Mystery shopping survey on territorial restrictions and geo … · b) Does volume of trade have an impact (e.g. more geo-blocking for countries with a low level of cross-border trade

GfK Belgium PS May – 2016

Justice and Consumers

Mystery shopping survey on territorial restrictions and

geo-blocking in the European

Digital Single Market

Final Report

Territorial Restrictions and Geo-Blocking in the European Digital Single Market

EUROPEAN COMMISSION

Directorate-General for Justice and Consumers

Directorate E – Consumers

Unit E1 – Consumer Markets

Contact: Konstantinos Zisis

E-mail: [email protected]

European Commission

B-1049 Brussels

EUROPEAN COMMISSION

Directorate-General for Justice and Consumers EU Consumer Programme (2014-2020)

2016

Mystery shopping survey on territorial restrictions and

geo-blocking in the European Digital Single Market

Final Report


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Abstract

The present study was conducted as part of a wider evidence gathering by the

Commission on geo-blocking as a barrier to online cross-border trade in the European

Digital Single Market. The primary objective of this study was to investigate the

prevalence and characteristics of geo-blocking practices across the EU28 using a broad-

based approach covering all forms of territorial restrictions that apply to cross-border

online commerce. It was not within the scope of the study to look into retailers’

motivations for engaging in geo-blocking, nor into whether these practices are justified in

accordance with existing EU legislation. An EU28-wide Mystery Shopping Survey was

conducted to examine the various types of geo-blocking practices consumers face at each

stage of the online shopping process and their prevalence by region, country, sector,

product, and type of retailer. The focus was on six tangible goods and two online services

sectors where cross-border e-commerce is most prevalent. Over 10,000 online retailers

were surveyed, using a sampling methodology based on the level of cross-border e-

commerce between 143 specific country pairs, making the results broadly representative

of the current e-commerce patterns across all Member States in the EU28. The study

finds that geo-blocking practices are widespread, and mostly apply in relation to delivery.

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TABLE OF CONTENTS

1 INTRODUCTION ........................................................................................ 8

1.1 Study objectives ............................................................................... 8

1.2 Research questions and sampling ....................................................... 9

1.3 Sectors covered .............................................................................. 10

1.4 Goods and services covered and website selection ............................... 11

1.5 Sample overview ............................................................................. 13

1.6 Measuring geo-blocking practices via the mystery shopping

questionnaire .................................................................................. 17

1.7 Definition of breakdowns .................................................................. 18

1.7.1 EU Regions.......................................................................... 18

1.7.2 Regional direction of trade .................................................... 19

1.7.3 Country pair distance ........................................................... 19

1.7.4 Retailer size ........................................................................ 20

1.8 Weighting ....................................................................................... 21

1.8.1 Weight based on the level of cross-border e-commerce ............ 22

1.8.2 Weight based on yearly cross-border website traffic ................. 22

2 GEO-BLOCKING PREVALENCE ACROSS THE EU28 ........................................ 24

2.1 Geo-blocking and the four stages of the shopping process .................... 24

2.2 Overview of geo-blocking prevalence during each stage of the shopping

process .......................................................................................... 25

2.3 Contribution of geo-blocking practices of each stage of the shopping

process (as a proportion of the overall process)................................... 27

2.4 Mystery shopping success rates (% of all shopping attempts) –

comparing the different weights used ................................................. 28

2.5 Prevalence by seller’s country of origin and EU region ......................... 30

2.6 Prevalence by shopper’s country of residence and EU region ................. 33

2.7 Prevalence by country pair ................................................................ 35

2.8 Prevalence by direction of trade – EU15 and EU13 ............................... 38

2.9 Prevalence by sector ........................................................................ 39

2.10 Prevalence by product category ......................................................... 40

2.11 Prevalence by country pair distance ................................................... 42

2.12 Prevalence by size of retailer ............................................................. 44

3 GEO-BLOCKING PRACTICES RELATED TO ACCESS ....................................... 47

3.1 Automatic re-routing or immediate blocking of access .......................... 47

3.2 Differences between domestic and cross border websites ..................... 58

3.2.1 Differences in website content ............................................... 58

3.2.2 Differences in product availability ........................................... 65

4 GEO-BLOCKING PRACTICES RELATED TO WEBSITE REGISTRATION ............... 77

4.1 Registration requirements ................................................................. 77

4.1.1 Registration requirements by seller origin ............................... 78

4.1.2 Registration requirements by sector ....................................... 83

4.1.3 Registration requirements by retailer size ............................... 85

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4.2 Common issues with registration ....................................................... 85

4.2.1 Registration issues by seller and shopper origin ....................... 86

4.2.2 Registration issues by sector ................................................. 96

4.2.3 Registration issues by distance and retailer size ....................... 98

4.2.4 Price differences ................................................................ 100

5 GEO-BLOCKING PRACTICES RELATED TO DELIVERY RESTRICTIONS ............ 111

5.1 Overall delivery restrictions ............................................................ 111

5.2 Delivery restrictions by seller origin ................................................. 113

5.3 Delivery restrictions by sector ......................................................... 119

5.4 Delivery restrictions by product ....................................................... 120

5.5 Delivery restrictions by type and size of online retailer ....................... 123

5.6 Information availability on delivery restrictions .................................. 124

5.7 Delivery costs ............................................................................... 127

6 GEO-BLOCKING PRACTICES RELATED TO PAYMENT ................................... 137

6.1 Means of payment and entering payment details ............................... 137

6.2 Payment issues by region ............................................................... 138

6.3 Payment issues by country of the retailer ......................................... 141

6.4 Payment issues by sector ............................................................... 145

6.5 Payment issues by size of retailer, credit card type and distance ......... 146

6.6 Errors received after order confirmation ........................................... 148

7 ADDITIONAL ANALYSES .......................................................................... 150

7.1 Price differentiation by international online retailers: a case study ....... 150

7.1.1 Introduction ...................................................................... 150

7.1.2 Methodology ..................................................................... 151

7.1.3 Results and discussion ........................................................ 152

7.2 Predicting geo-blocking: a logistic regression analysis ........................ 155

7.2.1 Methodology ..................................................................... 155

7.2.2 Overall results ................................................................... 156

7.2.3 Geo-blocking, sectors and the direction of trade: in-depth

comparisons ...................................................................... 160

8 ANNEXES .............................................................................................. 162

8.1 Annex I – Mystery Shopping Survey Methodology .............................. 162

8.1.1 What is mystery shopping? ................................................. 162

8.1.2 Sampling methodology ....................................................... 164

8.1.3 Sampling overview ............................................................. 176

8.1.4 The use of Virtual Private Network (VPN) .............................. 177

8.2 Annex II – Mystery Shopping Survey: Final Questionnaire .................. 178

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1 Introduction

1.1 Study objectives

As part of the Commission’s Digital Single Market (DSM) Strategy, legislative steps will

be taken in order to tackle unjustified geo-blocking practices as a barrier to cross-border

e-commerce. To achieve this goal, the Commission needs a comprehensive pool of

evidence on the features and patterns of geo-blocking gathered from multiple sources

and perspectives. The Commission has recently announced the results of the public

consultation on geo-blocking and other geographically based restrictions when shopping

and accessing information in the EU launched as part of the EU DSM Strategy and

concluded at the end of December 20151. A sector inquiry into e-commerce in all EU28

Member States was also launched, in order to better understand what drives companies

to impose geographical restrictions, their implications for cross-border online trade and

how to remove them in the future. Initial results were presented in mid-March 20162.

