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 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 Query distribution by segments amount of Yandex queries within the category
0.7% 5% 0.6%
0.5% 10%
0.4% 61%
0.3%
0.2% 24% 0.1%
0.0% Clothing Shoes Accessories Underwear
Queries on clothes are the most popular in the category. They made up more than 60% of all category queries for last 12 months. 4
Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013 Category Dynamics In 2013 user interest in clothing and shoe shopping went up by 23%. (based on statistics from January to September).
40,000,000 35,000,000 +23% 30,000,000
25,000,000
20,000,000
15,000,000 271,560,805 221,538,124 10,000,000
5,000,000
0 1 2
5
Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013 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%. 2013 2014 50,000,000
45,000,000 +14%
40,000,000
35,000,000
30,000,000 25,000,000 438,802, 384,609, 20,000,000 224 15,000,000 233
10,000,000
5,000,000
0
Jul 1 Jul 2Jul Oct Oct Oct Oct Apr Apr Apr Jun Jun Jun Mar Mar Mar Mar Feb Feb Feb Feb Dec Dec Dec Dec Sep Sep Sep Aug Aug Aug Nov Nov Nov Nov May May May 2011 2011 2012 2013 2014 2015 6
Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013 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)
4,500,000 4,000,000 +58% 3,500,000
3,000,000
2,500,000
2,000,000 25,591,477 1,500,000
1,000,000 16,245,474
500,000
0 1 2
7
Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013 Query Dynamics within Category
User interest in clothes and shoes experience more significant seasonal changes than accessories or underwear.
Clothing Shoes Accessories Underwear
30000000
25000000
20000000
15000000
10000000
5000000
0
8
Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013 Category Dynamics Forecast (Clothing)
35,000,000
30,000,000 +15%
25,000,000
20,000,000 268,096, 15,000,000 233,589, 108 10,000,000 369
5,000,000
0 1 2 Jul Jul Jul Oct Oct Oct Oct Apr Apr Apr Jun Jun Jun Mar Mar Mar Mar Feb Feb Feb Feb Aug Sep Aug Sep Aug Sep Dec Dec Dec Dec Nov Nov Nov Nov May May May 2011 2011 2012 2013 2014 2015 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 9 14%). Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘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
100000000 +49%
90000000 -10% 60000000 +4% +46% 80000000
-4% -15% 50000000 +54% 70000000 -19% +1% 60000000 40000000 -16% +9% 50000000 -15% 30000000 40000000 +54% 30000000 +11% 20000000 -2% 20000000 -19% 10000000
Impressionsbyquarters 10000000
0 0 Russia CIS Moscow, St.Petersburg and Russian region (except reg. Moscow and Saint- 4 q. 2012 1 q. 2013 2 q. 2013 3 q. 2013 Petersburg)
4 q. 2012 1 q. 2013 2 q. 2013 3 q. 2013 10
Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013 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.
200%
180%
160%
140% Russia
120%
100% CIS
80% Russia: regions 60% (excl. Moscow and 40% St.Petersburg)
20%
0%
* (compared to 2012) 11
Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013 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.
100%
90%
80% 45% 44% 43% 43% 45% 43% 42% 42% 70%
60%
50% Moscow, St.Pete and reg. 40%
30% 55% 56% 57% 57% 55% 57% 58% 58% RF (excl. Moscow and 20% St.Pete) 10%
0%
12
Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013 Regional Popularity
Ural – 6% of queries North-West – 10% of queries Reg. popularity – 85% Far East – 1% of queries – 7% of queries Saint-Petersburg Reg. popularity – 77% Reg. popularity – 108%, 122% Siberia – 6% of queries, Reg. Central district – 43% of queries popularity – 77%; Moscow – 35% of queries, Reg. popularity – 135%, 155%
South – 4% of queries Volga reg. – 12% of queries Reg. popularity – 79% Reg. popularity – 81% CIS – 18% of queries, Reg. popularity – 93%
