USE CASES · NETWORK IMPACT

NETWORK IMPACT MODELLING · WHAT-IF DECISIONS

Model the network impact before you make the move

Opening, closing, relocating, or a competitor arriving next door: model what any change does to the whole network before a single lease or client is touched.

SCENARIO BOARD

NETWORK OF 214 SITES · 3 SCENARIOS

Schematic network map: one opening scenario with impact rings across neighbouring sites and a competitor entry zone

Your network

Scenario change

Impact zone

SCENARIOS · ONE CALIBRATED MODEL

S·01 · OPEN

Recommend

Riverside north

NET +3,100 VISITS · CANNIBAL. 9%

S·02 · COMPETITOR

Stress test

Discount entry, east

−6% VISITS AT 2 SITES · RESPONSE READY

S·03 · RELOCATE

Neutral

Old town, moved 400 m

OLD TOWN +400 M · NET NEUTRAL

WHY NETWORK CHANGES SURPRISE

Every change ripples further than the plan

A new site, a closure, a competitor opening: each one moves demand across the map. Plans that treat sites one by one keep being surprised by their own network.

01°

01°

The network reacts as a system

One change shifts visits at five other sites. A business case written for a single location cannot see any of it.

02°

02°

Cannibalisation arrives uninvited

The proud new flagship draws half its revenue from its own sister sites, and the plan only finds out at year end.

03°

03°

Competitors move too

Your plan is static, the market is not. A single competitor entry reshapes catchments overnight, and the response starts late.

04°

04°

Averages hide the losers

Network totals look fine while two regions quietly bleed. Without site-level impact, the damage hides in the average.

HOW NETWORK CHANGES RUN TODAY

Site-by-site business cases

Impact discovered in next quarter’s numbers

Competitor moves tracked in news, not models

Cannibalisation as a post-mortem

Every scenario a new analysis from scratch

WITH NETWORK IMPACT MODELLING

The whole network as one living model

Any change simulated before commitment

Cannibalisation and absorption quantified

Competitor scenarios stress-tested

Scenarios compared side by side, on demand

MODEL · SIMULATE · COMPARE

From a question to a quantified scenario

One modelling workflow. The network becomes a calibrated model, any change becomes a scenario, and scenarios come back quantified and comparable. Ask again tomorrow, the model is still there.

CALIBRATE · YOUR NETWORK

A model that mirrors your network

Your sites, hexagon-level demand and competitors in one model

Calibrated against real performance, not benchmarks

Updated as your network and the market move

SCENARIO IMPACT · NET VISITS

Open: Riverside north

Relocate: Old town

Close: Arcade

SIMULATE · ANY CHANGE

Run the what-if, not the argument

Open, close, relocate or resize, one scenario each

Add competitor entries and market shifts

See impact per site, per region and net

Scenarios run on Network Impact Modelling, part of the Performance solution, stress-tested on national branch and store networks.

SCENARIO S·02 · COMPETITOR ENTRY

Visits at risk, two sites

−6%

Defensive relocation tested

+400 M

Net effect after response

−1%

RESPONSE READY · BEFORE THEY OPEN

COMPARE · AND COMMIT

Decide between futures, not opinions

Scenarios compared on one scorecard

Winners carry their assumptions with them

The model stays for the next question

DECISION · Q3

Open: Riverside north

GO

Relocate: Old town

GO

Close: Arcade

HOLD

TWO MOVES APPROVED · MODEL UPDATED

WHAT THE MODEL WEIGHS

Why the same move lands differently across a network

The impact of a change is never just local. Distance decay, competitor pull and where demand can actually re-flow decide whether a closure is absorbed or lost, and whether a new site adds demand or steals it.

Under the hood is a Huff gravity model on a hexagonal grid of roughly 0.1 square kilometre cells, calibrated on your transactions and visits joined with trusted location data and competitor locations. Each site earns an attractiveness weight from the real environment around it, and demand re-routes by distance decay, so results stay comparable across regions and quarters.