The objective of the present study is to investigate geo-blocking practices from a

consumer perspective, focusing on their prevalence and characteristics across the EU28

Member States. The study uses a broad-based approach to the concept of geo-blocking,

investigating all forms of territorial restrictions that apply to cross-border online

commerce. As such, it is outside of the scope of this study to investigate whether all

practices described fit under the umbrella term “geo-blocking” and whether these

practices are justified or not. To address this objective, a large scope Mystery Shopping

Survey (MSS) was conducted to investigate the many different forms online geo-blocking

can take, the extent to which it is being practiced by type of sector and product category

and its prevalence by country and type of retailer. The MSS aims to draw a concrete,

comprehensive picture of the way territorial restrictions are applied at different stages in

the process of making a cross-border online purchase. In addition, some of the

information the study will generate on the characteristics of geo-blocking practices might

also produce preliminary and partial insights into the reasons why online firms apply geo-

blocking, as well as the precise level of price differentiation faced by consumers in

different markets.

The specific objective of the Mystery Shopping Survey was to collect a set of data on the

nature and incidence of geo-blocking that is representative of the types of sectors,

1 https://ec.europa.eu/digital-single-market/en/news/full-report-results-public-consultation-geoblocking 2 http://ec.europa.eu/competition/antitrust/sector_inquiries_e_commerce.html

https://ec.europa.eu/digital-single-market/en/news/full-report-results-public-consultation-geoblockinghttp://ec.europa.eu/competition/antitrust/sector_inquiries_e_commerce.html

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products and online retailers in the DSM across all Member States in the EU28. The

survey’s sampling methodology focused on achieving a sample of shopping attempts that

is representative of the current patterns of EU28 cross-border e-commerce. However, the

MSS does not address the question why firms/e-shops engage in geo-blocking and to

what extent these reasons may be justified in accordance with EU acquis, including

competition rules3, Art. 20 of the Services Directive

4 or any country specific legislation.

Since geo-blocking in digitally delivered media content can usually be justified by

copyright, the study focused only on tangible goods and online services to be used

offline. Other sectors that are illegal in certain Member States (such as online gambling)

were also excluded.

1.2 Research questions and sampling

The following five research questions were addressed by the present study. The sampling

approach taken and its specific steps can be found in Annex I.

1. How prevalent is the practice of geo-blocking in cross-border online

shopping?

2. In which stages of the shopping process does it occur and what form

does it take?

a) Is it a case of being redirected to another website at the beginning of the

purchase attempt, or does it take place at a later point in the shopping process?

b) Is it related to price, delivery, needing to register on the website, etc?

3. In what types of goods and services is it most prevalent?

a) Is it more prevalent in goods or services?

b) In what sectors is it most prevalent?

c) Within each sector, what types of products / services is it most prevalent (e.g.

high/low value goods, etc)?

4. In what type of web-shops is it more prevalent?

a) Is it more prevalent in large, medium or small web-shops?

b) Is it more prevalent in online-only shops or ‘bricks and clicks’ shops?

3 Block exemptions on vertical restraints 4 http://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32006L0123&from=EN

http://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32006L0123&from=EN

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5. Are there differences in the incidence of geo-blocking by country pairs

and direction of trade?

a) Does geographical distance have an impact (e.g. more geo-blocking for country

pairs that are far away from one another than for those that are close together)?

b) Does volume of trade have an impact (e.g. more geo-blocking for countries with a

low level of cross-border trade than countries with a high level of cross-border

trade)?

c) Can any insights be gained in terms of region or country grouping (e.g. more geo-

blocking in the EU13 or in Southern Europe)?

1.3 Sectors covered

A total of 8 sectors were assessed in order to provide sufficient breadth in terms of type

of sector whilst keeping a balance in delivering sufficient mystery shopping surveys per

sector to enable post-fieldwork analysis. The final 8 sectors consist of 6 tangible goods

and 2 services sectors. The two services sectors, in particular, were relatively challenging

in terms of being able to compare and sample similar services in multiple countries, but

their inclusion was key in order to ensure that the mystery shopping survey focuses on

services, as well as tangible products.

The sector selection was based on those goods and services sectors that are most

commonly purchased online in the EU according to the 2015 DSM Consumer Survey5.

The table below presents the final 8 sectors agreed upon. The only sector in the top 8

that was excluded was that for Non-electrical household products & interior design. This

sector was replaced by Computer games and software in order to investigate a more

diversified sample of markets. The table below presents an overview of the 8 sectors

surveyed.

5 GfK for the European Commission, Consumer survey identifying the main cross-border obstacles to the DSM

and where they matter most, 2015

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Table 1: Sectors surveyed

Sectors % EU28 online respondents who

purchased this good / service online in

2014 (DSM consumer survey)

Clothing, shoes & accessories 76%

Travel services (e.g. hotels,

transport)

68%

Electronics & computer hardware 66%

Books 64%

Online reservations of offline leisure

(e.g. event tickets)

63%

Electrical household appliances 61%

Cosmetics & healthcare products 60%

Computer games and software 50%

1.4 Goods and services covered and website selection

Within each sector, the mystery shopping survey was carried out with 6 specific goods or

services categories (except for the market “Online reservations of offline leisure”, where

only 5 services were surveyed). In addition, alternative products (belonging to the same

market) were considered by mystery shoppers when the pre-defined goods or services

were not available from a specific retailer. The final list of products surveyed in each

market was agreed upon after several rounds of discussions. It is shown in the Table that

follows from where it can be seen that the original product categories (column 1) were

subsequently recoded to new categories (column 2) in order to take into account all of

the alternative products that mystery shoppers assessed. By doing so, it was possible to

increase the final sample available for product level analyses. The recoded product

categories included a range of 3-6 specific products assessed per sector. Train services

were initially considered to be added within the travel services sector. However, they

were eventually excluded because of the extremely limited amount of websites selling

train tickets online in each Member State.

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By ensuring a high quality, representative sample of online websites6, mystery shoppers

were instructed to assess two products on the same website. Additional (reserve list)

websites were provided to each mystery shopper, in case certain retailers’ websites were

no longer available or did not sell the specific products or any suitable alternatives in a

given sector. The selection of products assessed on the websites was agreed to be

representative of the online basket for the consumer, whilst also taking into account the

size and relative value of the product. Below is a list of the specific products surveyed

and the final product categories they were recoded to, along with suitable alternatives.

Fieldwork took place during December 2015.

6 Based on a comprehensive database of online retailers provided by SimilarWeb (see Annex I for more details).

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Table 2: Original products assessed and recoded product categories for the analysis

1.5 Sample overview

The following flow chart provides an overview of the sample of websites that the mystery

shopping survey aimed to achieve including the exact number of country pairs, sectors

and websites per good/service.

