This document discusses simulation of buying flows and the possibilities of using point-of-sale planning. It introduces Geo Intelligence, which combines geographical data, methodology, automation and business knowledge to analyze retail real estate. Their buying flow model allocates potential sales from districts to surrounding shops based on distance, store attraction and other factors. This allows benchmarking store performance, optimizing regional marketing, and accurately assessing the impact of new stores. Geo Intelligence works with clients through assessment, providing a decision platform, and strategic studies to optimize networks.

1. Simulation of buying flows
Approach and Possibilities
Dieter.Debels@geointelligence.be (0495/44 24 01)
www.geointelligence.be

2. 2
Agenda
 Introduction Geo Intelligence
 Introduction ‘Simulation of buying flows’
 Possibilities with the Point-Of-Sales Planner

3. 3
About us
Geo Intelligence is…
…an innovating and flexible partner for all parties that get
involved with analyses of retail real estates. By combining
geographical data, methodology, automation and business
knowledge in an appropriate way, we succeed in giving wellfounded answers on fundamental questions.

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Our history
Transition to a professional organisation with ten highly
educated geomarketing experts
Research funding
(Baekeland) received
to improve our
methodologies
Development of
a new vision on
geomarketing
2012
2011
Market exploration
and development of
methodology and
software
2013
Development of
a web based
environment &
customer base
expansion
2010
2009
2008
Proof of concept with retailers and project
developers

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Our references
 Retail
 Government
 Real Estate

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Agenda
 Introduction Geo Intelligence
 Introduction ‘Simulation of buying flows’
 Possibilities with the Point-Of-Sales Planner

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Simulation of buying flows
Modelling buying flows
Estimating spending…
€, nr of people, nr of contracts, % of total spending
…for a market segment…
Groceries, sports, low or high fashion, …
… from each district …
19.700 blocks, 5.500 BDzones or 1.148 zipcodes
… to all competing shops surrounding

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Simulation and modelling of buying flows
Example: Estimated monetary spending for Electronics in the BD-zone
“ZELE 03B”
Suppose that we can estimate this spending with high precision, then…

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Suppose that we can estimate this spending with high precision,
then…
… we can benchmark store performance
… optimize regional marketing
… accurately assess the impact of a new store opening/a closure/
a surface modification on the existing network.
… optimize an entire network
… But first we have to get there!

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Definition of an accurate buying flow model
An accurate model produces buying flows …
…that highly correspond to real buying flows…
…by means of clear and logical decision parameters.
 Note: We hold a 90% accuracy guarantee (on shoplevel) in all our
contracts (which is better than 100%!)

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Steps towards an accurate buying flow model
Step 1
Define your market segment(s)
Step 2
Build up your market segment(s) from the supply side
Witgoed
Dagelijkse
aankopen
Inbouwelektro
Bruingoed
Periodieke
aankopen
Multimedia
Uitzonderlijke
aankopen

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How to construct an accurate buying flow model
Step 2
Build up your market segment(s) from the supply side
– Contains all shops that are fully or partly competitive with your own business

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Steps towards an accurate buying flow model
Step 1
Define your market segment(s)
Step 2
Build up your market segment(s) from the supply side
Step 3
Add as much real sales information as possible

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How to construct an accurate buying flow model
Step 3
Add as much real sales information as possible
 For your own segments to a test-environment
– For own shops: Turnover per shop and origin of customers
– For competitors: Global turnover per competitor
Real sales per own shop
Real sales per competitor

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Steps towards an accurate buying flow model
Step 1
Define your market segment(s)
Step 2
Build up you market segment(s) from the supply side
Step 3
Add as much real sales information as possible
Step 4
Calculate the sales potential per zone (= Demand side)

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How to construct an accurate buying flow model
Top down
approach
Step 4
Calculate the sales potential per zone (= Demand side)
Market reports/business knowledge
Modeled and real sales related to Wealth Indeces for owner X
Sales volume for owner X
Bottom up approach
Potential formula per district:
€300/yr*#families*…
Poor districts in Belgium
Real sales for owner X
Modeled sales for owner X
Rich districts in Belgium
+ substitution! (non-allocated
market)
- non-triggered demand
- non-modeled alternatives

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Steps towards an accurate buying flow model
Step 1
Define your market segment(s)
Step 2
Build up you market segment(s) from the supply side
Step 3
Add as much real sales information as possible
Step 4
Calculate the sales potential per zone (= Demand side)
Step 5
Allocate market potential per district to shops around

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How to construct an accurate buying flow model
Step 5
Distance to the shops
• Real driving times
• Micro accessibility of the shops
• Penalties for crossing cultural barriers
Store attraction
• Shop characteristics (surface, visibility, …)
• Competive strength per owner
• Shopping area strength
Other important elements
• Management
• Temporary situations
• Geographical differences
• Cannibalization strength
Allocate market potential per district to shops around

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How to construct an accurate buying flow model
 What’s the magic trick? Thanks to a transparant test environment we can
• Monitor the accuracy of the model in 9 different views by comparing the model results with the
real sales information
• Optimize the customer behaviour parameters
• Promise a 90% accurate model with an incredible added value

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Agenda
 Introduction Geo Intelligence
 Introduction ‘Simulation of buying flows’
 Possibilities with the Point-Of-Sales Planner

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Benchmark store performance
 Added value: Continuous monitoring proces
– Measure management power, franchising power, regional power, shopconcept
power, location type power, …
 Return-On-Investment:
– Relevant for each customer
– Depends on management power to take action!

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Optimize regional marketing
 Added value:
– Challenge low hanging fruit in 2 directions
 Return-On-Investment
– For leaflet distributing retailers: 10% - 20% switches (start/stop), leading to
5%-10% increased efficiency

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Impact analyses for case studies
 Sales impact after opening/closing/relocating one or more shops
– Own or competitors
– Including cannibalisation on own shops and competition
 Added value:
– Cost savings: Own studywork = 3d work, 3rd party analysis = 3k€/case
– Risk reduction: If it can save you from 1 wrong decision…
– Communication power: Towards shareholders, investors, …
 Return-On-Investment: In function of
– #cases/year
– cost/wrong decision

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Strategic optimal network
 Calculate the future optimal network (in terms of ROI)
 Added value
– Best possible answer to one of the most important questions for retailers
– Creates “out-of-the-box” ideas (e.g. 2vs1 scenarios, …)
– Transparant view in all details
 Return-On-Investment: Calculated into detail

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How we work
Phase 1: Assessment
Strategic Walk
-
Identify critical success factors Benchmark shops/shopconcepts
Validate model
Phase 2: Flexible partnership
Decision
platform
In-house platform
Case
Automate procedures -
2 case studies for
potential locations
OR …
-
Unlimited use for case
studies, benchmarking, internal communication, …
Strategic
studies
-
Strategic
studies
Extend platform to answer in depth questions about impact of
marketing, optimal split of every shop in departments,, optimal
long term network, …
Case
studies
-
Case
studies
On demand
48hrs delivery time
At your service
-
You will see opportunities
Case
studies