*

1. 1
OLIVER WYMAN IMPACT 2016
STRATEGY OF
LA VITA`S
DEVELOPMENT
by team
Might & Magic
Anaida Arakelyan
George Atomyan
Gagik Galstian
Olga Kazhaeva

2. 2
• Not effective management
• The mixed format is not
effective & unprofitable
Executive summary
We have identified the
following problems:
Commercial
Store Operations
Marketing
Revenue grows more
slowly than CoGS and
costs
Administrative
High fixed costs:
• labor
• rent
• Target audience narrows
• current target audience shift
to the goods-substitutes
• Traffic decreases
We offer the following measures for these
problems solution
1. Renegotiate with existing suppliers and work with small
suppliers to guarantee competitive CoGS and product
prices
2. Invest 10% of Sales in low prices (Keep commercial
margin at a 25% level)
3. Localize assortment range to meet consumer needs
Mr. CEO, we have analyzed the situation in your company in the market and
offer you our cooperation
1. Optimize and standardize number of personnel per
store
2. Continue employee training program
3. Add a small kitchen (25 m2) in light type stores
1. Promote the new company’s strategy of lower prices and
shift in assortment to improve value perception
2. Start two own-label product ranges:
- Low cost label: essential goods at low price
- Premium label: high margin products
3. Open a products delivery service
1. More competent person on the position of Head
Purchasing Department
2. Renegotiate the rent payments of mixed type stores to
the market level
3. Expand the light and small type store formats after
optimization process
4. Invest in opening central kitchen to provide own
production to stores
5. Add a small kitchen (25 m2) in light type stores
1. CoGS in 2016 +0,7%
2. Average check -5%
3. Sales in 2016 +3%
1. Traffic +8%
2. Improvement of customer
perception* by 2016
1. CoGS in 2016 +0,7%
2. Average check -5%
1. Rent payments of mixed
size store -20%
2. Own labor product share in
2018 – 12%
3. EBITDA margin in 2026 –
5,3%
*see CPM on Slide 9
Results of the strategy

3. 3
Current business
situation at La Vita

4. 4
Difficult macroeconomic situation in Russia shortens middle class and traffic
decreases in stores with low value perception
Comparable analysis of Exhibit 4 and 13; Source: Rosstat, Nielsen, Appendix 7, Team analysis
Target audience
Real income of the population in % to previous
year in Ekaterinburg and Chelyabinsk fell
The number of Russians, who searched for the lowest prices
in grocery retailers, increased almost 3 times
6,1
11,7
2013 2014
11,3
3,7
Expenditures
Income
+41pp.
22%
2014
63%
2015
The percentage of costumers who
searched for the lowest prices
• Russians became less payable
96
2014
104
-8pp
2013
99
-6pp
2013
105
2014
Ekaterinburg
+13,5%
16 189
14 261
Chelyabinsk
+7,2%
15 927
14 860
Costs on food commodities rose in
Russia faster than in Ekaterinburg
Russia Ekaterinburg
2013 2014 2013 2014
Costs on food commodities per month, RUB
Growth rate of income and expenses of
population sharply decreased in 2014
Growth rate of income and expenses, %
• Decreased the number of
customers who preferred
quality to price
Real income of the population, % to prev. year
• Our target audience reduced
2012 2013 2014 2015
3
0
-3
-6%
6%
Company with high
Company with low
value perception
Traffic declined as we have the lowest value perception
and our target audience reduced
Team analysis of La Vita average traffic growth and value perception*
value perception
Decline