Number of product categories per

sector

Theatre/ballet/opera ticket

Coffee machine

Leather boots

Sports shoes

Winter jacket/coat

Cocktail dress/men’s suit

Pair of jeans

A leather belt

Fiction book

Textbook

Business & finance book

Children's book

Refrigerator

Live concert ticket

Shampoo

Microwave oven

Live sports event ticket

Iron

Special party/event/fashion show ticket

Mixer

Amusement/theme or adventure park ticket

Vacuum cleaner

Luxury car rental

Perfume

Economy class airplane ticket

Business class airplane ticket

4 star hotel reservation for 2 (1 night)

Make-up set

Electric toothbrush

Set of shaving blades

All-inclusive ski holiday for 2

6 C

om

pu

ter

gam

es a

nd

so

ftw

are

7 E

lectric

al

ho

useh

old

ap

pli

an

ces

8 O

nli

ne

reservatio

ns o

f

off

lin

e

Original product categories

3 T

ravel

servic

es

(h

otels

,

tran

sp

ort)

4 C

osm

etic

s

an

d

healt

hcare

pro

du

cts

5 B

oo

ks

Printer

Satellite navigation

2 E

lectro

nic

s &

co

mp

uter

hard

ware

Laptop (Acer)

Media Tablet (Samsung)

Smartphone (Nokia)

Desktop computer (HP)

Microsoft Office software

Antivirus software

Adobe Photoshop software

Fifa PS4 video game

Assassin's Creed PC video game

Halo Xbox video game

Dictionary

Travel guide

Facial cream

Economy car rental

Computers and tablets

Mobile phones


Office equipment and accessories

Satellite navigation

Additional category

1 C

loth

ing

,

sh

oes a

nd

accesso

rie

s

Additional category

Additional category

Proposed new categories after merging

Shoes

Shoes

Outerwear (jackets, coats)

Overalls (costumes, dresses)

Lower garments (pants, skirts)

Underwear and accessories

Upper garments (t-shirts, sweaters)


Flight bookings

Flight bookings

Accommodation bookings

All-inclusive holidays

Creams, soaps and lotions

Photo and video equiment

Audio equipment

Car rentals

Car rentals

Console video games

Business/finance software

Fiction books

Educational books

Business & finance books

Children's books

Educational books

Perfumes

Make-up

Electric products and accessories

Electric products and accessories

Hair products

5

5

5

3

Other tickets (e.g. special party, event, fashion show)

Amusement/theme or adventure park tickets

Cultural event tickets

6

6

4

5

Small household appliances

Medium household appliances


Music event tickets

Sports event tickets

Security software

Other software

Large household appliances


Small household appliances

Travel and hobby literature (including magazines)

Console video games

Computer video games

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The country pairs (each representing the country of the seller and shopper) were also

selected based on the 2015 DSM consumer survey. The selection was based on the

reported prevalence of online shopping between specific country pairs7. Therefore, they

are broadly representative of the current state of play in cross-border e-commerce across

the EU. For example, consumers from all Member States appear to shop online from

either the UK and/or Germany, so country pairs involving either of these countries

represent 54 (i.e. 27 x 2) country pairs out of a total of 143 country pairs.

For every sector assessed (8 in total), 9 websites were visited by shoppers cross border

for each of the 143 country pairs identified. The total sample of websites surveyed, after

data cleaning, was 10537 (data will be reported at website level analysis throughout the

report unless explicitly specified otherwise). Each website was first assessed from a

domestic perspective where mystery shoppers looked for 2 specific products that were

available to purchase online domestically, via the use of suitable Virtual Private Network

technology8. In the second part of the survey the exact same website and the same two

products were assessed cross-border by shoppers setting their VPN location to their own

country (i.e. shoppers’ country to assess the websites from a cross-border perspective).

Nonetheless, the distribution of mystery shopping assessments per sector was somehow

unbalanced towards certain online sectors like clothing, shoes and accessories or

electronics & computer hardware and less so for sectors like online reservations of offline

leisure (see achieved MS assessments per website as opposed to the targeted ones in the

Table that follows). During the identification and selection of online retailers to be

included in the sample, it became clear that this unbalanced sample is likely to be

reflective of the actual distribution of online retailers across the 8 surveyed sectors. The

7 Those country pairs were covered where at least 4% of respondents from a given MS (country of the shopper) reported purchasing tangible goods and offline services online cross-border from another MS (country of the seller), with the exception of Bulgaria and Malta which were added to the sample, despite the highest percentages of respondents purchasing online from these countries cross-border being 3% for Bulgaria (from Greece) and 1% for Malta (from Finland) – see Annex 8.1.2.1 for more details.

8 Shoppers first set their VPN location to the country of the online retailer (i.e. domestic purchase). For more

information on how the Virtual Private Network technology works, please refer to Annex 8.1.4

143 country pairs

8 sectors 9 websites per sector

TOTAL: 10,296

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following 3 tables present an overview of the distribution of website assessments9

achieved per country of retailer, country of shopper, and per sector.

Table 3: Sample by sector

Sector Mystery shopping attempts (per website)

Achieved Target

Clothing, shoes and

accessories 1734 1287

Electronics & computer

hardware 1667 1287

Travel services (e.g.

hotels, transport) 1172 1287

Cosmetics and healthcare

products 1572 1287

Books 1120 1287

Computer games and

software 1029 1287

Electrical household

appliances 1208 1287

Online reservations of

offline leisure 1035 1287

Total 10537 10296

Table 4: Sample by country of the retailer

Website origin Number of shopping attempts (per

website)

Achieved Target

Austria 761 648

Belgium 213 216

Bulgaria 89 72

Croatia 71 72

Czech Republic 139 144

Cyprus 72 72

Denmark 74 72

Estonia 140 144

Finland 71 72

France 1152 1152

Germany 1936 1944

Greece 143 144

Hungary 155 144

Latvia 71 72

Lithuania 72 72

9 Overall, on each website shoppers assessed two different goods or services, making the maximum number of

product assessments a total of 10 296 x 2 = 20 592.

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Luxembourg 72 72

Ireland 257 216

Italy 929 936

Malta 71 72

Netherlands 354 360

Poland 360 360

Portugal 156 144

Romania 97 72

Slovakia 159 144

Slovenia 81 72

Spain 643 648

Sweden 208 216

the UK 1991 1944

Total 10537 10296

Table 5: Sample by country of the shopper

Shopper origin Number of shopping attempts (per

website)

Achieved Target

Austria 378 360

Belgium 369 360

Bulgaria 490 432

Croatia 539 504

Czech Republic 459 432

Cyprus 210 216

Denmark 313 288

Estonia 509 504

Finland 427 432

France 372 360

Germany 389 360

Greece 534 504

Hungary 343 288

Latvia 376 360

Lithuania 233 216

Luxembourg 606 576

Ireland 349 360

Italy 463 432

Malta 408 432

Netherlands 206 216

Poland 210 216

Portugal 250 288

Romania 479 504

Slovakia 445 432

Slovenia 358 360

Spain 322 360

Sweden 219 216

the UK 281 288

Total 10537 10296

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1.6 Measuring geo-blocking practices via the mystery shopping

questionnaire

Geo-blocking or territorial restriction practices are often based on some form of geo-

identification of the consumer using various means of data available online (e.g. IP

address, delivery address, phone number, credit card etc.). Geo-blocking practices during

cross-border online purchases can take one of four possible forms:

