Yandex- Fashion and Clothing Industry Update

Online Fashion
Retailers Category
Overview

User Interest in Category
Ø  Query dynamics
Ø  User interest growth in category
Ø  User interest growth forecast
Ø  User interest on online shopping in regions
Ø  User interest in Moscow, Saint-Petersburg
vs. regions
Ø  User interest in Russia vs. CIS

4
User Interest in Category
Queries related to the scope of clothing and shoe shopping make about
0,5% of the total Yandex queries.
Category queries share in total
amount of Yandex queries
Query distribution by segments
within the category
Queries on clothes are the most popular in the category. They made up
more than 60% of all category queries for last 12 months.
Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013
0.0%
0.1%
0.2%
0.3%
0.4%
0.5%
0.6%
0.7%
61%
24%
10%
5%
Clothing Shoes
Accessories Underwear

5
221,538,124
271,560,805
+23%
1 2
Category Dynamics
In 2013 user interest in clothing and shoe shopping went up by 23%.
(based on statistics from January to September).
0
5,000,000
10,000,000
15,000,000
20,000,000
25,000,000
30,000,000
35,000,000
40,000,000

6
384,609,
233
438,802,
224
+14%
1 2
2014

Category Dynamics Forecast
The whole interest in category (clothing, shoes, accessories) is expected
to grow by 17% in 2013.
In 2014 growth rate will be more moderate: user interest is expected to
grow by 14%.
0
5,000,000
10,000,000
15,000,000
20,000,000
25,000,000
30,000,000
35,000,000
40,000,000
45,000,000
50,000,000
2011
Nov
Dec
2012
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2013
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2014
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2015
Feb
Mar
2013

7
16,245,474
25,591,477
+58%
1 2
User Interest Growth in Online Shopping
Growth of queries connected with user intent to buy online exceeds user
interest growth in category overall - 58% vs. 23% (in total).
(based on statistics from January to September)
0
500,000
1,000,000
1,500,000
2,000,000
2,500,000
3,000,000
3,500,000
4,000,000
4,500,000

8
Query Dynamics within Category
User interest in clothes and shoes experience more significant seasonal
changes than accessories or underwear.
0
5000000
10000000
15000000
20000000
25000000
30000000
Clothing Shoes Accessories Underwear

9
233,589,
369
268,096,
108
+15%
1 2
Category Dynamics Forecast (Clothing)
Queries on clothing made up more than 60% of all category queries.
That is the main reason of similarities in trends of user interest in clothing category
and whole category “Clothing, shoes, accessories”.
Notice that growth rates are getting higher in clothing category.
In 2014 growth rate is expected to be +15% (in comparison to14% growth in 2014 in
“Clothing, shoes, accessories” category), in 2013 - +15,6% (in comparison with
14%).
0
5,000,000
10,000,000
15,000,000
20,000,000
25,000,000
30,000,000
35,000,000
2011
Nov
Dec
2012
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2013
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2014
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2015
Feb
Mar

10
0
10000000
20000000
30000000
40000000
50000000
60000000
Moscow, St.Petersburg and
reg.
Russian region (except
Moscow and Saint-
Petersburg)
4 q. 2012 1 q. 2013 2 q. 2013 3 q. 2013
0
10000000
20000000
30000000
40000000
50000000
60000000
70000000
80000000
90000000
100000000
Russia CIS
4 q. 2012 1 q. 2013 2 q. 2013 3 q. 2013
User Interest Growth Dynamics
In 2013 interest growth in category continued growing, but its rate has
slowed down compared to 2012. The number of queries has increased
steadily by ≈ +22-33% (depending on group requests) annually.
The growth rate of the amount of queries in category
+54%
-16%
-15%
+9%
+49%
-10%
-15%
+4%
+54%
-2%
-19%
+11%
+46%
-4%
-19%
+1%
Impressionsbyquarters

11
Interest towards Category in Regions: CIS,
Russia
In 2013* the number of queries in the category most actively has
increased in CIS (+25%).
In Russian regions growth rates are relatively higher, than in Moscow
and Saint-Petersburg.
* (compared to 2012)

0%
20%
40%
60%
80%
100%
120%
140%
160%
180%
200%
Russia
CIS
Russia: regions
(excl. Moscow and
St.Petersburg)