5. 5
All formats show same sales dynamics and EBITDA declines every year, that indicates an overall worsening of company’s operations
-50
-40
-30
-20
-10
0
10
Every format experiencing decline in profitability, which caused by increase in
OpEx across every store type
*For fixed costs has taken labor, rent and other store costs **Component= Growth Rate of Fixed Costs – Growth Rate of Component
Sources; Appendix 1-5
Stores analysis
Average La Vita Sales dynamics by
store types
La Vita EBITDA dynamics by store types
It is vital for the company to slow down the sharping growth rate of OpEx (which exceeds the growth rate of revenue), mostly
driven by rocket growth of CoGS
Large Mixed
2015
1,3%
3,3%
1,6%
1,0%
4,5%
1,0%
-0,1%
2014
0,6%
0,0%
3,0%
2012
0,9%
2013
0,5%
Light Small
2013
3,0%
0,5%
-0,1%
2012
4,5%
1,0%
0,6%
2014
1,6%
1,0%
1,3%
3,3%
2015
0,9%
0,0%
2015
0,5%
2014
0,4%
2,4%
1,4%
0,2%
3,6%
-0,9%
0,8%
0,0%
-0,1%
2013
-0,2%
0,1%
2012
20142013
0,2%
0,4%
2012
3,3%
0,4%
1,4%
3,4%
0,4%
1,1%
-0,1%
2015
1,1%
0,6%
0,2%
Variable OpExFixed
2,0%
2014 2015
3,7%
5,4%
2013
6,1%
2012
The average sales in Large,
Mixed, Light and Small are
almost the same
2012 2013 2014 2015
Mixed
Light
Small
Large
EBITDA of Mixed
type of store
significantly fell
That indicates that the
problem with profitability is
in the cost structure of the
store types

6. 6
м
Overall worsening of business operations affect mostly large and mixed store
types with heavy operation models, even making mixed type stores unprofitable
*Other income excluded ** in 2015; Sources: Appendix 2,3
Store formats(1/2)
Large Mixed
4,0% 3,3% 3,0% 2,7%
1,8% 2,2% 2,3% 2,2% 2,7%
1,6%
0,7%0,8%0,6%0,6%0,6%
18,4%
2011 2012
18,6%
75,5% 75,5%
75,6%
2013
18,9%
2015E
18,1%
75,7%
18,5%
2014
76,0%
OtherRent Total COGS EBITDA*Labor
2,3% 2,2% 1,9% 2,6% 2,7%
5,4% 5,3% 6,3% 6,3%
-1,3%
6,4%
15,6%
2015E
76,5%
2014
15,5%
0,5%
2012
0,4% -0,4%
76,4%
2011
76,3% 76,4%
-0,8%
15,7%
2013
15,7%
76,3%
15,8%
EBITDA*Rent Total COGSOther Labor
• Despite the highest Revenue per ratio that format shows
lowest EBITDA per ratio in 2015 and would lose money with no
other income
• Business model of the company and the store type cannot support
weight of the rent payments (6,4% ratio against 0,7% in Large type),
which are higher that on market (6 000-10 000 per on market
against 14 000 paid in 2015)
• We recommend renegotiate rent payments or close the stores of this
type
Large Type Store P&L vertical analysis Mixed Type Store P&L vertical analysis
Revenue per EBITDA per Average size
157 300
rub
5 400
rub
14161 200
rub
880
rub
7
• Store EBITDA margin declines from 4% in 2011 to 1,6% in
2015, because of the overall worsening of the company’s
operations
• Overall, the store type can be profitable, if there is no debt
and interest payments related to opening of the store
• Growth of other expenses from 1,8% in 2011 to 2,7% 2015
indicates problem with in store kitchens
Revenue per EBITDA per Number of stores**Average size
1400 1000
Number of stores**

7. 7
м
Light and small type stores show healthier EBITDA ratios and are more fitted
for current market position and after optimization can be used for expansion
*Other income excluded ** in 2015; Sources: Appendix 4,5
Store formats (2/2)
11,3% 10,3% 9,8% 9,8% 8,5%
11,6% 11,9% 12,3% 12,5% 12,8%
2,3%
0,9%
2,6%
75,0%
1,0%
2013
1,1%
2014
74,7%
2,2%
2015E
74,5% 74,6%
1,7%
0,8%
2,2%
74,7%
20122011
0,7%
OtherRent Total COGS EBITDA**Labor
7,8%
6,2% 5,3% 5,3% 4,2%
2,2% 2,3% 2,2% 2,6%1,8%
76,1%
13,7%
0,7%
14,4%
77,8%77,2%
0,9%
77,2%
2011 2014
0,6%
2015E
14,7%14,4%
0,6%
2013
14,2%
2012
76,8%
0,8%
Total COGSOther Labor EBITDA**Rent
• Experimental stores of this type has proven to be good format for
operating in Ekaterinburg and Chelyabinsk
• Small type store has less SKU than Light type store. That effects
in higher bonuses and therefore lower Total CoGS
• This store type also has been affected by worsening of the
company's operation model
• The light store type stores operation model shows
better results than the large and mixed store types, but
shares overall decline in EBITDA margin
• Store EBITDA margin significant fall (from 7,8% to
4,2% in 5 years) mostly caused by CoGS dynamics
(from 76,1% to 77,8% in 5 year)
Light Type Store P&L vertical analysis Small Type Store P&L vertical analysis
Light Small
Revenue per EBITDA per Number of stores**Average sizeRevenue per EBITDA per Number of stores**Average size
157 300
rub
9 300
rub
5161 200
rub
12 000
rub
124750 700