1) Denial of access to the website (i.e. blocking the consumer) by displaying an

error message

2) Automatic re-routing to a website in a different country (usually the country of

the consumer) without consumers’ consent or ability to stop the re-routing

3) A straightforward refusal to sell – at any stage during the ordering process

4) Changing the terms and conditions and/or prices based on the country where

the consumer resides

A comprehensive understanding of the range of geo-blocking practices requires an in-

depth exploration of these four practices, the different forms they may take and their

characteristics. The final questionnaire provided in Annex II addressed the first three

elements of geo-blocking, as defined above, by asking mystery shoppers questions

related to denial of access, automatic re-routing and refusal to sell. The fourth element,

‘changing the terms and conditions’, was covered only partially by the survey in terms of

differences in product availability and product price when attempting to purchase from

the same retailer domestically, compared to cross-border. However, the survey did not

require the mystery shopper to read the full terms and conditions of each website.

Moreover, the importance of the way delivery costs/restrictions are communicated on a

retailer’s website was investigated. Mystery shoppers were required to do a manual

search of the website, looking for information on both domestic and cross-border delivery

costs, as well as on delivery restrictions even prior to registering on the website. In

addition, the prominence with which delivery restrictions are communicated, during the

various steps of the shopping process, was captured10.

10 Article 8.3 of the 2011 Consumer Rights Directive dictates that online traders should indicate clearly and legibly at the latest at the beginning of the ordering process whether any delivery restrictions apply and

which means of payment are accepted.

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1.7 Definition of breakdowns

Throughout the report, the incidence of different types of geo-blocking practices is

discussed by comparing relevant groups based on:

1) region and country of the retailer;

2) region and country of the shopper;

3) direction of trade between EU15 and EU13 regions;

4) physical distance between a country pair (based on border or economic center

distance);

5) retailer size based on yearly website traffic;

1.7.1 EU Regions

The first breakdown highlights the degree to which geo-blocking takes place according to

EU regions, i.e. in the EU15 (i.e. those countries that joined the European Union prior to

the accession of the ten candidate countries on May 1, 2004) vs. the EU13 (i.e. those

Member States that joined the European Union on May 1, 2004 or after). Reporting also

takes place according to four distinct geographical regions within the EU: North, East,

South and West. The table below presents an overview of which Member States fall

within each geographical split. Where applicable, throughout the report, regional

differences are considered from two perspectives: the online retailer’s country of origin

and the shopper’s country of origin.

Table 6: Region splits by Member State

EU15 EU13 Region

North

Region

East

Region

South

Region

West

Austria Bulgaria Denmark Bulgaria Cyprus Austria

Belgium Croatia Finland Croatia Greece Belgium

Denmark Cyprus Sweden Czech

Republic Spain France

Finland Czech

Republic

Estonia Italy Germany

France Estonia

Hungary Malta Ireland

Germany Hungary

Latvia Portugal Luxembourg

Greece Latvia

Lithuania

Netherlands

Ireland Lithuania

Poland

UK

Italy Malta

Romania

Luxembourg Poland

Slovakia

Netherlands Romania

Slovenia

Portugal Slovakia

Spain Slovenia

Sweden

UK

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1.7.2 Regional direction of trade

Direction of trade represents a breakdown between the EU region of the country of the

online trader and that of the country of the consumer. Since it would be very laborious to

assess differences based on each of the 143 specific country pairs, all existing pairs were

recoded into regional pairs based on the EU13/EU15 breakdown.

1) EU15 EU15 represents cross-border trade flowing from an EU15 to an EU15

Member State;


Member State;


Member State;


Member State.

For example, for a mystery shopping assessment where the online retailer’s country is

Germany (EU15) and the shopper’s country is Poland (EU13), the direction of trade is

recoded as flowing from EU15 to EU13.

1.7.3 Country pair distance

Country pair distance is a breakdown based on the actual distance (in kilometres)

between the country where the online retailer is based and the country where the

shopper is based (e.g. a retailer based in Ireland and a shopper in the UK). In order to

examine differences in geo-blocking based on country pair distance, the distance

between each country pair in the sample was calculated using two different methods

where distance was defined differently.

The first method defined “distance” as the closest linear distance in kilometres between

the two borders of the country of the retailer and the country of the shopper. According

to this method, each country pair (mystery shopping assessment) was recoded to belong

to one of the three categories below:

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1) Neighbouring – i.e. the country where the retailer is based and the country of the

shopper share a common border11

;

2) Close – i.e. the distance between the country where the retailer is based and the

country of the shopper is less than the average distance between the remaining pairs

of retailers and shoppers;

3) Far – i.e. the distance between the country where the retailer is based and the

country of the shopper is more than the average distance between the remaining

pairs of retailers and shoppers.

The second method defined “distance” as the linear distance in kilometres between the

economic centres of the country of the shopper and the country of the retailer. For

example, for the UK and Austria, the distance between London and Vienna was used. In

line with this method, each country pair (mystery shopping assessment) was recoded

into one of the following three categories:

1) Small distance – i.e. the bottom 33rd percentile of country pairs based on the linear

distance between their two economic centres;

2) Medium distance – i.e the mid (33rd to 67th) percentile of country pairs based on the

linear distance between their two economic centres;

3) Large distance – i.e the top 33rd percentile of country pairs based on the linear

distance between their two economic centres.

Using two different approaches in defining distance between the seller and the shopper

allows for a more in-depth look at the role distance plays in geo-blocking, particularly as

it mostly relates to delivery restrictions.

1.7.4 Retailer size

This breakdown is based on data regarding total yearly website visits12

and the

distinction is between:

Marketplaces13

– retailers for which statistics on total yearly visits fall within +2

standard deviations above the mean yearly traffic. In addition to this rule, a manual

11 Malta and Cyprus do not have neighbouring countries given that they do not share a border. In this analysis, Ireland is treated as having a shared border with the UK given the shared border with Northern Ireland. Nevertheless, this does not take into account delivery restrictions that retailers based in the UK may have to delivering only to the UK mainland.

12 The total yearly traffic data was provided by Similarweb.com based on the final sample of websites assessed and covered approximately 99,3% of the total sample of websites. For more information on the methods

used by Similarweb.com on how to gather website traffic data see Annex 8.1.2.5

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check was conducted to incorporate marketplaces that operate in smaller countries and

may not have exceptionally high traffic.

Small retailers – retailers belonging to the bottom 33rd percentile based on statistics in

relation to the total number of yearly visits they receive;

Medium retailers – retailers belonging to the mid 33rd to 67th percentile based on

statistics about the total number of yearly visits they receive;

Large retailers - retailers belonging to the top 33rd percentile based on statistics about

the total number of yearly visits they receive.

The split between small, medium and large retailers based on the percentiles reported

above was completed only after removing the marketplaces identified.