12
Interest towards Category in Russian Regions
Share of queries from users in the regions with the highest internet
penetration (Moscow and Moscow region, St. Petersburg and the
Leningrad region) is gradually reducing.
The audience is steadily being reallocated in favor to the regions.
55% 56% 57% 57% 55% 57% 58% 58%
45% 44% 43% 43% 45% 43% 42% 42%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Moscow, St.Pete and reg.
RF (excl. Moscow and
St.Pete)

13
Regional Popularity
There is a fairly large margin of interest growth in Russian regions.
The majority of traffic on clothing and shoe shopping comes from Central
region. Thus, in Moscow popularity rate is 155%, whereas in most other
Russian regions it is less than 85%.
North-West – 10% of queries
Saint-Petersburg – 7% of queries
Reg. popularity – 108%, 122%
Volga reg. – 12% of queries
Reg. popularity – 81%
CIS – 18% of queries,
South – 4% of queries
Central district – 43% of queries
Moscow – 35% of queries,
Reg. popularity – 135%, 155%
Ural – 6% of queries
Siberia – 6% of queries, Reg.
popularity – 77%;
Far East – 1% of queries
Данные wordstat.yandex.ru, октябрь ‘2013

Online Fashion Retailers
Brand Dynamics
Ø  User interest in Russian and
International online fashion retailers
Ø  User interest growth towards cross-
border e-shops and Chinese trading
platforms

15
0
4000000
8000000
12000000
16000000
20000000
Russian online stores International Megamarkets, cross-
borders and trading
platforms
Oct 2011 - Sep 2012 Oct 2012 - Sep 2013
For the last 12 months, interest in local online retailers has increased by
almost 2 times. As a result, in September, their share has exceeded the share
of interest in international retail sites.
The shift was caused by changes in popularity among brand leaders: user
interest growth to Lamoda , Wildberries and drop in interest to Bonprix.
Online retailers share,
September 2013
User interest Dynamics
(based on retailers brands statistics)
Online Fashion Retailers Dynamics
57%

43%

Russian
International
91% -3% 148%

16
Данные wordstat.yandex.ru, январь ‘2012 – сентябрь ‘2013
Online Retailers, Cross-Borders and Trading
Platforms Brand Dynamics
0
100000
200000
300000
400000
500000
600000
700000
800000
900000
1000000
Aliexpress
eBay
Ozon
Bonprix
Wildberries
Lamoda
Otto
Sapato
Quelle

17
0
1000000
2000000
3000000
4000000
5000000
6000000
7000000
Online Fashion Retailers Popularity
Данные wordstat.yandex.ru, октябрь ‘2012 – сентябрь ‘2013
(based on data for the last 12 months)
Russian online retailers
International online retailers

18
Variation in User Interest in Russian Online
Retailers
57% 313%
28%
23%
35%
45%
4% 451% 135%
0%
50%
100%
150%
200%
250%
300%
350%
400%
450%
500%
0
1000000
2000000
3000000
4000000
5000000
2012 2013

19
Brand Dynamics of Russian Online Retailers
0
100000
200000
300000
400000
500000
600000
700000
800000
Wildberries
Lamoda
Sapato
Kupivip
Butik
Boutique
Z95
Brand-in-trend
Trendsbrands

20
-24%
7%
-6%
-9%
23%
4%
16%
25% -22% 8% -22%
-30%
-20%
-10%
0%
10%
20%
30%
0
1000000
2000000
3000000
4000000
5000000
6000000
2012 2013
Variation in User Interest in International
Online Retailers

21
Brand Dynamics of International Online
Retailers
0
100000
200000
300000
400000
500000
600000
700000
800000
900000
1000000
Bonprix
Otto
Quelle
La Redoute
Asos
Witt
Yoox
Klingel
3suisses
Wenz
Zappos

22
Cross-borders and Online Trading Platforms:
User Interest Dynamics
0
500000
1000000
1500000
2000000
2500000
eBay
Aliexpress
Ozon
Taobao
Deal Extreme
Shopotam
Vivatao
Club-sale
Lightinthebox
Kupinatao
Luxtao
Kitmall
0
5000
10000
15000
20000
25000
Taobao
Aliexpress
eBay
Ozon
Brand Interest Dynamics
Brand Interest Dynamics based on enclosed queries related to the category items

