customer's sales together with surrounding customers.
The result may reveal:
Area A — 99% significant hot spot
A strong concentration of high-spending customers.
Area B — Not statistically significant
Several high-value customers exist, but they do not form a consistent geographic concentration.
Area C — Significant cold spot
Low customer values consistently occur across the surrounding area.
Management now has three completely different geographic signals instead of simply a list of high and low customers.
That information can support marketing, expansion, sales territory planning, and investment decisions.
Hotspot Analysis + Other DynaCarto Tools
Hotspot Analysis becomes even more useful when combined with other DynaCarto analyses.
Heatmap → Explore the Pattern
Quickly visualize where activity appears concentrated.
Hotspot → Validate the Pattern
Determine where concentrations are statistically significant.
Cluster → Organize the Geography
Create natural geographic groups or territories.
Proximity & Coverage → Evaluate Service
Determine whether important hot spots are adequately covered.
Isochrone → Measure Accessibility
Understand whether facilities can realistically reach high-priority areas.
Suitability → Find the Best Location
Use spatial evidence to identify promising new sites.
Location Allocation → Optimize the Network
Determine how facilities should serve demand.
This creates a powerful decision workflow:
Visualize → Validate → Understand → Prioritize → Act
From Raw Values to Statistical Evidence
DynaCarto Hotspot Analysis transforms ordinary location data into a statistically informed view of geographic performance.
Instead of simply asking:
“Where are the highest values?”
you can ask:
“Where do high or low values form meaningful spatial patterns?”
That difference can turn a map from a visualization into a decision-support tool.
Find the Hot Spots. Reveal the Cold Spots. Understand What Really Matters.
DynaCarto Getis-Ord Gi* Hotspot Analysis — statistical spatial intelligence directly on your mobile device.