1.8 Weighting

The original sampling (unweighted data) reflected mostly consumers’ cross-border

shopping from larger EU15 Member States like Germany, the U.K, France, Italy etc. For

example, Germany has shoppers from the remaining 27 EU Member States shopping

online from Germany, whereas Hungary has shoppers from only 2 other Member States

(Romania and Slovakia) shopping online from Hungary. The weighting methodology

employed throughout the report varies depending on the type of breakdown used. For

example, marketplaces and large retailers account for a larger proportion of e-commerce

and, in turn, of cross-border e-commerce compared to small and medium-sized retailers.

There are different types of data that can be used to weight the gathered responses

towards either the size of cross-border e-commerce or the magnitude of the cross-border

websites themselves. In this study, we relied on two general data sources to compute the

weights used throughout the report: a) data on cross-border e-commerce and b) website

traffic data.

13 Marketplaces were defined as online shops that operate in at least three of the surveyed sectors, offering a significantly more varied choice of products (e.g. Amazon, Emag etc.) compared to specialized retailers. As can be expected, the number of marketplaces identified was relatively small (under 100), as a proportion of the total number of websites surveyed (+10 000). Therefore, the variance within the category “marketplaces” (much larger compared to all other retailers) and comparisons between marketplaces and

small, medium and large retailers should be treated with caution throughout the report.

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1.8.1 Weight based on the level of cross-border e-commerce

In the present report, in order to estimate the overall incidence of geo-blocking practices

and better reflect the actual volume of the cross-border e-commerce between each

country pair, the sample was weighted based on the estimated level of cross-border e-

commerce between each country pair. This weight was built with data from two different

sources:

The total level of cross-border trade of tangible goods and offline services per

country, based on the 2015 DSM Consumer Survey14

.

The proportion of cross-border purchasing that online consumers engage in

(based on self-reporting) per import/retailer country (re-totalled to 100%)15

.

Even though two weights were computed overall, this particular one is utilized the most

in the report since it led to more balanced results compared to the weight based on

website traffic data. This weight indeed gives more emphasis to the stronger e-commerce

country pairs (for example, Austrians buying online from Germany), capturing the reality

that most trade in terms of volumes takes place between large EU15 Member States.

1.8.2 Weight based on yearly cross-border website traffic

This weight was based on two sets of website traffic data:

Similarweb total yearly traffic data (covers 99.3% of the sample) for each website

assessed, from which the domestic traffic data was subtracted to arrive at an

estimate of the yearly cross-border traffic for each of the websites assessed.

Alexa aggregated cross-border traffic data per country pair, for online sectors

similar to the ones assessed in the report. This data was used as a population

estimate to introduce the country pair dimension to the individual websites’ cross-

border traffic, in order to make the weighting strategy more meaningful to our

exercise.

Since the sample includes only a handful of cross-border mystery shopping attempts per

website (even for very large websites like amazon.de), these cases receive an

exceptionally high weight according to this method. However, a few cases assessed

within our sample might not be representative of the overall incidence of geo-blocking

that occurs on marketplaces and large shopping websites. As such, the website traffic

weight might give somehow biased results and is used with caution throughout the

14http://ec.europa.eu/consumers/consumer_evidence/market_studies/obstacles_dsm/docs/21.09_dsm_final_report.pdf, pg. 131 15 2015 DSM consumer survey, page 78

EUROPEAN COMMISSION

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report, either for comparison purposes or to possibly shed light on findings that appear

counterintuitive. For some of the data in the study, where results are presented by

country of retailer/shopper or per EU region, any weighing of the data would have

skewed results even more towards the EU15, so in those cases the unweighted data was

presented instead.

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2 Geo-blocking prevalence across the EU28

2.1 Geo-blocking and the four stages of the shopping process

This section is focused on identifying the overall prevalence of geo-blocking practices in

cross-border online shopping. Geo-blocking practices can be divided into four main

categories: denial of access to a website, automatic re-routing, refusal to sell,

and changing the terms and conditions and/or prices. Each practice can take

different forms and can happen at different stages of the shopping process. In some

cases geo-blocking takes place immediately or automatically. Still, in the majority of

cases consumers spend significant time and effort on a website, attempting to make a

cross-border online purchase, before realising that the seller or service provider will not

sell to them or will only sell under different terms and conditions. In order to provide a

clear overview of geo-blocking practices, these are reported from the perspective of the

stage during the shopping process at which geo-blocking occurred. The online shopping

process can be broken down into four key stages during which different types of geo-

blocking practices can occur: access, registration, delivery and payment. A specific

proportion of cross-border shoppers are blocked at each of these stages of the shopping

process. Below is a summary of the types of geo-blocking practices that can occur in

each of the four shopping stages within the scope of the mystery shopping survey.

Access – website access is the first stage of the shopping process. It is defined as the

stage at which shoppers enter a website and can view product information (e.g. a

product page including specifications, pricing and delivery details). At this stage, three

key geo-blocking practices can potentially take place: denial of access, automatic re-

routing and changing the terms and conditions by altering product availability. The

present chapter looks at the access stage as a combination of these three types of geo-

blocking, while Chapter 3 explores these activities individually to provide more in-depth

insight into the prevalence of geo-blocking at the website access stage.

Registration – registration is defined as the stage at which, after finding a product they

wish to purchase, consumers need to provide specific personal information to the online

retailer in order to identify themselves and be able to complete the online purchase. The

requirements at this stage vary significantly per retailer and are explored more in-depth

in Chapter 4, which focuses on the registration stage. The present chapter presents the

prevalence of geo-blocking practices during the registration stage as the proportion of

mystery shopping assessments that were terminated prematurely due to an issue/s

related to unsuccessful registration. It is important to note that some of these issues

EUROPEAN COMMISSION

25

were closely linked to delivery, e.g. delivery address not being accepted. Nonetheless,

they are reported as part of the registration stage.

Delivery – delivery is defined as the stage at which consumers need to provide their

shipping information related to a specific purchase that they are attempting to complete.

This stage normally takes place after registering or providing the necessary personal

information on the website and after having chosen the product that they wish to

purchase online. Delivery is explored more in-depth in Chapter 5. The present chapter

looks at the incidence of geo-blocking during the delivery stage, as the proportion of

websites that refused to accept consumers’ shipping information because consumers’

delivery address is located in a country to which they do not ship.

Payment – payment is the last stage of the shopping process and is defined as the

stage at which consumers are required to select their preferred payment method and

enter their payment card details in order to complete a specific online purchase. This

stage normally takes place after successfully entering the shipping information. The

prevalence of geo-blocking during the payment stage is explored more explicitly in

Chapter 6. The present chapter considers geo-blocking during the payment stage, as a

combination of consumers’ preferred payment method not being accepted/offered and

errors occurring during entering their payment card details.

Overall – the overall incidence of geo-blocking is defined as the total proportion of

mystery shopping assessments (at website level) that were terminated prematurely at

any of the 4 shopping stages. More specifically, it is computed as the proportion of

assessments during which mystery shoppers did not reach the order confirmation stage

where they successfully entered their payment details.