23
50%
913%
-5%
52%
-19% 17% 116%
-47%
86% 260% -200%
0%
200%
400%
600%
800%
1000%
0
4000000
8000000
12000000
16000000
2012 2013
New players
Cross-borders and Online Trading Platforms: User
Interest Dynamics
73%
4675% 170%
20%
0%
500%
1000%
1500%
2000%
2500%
3000%
3500%
4000%
4500%
5000%
0
40000
80000
120000
160000
Taobao Aliexpress eBay Ozon
User interest in cross-border trading
platforms is growing rapidly. Their growth
rate is more than Russian retailers’ one for
both groups of queries: brand or category
related (ex. “Taobao clothes”).
The main threat comes from TaoBao and
Aliexpress as potential competitors in the
category.
Brand Queries related the Category
Brand Queries

Assortment analytics
(by segments)
Ø  Clothing
Ø  Shoes
Ø  Accessories
Ø  Underwear

Clothing
Ø  User interest dynamics in clothing
for men, women and kids
Ø  Interest distribution by types of
clothing
Ø  Interest seasonality

26
Clothing Query Dynamics
The number of queries on clothing for women is 4 times more than for men and
2 times more than for kids. However, interest growth in men’s and kids’ clothing
is higher than in women’s (+30% and +34% compared to 24% respectively).
+24%
+34%
+30%
+14%
Growth
january-september 2013/
january-september 2012
0
1,000,000
2,000,000
3,000,000
4,000,000
5,000,000
6,000,000
7,000,000
8,000,000
Women's clothes
Men's clothes
Kid's clothes
Maternity clothes

27
Interest distribution by types of clothing
TOP-3 the most popular search queries are for dresses, costumes
and jackets which make up more than 50%.
(based on statistics for the last 12 months)
25%
15%
12%6%
5%
5%
4%
4%
3%
3%
18%
dress - 25,2%
suits
jackets - 12,2%
coats - 6,4%
t-shirts - 5%
skirts - 4,4%
down jackets - 4%
jumpsuits - 3,5%
shirts - 3,3%
jeans - 3,1%
other 18,1%

28
Interest distribution by types of clothing
Women’s clothing Men’s clothing
Kid’s clothing
60%
9%
5%
3%
3%
3%
6%
dresses - 60,1%
skirts - 8,8%
womens jackets - 4,8%
sarafans - 3,3%
blouses - 2,8%
women's coats - 2,8%
women's suits - 2,7%
women's down jackets - 2,6%
tunics - 1,9%
women's pants - 1,4%
women's jeans - 1,3%
women's sports suits - 0,9%
other - 6,6%
23%
20%
10%7%
6%
6%
5%
5%
4%
6%
men's jackets - 22,7%
men's suits - 19,8%
men's shirts - 9,8%
men's jeans - 7,4%
men's coat - 6,4%
men's trousers - 5,8%
men's down jackets - 5,3%
men's jackets - 4,8%
men's t-shirts - 4%
sports suits - 3%
men's shorts - 2,8%
men's sweaters - 1,9%
other - 6,4%
45%
20%
14%
6%
rompers - 45,5% children's suits - 19,8%
girl's dresses - 14,1% children's jackets - 6,3%
children's down jackets - 2,5% children's coats - 2,4%
children's skirts - 1,7% children's t-shirts - 1,3%
children's pants - 1,2% children's jeans - 1%
children's summer dresses - 1% children's sweaters - 0,7%
other - 2,5%

29
0
500000
1000000
1500000
2000000
2500000
jackets coats
0
200000
400000
600000
800000
1000000
1200000
1400000
down jackets jumpsuits
Outerwear query dynamics
Query associated with outerwear, characterized by a pronounced
seasonality.
The demi-season clothes reach interest peaks at October and March,
winter clothes at October-November.
Demi-season clothes Winter clothes