SCORE COMPOSITION

What shapes a scenario result, by market type

Dense market

Sparse market

DEMAND FLOW

How freely demand re-routes between sites

88

84

DISTANCE DECAY

How far customers will actually travel

90

38

COMPETITOR PULL

How strongly rivals capture released demand

62

90

ABSORPTION

What your own sites can take over

80

52

SATURATION

How much headroom the market still has

66

72

RESPONSE

How the network can react to a move

70

55

Dense market: competitor pull decides the outcome

Sparse market: distance decay decides the outcome

SAMPLE WEIGHTS · CALIBRATED ON YOUR NETWORK

THE DIFFERENCE

What changes when moves are modelled first

CAPITAL AT RISK

No surprises after the ribbon cutting

Openings, closures and relocations carry a quantified network effect before capital commits, so the surprises happen in the model.

NETWORK RESILIENCE

Competitor moves stop being emergencies

Entry scenarios are stress-tested in advance, with responses ready before the competitor finishes their fit-out.

PLANNING CADENCE

Answers in days, standing model all year

Because the model lives on, the tenth scenario costs hours, not another consulting engagement.

BEYOND ONE-OFF ANALYSES

A business case for one site cannot see the network

SITE BUSINESS CASES

Good for the site, blind to the system

Each case assumes the rest of the network stands still. It never does, and the error lands in next year’s numbers.

MARKET RESEARCH

Good for context, weak for consequences

Research describes demand as it is. It cannot tell you what your own move, or a competitor’s, will do to it.

POST-HOC REVIEWS

Good for lessons, late for decisions

Measuring impact after the fact explains the loss. Modelling it first is what prevents it.

STATIC GIS STUDIES

Good maps, frozen assumptions

A study models one moment. Networks and competitors keep moving, and the study cannot answer the follow-up question.

CLEVERMAPS

A living what-if for the whole network

Any change simulated on a calibrated model of your network, comparable across scenarios and repeatable every quarter. The heart of the Performance solution.

Network impact modelling is the heart of the Performance solution, built on trusted location data and shared decision logic.

TESTED ON REAL NETWORKS

Proven where networks change fast

FEATURED CASE STUDY

Optimization of branch network using location insights

TETA used location insights and network modelling to optimise its retail network, understanding which stores support each other and where changes strengthen coverage instead of cannibalising it.

RETAIL · DRUGSTORE NETWORK

ALSO AT NATIONAL SCALE

Reducing a branch network by 35% while maintaining client access, with Generali

Read the story →

A calibrated model of your whole network that simulates what any change does to demand, visits and revenue across every site, before the change happens. Openings, closures, relocations and competitor moves all run as scenarios on the same model.
50.1033, 14.4458 · DĚLNICKÁ HQ

30-MINUTE WORKING SESSION

Bring the move you are debating

An opening, a closure or a competitor threat: in 30 minutes we will run it as a scenario on a model of your network and show the impact, site by site.

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The GeoDecision platform
for the people who decide

CONTACT

CleverMaps, a.s.

Vídeňská 101/119

619 00 Brno, Czech Republic

© 2026 CleverMaps, a.s. · VAT CZ03728277

SOC 2 TYPE II · ISO 27001 · EU DATA RESIDENCY

CleverMaps footer visual for location intelligence and GeoDecision workflows

The GeoDecision platform
for the people who decide

CONTACT

CleverMaps, a.s.

Vídeňská 101/119

619 00 Brno, Czech Republic

© 2026 CleverMaps, a.s. · VAT CZ03728277

SOC 2 TYPE II · ISO 27001 · EU DATA RESIDENCY

CleverMaps footer visual for location intelligence and GeoDecision workflows

The GeoDecision platform
for the people who decide

CONTACT

CleverMaps, a.s.

Vídeňská 101/119

619 00 Brno, Czech Republic

© 2026 CleverMaps, a.s. · VAT CZ03728277

SOC 2 TYPE II · ISO 27001 · EU DATA RESIDENCY