2.2 Overview of geo-blocking prevalence during each stage of the

shopping process

The graph below represents a summary of the proportion of retailers who engage in geo-

blocking practices at each stage of the online shopping process16

. At the beginning of the

mystery shopping assessments, approximately 5% of online retailers engaged in

automatic re-routing, directly blocked mystery shoppers or changed their product

16 Data is weighed by the level of cross-border e-commerce

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26

offerings based on a shopper’s country of residence or IP address17

. During website

registration, 27% of online retailers blocked cross-border mystery shoppers by

preventing them from successfully registering on their website in order to place an order.

These practices relate to any of five different pieces of personal information provided by

the shopper not being accepted by the website. The most common registration issue

reported by mystery shoppers was their foreign delivery address not being accepted by

the website. This suggests that outright refusal to sell in the form of delivery restrictions

is a common means of geo-blocking that online shoppers experience already during the

website registration stage. Even after allowing mystery shoppers to successfully register

on their website, 32% of online retailers assessed during the delivery stage refused to

deliver a product or provide an online service to shoppers if the delivery address they

entered was outside a predefined list of countries to which the seller or service provider

delivers. Considering only the mystery shoppers who reached the final stage of the online

shopping process, 26% of online retailers refused to sell to them because of payment-

related issues (either the payment method was not offered/accepted or errors occurred

whilst entering one’s payment card details). Overall, geo-blocking practices were

identified in approximately 63% of all assessed websites18

.

17 The 5% reported here includes websites which blocked or redirected shoppers and those where shoppers could not find the exact same product for at least one of the two products that they assessed per website. As such, 5% relates to the aforementioned issues experienced at the access shopping stage but, as seen in Figure 2 that follows, the proportion of websites which blocked or re-routed shoppers without allowing them to further continue their shopping procedure did not surpass 2%. It should be noted that in those cases where shoppers were re-routed, they were instructed to try and go back to the original website in order to try to find the 2 very same products that they had assessed as part of their domestic website visit.

18 The overall geo-blocking prevalence (i.e. 63% in our case) might be difficult to interpret from this graph since it is cannot be represented by the sum of the geo-blocking incidences at each stage of the shopping process due to differences in the base sizes used. A breakdown of how each stage of the shopping process contributes to the overall geo-blocking can be seen in Figure 2 (see the following section). The current graph presents geo-blocking at each separate stage of the shopping process by taking into account only those mystery shoppers who actually reached that particular stage (e.g. 32% of those shoppers who reached the delivery stage were geo-blocked). As such, the overall figure corresponds to all shoppers who did not reach

the order confirmation stage.

EUROPEAN COMMISSION

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Figure 1: Geo-blocking prevalence at different stages of the online shopping process

expressed as a proportion within each stage of the shopping process

Source: Q11, Q13, Q15 - Access, N = 10537; Q19 - Registration, N = 10382; Q20 – Delivery, N =

7628; Q24, Q25 – Payment, N = 5180; weighted data.

2.3 Contribution of geo-blocking practices of each stage of the shopping

process (as a proportion of the overall process)

The previous section reported on the proportion of online retailers who engaged in

certain forms of geo-blocking practices within each stage of the online shopping process

by looking at the incidence of geo-blocking based on mystery shoppers who reach a

specific stage. This section presents a graphic overview of the contribution of each stage

of the shopping process to the total geo-blocking, as a proportion of the overall process.

At the access stage, less than 2% of mystery shopping assessments were terminated due

to automatic re-routing or outright blocking of cross-border mystery shoppers (not taking

into account the differences observed with product availability). During the website

registration stage, approximately 26% of all mystery shopping assessments ended

because retailers did not accept one or more of the personal details that shoppers were

asked to provide during registration. After successful registration, another 23% of all

mystery shopping assessments were terminated due to delivery restrictions (when

shoppers had to enter a foreign delivery address to continue with the online process).

Immediately before confirming the cross-border order, approximately 12% of all

shopping assessments were recorded as unsuccessful due to issues related to the

payment method not being accepted or an error experienced with the payment details

provided. Looking at the overall level of geo-blocking at each stage of the shopping

5% 27% 32% 26%

Geoblocking - per shopping stage

Access Registration Delivery PaymentOverall 63%

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process, only slightly over one third (37%)19

of the mystery shopping assessments

conducted reached the last shopping stage (order confirmation) during a realistic online

shopping scenario. These figures suggest that geo-blocking practices represent, to a

large extent, a reality which currently prevents shoppers from accessing goods and

services within the Digital Single Market.

Figure 2: Contribution of each stage of the online shopping process, expressed as a

proportion of all websites assessed

Source: Q11, Q13, Q15 – Access; Q19 - Registration; Q20 – Delivery; Q24, Q25 – Payment; N = 10537, weighted data.

2.4 Mystery shopping success rates (% of all shopping attempts) –

comparing the different weights used

This section presents the incidence of geo-blocking by looking at the proportion of

mystery shopping assessments that were successful after each stage of the shopping

process was completed, as a proportion of all websites assessed. The breakdown also

serves as a comparison of the two weights used, as opposed to the raw data when no

weights were applied.

Using the e-commerce weight, 98% of all websites allowed mystery shoppers to go to

the exact website they aimed to visit, without being blocked or automatically redirected.

This number is very close to the unweighted data (98,1%), while using the website traffic

data, this proportion is significantly lower (91,6%). This difference can be attributed to

the fact that the website traffic weight assigns more importance to websites with high

cross-border traffic, which are also more likely to geo-block consumers at the access

19 37% is calculated as follows: 100% – (2%+26%+23%+12%)

2% 26% 23% 12% 37%

Geoblocking - overall

Access Registration Delivery Payment Successful shoppers

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stage by blocking, redirecting them or changing their product offers when a consumer is

located abroad.

A smaller difference in the same line can be observed with websites where mystery

shoppers were able to find the same product cross-border: 94,2% based on the website

traffic weight vs. 97,2% and 97,1% based on the e-commerce weight and the

unweighted data, respectively. As will also be seen below, significant differences are

observed when comparing the analysis of website traffic weighted data to that of the e-

commerce weighted data or the unweighted data. This suggests that if marketplaces or

large websites are given a higher weight corresponding to the cross-border traffic they

generate, the proportion of consumers who faces issues during the access stage (based

on re-routing, blocking and product availability) would be significantly higher than when

the sample is only weighted by the level of cross-border e-commerce (or with no weights

applied). In reality, the prevalence of geo-blocking at the access stage would be more

substantial when looking at it from the perspective of the level of cross-border website

traffic.

While 68,3% of the unweighted mystery shopping assessments (websites) continued to

the delivery stage after shoppers successfully registered on the website, this number was

75,4% when the website traffic weight is applied and 72,4% with the e-commerce based

weight.

Here, it is particularly important to notice the large drop of the success rates between the

registration and delivery stages when using the website traffic weight (from 75% to as

low as 32%)20. This sudden decrease during the delivery stage is likely to be due to the

difference in geo-blocking practices between large and small online retailers. Small and

medium retailers are much less likely to geo-block at this stage compared to large

retailers and marketplaces (see Section 2.12); the latter are given a much bigger weight

when the data are weighted by website traffic. As such, the drop between registration

and delivery is much more acute than observed with the e-commerce weighted data,

where the weights are based on the level of cross-border e-commerce between country

pairs (49,2% success rate with the latter vs. only 32% with the former).