30
0
100000
200000
300000
400000
500000
suits jeans
Types of clothing query dynamics
There are several models of seasonality:
•  Types of clothes, popular in spring and
autumn (peaks in October, March);
•  Types of clothes, popular in winter (October-
November);
•  Clothes with growing interest in the spring-
summer;
•  Clothes with growing interest in the spring
only (the peak in March-April);
•  Queries with clear «festive» seasonality
(growth before the New year and the
February 23d holidays);
Spring-summer seasonality Spring seasonality
Holiday seasonality
0
20000
40000
60000
80000
100000
120000
men's shirts
0
100000
200000
300000
400000
500000
600000
700000
800000
t-shirts skirts

31
Dresses query dynamics
Queries on dresses can be divided into two groups: for the New Year
celebration and dresses of new spring-summer collection.
Queries from the first group match with the trend of selling queries (a
significant share of queries includes a clear shopping intent).
Queries from the second group are more informative because include
inlaid queries on photos.
Holiday seasonality Spring-summer seasonality
0
100000
200000
300000
400000
500000
600000
700000
evening dresses beautiful dresses
black dresses buy dress
0
20000
40000
60000
80000
100000
120000
140000
160000
180000
200000
long dresses white dresses

32
Popular queries of kinds of dresses
*
* interest to wedding dresses was not taken into account (in the earlier slides on trends in clothing)
0 100000 200000 300000 400000 500000 600000 700000 800000 900000
Pencil dresses
Lace dresses
Greek dresses
Blue dress
Large size dresses
Cocktail dresses
Knitted dress
Party dresses
Fancy dresses
Floor-length dress
Red dresses
Dresses with sleeves
Short dresses
Dresses for thick
Dresses for prom
Black dresses
Long dresses
White dresses
Evening dresses
Wedding dresses
The number of impressions per month

Shoes
Ø  User interest dynamics in shoes for men, women and
kids
Ø  Interest distribution by types of shoes

34
Generic query dynamics of shoes
The biggest interest to the shoes is observed in spring and autumn.
Number of search queries on children's and women's shoes is two times higher than
on the men's.
0
100000
200000
300000
400000
500000
600000
700000
women's shoes men's shoes kid's shoes

35
Interest distribution by kinds of shoes
TOP-3 the most popular search queries are for boots, sneakers and
shoes, which make up more than 55%.
26%
19%
17%
11%
7%
5%
4%
3%
2%
2% 4%
boots - 26,1%
sneakers - 19,4%
shoes - 16,6%
high shoes - 11,1%
plimsolls - 6,7%
felt boots - 4,6%
uggs - 3,8%
sandals - 3,4%
shoe boots - 2,3%
pumps - 2%
other - 3,9%

36
0
200000
400000
600000
800000
1000000
sneakers shoes plimsolls
0
100000
200000
300000
400000
500000
600000
high shoes felt boots uggs
0
50000
100000
150000
200000
250000
300000
sandals pumps loafers
0
200000
400000
600000
800000
1000000
boots shoe boots
Types of shoes query dynamics
Demi-season seasonality Summer seasonality
Winter seasonality Spring seasonality

Accessories
Ø  Interest distribution by types of accessories

38
Distribution of queries by kinds of accessories
TOP-3 the most popular queries are for bags, hats and scarves, which
make up more than 85%.
63%
18%
6%
6%
3%
2% bags - 63,1%
caps - 17,6%
scarves - 6,2%
peaked caps - 5,8%
purses - 2,6%
gloves - 1,6%
belts - 1,3%
hats - 1%
shawls - 0,5%
berets - 0,3%
snoods - 0,1%

39
Popular search queries of kinds of bags
0 20000 40000 60000 80000 100000 120000 140000 160000
Bags for documents
Beach bags
Small bags
Bags suitcases
Camera bags
Suede bags
Big bags
Bags for girls
Bags backpacks
Brand bags
Copies of bags
Bags on wheels
Shoulder bags
Sports bags
Laptop bags
Travel bags
Leather bags
Men's bags
Women's bags
The number of impressions per month

40
Types of accessories query dynamics
The query data on bags and hats are displayed on the right
(additional) axis.
Winter seasonality Demi-season seasonality
0
500000
1000000
1500000
2000000
2500000
3000000
0
50000
100000
150000
200000
250000
300000
peaked caps hats bags
0
4000
8000
12000
16000 berets snoods
0
200000
400000
600000
800000
1000000
1200000
1400000
0
50000
100000
150000
200000
250000
300000
350000
400000
450000
scarves gloves caps