8. 8
Strategy to improve the
situation at La Vita

9. 9
La Vita should optimize business model by increasing value perception and
after that continue expansion of small and light format
Sources: team analysis, OW Primer
Format optimization & Expansion
Light
5,8%
Mixed
0,5%
Large Small
10,2%
3,4%
EBITDA margin
in 2015 by
formats (%)
La Vita’s stores with low complexity operation model are showing good
margins and better suited for further expansion in current situation
Low complexity
models
High complexity
model
OFFERPERCEPTIONHIGHLOW
VALUE PERCEPTION HIGHLOW
Enisey
Pesso
Minutka
TGM
AtfieldsGottit
LaVita
Vyatsky
Supermarkets Hypermarkets
Discounters
In order to beat low price competitors La Vita should keep the
offer perception on the came level and improve offer perception
In Chelyabinsk we recommend not to open new stores of any
format until getting new information about customer perception
To 2020 year in Ekaterinburg will be opened 85 new stores
Situation in Chelyabinsk is affected by many factors:
29
22
19
10
5
2020201920182016 2017
Dynamic of all stores` opening in Ekaterinburg, 2016-2020
We recommend expansion of
light and small type stores,
and concentration on LFL
development of existing large
and mixed type supermarkets
Unexperienced MD
Overall worsening of Company’s Operations
Average check is smaller than in Ekaterinburg and
consumers buy only low margin products

10. 10
Private label production will decrease CoGS and cover wider target audience
with different, but necessary assortment
Source: Nielsen, team analysis
Assortment & Private Label
% of Russians, reduced buying in some categories
Don’t buy
17%
Rarely 20%
Every visit
41%
22%
One time in 2 visits
83% of Russians buy private label
products
Because of decline of incomes, lots of Russians
changed their product preferences
For which categories are you ready to pay
more than mean price?
There are still some categories in which
quality is more important than price
How often do you buy private label’s products?
La Vita should produce 2 types of private label
products for raising traffic and margin
Buy
La vita è facile
•Oil
•Water
•Cereals
Low cost label:
Essential goods
at low price
•Tea
•Canned food
•Juice
La vita è bella •Cheese
•Milk
•Yoghurt
Premium label:
High margin
products
•Pasta
•Bakery
•Cookies
26
26
28
32
37
39
41
Candies
Milk
Eggs
Juice
Meat/Seafood
Cheese
Bakery
La Vita should change the assortment in favor of
discount brands to match customers’ needs
71
56
70
43
47
53
53
Dairy products
Premium alcohol
Cheese
Fresh fruits
Fruit juice
Chips, snacks
Chocolate
Change the
assortment to more
discount brands
Localization of
product range by
paying capacity of
citizens
Assortment`s
optimization in prestige
and bedroom districts,
so as to increase sales
Analysis of target
audience has shown that
it is necessary to add
lower-cost products, so
as not to lose traffic
Consumers
Low
class
Premium
class

11. 11
La Vita should develop delivery service and centralized kitchen system for
adapting to changing buying habits of target audience
*We found the analogic shops in Ekb.: shop.monetka.ru, da-mart.ru, elisey-mag.ru/culinary; Source: team analysis
Marketing
Residents of Ekaterinburg have specific buying habits, which
should be took into account to drive our traffic & sales
42%
Buy a product if
price is reduced
by promo-action
26%
Buy a product if it is
sold by promo-action
“2 at the price of 1”
61%
Ready to pay more if
company cares about
environment and ecology
Ratio of products
delivery services
to population of
Ekaterinburg is
low (1/130 000)
Market of food delivery in Ekaterinburg is not saturated, that is
why we should open our delivery service to catch competitors
Our competitors have
this services*
Vyatsky
Enisey
Pesso
Orders per day: 72
Forecasted profit in 2016: 2 932 927,08 ₽
We recommend to change price positioning of La Vita and shift
the focus on promo-actions and healthy products
Factory-kitchen
Centralized factory kitchen will cook food for light and small
type stores, where light kitchens will increase traffic
• Salads
• Bakery
(private label)
• Semi-finished
products
Traffic will
increase by 1%
Optimization of stores will
cost 200 000 ₽ per store
Increase of value
perception by price
lowering
Improve the quality
of service
Support the quality
of products and add
ecological series of
products
La Vita becomes
“Agent of
consumers”
• broaden the target
audience
• increase traffic
Average check: 1000 ₽
Number of couriers: 7
Transportation
Production: • Build mini-kitchens in the
Light store formats
(about 20 m2 )
• Cook bakery
• Show salads and
semi-finished products
Store

