1

Retail for Business Analysts and Management Consultants

Practical guide how to improve retail business

2

Retail has become extremely competitive. Therefore, you have to become very analytical and innovative to survive and develop your business

3

Thanks to this presentation you will learn how in practice to

improve the profits of a Retailer

4

How the presentation is organized?

5

This presentation is organized into 7 sections that will show you different aspect of Retail business. You will also find movies with examples.

Basic analyses that you should perform

Modeling Retail Business in Excel

Optimization of in-store processes –

case study

Business Hacks used by Retailers

In-store engagement and productivity

analysis

MultichannelExpansion Strategy

6

This is part of my on-line course where I show step by step improve results of a Retailer. You will find there additional Excels with calculations

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7

Basic analyzes that you should perform

8

Introduction to Basic Analyses

9

In this section I will show you the basic analyses that you should perform during your first week in a new retail business. You should start with creating issue tree

Issue tree for retail

Analyses by cohorts

Product Range Analysis

Sales and margin efficiency of

retailStore checks

Inventory analysis

10

Issue tree

11

Issue tree is an interesting concept that helps you go from a suspected problem to potential resasons and analyses that you have to carry out

Area of analysis

Area 1

Problem 1

Problem 2

Possible Reason 1

Possible Reason 2

Possible Reason 3

Possible Reason 4

Possible reasonsSuspected problemsAnalysis to be performed

Analysis 1

Analysis 2

Analysis 3

Analysis 4

12

Have a look at an issue tree of a chicken meat producer

Area of analysis

Transport

High costs of transport per ton of goods

Big level of waste and breakage in transport

Possible reasonsSuspected problemsAnalysis to be performed

Analysis of correlation between type of packaging and percentage of damaged

Analysis of time spent on the way and kilometers covered in that time

Analysis of designed routes, their length and the influence of possible changes

Analysis of fuel usage and kilometers covered by vehicles

Analysis of load carried on the way back

Badly designed routes

Too big fuel usage

No shipments on the way back

Low usage of resources

Badly designed method of packaging which makes the product prone to damage

Speed not adjusted to the product

Badly organized work and schedule of deliveries

Limitation on delivery time of finished goods

Analysis of level of overtime, daily organization of drivers work

Analysis of Clients’ preferences on delivery time

13

Issue tree in Retail -examples

14

When you are talking about retail you should have a look a the following areas

Retail chain development

Product Range / Category Range Management

Pricing

Logistic / Supply Chain

Expansion model

In-store process

HR especially trainings

15

Below you can see example of issue tree in Retail Chain Development

Area of analysis

Retail chain development

Low growth in sales

Decreasing EBITDA of new stores

Possible reasonsSuspected problemsAnalysis to be performed

Analysis of rents vs comparable competition

Salaries growth vs rotation – comparison with competition

Analyze the change in sales after opening new stores / on-line introduction

Analysis of number of openings vs availability of new places

Low LFL due to cannibalization (on-line, new stores in old locations)

Few new openings in locations

Increasing rents due not proper usage of purchasing power

Growing salaries to keep low rotation

High cost of building new stores

No support from the shopping malls

Not optimized formats, expensive fixtures

Analysis of contracts with shopping malls

Analysis of cost per 1 sq. m, number of fixtures, cost per fixtures

16

Areas you should pay attention to in Retail

17

There are number of areas of Retailer activities you should look at during consulting projects

Value Proposition and formats of the

stores

Retail business model logic

Product Range Management

Private Labels

MultichannelExpansion Model

Supply ChainIn-store Processes

In-store engagement and productivity

analysis

Automation Pricing

18

Analyses of stores by cohorts - Introduction

19

You can analyze a retail chain by following cohorts / segments

Vintage (which year it was open)

Format type

Format evolution phases

Location

Type of city

Type of traffic

Others

20

You usually show for specific cohort / segment the following metrics

Sales density (Sales per sq. m)

Margin density (Sales per sq. m)

Number of stores

Total sales generated by the cohort

Total margin generated by the cohort

% in total sales generated

% in total margin generated

21

Product range analyses -Introduction

22

In Retail you have space that you divide among different product groups

Group A

Group B

Group E

Group C

Group D

Group F

23

For every group you should calculate the total margin using sales density, % Gross Margin and space allocated to specific group