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
13 Russian regions it is less than 85%.
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 Online Fashion Retailers Dynamics
User interest Dynamics Online retailers share, (based on retailers brands statistics) September 2013
Oct 2011 - Sep 2012 Oct 2012 - Sep 2013 20000000
16000000 91% -3% 148% 12000000 43% 8000000 57% 4000000
0 Russian online stores International Megamarkets, cross- borders and trading Russian platforms International
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. 15
Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013 Online Retailers, Cross-Borders and Trading Platforms Brand Dynamics
1000000
900000
800000
700000 Aliexpress
600000 eBay Ozon 500000 Bonprix Wildberries 400000 Lamoda
300000 Otto Sapato 200000 Quelle
100000
0
16
Данные wordstat.yandex.ru, январь ‘2012 – сентябрь ‘2013 Online Fashion Retailers Popularity (based on data for the last 12 months)
7000000
6000000 Russian online retailers
International online retailers 5000000
4000000
3000000
2000000
1000000
0
17
Данные wordstat.yandex.ru, октябрь ‘2012 – сентябрь ‘2013 Variation in User Interest in Russian Online Retailers
2012 2013 5000000 500% 313% 57% 450%
4000000 400%
350%
3000000 300%
250% 28% 2000000 200%
23% 150%
1000000 35% 100%
45% 50% 4% 451% 135%
0 0%
18
Данные wordstat.yandex.ru, январь ‘2012 – сентябрь ‘2013 Brand Dynamics of Russian Online Retailers
800000
700000
600000
Wildberries 500000 Lamoda Sapato 400000 Kupivip Butik
300000 Boutique Z95 Brand-in-trend 200000 Trendsbrands
100000
0
19
Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013 Variation in User Interest in International Online Retailers
2012 2013 6000000 -24% 30%
5000000 20%
4000000 10%
3000000 7% 0%
-6% 2000000 -10%
-9% 23% 1000000 4% -20% 16% 25% -22% 8% -22%
0 -30%
20
Данные wordstat.yandex.ru, январь ‘2012 – сентябрь ‘2013 Brand Dynamics of International Online Retailers
1000000
900000
800000
Bonprix 700000 Otto
600000 Quelle La Redoute 500000 Asos Witt 400000 Yoox
300000 Klingel 3suisses 200000 Wenz Zappos 100000
0
21
Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013 Cross-borders and Online Trading Platforms: User Interest Dynamics
2500000 Brand Interest Dynamics eBay 2000000 Aliexpress Ozon 1500000 Taobao Deal Extreme 1000000 Shopotam Vivatao 500000 Club-sale Lightinthebox 0 Kupinatao Luxtao Kitmall
25000 Brand Interest Dynamics based on enclosed queries related to the category items
20000
15000 Taobao Aliexpress 10000 eBay 5000 Ozon
0
22
Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013 Cross-borders and Online Trading Platforms: User Interest Dynamics
Brand Queries 50% 16000000 1000% 913% 2012 2013 800% 12000000 -5% 600% 8000000 400% 52% 200% 4000000 New players 0% -19% 17% -47% 0 116% 86% 260% -200%
Brand Queries related the Category
160000 73% 5000% User interest in cross-border trading 4500% 4000% platforms is growing rapidly. Their growth 120000 3500% rate is more than Russian retailers’ one for 3000% both groups of queries: brand or category 80000 2500% 4675% 170% 2000% related (ex. “Taobao clothes”). 1500% 40000 The main threat comes from TaoBao and 20% 1000% 500% Aliexpress as potential competitors in the 0 0% category. Taobao Aliexpress eBay Ozon
23
Данные wordstat.yandex.ru, январь ‘2012 – сентябрь ‘2013 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 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).
+14% 8,000,000
+30% 7,000,000
6,000,000 +34%
5,000,000 +24% Women's clothes
4,000,000 Men's clothes
Kid's clothes 3,000,000 Maternity clothes
2,000,000
Growth 1,000,000 january-september 2013/ january-september 2012
0
26
Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013 Interest distribution by types of clothing (based on statistics for the last 12 months)
dress - 25,2% 18% 25% suits jackets - 12,2% 3% coats - 6,4% 3% t-shirts - 5% skirts - 4,4% 4% down jackets - 4% 4% 15% jumpsuits - 3,5% 5% shirts - 3,3% 5% jeans - 3,1% other 18,1% 6% 12%
TOP-3 the most popular search queries are for dresses, costumes and jackets which make up more than 50%. 27
Данные wordstat.yandex.ru, октябрь ‘2012 – сентябрь ‘2013 Interest distribution by types of clothing
Women’s clothing Men’s clothing
dresses - 60,1% men's jackets - 22,7% skirts - 8,8% men's suits - 19,8% 6% womens jackets - 4,8% 6% men's shirts - 9,8% sarafans - 3,3% men's jeans - 7,4% blouses - 2,8% 23% 3% 4% men's coat - 6,4% 3% women's coats - 2,8% 5% men's trousers - 5,8% 3% women's suits - 2,7% 5% men's down jackets - 5,3% 5% 60% women's down jackets - 2,6% men's jackets - 4,8% 6% tunics - 1,9% 20% 9% men's t-shirts - 4% women's pants - 1,4% 6% sports suits - 3% women's jeans - 1,3% 7% 10% men's shorts - 2,8% women's sports suits - 0,9% men's sweaters - 1,9% other - 6,6% other - 6,4%
Kid’s clothing rompers - 45,5% children's suits - 19,8% girl's dresses - 14,1% children's jackets - 6,3% 6% 45% children's down jackets - 2,5% children's coats - 2,4%