41
Holiday seasonality of accessories
User interest in category in strongly connected to public holidays.

That these accessories become most popular before the NewYear holidays, February
23 (Defender of the Fatherland Day) and March 8 (International Women's Day) (the
main growth is 30 days before the holidays).
User interest dynamics are similar for most popular types of accessories
with peaks in the pre-New Year period and February - March.
0
20000
40000
60000
80000
100000
120000
140000
purses belts shawls

Underwear
Ø  Interest distribution by types of underwear

43
Underwear query dynamics
Swimsuits define almost all seasonal changes in user interest in category.
Nevertheless, the seasonality of interest to the lingerie is almost the reverse (the
main growth occurs in winter and the beginning of spring).
0
500000
1000000
1500000
2000000
2500000
Generic queries Underwear Swimsuits

44
Interest distribution by types of underwear
TOP-3 the most popular search queries are for swimwear, lingerie, tights
and socks which make up more than 78%.
41%
20%
17%
11%
8%
swimsuits - 41,4%
underwear - 19,5%
tights and socks - 17,1%
bras - 10,7%
briefs - 7,6%
bodysuits - 1,5%
swim briefs - 1,3%
corsets - 0,5%
corsages - 0,3%
modeling lingerie - 0,1%
negligee - 0,04%

45
Types of underwear query dynamics
Interest on the underwear reaches its maximum in February-March,
on the swimsuits – right before the summer months.
Querydatabyswimbriefs

Querydatabyswimsuits

0
50000
100000
150000
200000
250000
300000
350000
400000
450000
underwear tights and socks
bras briefs
bodysuits
0
10000
20000
30000
40000
50000
60000
0
200000
400000
600000
800000
1000000
1200000
1400000
swimsuits swim briefs

Brand analytics
Ø  Dynamics and distribution of brand queries:
Ø  in luxury-segment
Ø  in mass-segment
Ø  Geography of brand interest
Ø  TOP popular brands: dynamics and change of interest

47
0
10000000
20000000
30000000
40000000
50000000
0
1000000
2000000
3000000
4000000
5000000
6000000
7000000
2011-10 2011-12 2012-02 2012-04 2012-06 2012-08 2012-10 2012-12 2013-02 2013-04 2013-06 2013-08
TOP-40 mass brands TOP-40 luxury brands Generic category queries
Dynamics of brand query corresponds the generic queries in the category.
However, the interest towards luxury brands is higher in pre-new year
period.
Данные wordstat.yandex.ru, октябрь ‘2012 – сентябрь ‘2013,
ТОП-40 премиум и массовых брендов
+15,0%
+13,9%
Brand dynamics
The generic queries are displayed on the right (additional) axis.

48
Brand interest distribution
Luxury vs. mass brands TOP-5 brands
Interest in mass brands is 2 times higher than the interest towards luxury
brands, according to the TOP-40 of both groups. More than a quarter of
requests are sports brand Adidas and Nike.
67%
33%
TOP-40 mass brands
TOP-40 luxury brands
15%
12%
3%
3%
3%
64%
Adidas Nike Incity
Reebok Ecco Other

49
0%
50%
100%
150%
200%
0%
10%
20%
30%
40%
0%
50%
100%
150%
200%
0%
10%
20%
30%
40%
Geography of brand interest
LuxurybrandsMassbrands
RegionalAfﬁnity

Shareofqueries

RegionalAfﬁnity

Shareofqueries

51
TOP-20 popular luxury brands
Impressions
0
500000
1000000
1500000
2000000
2500000

52
Query dynamics of TOP-10 luxury brands
0
50000
100000
150000
200000
250000
Lacoste
Gucci
Armani
Givenchy
Calvin Klein
D&G
Hermes
Burberry
Diesel
Louis Vuitton
The interest to the brand Lacoste is kept at a high level throughout the year.
In some months the interest to brands Gucci and Armani exceeds Lacoste.