% Gross Margin

Sales density

Margin density Space in sq. mx

Total margin

x

24

You have to analyze their performance and decide how to split the space

4 250

3 0002 500

2 0002 400

4 000

Group A Group B Group C Group D Group E Group F

Sales densityIn USD/ sq. m

40%

55%44%

60%

40%

60%

Group A Group B Group C Group D Group E Group F

% MarginIn %

1 700 1 650

1 100 1 200960

2 400

Group A Group B Group C Group D Group E Group F

Margin densityIn USD/ sq. m

400

200

50

300

200

100

Group A Group B Group C Group D Group E Group F

Space allocationIn sq. m

Total margin generated by the store

25

Product range analyses -Example

26

Let see how we can allocate the space differently for our example

4 250

3 0002 500

2 0002 400

4 000

Group A Group B Group C Group D Group E Group F

Sales densityIn USD/ sq. m

40%

55%44%

60%

40%

60%

Group A Group B Group C Group D Group E Group F

% MarginIn %

1 700 1 650

1 100 1 200960

2 400

Group A Group B Group C Group D Group E Group F

Margin densityIn USD/ sq. m

400

200

50

300

200

100

Group A Group B Group C Group D Group E Group F

Space allocationIn sq. m

Total margin generated by the store

27

Different split of space among categories enabled us to increase the Gross Margin by USD 227 K

680 744

330413

360 210

192120

240570

Margin generated Basic OptionIn thousands of USD

Margin generated - Modified OptionIn thousands of USD

Group A Group B Group C Group D Group E Group F

Total margin generated by the shopIn sq. m

1 857 2 084

28

Sales and margin efficiency of retail

29

Imagine that you were asked to have a look at the efficiency of retailer with many concepts in cities in Poland

Gdańsk

Szcecin

Bydgoszcz

Poznań

Wrocław

Katowice

Łódź

Kraków Rzeszów

Kielce

Lublin

Warszawa

Białystok

Gdynia-Sopot

Gliwice

Olsztyn

Opole

Zielona

Góra

Current number of stores

30

In the case of efficiency there are to main KPIs retailers use

Sales density Margin density

31

You want to see which format and city are the most efficient

Formants / Concepts City

▪ What is the sales density per format? Which one is the best

▪ What is the margin density per format? Which one is the best

▪ What is the sales density per city? Which one is the best

▪ What is the margin density per city? Which one is the best

32

Inventory analysis

33

In our example of single store when we look at the sales and inventory level it is clear that there is too much stock

1 700

600

125

600480 400

Group A Group B Group C Group D Group E Group F

Sales in the storeIn thousands of USD

200

300

50

150200

100

Group A Group B Group C Group D Group E Group F

Inventory level in retail pricesIn thousands of USD

42

180

144

90

150

90

Group A Group B Group C Group D Group E Group F

Inventory turnoverIn Days of Sales

34

There could be plenty of reason for the inventory too be so high in Days of Sales

High share of push vs pull

Low responsiveness of supply chain

Bad allocation

Bad segmentation of the store –wrong customer profile

High level of dead stock that does not rotate

Problems with the format / layout

Problems with execution (i.e. Not right VM of goods, keeping

the stock in the backroom)

35

For every store you can present the potential to reduce the inventory using the waterfall

Inventory level in a store AIn thousands USD

1 000

304

696

Inventory before Potential Reduction Inventory after

36

If you have more stores than you can also show how you get to the total inventory reduction by showing contribution of specific stores

Inventory reduction potential by storesIn thousands USD

304

400

200

500

900

100200

200100

200

3 104

Store 1 Store 2 Store 3 Store 4 Store 5 Store 6 Store 7 Store 8 Store 9 Store 10 Total

37

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38

Store checks in Retail -examples

39

5 10 15 5 35

Number of SKU

Location:

Number of salesmen:

Competition: Saturn, Karen Notebook, iSpot

Size:

Number of SKU

Presented products

Structure of the exposition (%)

=100

PC Laptop Printers Phones Monitors Photos Others

-

3

E

+

Knowledge of

the product

offer

Sales skills

How active

salesmen are

Behavior

Usage of

marketing

materials

Level of service

• Salesman was able to respond to the request placed by the customer and it seemed that he had deep

knowledge of the products

• Salesman did not try to figure out what price level I was interested in. Surprisingly was proposing always the

cheapest products

• Salesman did not show the full potential range of benefits coming from the purchase (price of the software was

for some models incl. in the price, possibility to buy in installment)

• Salesman was very enthusiastic during the talk

• Salesman did not try to convince that the price is good and did not try to understand why I leave without the

purchase

• Salesmen did not try to do some cross selling or up-selling to other customers who purchased the base

products

Shopping mall

70 sq m

2

Other observations

Here you can see an example of store check for B2C – a shop selling computers

Laptops:

Pendrives: Firm No. of pieces

Cool drive

Kingston

Toshiba

6

1

1

Brand No. of pieces

HP

Toshiba

Asus

Sony

Samsung

Lenovo

Fujitsu

10

11

5

3

2

1

1

40

10 5 85 00000

Store profile

Location:

Rating of the location:

No. of salesmen

Competition level:

Size:

Number of SKU

Presented products

Structure of the exposition (%)

OSB Others

=100

-

3

E

+

Ability to adjust the product to the customerTechnical knowledge and knowledge

on the application of the products

Ocena pracowników składu

Center

1

500 m2

4

Service level

3

Plywood

Chipboard

MDF i HDF

OSB

Plank

Veneer

Countertops

Furniture fronts

Fittings

Other

0

0

0

2

0

0

0

0

1

1

Number of competitors in

radius of 3 km

3

Fittings

No. of SKU

Lead time

Home delivery

Other services offered

Shop with fittings

Limit on receivables

Payment terms

Other non standard products

immediate

n/a

no

Yes

n/a

n/a

Building materials

Here you can see an example of store check in B2B sector for a company selling wooden semi-products

Sales skills

How active

salesmen are

Knowledge of the

product offer

41

Store checks - examples in restaurants

42

Let’s have a look at the store check done at a Bobby Burger – a slow burger concept

Country of origin ▪ Poland

Typical sizeIn sq m

▪ 60-120

Investment needed In thousands of USD

▪ 50

Average priceIn USD

▪ 6.5

Production of food ▪ Produce to order

StaffIn people per shift

▪ 1+ 2 cook

Monthly revenues In thousands of USD

▪ 45

Number of open restaurantsIn pieces

▪ 38

Food Main competitors

Basic Data

43

Let’s have a look at the store check done at a Café Vincent – a french cafe and bakery

Country of origin ▪ Poland

Typical sizeIn sq m

▪ 130

Investment needed In thousands of USD

▪ 200

Average priceIn USD

▪ 3.5

Production of food ▪ Produce to shelf

StaffIn people per shift

▪ 2+3 baker

Monthly revenues In thousands of USD

▪ 100

Number of open restaurantsIn pieces

▪ 4

Food Main competitors

Basic Data

44

How to use store checks to check a specific location?

45

You should do store-checks at similar concepts and at the location where you want to open the restaurant

Passing by

Engaged / stopping

Leaving

Taking away

In store

46

Have a look at the location related KPIs for Bobby Burger concept

# of visitors ▪ 29

Conversion in-storeIn %

▪ 90%

Conversion take-awayIn %

▪ 3%

Engagement rateIn %

▪ 10%

Estimated revenuesIn K USD

▪ 45

Location Data

47

Have a look at the location related KPIs for Vincent concept

# of visitors ▪ 44

Conversion in-storeIn %

▪ 7%

Conversion take-awayIn %

▪ 73%

Engagement rateIn %

▪ 3%

Estimated revenuesIn K USD

▪ 100

Location Data

48

Retail business model

49

Introduction to retailer business model

50

Retail sounds very simple. You have to get the right stock in front of the right customers at the right moment

51

Yet there are some issues that simple make it difficult in execution

You have many segments of customers

Their come with different missions

Product Range is huge

Demand is very erratic / seasonal

Your supply chain is very complex

52

Let’s have a look at the example of a home improvement /DIY store

You have many segments of customers

Their come with different missions

Product Range is huge

Demand is very erratic / seasonal

Your supply chain is very complex

▪ Regular people that do renovation infrequently

▪ Fans of renovation you are constantly doing something

▪ B2B customers

▪ Building new house

▪ Preparing the apartment to move in

▪ Renovation

▪ Small improvements

▪ Small refill purchases

▪ 60 K SKUs regular

▪ 15 K SKUs seasonal

▪ Peaks in the Spring and summer

▪ Low season in winter

▪ You have local suppliers of heavy things (i.e. bricks),

▪ National suppliers

▪ Foreign regional suppliers (i.e. European)

▪ Asian suppliers (especially China)

53

Let’s have a look at another example of a kids’ ware retail chain

You have many segments of customers

Their come with different missions

Product Range is huge

Demand is very erratic / seasonal

Your supply chain is very complex

▪ Parents

▪ Non-parents

▪ Pre-born purchase

▪ Regular purchases

▪ Gifting

▪ Education and Development

▪ 40 K SKUs regular

▪ 10 K SKUs seasonal

▪ Short life of SKUs – Toys last in most cases up to 1 year; Fashion –6 months

▪ Peaks in the Christmas and around special gifting days

▪ Low season in Summer and after Christmas

▪ Regional brand suppliers

▪ Asian suppliers (especially China, India, Bandgladesh)