Looking at the success rates at all stages, the e-commerce weight provides the most

conservative interpretation of the obtained results, with 36,6% of the shopping attempts

reaching the last stage of the process, where payment card details are entered

successfully. Using the website traffic weight, this proportion drops to 30,1% and it is

20 75% corresponds to 7902 websites which allowed shoppers to successfully register, as opposed to only 3771

websites where no delivery restrictions were imposed (32%).

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equal to 31% with the unweighted data. Since both types of weights are not standard

and do not use reliable population statistics (they were prepared accordingly for this

mystery shopping exercise), we have opted to use the more conservative weight

throughout the report, in order to avoid overestimating the incidence of geo-blocking due

to inherent issues with the validity of the weighting data.

Figure 3: Success rates in terms of not encountering various forms of geo-blocking, as a

proportion of all websites assessed -comparison of weighted and unweighted data

Source: Q11, Sent to same website; Q13, Q15 find same product; Q19 – Can register successfully; Q20 – Delivery is possible; Q24 – Payment is possible; Q25 – Can enter payment details; N = 10537

2.5 Prevalence by seller’s country of origin and EU region 21

Comparing the overall prevalence of geo-blocking practices by region (unweighted data),

retailers based in the EU13 (84%) are more likely to block online shoppers based on their

geographic location compared to retailers based in the EU15 (66%). This difference

21 Our sampling was based on the size and direction of cross-border e-commerce (most of the trade originates from the larger EU 15 Member States like Germany, UK etc.). As such, the sample is unbalanced when it comes to country of retailer and region comparisons. Applying a weighting strategy would lead to an even higher imbalance because it would give more weight to the bigger country retailers. Hence, taking this into account, in order for region and country comparisons to be meaningful their analysis is based on unweighted

results.

91,6%

94,2%

75,4%

32%

31,3%

30,1%

98%

97,2%

72,4%

49,2%

41,9%

36,6%

98,1%

97,1%

68,3%

42,5%

36,4%

31%

Sent to samewebsite

Find same product

Can registersuccessfully

Can have productdelivered

Possible to pay

Can enter paymentdetails successfully

Success rates per weight

Weight 1

Weight 2

Unweighted

EUROPEAN COMMISSION

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appears to stem primarily from delivery restrictions (52% in the EU13 vs 35% in the

EU15) and issues linked to payment (52% in the EU13 vs 24% in the EU15) which are

both more common with EU13-based online retailers. Overall, geo-blocking is most

common when shopping from online retailers in Eastern Europe (84%) and least common

with Western European online retailers (65%). Geo-blocking practices at the access

shopping stage22 are slightly more common for South-Europe based retailers (6%) and

least common by Northern European ones (3%), whereas retailers from the South are

the most likely to geo-block shoppers during website registration (38%). Online retailers

operating in the Eastern and Northern parts of Europe are the most likely to geo-block

shoppers by means of applying delivery restrictions (52% for both), whereas Eastern

European online retailers stand out as by far the most likely to geo-block consumers due

to payment-related issues (53% vs only 19% by Northern ones).

Figure 4: Geo-blocking prevalence at different stages of the online shopping process by

retailers’ region (expressed as a proportion within each stage of the process)

Source: Q11, Q13, Q15 - Access, N = 10537; Q19 - Registration, N = 10366; Q20 – Delivery, N = 7198; Q24, Q25 – Payment, N = 4485; unweighted data.

Comparisons based between specific Member States in which online retailers are based

are consistent with the observations made above by region but reveal more subtle

country-specific differences. Hungary, Cyprus, Lithuania and Bulgaria were the Member

States most likely to geo-block online shoppers with at least 90% of all mystery shopping

22 Blocking access, website re-routing or not offering the same product

5%

4%

3%

4%

6%

5%

31%

28%

34%

29%

38%

29%

35%

52%

52%

52%

31%

36%

24%

52%

19%

53%

29%

23%

EU15

EU13

North

East

South

West

Region of the retailer

Access

Registration

Delivery

Payment

66%

Overall

84%

75%

84%

70%

65%

EUROPEAN COMMISSION

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assessments not reaching the final order confirmation stage. In contrast, the UK,

Luxembourg, Spain, Ireland and France were the least likely to geo-block shoppers who

shop online from other countries with the overall geo-blocking reaching a maximum of

64%. Geo-blocking related to access was most prevalent with Luxembourgish, Czech,

Estonian and Portuguese online retailers and was not observed at all for online shops

based in Slovakia, Slovenia and Denmark. Half of the Italian, Dutch and Hungarian

websites surveyed blocked mystery shoppers during the registration phase, with

Portuguese online retailers in the lead (52%). Retailers based in Hungary (79%),

Romania (72%) and Finland (65%) were the most likely to impose delivery restrictions

after mystery shoppers completed the registration stage. Payment-related issues were

most common on websites based in Hungary (88%), Cyprus (79%) and Lithuania (77%).

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country of retailer (expressed as a proportion within each stage of the process)


2.6 Prevalence by shopper’s country of residence and EU region

Looking at the unweighted results based on shoppers’ origin, online retailers were more

likely to geo-block shoppers from the EU13 (74%) compared to EU15 (64%). Mystery

shoppers residing in the Eastern part of Europe were the least likely to reach the order

confirmation stage (26%) while those residing in the Western or Northern parts were the

most likely (36% and 35% respectively). The largest differences between these regions

were based on geo-blocking stemming from delivery restrictions (43% in the East vs.

5%

6%

8%

7%

2%

2%

1%

11%

10%

12%

11%

2%

2%

10%

3%

6%

3%

1%

4%

6%

9%

4%

5%

5%

18%

6%

31%

51%

40%

24%

39%

23%

40%

25%

7%

6%

30%

31%

52%

33%

35%

51%

42%

6%

50%

7%

21%

29%

3%

35%

21%

29%

27%

19%

21%

38%

79%

33%

53%

56%

72%

46%

53%

61%

44%

65%

44%

16%

48%

39%

17%

51%

49%

23%

52%

36%

35%

50%

34%

46%

39%

32%

29%

35%

27%

88%

79%

77%

63%

29%

48%

50%

52%

66%

18%

45%

38%

24%

32%

32%

5%

43%

25%

35%

40%

31%

27%

18%

15%

14%

24%

31%

18%

EU28

Hungary

Cyprus

Lithuania

Bulgaria

Romania

Poland

Estonia

Slovenia

Slovakia

Finland

Czech Republic

Portugal

Sweden

Austria

Netherlands

Denmark

Greece

Italy

Croatia

Latvia

Germany

Malta

Belgium

Ireland

France

Spain

Luxembourg

the UK

Country of the retailer

Access

Registration

Delivery

Payment

99%

92%

92%

90%

85%

83%

83%

83%

82%

80%

79%

75%

75%

73%

73%

73%

73%

72%

72%

70%

69%

69%

66%

64%

64%

63%

63%

58%

Overall

69%

EUROPEAN COMMISSION

34

28% in the West) and payment issues (32% in the East vs. 24% in the West and 21% in

the North of Europe).


shoppers’ EU region (expressed as a proportion within each stage of the process)


UK-based online shoppers were the least likely to experience geo-blocking during the

mystery shopping assessments (57%), followed by Belgium (57%) and Portugal (60%)

based ones. Shoppers from Latvia (78%), Slovakia (77%) and Malta (77%) were the

most likely. This is quite interesting a result for Malta since this is the country where

cross-border e-commerce is the second highest according to ESTAT (after Luxembourg)

and the highest according to the 2015 DSM Consumer Survey. Overall, the country

differences in geo-blocking prevalence at the different stages of the shopping process are

less pronounced when exploring them from the perspective of shoppers’ country of

residence. While this initial observation needs to be explored further, it is an indication

that the primary motivations behind geo-blocking practices may stem from retailers’

rather than shoppers’ origin.