53
Change of interest to luxury brands
12%
14% 14%
21% -3%
42%
9% 2%
20%
-8%
-20%
-10%
0%
10%
20%
30%
40%
50%
0
500000
1000000
1500000
2000000
2500000
Lacoste Gucci Armani Givenchy Calvin
Klein
D&G Hermes Burberry Diesel Louis
Vuitton
окт 2011 - сен 2012 окт 2012 - сен 2013

55
TOP-20 popular mass brands
0
2000000
4000000
6000000
8000000
10000000
12000000
14000000
16000000

56
Query dynamics of TOP-10 mass brands
Undisputed leaders over the last 2 years are Adidas and Nike. 3rd place,
depending on the month, divided between brands Incity,Adidas and Ecco.
0
200000
400000
600000
800000
1000000
1200000
1400000
1600000
1800000
Adidas
Nike
Incity
Reebok
Ecco
Mango
oodji
Puma
Bershka
Columbia

57
Change of interest to mass brands
25%
28% 19% 45%
18% 15% 13% 25%
36%
0
2000000
4000000
6000000
8000000
10000000
12000000
14000000
16000000
Oct 2011 - Sep 2012 Oct 2012 - Sep 2013
-1%

Interest seasonality in
segment

59
Main growing segments (by seasons): clothing
The greatest increase of interest to the clothing segment is in autumn:
interest becomes 2.5 times higher than in winter and more than 5 times
higher than in spring. In summer there is the decline of interest.
Growth of interest in autumn Growth of interest in winter
Growth of interest in spring
Данные wordstat.yandex.ru, июль ‘2012 – сентябрь ‘2013
0
1000000
2000000
3000000
4000000
5000000
0
500000
1000000
1500000
2000000
2500000
0
50000
100000
150000
200000
250000
300000
350000

60
The growth of interest in autumn and spring is about 4 times higher, than
in winter.
There is the decline of interest almost of all types of shoes in summer.
Main growing segments (by seasons): shoes
0
200000
400000
600000
800000
1000000
0
50000
100000
150000
200000
250000
0
200000
400000
600000
800000
1000000

61
The growth of interest at autumn is 2 times higher than in winter and 3,8
times higher than in spring.
Main growing segments (by seasons): accessories
0
400000
800000
1200000
1600000
2000000
0
200000
400000
600000
800000
1000000
0
100000
200000
300000
400000
500000
bags peaked caps hats

62
The increase in the segment falls in winter and spring, when interest is 4
times higher than in the autumn.
Main growing segments (by seasons): underwear
0
20000
40000
60000
80000
100000
120000
0
50000
100000
150000
200000
250000
300000
350000
400000
450000
0
200000
400000
600000
800000
1000000
swimsuits bras swim briefs

63
Seasonal Popularity of Destinations
Clothing Shoes Accessories Underwear
Autumn Winter Spring Summer
jackets dresses swimsuits shirts
coats bags sneakers swim briefs
down jackets t-shirts boots shorts
caps swimsuits shoes sandals
jumpsuits shirts bags sandals
high shoes shoes plimsolls
boots underwear peeps
scarves skirts shorts
dresses suits jeans
felt boots felt boots sundresses
uggs high shoes peaked caps
sweaters shorts t-shirts
sweatshirts sundresses wind jackets
sneakers bras pants
ankle boots briefs skirts

Regional user interest in
segment

65
Regional popularity: clothes
TOP 20 cities with the biggest number of queries for buying clothes
Regionalafﬁnity

Thenumberofquery(permonth)

The most regional popularity is observed in the capital cities of Russia
and CIS and also in a part of the cities of Ukraine.
0%
20%
40%
60%
80%
100%
120%
140%
160%
180%
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%

66
Regional popularity: shoes
TOP 20 cities with the biggest number of queries for shoes
Regionalafﬁnity


High regional popularity is observed in the cities of the CIS, especially in
Ukraine.
0%
20%
40%
60%
80%
100%
120%
140%
160%
180%
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%

67
Regional popularity: accessories
TOP 20 cities with the biggest number of queries for accessories of online
retailers of clothing and shoes

Regionalafﬁnity

0%
20%
40%
60%
80%
100%
120%
140%
160%
180%
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%

68
Regional popularity: underwear
In the segment of underwear the greatest interest and regional
popularity falls on Moscow.
TOP 20 cities with the biggest number of queries for underwear

Regionalafﬁnity

0%
20%
40%
60%
80%
100%
120%
140%
160%
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%

