H&M Retail Site SelectionIntroduction to GIS Final ProjectDushyanthi Pieris

• H & M Hennes & Mauritz AB (H&M) is a Swedish multinational retail-clothing company, known for its fast-fashion clothing for men, women, teenagers and children

• The company has 3,100 stores in 53 countries and just over 116,000 employees

Store Background

H&M US SWOT Analysis

Strengths• Reputation as a brand that offers

fashionable clothing at a reasonable price – knowledge of the mainstream customer

• Fast and well established distribution system

Weaknesses• New to U.S. online markets compared to

competitors GAP, Zara, Forever 21• Business model complicates entry to the

online market (clothing sizes)

Opportunities• Expansion of retail brick-and-mortar offer

an opportunity to introduce the online shopping to new customers

Threats• International economic instability effecting

the supply chains• Slow economy effecting the 10%-15%

expansion rate

H&M - U.S.

Goal & Analytical Process

Who is the H&M customer

Select the ZIP codes best matching the

above characteristics

GOALSelect a new site for H&M store in Massachusetts with maximum

market potential

Reco

gniz

ing

H&

M C

usto

mer - Analyze current

H&M locations to recognize how H&M identify their customers- Compare results of the above process with ESRI’s H&M spending- Recognize what characteristics isolate H&M customers

Sele

cting

the

Site - Filter the ZIP codes

best matching the above characteristics- Recognize sites in the filtered ZIP codes- Compare the geographical details and physical characteristics of the sites to select the best candidate

Where are the H&M Customers?

Data Source: ESRI Gfk MRI via ESRI Business Analyst Online and current locations via H&M website

Geographical comparison of current H&M locations and H&M spending

ZIP Code Demographic Details

Attribute Current H&M Locations *ZIP codes with highest H&M Spending

Total Population 4,200 – 35,000 21,769 – 34,211

ESRI Common Tapestry Segment 10 and 27 10

Per-Captia Income $31,500 - $55,000 $26,877 - $42,702

Percentage of Population enrolled in College & Grade 9-12

8% -10% 9% - 12%

* 124 ZIP codes (3rd quartile) that produce the highest amount of spending at H&M using ESRI’s H&M spending data from ESRI Business Analyst Online

Analyzing twenty four different characteristics, following best signified an H&M customer

Four Best ZIP Codes for H&M

The Best LocationThe best location is Woburn Mall

• Woburn is the closest match for ZIP codes with highest H&M sales

• The shopping center is conveniently located in a highway intersections, 95 and 93.

• The shopping mall matches the general characteristics of other shopping malls with H&M stores

• Located loser to two educational institutions

Q&A

Appendix

ZIP Name Per Capita Income Total Population % of Population in College or Grade 9 -12

BILLERICA $ 36,421 30,486 11%

FRAMINGHAM $ 43,492 31,217 8%

WOBURN $ 34,555 38,078 9%

TEWKSBURY $ 36,378 28,838 11%

Demographic Details for Final 4 ZIP Codes

List of 24 Characteristics Compared

Apparel Buying Habits1. 2013 Dept./cloth/ shoe/spec store/ 3 Months: H&M2. 2013 Dept./cloth/ shoe/spec store/ 3 Months: Forever213. 2013 Dept./cloth/ shoe/spec store/ 3 Months: GAP4. Apparel and services index5. Bought clothing online in last 6 months

Population6. Number of Household units7. Households8. Families9. Total population10. Total population in ages 20-2411. Total population in ages 25-2912. Total population in ages 15-2913. Median age14. 15+: never married

Other household characteristics15. % without vehicle ownership16. % rent occupied houses: (2010 owner-occupied houses/ (2010 owner-occupied houses + 2010 renter-occupied houses)%17. Dominant tapestry segment

Education18. Population enrolled in Grade 9-1219. Population enrolled in college20. Population enrolled in grad and professional school21. Population 3+ not in school

Income22. Median household income23. Average Household income 24. Per-capita income

Limitations and Further Recommendations

• Limitations• Most of the detailed analysis was limited by the data integrity and

availability.• Further recommendations for analysis• Compare how each H&M store sales differ based on the

demographical data by location and physical characteristics.• Is there seasonal differences in sales by location (ex. How having a

store in a college town may affect sales through the year)• It was apparent high H&M spending was correlated to physical

location though there were several ZIP codes father away from the H&M physical stores. Why the anomaly?

• Use GIS to produce a detailed analysis on shopping center locations; demographic data, gross leasable areas, types of stores in the center etc.

Data sources and Tools

Data Sources• ESRI Business Analyst Online • Mass GIS• H&M website

Tools• ArcMap• ArcCatalog• ESRI Business Analyst Online• MS Excel• MS Access• GeoCoder.US