14% 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% 28 20% other - 2,5% Данные wordstat.yandex.ru, октябрь ‘2012 – сентябрь ‘2013 Outerwear query dynamics
Demi-season clothes Winter clothes
jackets coats down jackets jumpsuits
2500000 1400000
1200000 2000000 1000000
1500000 800000
1000000 600000
400000 500000 200000
0 0
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. 29
Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013 Types of clothing query dynamics
Spring-summer seasonality Spring seasonality
t-shirts skirts suits jeans 800000 500000 700000 600000 400000 500000 300000 400000 300000 200000 200000 100000 100000 0 0
Holiday seasonality There are several models of seasonality: • Types of clothes, popular in spring and men's shirts autumn (peaks in October, March); 120000 • Types of clothes, popular in winter (October- 100000 80000 November); 60000 • Clothes with growing interest in the spring- 40000 summer; 20000 • Clothes with growing interest in the spring 0 only (the peak in March-April); • Queries with clear «festive» seasonality
30 (growth before the New year and the
February 23d holidaysWordstat.yandex.ru); statistics, Oct ‘2011 – Sep ‘2013 Dresses query dynamics
Holiday seasonality Spring-summer seasonality
evening dresses beautiful dresses black dresses buy dress long dresses white dresses 700000 200000 180000 600000 160000 500000 140000 400000 120000 100000 300000 80000 200000 60000 40000 100000 20000 0 0
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 31
inlaid queries on photos. Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013 Popular queries of kinds of dresses
The number of impressions per month
* Wedding dresses Evening dresses White dresses Long dresses Black dresses Dresses for prom Dresses for thick Short dresses Dresses with sleeves Red dresses Floor-length dress Fancy dresses Party dresses Knitted dress Cocktail dresses Large size dresses Blue dress Greek dresses Lace dresses Pencil dresses
0 100000 200000 300000 400000 500000 600000 700000 800000 900000 32 * interest to wedding dresses was not taken into account (in the earlier slides on trends in clothing) Shoes
Ø User interest dynamics in shoes for men, women and kids Ø Interest distribution by types of shoes Ø Interest seasonality 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.
women's shoes men's shoes kid's shoes 700000
600000
500000
400000
300000
200000
100000
0
34
Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013 Interest distribution by kinds of shoes (based on statistics for the last 12 months)
2% 4% 2% boots - 26,1% 3% sneakers - 19,4% 4% 26% shoes - 16,6% 5% high shoes - 11,1% plimsolls - 6,7% 7% felt boots - 4,6% uggs - 3,8% sandals - 3,4% 11% shoe boots - 2,3% 19% pumps - 2% other - 3,9% 17%
TOP-3 the most popular search queries are for boots, sneakers and shoes, which make up more than 55%. 35
Данные wordstat.yandex.ru, октябрь ‘2012 – сентябрь ‘2013 Types of shoes query dynamics
Demi-season seasonality Summer seasonality
boots shoe boots sandals pumps loafers 300000 1000000 250000 800000 200000 600000 150000 400000 100000
200000 50000
0 0
Winter seasonality Spring seasonality
high shoes felt boots uggs sneakers shoes plimsolls
600000 1000000
500000 800000 400000 600000 300000 400000 200000
100000 200000
0 0
36
Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013 Accessories
Ø Interest distribution by types of accessories Ø Interest seasonality Distribution of queries by kinds of accessories (based on statistics for the last 12 months)
2% bags - 63,1% 3% 6% caps - 17,6% scarves - 6,2% 6% peaked caps - 5,8%
purses - 2,6%
gloves - 1,6%
18% belts - 1,3%
63% hats - 1%
shawls - 0,5%
berets - 0,3%
snoods - 0,1%
TOP-3 the most popular queries are for bags, hats and scarves, which make up more than 85%. 38
Данные wordstat.yandex.ru, октябрь ‘2012 – сентябрь ‘2013 Popular search queries of kinds of bags
The number of impressions per month
Women's bags Men's bags Leather bags Travel bags Laptop bags Sports bags Shoulder bags Bags on wheels Copies of bags Brand bags Bags backpacks Bags for girls Big bags Suede bags Camera bags Bags suitcases Small bags Beach bags Bags for documents
0 20000 40000 60000 80000 100000 120000 140000 160000
39 Types of accessories query dynamics
Winter seasonality Demi-season seasonality
peaked caps hats bags
scarves gloves caps 300000 3000000 450000 1400000
400000 1200000 250000 2500000 350000 1000000 300000 200000 2000000 250000 800000 150000 1500000 200000 600000 150000 100000 1000000 400000 100000 50000 500000 50000 200000 0 0 0 0
16000 berets snoods
12000
8000
4000
0 The query data on bags and hats are displayed on the right (additional) axis. 40
Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013 Holiday seasonality of accessories
User interest dynamics are similar for most popular types of accessories with peaks in the pre-New Year period and February - March.