12. 12
Revealed operational problems have the solutions, which will improve La
Vita’s CoGS and fixed costs problems
Commercial & Management
Resigning contracts
on favorable terms
with suppliers will
decrease
purchasing prices
• La Vita’s purchasing prices are
higher than some final competitors
prices
• The CoGS increases
• Profit declines
• Limited number of suppliers
Producer Supplier La Vita store
New logistic system
• Current suppliers set too high purchasing prices,
margin can be increased by removing the
number of suppliers from logistic chain
cooperating with direct manufacturers
• Tamara Rudiani shows her
ineffectiveness in dealing with
suppliers
• Anyway she is good at assortment
Dividing responsibilities of
purchasing and
assortment department
will help us to avoid
incompetent employees in
the administration
• Leave Tamara Rudiani in the Department of
Assortment
• Find a new Manager in the purchasing
Department with related competence
• Not all stores have the optimization
of staff: not excessive staff number
• La Vita is not efficient in the number
of working hours per shift, giving way
to competitors in the indicator
• High costs on special training
program for labor
• The costs are justified as they have
improved:
- efficiency of product handling
- customer orientation by improving
personnel skills and individual approach to
each store
• Decrease number of working hours per shift
on 5 % below minimum Vyatsky level
Schedule should be
optimized to raise
effectiveness of working
schedule
Dividing responsibilities helps to
improve negotiations with suppliers

13. 13
La Vita sustainable development will be possible with consistent
implementation of proposed initiatives
Implementation plan
Direction of
development Main ideas
Realization the strategy
of lower prices
Administration restructure
2017
Development the strategy
Investment of Sales in
low prices
Renegotiation with
suppliers
2016 2018 2019 2020
Marketing
Commercial
Store
Operations
Administrative
Optimization of labor
force
Start two own-label
product
Delivery service
Expansion of the light
and small type store
formats
Opening central kitchen
Restructure light type
stores with small
kitchen

14. 15
Appendix

15. 16
Appendix 1 Forecasted P&L of La Vita (general)
Team analysis
Appendix P&L
2015 2016 2017 2018 2019 2020
Sales 19,1 21,6 23 27,1 32,1 39,6
Total COGS -14,4 -14,5 -15,5 -18,2 -21,6 -26,6
Total COGS, % -75,4 -78,6 -78,6 -78,4 -77,4 -77,4
Other income 0,3 0,4 0,4 0,5 0,6 0,7
Gross profit 5,1 5,0 5,3 6,3 7,8 9,7
Gross margin, % 26,7 23,2 23,2 23,4 24,4 24,4
Labor 2,8 -3,0 -3,2 -3,8 -4,5 -5,5
Labor, % -14,7 -14,0 -13,9 -13,9 -13,9 -13,9
Rent -0,9 -0,3 -0,3 -0,4 -0,4 -0,6
Other -0,5 -0,6 -0,6 -0,7 -0,8 -1,0
EBITDA 0,9 1,1 1,2 1,5 2,1 2,5
EBITDA margin, % 4,7 5,3 5,4 5,5 6,5 6,4
Forecasted P&L (bn. rub.) Schedule of opening new stores
2016 2017 2018 2019 2020
Large 0 0 1 0 1
Mixed 0 0 4 6 8
Light 3 5 7 8 10
Small 2 5 7 8 10
All 5 10 19 22 29
Schedule of all stores
2015 2016 2017 2018 2019 2020
Large 7 7 7 8 8 9
Mixed 17 17 17 21 27 35
Light 134 137 142 149 157 167
Small 5 7 12 19 27 37
All 163 168 178 197 219 248
New 21 5 10 19 22 29
2012 2013 2014 2015
Large 6,06% 1,97% 5,36% 3,67%
Mixed 6,08% 1,96% 5,36% 3,70%
Light 6,01% 1,98% 5,37% 3,69%
Small 6,10% 1,92% 5,35% 3,71%
Presumable number of La Vita stores
by format, 2014
Ekaterinburg Chelyabinsk
Large 7
Mixed 7 4
Light 102 17
Small 5
Average La Vita Sales dynamics by store types