54

Main challenges in Retail

55

Let’s have a look at the main challenges in Retail

Margin ManagementStock / Inventory

ManagementMultichannel

Strategy

Managing price across channels

Expansion to new markets

Saturation of existing markets

New product development

Managing customer experience across

channels

Format evolution (possible death)

People rotation and knowledge

management

Disruption esp. from external forces / business models

Automation

56

Business model of Retailer in Excel

57

We start by estimating the total sales of Stores. That depend on average transaction value (ATV) and the number of transactions

# Transactions

Average Value Transaction

Total store revenue

x

58

We can estimate the number of transaction using the number of visits and conversion rate

# Transactions

Average Value Transaction

Total store revenue

x

# of Visitors % Conversion

x

59

Average Transaction Value depends on the average value of basic purchase as well as some suggested purchases (i.e. suggested products)

# Transactions

Average Value Transaction

Total store revenue

x

Average Value Transaction of basic purchase

Average Value Transaction of additional purchase

# of Visitors % Conversion

+

x

60

If we have the % Gross margin we can use it to estimate the total gross margin generated by stores

# Transactions

Average Value Transaction

Total store revenue

x

Average Value Transaction of basic purchase

Average Value Transaction of additional purchase

# of Visitors % Conversion

+

x

% Gross Margin

Gross Margin generated by the store

x

61

The last piece is getting the fixed costs (esp. rent and people

# Transactions

Average Value Transaction

Total store revenue Total store costs

x

Store EBITDAAverage Value Transaction of basic purchase

Average Value Transaction of additional purchase

# of Visitors % ConversionRent

People

+

x

Others

+

% Gross Margin

Gross Margin generated by the store

x -

62

We can also show what drives rent and salaries costs

# Transactions

Average Value Transaction

Total store revenue Total store costs

x

Store EBITDAAverage Value Transaction of basic purchase

Average Value Transaction of additional purchase

# of Visitors % ConversionRent

People

# of People

Average wages

+

xx

Others

+

# of sq. m

Fee per sq. m x

% Gross Margin

Gross Margin generated by the store

x -

63

To see how to transfer it into Excel go to my on-line course. Below link with great discount

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64

Introduction to e-commerce

65

In e-commerce you will have 3 types of players depending on their presence in off-line and their approach to both channels

E-commerce

Pure players

Off-line players with separate on-line presence

Multichannel /Omni players

66

Customer behaviors has huge impact on the business model and on what the e-commerce should concentrate on

▪ Less than 40% of the buyers will buy this year

▪ Focus is on customer acquisition

▪ Loyalty program are not good investment

▪ 70% of e-commerce businesses are in this modelAcquisition mode

Description of the business model Examples

▪ E-commerce selling only 1 type of Slow Moving Consumer Goods (SMCG) bought infrequently i.e. vacuum cleaner, scuba diving, furniture

▪ E-commerce for 1-time in the life event: strollers,

▪ 40%-60% of the buyers will buy this year

▪ You have a nice mix of new and returning customers

▪ Focus is on customer acquisition as well increasing the value of the customer (increased frequency and increased purchase per visit)

Hybrid mode

▪ E-commerce that sells SMCG with relatively big frequency of purchase(1.0-2.5 times a year ) i.e. shoes (Zappos)

▪ More than 60% of the buyers will buy this year

▪ Focus is on increasing the value of the customer (increased frequency and increased purchase per visit)

▪ 10% of businesses are in this modelLoyalty mode

▪ Very strong brands with high frequency of purchase (i.e. Zara, Amazon)

▪ Marketplaces i.e. Udemy, Uber

Source: Lean Analytics: Use Data to Build a Better Startup Faster; A. Croll, B. Yoskovitz

67

Just to remind you some examples of well known e-commerce businesses

Products sold On-line / Off-line situation

▪ Virtually everything esp. books, toys, fashion

Mode

▪ Pure on-line player ▪ Loyalty mode

▪ Fashion ▪ Multichannel player ▪ Loyalty mode

▪ Tickets for events ▪ Pure on-line player ▪ Acquisition mode

▪ Groceries ▪ Multichannel player ▪ Hybrid mode

▪ Razors and cosmetics for men

▪ Pure on-line player ▪ Loyalty mode

▪ Fashion ▪ Pure on-line player ▪ Hybrid mode

68

VISIT

PAID DIRECT SEARCH

To understand the logic of e-commerce business model have a look at the visualization of how it works