purses belts shawls 140000
120000
100000
80000
60000
40000
20000
0
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
41 main growth is 30 days before the holidays).
Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013 Underwear
Ø Interest seasonality Ø Interest distribution by types of underwear 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).
Generic queries Underwear Swimsuits 2500000
2000000
1500000
1000000
500000
0
43
Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013 Interest distribution by types of underwear (based on statistics for the last 12 months)
swimsuits - 41,4% 8% underwear - 19,5% tights and socks - 17,1% 11% bras - 10,7% 41% briefs - 7,6% bodysuits - 1,5% swim briefs - 1,3% 17% corsets - 0,5% corsages - 0,3% modeling lingerie - 0,1%
20% negligee - 0,04%
TOP-3 the most popular search queries are for swimwear, lingerie, tights and socks which make up more than 78%. 44
Данные wordstat.yandex.ru, октябрь ‘2012 – сентябрь ‘2013 Types of underwear query dynamics
Interest on the underwear reaches its maximum in February-March, on the swimsuits – right before the summer months.
underwear tights and socks bras briefs swimsuits swim briefs bodysuits 1400000 60000 450000
400000 1200000 50000 data by swim briefs Query 350000 1000000 40000 300000 800000 250000 30000 200000 600000
Queryswimsuits by data 20000 150000 400000
100000 10000 200000 50000 0 0 0
45
Данные wordstat.yandex.ru, октябрь ‘2012 – сентябрь ‘2013 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 Brand dynamics Dynamics of brand query corresponds the generic queries in the category. However, the interest towards luxury brands is higher in pre-new year period. TOP-40 mass brands TOP-40 luxury brands Generic category queries 7000000 50000000
6000000 +15,0% 40000000
5000000
30000000 4000000
3000000 +13,9% 20000000 2000000
10000000 1000000
0 0 2011-10 2011-12 2012-02 2012-04 2012-06 2012-08 2012-10 2012-12 2013-02 2013-04 2013-06 2013-08
47 The generic queries are displayed on the right (additional) axis. Данные wordstat.yandex.ru, октябрь ‘2012 – сентябрь ‘2013, ТОП-40 премиум и массовых брендов Brand interest distribution
Luxury vs. mass brands TOP-5 brands
TOP-40 mass brands Adidas Nike Incity TOP-40 luxury brands Reebok Ecco Other
15%
33% 12%
3% 64% 67% 3% 3%
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.
48
Данные wordstat.yandex.ru, октябрь ‘2012 – сентябрь ‘2013 Geography of brand interest
40% 200%
Regional Affinity
30% 150%
20% 100%
10% 50% Share of queries of Share
0% 0% Luxurybrands
40% 200%
Regional Affinity 30% 150%
20% 100%
10% 50% Share of queries of Share
Massbrands 0% 0%
49
Данные wordstat.yandex.ru, октябрь ‘2013 Luxury brands TOP-20 popular luxury brands (based on statistics for the last 12 months)
Impressions
2500000
2000000
1500000
1000000
500000
0
51
Данные wordstat.yandex.ru, октябрь ‘2012 – сентябрь ‘2013 Query dynamics of TOP-10 luxury brands
250000
200000 Lacoste Gucci
150000 Armani Givenchy Calvin Klein
100000 D&G Hermes Burberry 50000 Diesel Louis Vuitton
0
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.