16. 17
Appendix 2 Forecasted P&L of large format stores
Team analysis
Appendix P&L
2015 2016 2017 2018 2019 2020
Sales 220,2 225,9 229,9 246,2 263,8 288,0
Total COGS -167,4 177,6 180,7 193,0 204,1 222,9
Total COGS, % -75,7 78,6 78,6 78,4 77,4 77,4
Other income 4 4,1 4,2 4,5 4,8 5,2
Gross profit 56,8 52,5 53,4 57,7 64,4 70,3
Gross margin, % 25,4 23,2 23,2 23,4 24,4 24,4
Labor -41,7 -39,6 -40,3 -43,2 -46,2 -50,5
Labor, % -18,6 -17,5 -17,5 -17,5 -17,5 -17,5
Rent -1,6 -1,6 -1,7 -1,8 -1,9 -2,1
Other -5,9 -6,1 -6,2 -6,6 -7,1 -7,7
EBITDA 7,6 5,1 5,2 6,1 9,2 10,0
EBITDA margin, % 3,4 2,3 2,3 2,5 3,5 3,5
Forecasted P&L (mln. rub.)
Assumptions of model
2016 2017 2018 2019 2020
The growth rate of sales (%) 3% 2% 7% 7% 9%
The growth rate of traffic per
year (%) 8% 6% 5% 3% 4%
The growth rate of the
average check per year (%) -5% -4% 2% 4% 5%

17. 18
Appendix 3 Forecasted P&L of mixed format stores
Team analysis
Appendix P&L
2015 2016 2017 2018 2019 2020
Sales 165,2 169,5 172,5 184,7 197,9 216,1
Total COGS -126,3 -133,2 -135,6 -144,8 -153,2 -167,2
Total COGS, % -76,5 -78,6 -78,6 -78,4 -77,4 -77,4
Other income 3 3,1 3,1 3,4 3,6 3,9
Gross profit 41,8 39,3 40,0 43,3 48,3 52,8
Gross margin, % 24,9 23,2 23,2 23,4 24,4 24,4
Labor -26,1 -24,8 -25,2 -27,0 -28,9 -31,6
Labor, % -15,5 -14,6 -14,6 -14,6 -14,6 -14,6
Rent -10,5 -7,7 -8,0 -8,4 -8,9 -9,3
Other -4,4 -4,5 -4,6 -4,9 -5,3 -5,8
EBITDA 0,9 2,4 2,2 2,9 5,2 6,1
EBITDA margin, % 0,5 1,4 1,3 1,6 2,6 2,8
Forecasted P&L (mln. rub.)
Assumptions of model
2016 2017 2018 2019 2020
The growth rate of sales (%) 3% 2% 7% 7% 9%
The growth rate of traffic per
year (%) 8% 6% 5% 3% 4%
The growth rate of the
average check per year (%) -5% -4% 2% 4% 5%

18. 19
Appendix 4 Forecasted P&L of light format stores
Team analysis
Appendix P&L
2015 2016 2017 2018 2019 2020
Sales 118 121,1 123,2 131,9 141,3 154,3
Total COGS -91,8 -95,2 -96,8 -103,4 -109,4 -119,5
Total COGS, % -77,8 -78,6 -78,6 -78,4 -77,4 -77,4
Other income 2,1 2,2 2,2 2,3 2,5 2,7
Gross profit 28,3 28,1 28,6 30,8 34,5 37,6
Gross margin, % 23,6 23,2 23,2 23,4 24,4 24,4
Labor -17,3 -16,4 -16,7 -17,9 -19,2 -21,0
Labor, % -14,4 -13,6 -13,6 -13,6 -13,6 -13,6
Rent -0,9 -0,9 -0,9 -1,0 -1,1 -1,2
Other -3,1 -3,2 -3,2 -3,5 -3,7 -4,1
EBITDA 7 7,5 7,7 8,5 10,5 11,4
EBITDA margin, % 5,8 6,2 6,2 6,4 7,4 7,4
Forecasted P&L (mln. rub.)
Assumptions of model
2016 2017 2018 2019 2020
The growth rate of sales (%) 3% 2% 7% 7% 9%
The growth rate of traffic per
year (%) 8% 6% 5% 3% 4%
The growth rate of the
average check per year (%) -5% -4% 2% 4% 5%