69
Regions vs. Capitals: Clothing
Share by type of clothingMoscow, Saint Petersburg
and region
Russ.Fed.: regions
19%
16%
13%
10%
8%
7%
6%
4%
17%
dresses
jackets
suits
coats
down jackets
jeans
t-shirts
skirts
other
26%
15%
11%
7%
7%
7%
6%
5%
18%
dresses
suits
jackets
coats
skirts
jeans
t-shirts
down jackets
other
57% 52% 51% 48% 47% 44% 43% 43% 43% 43% 42% 41% 40% 39% 34% 32% 31% 29%
41%
43% 48% 49% 52% 53% 56% 57% 57% 57% 57% 58% 59% 60% 61% 66% 68% 69% 71%
59%
0%
20%
40%
60%
80%
100%
Moscow, Saint Petersburg and region Russ.Fed.: regions

70
84% 91% 87% 87% 87% 87% 85% 85% 85% 84% 84% 84% 83% 83% 83% 82% 82% 79% 79%
16% 9% 13% 13% 13% 13% 15% 15% 15% 16% 16% 16% 17% 17% 17% 18% 18% 21% 21%
0%
20%
40%
60%
80%
100%
Russia CIS
Russia vs. CIS: Clothing
Share by type of clothing
Russia CIS
23%
14%
13%
8%
7%
6%
6%6%
17%
dresses
suits
jackets
coats
jeans
down jackets
t-shirts
skirts
other
25%
14%
12%
7%
7%
6%
6%
5%
17%
dresses
suits
jackets
jeans
skirts
coats

71
46%
66% 63% 62% 57% 56% 53% 52% 52% 49% 48% 46% 45% 45% 44% 42% 41%
54%
34% 37% 38% 43% 44% 47% 48% 48% 51% 52% 54% 55% 55% 56% 58% 59%
0%
20%
40%
60%
80%
100%
Regions vs. Capitals: Shoes
Share by type of shoesMoscow, Saint Petersburg
and region Russ.Fed.: regions
26%
18%
15%
13%
7%
5%
4%
3%
9%
boots
sneakers
shoes
high shoes
plimsolls
felt boots
uggs
peeps
27%
20%
18%
10%
6%
5%
3%
8% boots
sneakers
shoes
high shoes
plimsolls
felt boots
peeps

72
83% 91% 91% 90% 87% 86% 85% 84% 84% 84% 84% 84% 81% 81% 81% 80% 75%
17% 9% 9% 10% 13% 14% 15% 16% 16% 16% 16% 16% 19% 19% 19% 20% 25%
0%
20%
40%
60%
80%
100%
Russia CIS
Russia vs. CIS: Shoes
Share by type of shoes
Russia CIS
26%
19%
17%
11%
7%
5%
4% 8%
boots
sneakers
shoes
high shoes
plimsolls
felt boots
uggs
24.10%
21.61%
19.51%
10.04%
5.88%
5.59%
7.95%
boots
sneakers
shoes
high shoes
plimsolls
peeps
uggs
pumps

73
48%
65% 65% 62% 61% 56% 56% 53% 50%
37% 35% 33%
52%
35% 35% 38% 39% 44% 44% 47% 50%
63% 65% 67%
0%
20%
40%
60%
80%
100%
Regions vs. Capitals: Accessories
Share by type of accessoriesMoscow, Saint Petersburg
and region Russia: regions
70%
13%
4%
4%
3%
bags
caps
peaked caps
scarves
purses
gloves
belts
hats
other
57%22%
8%
7%
2%
1%
bags
caps
scarves
peaked caps
purses
gloves
belts
hats

74
84% 90% 87% 86% 86% 85% 85% 83% 83% 81% 81% 81%
16% 10% 13% 14% 14% 15% 15% 17% 17% 19% 19% 19%
0%
20%
40%
60%
80%
100%
Russia CIS
Russia vs. CIS: Accessories
Share by type of accessories
Russia CIS
64%
17%
6%
6%
2%
2%
bags
caps
scarves
peaked caps
purses
gloves
belts
hats
60%19%
7%
7%
3% 1%
bags
caps
scarves
peaked caps
purses
gloves
belts
hats

Thank you!
Preston Carey
Business Development Director
preston.carey@yandex.ru

Yandex- Fashion and Clothing Industry Update

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