52
Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013 Change of interest to luxury brands
окт 2011 - сен 2012 окт 2012 - сен 2013 2500000 50%
12% 40% 2000000 14% 14% 21% -3% 30% 42% 9% 1500000 2% -8% 20% 20%
10% 1000000
0%
500000
-10%
0 -20% Lacoste Gucci Armani Givenchy Calvin D&G Hermes Burberry Diesel Louis Klein Vuitton
53
Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013 Mass-segment TOP-20 popular mass brands (based on statistics for the last 12 months)
16000000
14000000
12000000
10000000
8000000
6000000
4000000
2000000
0
55
Данные wordstat.yandex.ru, октябрь ‘2012 – сентябрь ‘2013 Query dynamics of TOP-10 mass brands
1800000
1600000
1400000 Adidas
1200000 Nike Incity 1000000 Reebok Ecco 800000 Mango 600000 oodji Puma 400000 Bershka
200000 Columbia
0
Undisputed leaders over the last 2 years are Adidas and Nike. 3rd place, depending on the month, divided between brands Incity, Adidas and Ecco.
56
Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013 Change of interest to mass brands
Oct 2011 - Sep 2012 Oct 2012 - Sep 2013 16000000 -1%
14000000
12000000 25%
10000000
8000000
6000000
4000000 28% 19% 45% 18% 36% 15% 13% 25% 2000000
0
57
Wordstat.yandex.ru statistics, Oct ‘2011 – Sep ‘2013 Interest seasonality in segment 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
5000000 2500000
4000000 2000000
3000000 1500000
2000000 1000000
1000000 500000
0 0
Growth of interest in spring
350000 300000 250000 200000 150000 100000 50000 0
59
Данные wordstat.yandex.ru, июль ‘2012 – сентябрь ‘2013 Main growing segments (by seasons): shoes
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. Growth of interest in autumn Growth of interest in winter
1000000 250000
800000 200000
600000 150000
400000 100000
200000 50000
0 0
Growth of interest in spring
1000000 800000 600000 400000 200000 0
60
Данные wordstat.yandex.ru, июль ‘2012 – сентябрь ‘2013 Main growing segments (by seasons): accessories
The growth of interest at autumn is 2 times higher than in winter and 3,8 times higher than in spring.
Growth of interest in autumn Growth of interest in winter
2000000 1000000
1600000 800000
1200000 600000
800000 400000 400000 200000 0 0
Growth of interest in spring
500000
400000
300000
200000
100000
0 bags peaked caps hats 61
Данные wordstat.yandex.ru, июль ‘2012 – сентябрь ‘2013 Main growing segments (by seasons): underwear
The increase in the segment falls in winter and spring, when interest is 4 times higher than in the autumn.
Growth of interest in autumn Growth of interest in winter
450000 120000 400000 350000 100000 300000 80000 250000 60000 200000 150000 40000 100000 20000 50000 0 0
Growth of interest in spring
1000000
800000
600000
400000
200000
0 swimsuits bras swim briefs 62
Данные wordstat.yandex.ru, июль ‘2012 – сентябрь ‘2013 Seasonal Popularity of Destinations
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
Clothing Shoes Accessories Underwear 63
Данные wordstat.yandex.ru, июль ‘2012 – сентябрь ‘2013 Regional user interest in segment Regional popularity: clothes
TOP 20 cities with the biggest number of queries for buying clothes
35.0% 180%
160% 30.0% 140% 25.0% 120% Regional affinity
20.0% 100%
15.0% 80%
60% 10.0% 40% 5.0% 20%
0.0% 0% The number of query of number The (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. 65
Данные wordstat.yandex.ru, октябрь ‘2013 Regional popularity: shoes
TOP 20 cities with the biggest number of queries for shoes
30.0% 180%
160% 25.0% 140%
20.0% 120% Regional affinity 100% 15.0% 80%
10.0% 60%
40% 5.0% 20%
0.0% 0%
The number of query of number The (permonth)
High regional popularity is observed in the cities of the CIS, especially in Ukraine. 66
Данные wordstat.yandex.ru, октябрь ‘2013 Regional popularity: accessories
TOP 20 cities with the biggest number of queries for accessories of online retailers of clothing and shoes
35.0% 180%
160% 30.0%
140% Regional affinity 25.0% 120%
20.0% 100%
15.0% 80%
60% 10.0%
40%
5.0% 20%
The number of query of number The (permonth) 0.0% 0%
67
Данные wordstat.yandex.ru, октябрь ‘2013 Regional popularity: underwear
TOP 20 cities with the biggest number of queries for underwear
35.0% 160%
30.0% 140% Regional affinity 120% 25.0% 100% 20.0% 80% 15.0% 60% 10.0% 40%
5.0% 20%
0.0% 0% The number of query of number The (permonth)
In the segment of underwear the greatest interest and regional popularity falls on Moscow.
