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

N

ov

Dec

20

12

Feb

Mar

A

pr

May

Ju

n Ju

l A

ug

Sep

O

ct

Nov

D

ec

2013

Fe

b M

ar

Apr

M

ay

Jun

Jul

Aug

S

ep

Oct

N

ov

Dec

20

14

Feb

Mar

A

pr

May

Ju

n Ju

l A

ug

Sep

O

ct

Nov

D

ec

2015

Fe

b M

ar

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


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

N

ov

Dec

20

12

Feb

Mar

A

pr

May

Ju

n Ju

l A

ug

Sep

O

ct

Nov

D

ec

2013

Fe

b M

ar

Apr

M

ay

Jun

Jul

Aug

S

ep

Oct

N

ov

Dec

20

14

Feb

Mar

A

pr

May

Ju

n Ju

l A

ug

Sep

O

ct

Nov

D

ec

2015

Fe

b M

ar

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%

Impr

essi

ons

by q

uarte

rs

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, Reg. popularity – 93%

South – 4% of queries Reg. popularity – 79%

Central district – 43% of queries Moscow – 35% of queries, Reg. popularity – 135%, 155%

Ural – 6% of queries Reg. popularity – 85%

Siberia – 6% of queries, Reg. popularity – 77%;

Far East – 1% of queries Reg. popularity – 77%

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 Данные wordstat.yandex.ru, январь ‘2012 – сентябрь ‘2013

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

Данные wordstat.yandex.ru, январь ‘2012 – сентябрь ‘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

Данные wordstat.yandex.ru, январь ‘2012 – сентябрь ‘2013

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 New Year 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.


Query data by sw

im briefs

Que

ry d

ata

by s

wim

suits

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 Lu

xury

bra

nds

Mas

s br

ands


Regional A

ffinity

Shar

e of

que

ries

Regional A

ffinity

Shar

e of

que

ries

Luxury brands

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

Mass-segment

55

TOP-20 popular mass brands (based on statistics for the last 12 months)


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



Autumn Winter Spring Summerjackets 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

Regional affinity

The

num

ber

of q

uery

(pe

r m

onth

)


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

Regional affinity

The

num

ber

of q

uery

(pe

r m

onth

)


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


The

num

ber

of q

uery

(pe

r m

onth

) R

egional affinity

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

The

num

ber

of q

uery

(pe

r m

onth

) R

egional affinity

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 clothing Moscow, 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 shoes Moscow, 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 accessories Moscow, 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

[email protected]