19. 20
Appendix 5 Forecasted P&L of small format stores
Team analysis
2015 2016 2017 2018 2019 2020
Sales 75,5 77,5 78,8 84,4 90,4 98,8
Total COGS -56,6 -60,9 -62,0 -66,2 -70,0 -76,4
Total COGS, % -74,9 -78,6 -78,6 -78,4 -77,4 -77,4
Other income 1,4 1,4 1,5 1,6 1,7 1,8
Gross profit 20,3 18,0 18,3 19,8 22,1 24,1
Gross margin, % 26,4 23,3 23,3 23,5 24,5 24,5
Labor -9,7 -9,2 -9,4 -10,0 -10,8 -11,7
Labor, % -12,6 -11,9 -11,9 -11,9 -11,9 -11,9
Rent -0,8 -0,8 -0,8 -0,9 -1,0 -1,0
Other -2 -2,1 -2,1 -2,2 -2,4 -2,6
EBITDA 7,8 5,9 6,0 6,6 8,0 8,7
EBITDA margin, % 10,2 7,6 7,6 7,8 8,8 8,8
Forecasted P&L (mln. rub.)
Assumptions of model
2016 2017 2018 2019 2020
The growth rate of sales (%) 3% 2% 7% 7% 9%
The growth rate of traffic per
year (%) 8% 6% 5% 3% 4%
The growth rate of the
average check per year (%) -5% -4% 2% 4% 5%
Appendix P&L

20. 21
Appendix 6 A typical grocery retailer’s organization structure (simplified)
Team analysis
Appendix Problem Stating
Service
Profitability
Sales
Costs
Traffic
Pricing
Assortment (SKU)
Store locations
Store format
Average items sold
Average price
Promo activities
Loyalty program
Deli (Kitchen)
Merchandise
Store design
CoGS
Transportation
Shrink
Bonuses
“Store environment”
Operation factors
Offer communication
Value communication
Staff per shift
Square meters
Staff qualification
Administrative
Advertisement
Average check
Variable (Total CoGS)
Fixed
Labor
Rent
Other
Supply chain management
Supplier relationship
management
Status
Problems
• Mixed format is
unprofitable
• Kitchens are not
in all stores
• Rent is high and
decreases EBITDA
• CoGS grows faster
than revenue
• Prices are high for
changed target
audience
• Optimization of work
process is required
• Assortment should
be restructured

21. 22
Appendix 7 Socio-economic indicators of Russians
Gks.ru, statdata.ru
Appendix Target Analysis
1315000
1335000
1355000
1375000
1395000
1415000
1435000
1455000
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
Фактические
данные
Прогноз по
среднему
абсолютному
приросту
Прогноз по
среднему
темпу роста
111,9
110
106,4
107,3
107
110,6
111,7
109,6
108,3
106,3
105,4
109,9
105
106
107
108
109
110
111
112
113
2005 2010 2011 2012 2013 2014
Свердловс
кая
область
Челябинск
ая область
22,5
23,5
24,5
25,5
26,5
27,5
28,5
29,5
2005 2010 2011 2012 2013 2014
90
95
100
105
110
115
120
125
2005 2010 2011 2012 2013 2014
Население Екатеринбурга, 2002-2015, до 2019 прогноз
Динамика реальных доходов населения с 2005-2014 гг.
Динамика индекса потребительских цен с 2005-2014 гг.
Структура потребительских расходов домашних
хозяйств с 2005-2014 гг.

22. 23
Appendix 8 Sales in different formats
Nielsen
Appendix Target Analysis
Sales of largest categories reduced in hypermarkets and
grew in discounters in 2015 (%)
-8
-4
-4
-4
-10
-10
-1
Cheese
Canned food
Сonfectionery
Tea
Premium hard alcohol
Chocolate
Coffee
Hypermarkets
Where Russians spend most of money in 2015
8%
Hypermarkets 31%
Supermarkets
39%
Discounters
Others
22%
10 10
4
Discounters HypermarketsSupermarkets
Number of visits per month
4
10
6
8
15
1
1
Discounters