To find out if check-in data presents any actual value to retailers, SuperData Research ran a study that compared outlets for Whole Foods and Trader Joe's in New York City.

1. Whole Foods Case Study
September 2010
Joost van Dreunen, Ph.D.
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© 2010 SuperData Research

2. Executive Summary
what we found
Based on a comparative analysis using Foursquare check-in data we made the following
observations:
Measured by check-ins, Whole Foods’ share of Grocery Store category is more
than twice as large as Trader Joe’s
Weekday traffic for Whole Foods concentrates around lunchtime, while Trader
Joe’s traffic peaks at dinnertime
Whole Foods sees steady traffic throughout the week, compared to a spike in
traffic in Trader Joe’s outlets during the weekend
Both Whole Foods and Trader Joe’s are equally distributed for gender, despite
men representing a larger share in the overall data set
Over 9% of Whole Foods’ traffic checks in at its restaurants and coffee shops,
and 2% of Trader Joe’s traffic checks in at its wineshop
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3. Section 1
Overview
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4. Index
what’s in here?
Overview
Index
Methodology
Market Share
Whole Foods vs. Trader Joe’s in Tri-State area
Days of the Week
Time of Day Comparison
Gender Distribution
Category Breakdown
Store-to-Store Comparison
Hyper-Local Comparison
Market Share: Union Square
Daily Traffic: Union Square
Market Share: 6th Avenue
Daily Traffic: 6th Avenue
Everything Else
About, Contact, Fine Print
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5. Methodology
what did we do, and how did we do it?
Data: 179,129 unique Foursquare check-ins for Grocery store segment in New York
Tri-State area
Time Period: July 19 to August 26, 2010
Venues: top 15 most popular outlets for both Whole Foods and Trader Joe’s,
totaling 30 stores
Analysis: compare branches to each other and to overall grocery store traffic across
different variables
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6. Section 2
Market Share
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7. Market Share
Whole Foods 2.3x more traffic than Trader Joe’s in NYC market
Market Share in New York’s Grocery-segment (%)
Trader Joe’s
30% averages 107 daily
check-ins; Whole
25% Foods 251
20% On peak days, Whole
Foods claims 25% of
15% entire grocery
segment
10%
For Total Market,
5% Saturdays are busiest
day, with 21.4% of
0% weekly traffic
7/23
7/24
7/25
7/26
7/27
7/28
7/29
7/30
7/31
8/1
8/2
8/3
8/4
8/5
8/6
8/7
8/8
8/9
8/10
8/11
8/12
8/13
8/14
8/15
8/16
8/17
8/18
8/19
8/20
8/21
8/22
8/23
Whole Foods Trader Joe's
n = 35,360 check-ins recorded in Tri-State region, from July 23rd to August 23rd, 2010.
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© 2010 SuperData Research

8. Days of the Week
day-to-day traffic throughout the week
Share of Check-in Traffic Distributed by Day of
the Week (%)
25%
For Trader Joe’s, Saturday weekend
(18.0%) and Sunday
(22.6%) are busiest 20%
Whole Foods’ peak days
15%
are Mondays (17.2%) and
Sundays (16.9%)
10%
Whole Foods more equally
distributed throughout 5%
week, with high/low
difference of 6%, compared
0%
to Trader Joe’s 14% Mon Tues Wed Thurs Fri Sat Sun
Whole Foods Trader Joe’s
n = 11,272 check-ins.
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9. Time of Day
what time do people check-in during the day?
Check-in Traffic by Time of Day (hourly, standardized)
15% 1 Compared to overall
3 segment, both Whole
2 Foods and Trader Joe’s
show above average
10% traffic during lunch time
1
2 But Whole Foods sees
most lunchtime traffic...
5%
3 ...and Trader Joe’s
dominates during
dinner time
0%
1: M
2: M
3: M
4: M
5: M
6: M
7: M
8: M
9: M
AM
11 AM
12 AM
1: M
2: M
3: M
4: M
5: M
6: M
7: M
8: M
9: M
PM
11 PM
PM
A
A
A
A
A
A
A
A
A
P
P
P
P
P
P
P
P
P
0
00
00
00
00
00
00
00
00
00
0
0
0
00
00
00
00
00
00
00
00
00
0
0
:0
:0
:0
:0
:0
:0
12
10
10
Whole Foods Trader Joe’s Total Grocery Segment n = 112,934 check-ins.
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© 2010 SuperData Research

10. Gender Breakdown
overall grocery segment skews male
Gender Distribution by Branch, Overall (%)
70.0%
60.0% Both Whole Foods
(53.7% male, 47.3%
50.0% female) and Trader Joe’s
(50.9%, 49.1%) are
40.0%
equally distributed...
30.0%
...while the overall grocery
20.0% check-ins tend to be
61.4% male and 38.6%
10.0%
female
0%
Wholefoods Trader Joe's Total Grocery Segment
Male Female
n = 176,208 check-ins.
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© 2010 SuperData Research

11. Category breakdown
store check-ins by category
Category Distribution
Foursquare Category Whole Foods Trader Joe’s Total
Shops:Food & Drink:Grocery / Supermarket 57.4% 27.6% 85.0%
Shops:Food & Drink 9.2% 0.0% 9.2%
Shops:Food & Drink:Wine Shop 0.0% 2.3% 2.3%
Food:Vegetarian / Vegan 1.5% 0.0% 1.5%
Food:Coffee Shop 1.1% 0.0% 1.1%
Nightlife:Wine Bar 0.0% 0.6% 0.6%
Shops:Food & Drink:Gourmet 0.0% 0.3% 0.3%
n = 11,133 check-ins.
In total, 15% of check-ins are labeled under something other than Grocery
Store
Whole Foods’ wine shop receives no mention at all (despite its specials),
compared to Trader Joe’s
With 9.2% of Whole Foods’ traffic coming from people at its restaurants,
Trader Joe’s may consider offering a comparable feature
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© 2010 SuperData Research