68
Данные wordstat.yandex.ru, октябрь ‘2013 Regions vs. Capitals: Clothing
Moscow, Saint Petersburg Share by type of clothing Russ.Fed.: regions and region
dresses dresses 16% jackets 15% suits 26% suits jackets 19% 13% coats 11% coats down jackets skirts 10% jeans 7% jeans 17% 18% t-shirts 8% t-shirts 7% 7% down jackets 4% 7% skirts 5% 6% 6% other other
100%
80% 43% 48% 49% 52% 53% 56% 57% 57% 57% 57% 58% 59% 60% 59% 61% 66% 68% 69% 60% 71%
40% 57% 52% 51% 48% 20% 47% 44% 43% 43% 43% 43% 42% 41% 40% 39% 41% 34% 32% 31% 29% 0%
69 Moscow, Saint Petersburg and region Russ.Fed.: regions
Данные wordstat.yandex.ru, октябрь ‘2012 – сентябрь ‘2013 Russia vs. CIS: Clothing
Share by type of clothing Russia CIS
dresses dresses 14% suits 23% jackets 14% suits 13% coats 25% jackets jeans 12% 8% down jackets 7% 17% 17% jeans 7% t-shirts 6% 6% 6% skirts 6% 7% skirts other 5% 6% coats
100% 9% 13% 16% 13% 13% 13% 15% 15% 15% 16% 16% 16% 17% 17% 17% 18% 18% 21% 21% 80%
60% 91% 87% 40% 84% 87% 87% 87% 85% 85% 85% 84% 84% 84% 83% 83% 83% 82% 82% 79% 79%
20%
0%
70 Russia CIS Данные wordstat.yandex.ru, октябрь ‘2012 – сентябрь ‘2013 Regions vs. Capitals: Shoes
Moscow, Saint Petersburg Share by type of shoes and region Russ.Fed.: regions
3% 3% boots 5% 8% boots 4% 9% sneakers sneakers 27% 26% 5% shoes shoes high shoes 6% 7% high shoes 10% plimsolls plimsolls 13% 18% felt boots 20% 18% felt boots 15% uggs peeps peeps
100%
34% 37% 38% 80% 43% 44% 47% 48% 48% 54% 51% 52% 54% 55% 55% 56% 58% 59% 60%
40% 66% 63% 62% 57% 56% 53% 52% 52% 20% 46% 49% 48% 46% 45% 45% 44% 42% 41%
0%
71 Moscow, Saint Petersburg and region Russ.Fed.: regions Russia vs. CIS: Shoes
Share by type of shoes Russia CIS
7.95% boots boots 4% 8% sneakers 5.59% sneakers 5% 26% shoes shoes 24.10% 5.88% 7% high shoes high shoes 11% plimsolls 19% plimsolls 10.04% 21.61% peeps 17% felt boots 19.51% uggs uggs pumps
100% 9% 9% 10% 13% 14% 15% 16% 16% 16% 16% 16% 17% 19% 19% 19% 20% 25% 80%
60%
91% 91% 90% 87% 86% 85% 84% 84% 84% 84% 84% 40% 83% 81% 81% 81% 80% 75%
20%
0%
72 Russia CIS Regions vs. Capitals: Accessories
Moscow, Saint Petersburg Share by type of accessories and region Russia: regions 3% bags 2% 1% 4% 7% bags 4% caps caps peaked caps 8% scarves scarves 13% peaked caps purses 22% 57% purses gloves 70% gloves belts belts hats hats other
100%
80% 35% 35% 38% 39% 52% 44% 44% 47% 50% 63% 65% 67% 60%
40% 65% 65% 62% 61% 48% 56% 56% 53% 50% 20% 37% 35% 33% 0%
Moscow, Saint Petersburg and region Russ.Fed.: regions 73 Russia vs. CIS: Accessories
Share by type of accessories Russia CIS
2% 2% 3% 1% 6% bags bags 6% caps 7% caps scarves 7% scarves peaked caps peaked caps 17% purses 19% purses 64% 60% gloves gloves belts belts hats hats
100% 16% 10% 13% 14% 14% 15% 15% 17% 17% 19% 19% 19% 80%
60% 90% 40% 84% 87% 86% 86% 85% 85% 83% 83% 81% 81% 81%
20%
0%
74 Russia CIS Preston Carey Business Development Director [email protected]
Thank you!