RECO ENGINENAVIGATION

BOUNCED

NOT INTERESTED

ABANDONED

UNSATISFIED

ONE-TIME BUYER UNSOCIAL BUYERCALL TO ACTION

OPEN RATE

SEARCH

CART

ADDITIONS

CONVERSION

LOGISTICS, DELAYS

VIRALRETURNING

CAC PageRank

Bounce rate

Sharing rateAbandonment, conversion rates

Ratings, delivery issues

Signups

Mail/RSS/TwitterReturning rate

Customer Lifetime Value Transaction size

Emphasis on repurchase rate, frequency, click-through rate, lifetime value

Emphasis on maximizing cart value, minimizing acquisition costs

DELIVERY

SHARINGENROLLMENT

Source: Lean Analytics: Use Data to Build a Better Startup Faster; A. Croll, B. Yoskovitz

69

Business model of e-commerce in Excel

70

Before we go to Excel let’s talk about the logic we used to build the e-commerce Excel model

▪ Conversion rate

Visits# of

transactionsRevenues

Gross Margin

Net MarginOperating

Profit

▪ ATV

▪ Cost of traffic

▪ Cost of logistics

▪ Transaction fees

▪ Fixed Costs

▪ % Gross Margin

71

Optimization of in-store processes – case study

72

1,8

6,0

3,9

1,5

3,8

3,3

8,4

28,8

In Retail you can achieve a lot by optimizing the operations in the store. Below example of a store were we carried out optimization and the saving we achieved per 1 store

12,7

17,3

6,1

2,6

6,2

15,7

27,1

87,7

Direct deliveries

Deliveries from Central Warehouse (CW)

Price change

Price monitoring

Cash till operations

Advices at the selling store area

Total monthly costsIn ‘000 USD

Potential savingsIn ‘000 USD

Total

▪ Potential savings are USD 29K (32% of all addressable costs)

▪ We assume that 50% of those savings can be achieved we can reduce the number of FTE in the store by 4

Others

73

You will see an example of optimizing 1 process. It was carried out in home improvement store. The test store was 4 000 sq. m big (43 000 sq. ft.)

Warehouse

Offices

Warehouse /store racks (shelving)

Cash Till

Employee

Customer

74

Price change – example of how we optimized 1 process

in the store

75

Price change is the process of changing the price tags. It generated for our customer 7% of costs in the test store but generated 16% of all savings

CC: Wikimedia

76

Let’s have a look how the price change process looks

Printing and preparation of new price tags

Price tag distribution Change of price tags

▪ Done by an Office Specialist

▪ Around 300-400 changes per day

▪ Office Specialist calls 4-7 Sales Reps to the Office and hands them over the price tags

▪ Sales Reps change prices in their departments

▪ A lot of problems were caused by lack of tools and infrastructure (scissors, ladder, pallet truck, dustbin etc.)

CC: Wikimedia

77

We have increased the number of tools an infrastructure

78

292

107

Before After

The change in the process was giving quite big potential savings

Cost of 1 price changeIn USD per change

6 124

2 249

Before After

Change in monthly cost in the test storeIn USD

▪ Given the number of stores (70) this could give potential savings of USD 3.3 M

79

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80

Business Hacks used by retailers

81

IKEA

82

IKEA has been very successful in implementing low cost model in furniture

Model „big box” built outside the city center

Design

Consistent message

Diversified revenue streams

Operational excellence

Business scale

Retail

Acquisition

Activation

Retention

Revenue

Referral

83

Model „big box” built outside the city center

84

Swedish design

85

Communication cheap, convenient solutions

86

Diversified revenue streams

87

Very efficient operations management at every level

88

The scale of activity is so high that orders for the same chair are apportioned between the various production plants, because one would not be able to execute orders

89

Biedronka

90

Biedronka keeps it simple on the operational side

Retail

Acquisition

Activation

Retention

Revenue

Referral

Narrow range – they used to have just 1000 SKUs

1 retail format

Optimize supply chain and in-store process

Scale

Expansion model similar to Walmart and Starbucks

91

They went deep into product management

Retail

Acquisition

Activation

Retention

Revenue

Referral

Gradual move from discounter to supermarket

Quality and origin obsessed

Own brands & selected premium brands (often powered by)