12. Section 3
Store-to-Store Comparison
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13. Hyper-Local Comparison
local data allows for competitive analysis in small area
Union Square 6th Avenue
Whole Foods: 4 Union Square Whole Foods: 250 7th Avenue
Trader Joe’s: 142 East 14th Street Trader Joe’s: 675 6th Avenue
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14. Market Share: Union Sq.
store traffic compared to total grocery segment check-ins
Union Square Area Hyper-Local: Check-in Traffic by Time of Day
(standardized hourly)
1 Both outlets have 12%
n= 5,345.
below average traffic
during morning and 1 2
early afternoon,...
8%
2 ...and above average
around dinner time.
This indicates an 4%
opportunity to draw
in more grocery
shoppers during first
0%
half of the day
1: AM
2: AM
3: AM
4: AM
5: AM
6: AM
7: AM
8: AM
9: AM
10 AM
11 AM
12 AM
1: PM
2: PM
3: PM
4: PM
5: PM
6: PM
7: PM
8: PM
9: PM
10 PM
11 PM
PM
0
00
00
00
00
00
00
00
00
00
0
0
0
00
00
00
00
00
00
00
00
00
0
0
:0
:0
:0
:0
:0
:0
12
Hyper-Local Market Area
Whole Foods on Union Square
Trader Joe’s on 142 East 14th Street
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15. Daily Traffic: Union Sq.
day-to-day check-ins for hyper-local market area
Share of Check-in Traffic Distributed by
Day of the Week (%, standardized)
1 Whole Foods excels
35% on Tuesdays, when
n= 5,345
3 overall traffic is slow
30%
4
25% but falls behind
2
20% 1 during the weekend
2
15% as overall traffic in the
3
10%
area peaks on
Saturdays
5%
0% 4 and is followed by
Mon Tues Wed Thurs Fri Sat Sun strong Sundays for
Whole Foods on Union Square Trader Joe’s
Trader Joe’s on 142 East 14th Street
Hyper-Local Market Area
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© 2010 SuperData Research

16. Market Share: 6th Avenue
store traffic compared to total grocery segment check-ins
Hyper-Local: Check-in Traffic by Time of Day
(standardized hourly)
15% 1 Whole Foods sees more
n= 2,308 traffic during early
2 morning breakfast traffic
3
10%
2 During lunchtime, both
stores are on par with the
1 area average
5%
3 Toward dinnertime Trader
Joe’s dominates, leaving
0%
room for growth for
Whole Foods
1: AM
2: AM
3: AM
4: AM
5: AM
6: AM
7: AM
8: AM
9: AM
10 AM
:0 M
:0 M
1: PM
2: PM
3: PM
4: PM
5: PM
6: PM
7: PM
8: PM
9: PM
10 PM
:0 M
PM
11 0 A
12 0 A
11 0 P
0
00
00
00
00
00
00
00
00
00
0
00
00
00
00
00
00
00
00
00
0
:0
:0
:0
12
Hyper Local Market Area
Whole Foods on 7th Ave
Trader Joe’s on 6th Ave
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© 2010 SuperData Research

17. Daily Traffic: 6th Avenue
day-to-day check-ins for hyper-local market area
Share of Check-in Traffic Distributed by
Day of the Week (%, standardized)
1 Both outlets see 25%
n= 2,308
strong traffic on 1
Mondays 20%
2 3
2 and Whole Foods 15%
maintains its share
when the overall
10%
market slows
5%
3 but fails to recover
when traffic picks up
0%
again during the Mon Tues Wed Thurs Fri Sat Sun
weekend Whole Foods on 7th Ave
Trader Joe’s on 6th Ave
Hyper Local Market Area
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© 2010 SuperData Research

18. Section 4
Everything Else
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© 2010 SuperData Research

19. About
SuperData Research, Inc. is a research provider specialized in digitally distributed entertainment. We help
clients think through challenges and opportunities related to digital entertainment, including location-based
media, smartphone business models, monetization, alternative payment methods, and virtual item sales.
We apply traditional retail expertise to online entertainment consumption and digital distribution.
SuperData Research employs a multidisciplinary approach in compiling the data to drive its analyses. This
includes over 50 million unique online transactions, ethnographic observation, expert interviews, and
surveys.
In January 2010, SuperData Research secured multi-year angel funding. Our client base includes brand
owners, developers, payment providers, publishers, retailers and VCs.
About the Author
Joost has over a decade of commercial research experience on interactive entertainment and technology
industries. Prior to founding SuperData he held senior analyst positions at Nielsen Online and DFC
Intelligence. He specializes in digital entertainment and has written extensively on video games, digital
audiences, micro-transactions, monetization and digital distribution.
Joost is an affiliate researcher at the Columbia Institute for Tele-Information, a member of the Center of
Organizational Innovation and teaches at the NYU Game Center. He holds a doctorate degree from
Columbia University.
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© 2010 SuperData Research

20. Contact
Lead Analyst
Joost van Dreunen, Ph.D.
joost@superdataresearch.com
116 West 23rd Street, 5th floor
New York, NY 10011
(646) 375 2273
www.superdataresearch.com
Twitter @_SuperData
Confidential & Proprietary Copyright
© 2010 SuperData Research

21. Fine Print
Conditions of Purchase
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SuperData Research has made every attempt to verify the accuracy and completeness of information in this
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and recommendations represent the judgment of our analysts, based on the best information available at the time
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