Market data for Europe-wide location and sales planning



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Transcription:

Market data for Europe-wide location and sales planning MRS: European Geodemographics Conference, April 1, 2009 Simone Baecker-Neuchl: GfK GeoMarketing GmbH Nuremberg, Germany.

Agenda 1 Market data for Europe 2 Data research and evaluation 3 Case study: Location planning in Bulgaria.

1 Market data for Europe.

Geomarketing services Geomarketing defined 4 Geomarketing is the analysis of the location-related information contained in market and company data for the purpose of making better business decisions.

Geomarketing services Areas of application 5

Questions about regional sales planning and sales controlling 6 What sales turnover can an individual sales representative achieve? How can I evaluate the performance of my sales team? Where are areas of untapped potential? How can external sales areas be defined? How many external sales areas are suitable?

Questions about planning and evaluating store catchment areas 7 How can I evaluate store catchment areas? Where is there enough sales potential to warrant opening a new store? How can I define my catchment areas? Who is my target group? How many competitors are in my catchment area? How many prospects are in my catchment area? How much purchasing power is in my catchment area? How can I structure my sales program to respond to different consumer habits?

Reasons and point of time for site and market analysis 8 Strategy/planning phase: What are the market risks and opportunities? Determination of alternative usages Optimal and sustainable configuration of the project Purchase decision: Is the purchasing price appropriate? Worst case scenario: Limitation of damage (professional crisis management)

Purchasing power in Europe 9

Purchasing power in Poland 10

Local potential: Target groups and market area 11 Consumer Where does the consumer live? Where can you find your target group? What is the spending power of the immediate population? Retailer Where does the consumer spend money? Which product lines are involved? What is distribution of your turnover potential? Who are you trying to reach?

Retail centrality in Spain 12 Cerdanyola del Vallès Barcelona

Local market potential in Spain 13 What is the retail draw of city? GfK Purchasing Power for women s wear 2007 GfK Retail Turnover for women s wear 2007 (per capita / Spain = 100) 114.3 182.2 109.0 44.4 Barcelona Cerdanyola del Vallès

Demand and potential Population within the catchment area City of Ceske Budejowice in the Czech Republic 14 Retail purchasing power (in mio. ) Catchment area is defined by modified time-distance zones

2 Data research and evaluation.

Data sources 16 Official sources (Eurostat, national bureaus of statistics, UN, etc.) Private sources from national and international companies On-site evaluations performed by GfK GeoMarketing experts Data from partners Own calculations

GfK GeoMarketing s international partners 17

Data relevant to purchasing power Good regional indicators: Net income Gross income Average wages, salaries Government subsidies (pensions, social benefits, etc.) 18 Additional regional indicators: GDP per capita Unemployment / employment rate Educational level Percentage of those employed in agriculture Occupational status (for example, blue collar / white collar employees, low/high level, managers, entrepreneurs) Age distribution of population, percentage of population that is economically active (i.e., those 20 65 years old) Population density (inhabitants per m 2 ) Household possessions: Distribution of automobiles, TVs, color TVs, phones, mobile phones, PCs, washing machines, refrigerators, etc. Number of physicians, dentists Living space (Qm per capita in households)

European purchasing power regional levels country product administrative level number of units postal level number of units AL Republika e Shqipërisë municipalities 374 AT Österreich /Austria municipalities 2.379 4 2.153 BA Bosna i Hercegovina municipalities 142 5 611 BE Belgique-België municipalities 589 4 1.146 BG Bulgaria municipalities 264 4 4.698 BY Respublika Belarus municipalities 138 6 3.836 CH + LI Schweiz/Suisse/Svizzera plus Liechtenstein municipalities 2.647 4 3.208 RS Republika Srbija municipalities 165 2 20 CY Kypros / Kibris municipalities 613 2 45 CZ Ceska Republika municipalities 6.249 5 3.386 DE Deutschland municipalities 12.228 5 8.235 DK Danmark municipalities 99 4 1.077 EE Eesti municipalities 227 5 5.230 ES España municipalities 8.112 5 10.949 FI Suomi / Finland municipalities 415 5 3.044 FR France municipalities 36.612 5 6.053 UK United Kingdom districts 436 PC sectors 9.481 GR Ellada submunicipalities 6.130 5 1.189 HR Hrvatska municipalities 556 5 942 HU Magyarorszag municipalities 3.174 4 3.049 IE Ireland municipalities 3.441 IS Ísland municipalities 79 3 126 IT Italia municipalities 8.103 5 4.434 LT Lietuva municipalities 60 5 15.654 LU Luxembourg (Grand-Duché) municipalities 116 2 56 LV Latvija municipalities 525 4 684 MD Moldova municipalities 986 4 1.250 ME Montenegro / Crna Gora municipalities 21 2 3 MK Poranesnata Jugoslovenska Republika Makedonija municipalities 84 2 20 MT Malta municipalities 68 3 68 NL Nederland municipalities 443 4 4.031 NO Norge municipalities 431 4 3.076 PL Polska urban/rural municipalities 3.096 5 20.602 PT Portugal municipalities 4.260 4 507 RO Romania municipalities 3.188 6 14.166 SE Sverige municipalities 290 5 9.417 SI Slovenija municipalities 210 4 467 SK Slovenska Republika municipalities 2.928 5 1.491 TR Turkiye counties 938 5 3.237 UA Ukrajina counties 681 3 592 19

Potential problems when analyzing data Limited data availability e.g., Albania Reasons: - No public statistics infrastructure compared to Western Europe Data collection is difficult e.g., Russia Reasons: - Linguistic competence is necessary - Some data is not available electronically and can only be accessed in person Data quality varies signficantly e.g., Turkey Reasons: - Official bureau of statistics reformed its data reporting system - Distinct municipal boundaries do not exist Data exhibits major differences from one year to the next e.g., Italy Reasons: - The political conditions have been changed in the south of Italy in order to signficantly reduce the unemployment rate There are missing values in the data e.g, Germany Reasons: - Anonymization of data in accordance with data protection regulations, which vary from federal state to federal state 20 Conclusion: In addition to rigorous research, precise market knowledge and an intensive evaluation of the data are necessary.

3 Case study: Location planning in Bulgaria.

Location and real estate consultancy 22 Appraisals for Investors Banks Project developers Retail trade Public authorities

Study objective 23 Our clients needed support for an investment decision regarding the purchasing and financing of a certain commercial real estate object in Bulgaria. This location analysis addressed the following aspects: Country overview (Bulgaria) Macro-location Micro-location Current shopping center situation and structure Competitive situation in the shopping center market Catchment area and volume demand Analyses of the center s sales figures and market position

Thank you very much! Contact: Simone Baecker-Neuchl 24 Tel.: +49 (0)911 3954690 E-mail: s.baecker-neuchl@gfk-geomarketing.com

About GfK GeoMarketing Company profile 25 Consultancy and reports Market data Digital maps RegioGraph software