No e-commerce

For long time excepting only cash

92

Cinema City

93

Cinema City has used number of techniques to sell the unused space

Acquisition

Activation

Retention

Revenue

ReferralB2B

Ladies night

Unlimited Card Every Wednesday half price

Halloween party

Birthday party

Lower price in the low season

Group events

New needs

Getting the heavy users to visit more

94

Expansion

95

Introduction to Expansion

96

Once your business model is right you will want to expand and grow. There are some options to do that

Increase size in current locations

Enter new locations but still the cities were you are

already

Enter new cities in your country

Enter new countries

Add new brands but within the same concept

Create new concepts in Retail

Enter totally new business models

97

Expansion of current model -options

98

When it comes to expanding of current business models there are 2 aspect at which you should look: management and type of format

Own Stores

Franchising

Joint Management

Stand alone storeStore in Store /

Corner

99

Saturating existing markets -intro

100

If you are present on specific market you want to know when you will reach a saturation market – the maximal number of shops that will not cause much cannibalization

1 000

1 500

800

2 000

# of stores Saturation 1 Saturation 2 Saturation 3

101

Are you much below it?

1 000

1 500

800

2 000

# of stores Saturation 1 Saturation 2 Saturation 3

102

Or maybe you have already crossed it over and you should actually start closing down stores?

1 000

1 500

800

2 000

# of stores Saturation 1 Saturation 2 Saturation 3

103

You may also discover that the saturation point is far away and you have nothing to worry about

1 000

1 500

800

2 000

# of stores Saturation 1 Saturation 2 Saturation 3

104

You should also carry out such analyses by provinces

Gdańsk

Szcecin

Bydgoszcz

Poznań

Wrocław

Katowice

Łódź

Kraków Rzeszów

Kielce

Lublin

Warszawa

Białystok

Gdynia-Sopot

Gliwice

Olsztyn

Opole

Zielona

Góra

Current number of stores

105

In some provinces you may already reached the saturation point

Gdańsk

Szcecin

Bydgoszcz

Poznań

Wrocław

Katowice

Łódź

Kraków Rzeszów

Kielce

Lublin

Warszawa

Białystok

Gdynia-Sopot

Gliwice

Olsztyn

Opole

Zielona

Góra

Targeted number of stores

Current number of stores

106

Expansion strategy into other countries - Introduction

107

Creating an expansion strategy requires you to do a number of things

Define criteria and weights for the criteria

Gather data on the markets

Create the ranking of markets to enter

Define limits that you have

Set priorities

▪ 4-6 criteria on the basis of which you will value specific markets

▪ Ranking on the basis of criteria and weights created

▪ Money for expansion

▪ People for expansion

▪ Logistics

▪ Lead time due to your supply chain

▪ Limitation in stock

108

Expansion strategy into other countries - Example

109

Let’s imagine that you were to create an expansion plan for expansion into new countries for a fashion brand

110

As you remember we have create a ranking of countries

Define criteria and weights for the criteria

Gather data on the markets

Create the ranking of markets to enter

Define limits that you have

Set priorities

▪ 4-6 criteria on the basis of which you will value specific markets

▪ Ranking on the basis of criteria and weights created

▪ Money for expansion

▪ People for expansion

▪ Logistics

▪ Lead time due to your supply chain

▪ Limitation in stock

111

For this we will use 4 criteria and we will estimate the size of the markets in standard stores

▪ GDP per capita PPP

▪ Similarity in product range

▪ Competition level

▪ Franchising infrastructure and theCriteria for measuring the attractiveness of the market

Potential of the market

▪ Potential was measured using the size of the markets in terms of potential number of standard stores

112

Potential markets for expansion – Ranking vs Potential – region

2,2

2,3

2,5

2,6

2,7

2,7

2,9

3,0

3,3

3,3

3,4

3,4

3,5

3,6

3,9

4,3

Philipines

North America

Australia

Turkey

South America

Indonesia

China

Africa

ex USRR

Western Europe

India

Middle East

Malaysia

Thailand

Eastern Europe

Poland

Ranking of market attractiveness(1-low; 6-High)

Potential of countries / regions to capture assuming achieving share like in PolandIn standard stores

579

2 215

76

324

1 870

1 255

4 287

4 944

534

1 136

6 288

208

134

209

215

100

Philipines

North America

Australia

Turkey

South America

Indonesia

China

Africa

ex USRR

Western Europe

India

Middle East

Malaysia

Thailand

Eastern Europe

Poland

113

Potential markets for franchise – Ranking vs Potential – region

0

500

1 000

1 500

2 000

2 500

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5 4,0 4,5 5,0

Poland

Middle East

Philippines

Eastern Europe

Russia + Asian ex USRR

Thailand

Malaysia

Indonesia

Australia

North America

South America

Turkey

Western Europe

PotentialIn number of standard stores

Attractiveness(1-Low;6-High)

114

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115

Example of expansion into other business models

116

There are 12 business models that you can consider. Some Retailers enter other business models

SaaS

E-commerce

Media site

2-sided market

User Generated Content

Mobile Applications

B2B Service

Retail

B2C Service

B2C Products

B2B Products

Freelancing

117

Interesting examples is Amazon that started as e-commerce and entered many different business models including Retail

SaaS

E-commerce Media site2-sided market

UGC

B2B Service

B2C ServiceRetailer

118

Multichannel

119

What is multichannel?

120

For the customer your off-line and on-line presence are the same brand and he expect the on-line experience to be at least as good as off-line

On-line belonging to retail chain

Off-line retail chain

One brand

121

This means that certain things should be managed across both channels

Products

Price

Customer Data

Relations with the customers

Customer Experience

Marketing communication

122

Main problems with multichannel

123

Let’s have a look at the main problems with multichannel

Cannibalization with off-line

Different customer experience

Operational problems coming

from on-line

Pricing Management

Competition with pure players

Big data unified approach

SegmentationMarketing

communication

People and firms take advantage of lower

on-line pricing

Falling traffic in off-line

124

Pricing dilemma - case study

125

Imagine that you have a chain of physical stores and on-line store. What pricing would you use

On-line belonging to retail chain

Off-line retail chain

?$ 100 $ 90

On-line market

126

Before you try to solve the case on your own you should answer the following questions

Establish what is the structure of the market?

▪ What is the current share of on-line in the market ?

▪ Is it growing?

Decide what you want to have in terms of share of

on-line in your sales?

What price difference between on-line and off-

line is acceptable

What price difference is noticeable?

▪ What is the current share of on-line in your sales ?

▪ Do you want to be above or below the market?

▪ What price difference between on-line and off-line customer treat as fair?

▪ Do we want to be fair?

▪ What price difference is noticeable?

▪ Do we want to stay unnoticed?

127

The prices we want to set for the on-line business that belongs to Retailer should be considered and still competitive for on-line market

On-line belonging to retail chain

Off-line retail chain

?$ 100 $ 90

On-line market

▪ The difference in prices is fair it is not bigger than 6%

▪ The customer notices / cares if the difference in prices is up to 3%

128

Out of this we get the following brackets that we can consider

$ 90 $ 100$ 93

Fair prices

$ 97

Practically the same prices Practically the same prices

Here you are not on-line competitive

$ 94

129

If you have the answer to the questions from the beginning you can decide on the set of prices to use in online and offline

$ 93

Do you want the on-line to have bigger share in your sales than it has in the whole market?

Yes

No

Do you want the difference between on-line and off-line to be fair?

Do you want the difference between on-line and off-line to be fair?

Yes

No

Yes

No

$ 93<

> $ 94

$ 98

$ 100

$ 100

$ 93- $ 100 $ 100

130

Cannibalization of sales -Introduction

131

When you start building more stores you are bound to cause a lot of cannibalization

132

You can minimize the cannibalization by picking the right locations. Just remember that cannibalization may be there by design

133

There are plenty of reasons why you could be still ok with cannibalization

You are reaching new customers

You are taking away more from competitors than your

own chain

You are killing competition

More visibility = equivalent on marketing money

Increased purchasing power especially when it comes to

rent

134

Cannibalization of sales by on-line

135

On-line is a different story as it can cannibalize any store at your chain and it is beyond your control. You actually more likely to hurt yourself than your competition

136

Still there are some reasons why as a multichannel you would be ok with some level of cannibalization

Market is going on-line – if you don’t have on-line customer

they may altogether leave you

Some customers will pick-up the things at the store and buy

additional products

You may start managing your stock differently – i.e. long tail

only on-line

You can improve the customer experience without hiring a lot

of people

137

Cannibalization of sales - case study

138

Imagine that you have to estimate the impact of cannibalization of off-line channel by on-line on margins.

139

The Retailer has 400 shops in the whole Europe and sells 3 types of goods

Toys Fashion Hardware

140

You have to check which effect is bigger

Margin loss due to cannibalization

▪ For most products you will have lower margins for the same products in on-line sales than in off-line

▪ Difference in margin will be different for different groups

Margin gain from additional purchases generated by on-line

▪ If the product is picked-up at the off-line store you can sell additional products to some of the customers

141

To estimate the cannibalization effect we will have to look at 2 things

Total on-line sales

Difference in Margins

Margin LostAdditional Margin Gained

Net impact of on-line on off-line P&L

-

Off-line margin On-line margin

Average additional value bought

Number of transaction picked at the off-line store

-

% generated by cannibalizing off-line sales

x

% Gross Margin on additional things bough

x

142

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143

Private labels - introduction

144

Private labels are products created for the Retailer and sold under a brand belonging to him (can be named different than Retailer brand)

Retailer brand

145

There are plenty of reasons why it makes sense for retailer to have private labels

You can use it to kill low price brands

Unique products – no way to compare with other channels

Higher margins

Bigger influence on product

Shorter lead time

146

How to analyze private labels?

147

In order to get candidates for private labels you have to map product groups against price intervals. Find competitors to in each segment to know whom you take your sales from

Group 1

Group 2

Group Z

Price Interval 1

Price Interval 2

Price Interval X

….

….

148

In-store engagement and productivity analysis

149

Introduction to in-store engagement

150

You wan to track the behavior of customers. Below example in the case of a restaurant business

Passing by

Engaged / stopping

Leaving /Not entering

Take away

Inside the restaurant

151

For a Retailer we would define the specific categories a little bit differently

Passing by

Visitors (entered the store)

Visitors that left without stopping

Buyers

Visitors that stopped but did not buy

Did not enter the store

152

You want to do it on the level of specific department so you have to define the physical boundaries of departments

Warehouse

Offices

Warehouse /store racks (shelving)

Cash Till

Employee

Customer

153

Main rules according to which people behave

154

It is worth remembering some universal laws about customer engagement

1-lane lead is the best solution

It’s important to lead fast the customer to first purchase

Bestsellers should be in top locations

Replenishments trips are the most frequent

Inspirational Visual Merchandising works

155

KPIs that you should follow

156

Dwells shows you want attracts customer to enter the store

Number of dwells per department =

▪ number of shoppers who stop in a given zone for longer than defined time

157

Engagement shows you whether specific department has the stopping power

Engagement Rate by departments =

▪ percentage of shoppers walking by a location who stopped at that location

40,0%38,0%

36,0%34,0%

32,0%30,0%

28,0%26,0%

24,0%22,0%

20,0%18,0%

16,0%14,0%

A B C D E F G H I J K L M N

158

Overall conversion shows you what they came to really buy

Overall conversion = ▪ percentage of people visiting the store that are buying from given department

8,0%

7,0%

6,5%

6,0%

5,5%

5,0%

4,5%

4,0%

3,5%

3,0%2,8%

2,6%2,4%

2,2%

A B C D E F G H I J K L M N

# of transactions in specific department

# of people that visited the store

159

Exposure rate shows you to what extent they reach the product

Exposure Rate by departments =

▪ percentage of shoppers who reach specific location as compared to the total store traffic

# Entries to specific department

# of people that visited the store

=

160

Local conversion tell you how good you are in closing the deal

Local conversion =▪ Number of people that bought from a

specific department divided by the number o people who stopped there

# of transactions in specific department

# of dwells in a specific departments

25,0%

23,0%

21,0%

19,0%

17,0%

15,0%

13,0%

11,0%

9,0%

7,0%

5,0%

3,0%

1,0%

A B C D E F G H I J K L M

161

Shopper Yield shows you the value of visitor expressed in sales

Shopper Yield =▪ Average sale amount for each shopper

visiting the store within a specified period

Total revenues

# of visitors

0,80 0,800,77 0,75 0,77

0,81 0,83 0,81

0,740,80 0,78

0,740,77 0,75

0,80 0,780,84 0,86

0,50

0,790,76 0,74

0,80 0,780,74 0,75 0,73

0,800,74

0,77 0,75

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

0,7

162

On top of that you should look at other interesting metrics

Average visit duration

Average Dwell Time

Structure of visitors by age groups

Breakdown of customers by gender

Number of transactions per sq. m by departments

Sales density departments

Average value of item by department

Number of products per 1 transaction by departments

163

Format - designing new ones

164

Format - introduction

165

When we talk about format there are plenty of issues that have to be set

Look & FeelBrandValue propositionCustomer Experience

Product range

Push vs PullReplenishment

Service Level

Pricing

Customer Experience

Customer Groups

Mission served

Capex Capacity Inventory level

166

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167

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