5%

5%

3%

5%

4%

6%

29%

32%

24%

32%

29%

32%

32%

44%

41%

43%

37%

28%

24%

32%

21%

32%

27%

24%

EU15

EU13

North

East

South

West

Region of the shopper

Access

Registration

Delivery

Payment

74%

64%

64%

68%

74%

65%

Overall

EUROPEAN COMMISSION

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country of shopper (expressed as a proportion within each stage of the process)23


2.7 Prevalence by country pair

The table below presents an overview of the incidence of geo-blocking per country pair

surveyed, with country of the seller presented in columns and country of the shopper

presented in rows. The level of geo-blocking is indicated in percentages as well as in a

23 For easier comparison between countries, note that the EU28 overall geo-blocking also corresponds to the

unweighted data, hence is different to the 37% (weighted data).

5%

7%

5%

5%

5%

7%

6%

4%

5%

9%

4%

4%

8%

5%

3%

5%

8%

7%

4%

8%

3%

5%

5%

4%

1%

6%

2%

6%

4%

31%

22%

44%

35%

33%

41%

36%

34%

27%

25%

32%

27%

25%

31%

17%

30%

31%

34%

23%

32%

25%

25%

35%

30%

26%

36%

23%

27%

28%

38%

50%

40%

47%

51%

43%

30%

43%

47%

38%

42%

42%

37%

34%

46%

41%

32%

35%

40%

25%

42%

38%

28%

30%

41%

23%

33%

20%

32%

27%

41%

32%

33%

27%

24%

43%

33%

28%

39%

24%

30%

36%

33%

30%

23%

29%

24%

28%

29%

16%

21%

21%

24%

13%

21%

22%

26%

11%

EU28

Latvia

Slovakia

Malta

Bulgaria

Croatia

Czech Republic

Romania

Estonia

Poland

Lithuania

Slovenia

Netherlands

Greece

Hungary

Cyprus

Ireland

Germany

Finland

France

Denmark

Italy

Luxembourg

Spain

Sweden

Austria

Portugal

Belgium

the UK

Country of the shopper

Access

Registration

Delivery

Payment

Overall

69%

57%

57%

60%

61%

62%

63%

63%

63%

65%

65%

67%

68%

68%

69%

69%

70%

70%

71%

71%

72%

73%

75%

75%

75%

76%

77%

77%

78%

EUROPEAN COMMISSION

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colour gradient ranging from green (lowest value) to red (highest value) with a yellow

mid-point (50th percentile). This breakdown allows for a more detailed interpretation of

the varying prevalence of geo-blocking not only by country of the retailer and country of

the shopper but also by specific country pair. For example, Austrian shoppers are more

likely to be geo-blocked by Italian (76%) and Dutch (71%) retailers compared to German

(49%) and UK (46%) retailers. Surprisingly, Belgian-based mystery shoppers were most

likely to experience geo-blocking when shopping at online retailers based in the

Netherlands (72%), a neighbouring country which also shares a common language with

Belgium, compared to online retailers in the UK (44%) and France (51%). UK-based

retailers were most likely to block shoppers from Malta (86%), Germany (79%) and the

Netherlands (78%).

Looking closer at the table, some key differences in the variability of geo-blocking for

specific countries (from a shopper’s perspective) could be observed. More specifically,

shoppers from Malta were consistently geo-blocked above average by all retailer

countries surveyed, a range between 71% (from France) to 86% (from the UK). In

contrast, this range was a lot larger for shoppers from Ireland, who were geo-blocked in

50% of their shopping assessments by UK-based retailers and in as many as 94% by

Italian-based online retailers. Retailers based in France were least likely to geo-block

shoppers from the UK (46%), Luxembourg (49%), and Belgium (51%), while German-

based retailers were most willing to sell cross-border to shoppers from Austria (49%

overall geo-blocking) and Sweden (51%). In addition, Spanish online retailers were

overall less likely to geo-block consumers compared to Italian retailers, with the

exception of shoppers residing in Greece, 55% of whom were blocked by Italian online

retailers compared to 72% by Spanish ones. Online retailers based in the UK were most

likely to sell goods cross-border to shoppers residing in Eastern and Central Europe,

compared to other retailers from other major markets such as Germany and France. For

example, Hungarian shoppers were geo-blocked by 93% of French and 83% of German

online retailers but by only 51% of UK retailers. A similar trend can be observed for

shoppers residing in Bulgaria, who were geo-blocked by 76% of German compared to

64% of UK-based retailers.


Table 7: Overall geo-blocking prevalence by country pair surveyed

Country of the seller

Co

un

try o

f th

e s

ho

pp

er

C AT BE BG HR CZ CY DK EE FI FR DE EL HU LV LT LU IE IT MT NL PL PT RO SK SL ES SE UK

AT 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 65,1% 48,5% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 76,3% 0,0% 70,8% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 45,7%

BE 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 50,6% 62,0% 0,0% 0,0% 0,0% 0,0% 62,5% 0,0% 0,0% 0,0% 71,9% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 43,8%

BG 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 71,8% 75,9% 81,2% 0,0% 0,0% 0,0% 0,0% 0,0% 79,5% 0,0% 0,0% 0,0% 0,0% 84,5% 0,0% 0,0% 0,0% 0,0% 64,1%

HR 79,3% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 62,1% 78,8% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 79,2% 0,0% 80,9% 0,0% 0,0% 0,0% 0,0% 82,7% 0,0% 0,0% 62,7%

CZ 82,4% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 68,7% 72,6% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 90,7% 0,0% 0,0% 90,8% 0,0% 0,0% 0,0% 43,1%

CY 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 84,1% 64,9% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 56,7%

DK 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 60,5% 74,6% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 78,2% 47,6%

EE 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 80,3% 0,0% 71,8% 0,0% 0,0% 70,4% 0,0% 0,0% 0,0% 63,0% 0,0% 0,0% 87,7% 90,0% 0,0% 0,0% 0,0% 0,0% 77,4% 60,8%

FI 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 78,9% 0,0% 72,9% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 66,2% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 52,0% 68,8% 56,2%

FR 0,0% 63,8% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 74,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 73,7% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 63,5% 0,0% 50,0%

DE 65,9% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 56,7% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 68,8% 0,0% 72,2% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 79,3%

EL 0,0% 0,0% 89,9% 0,0% 0,0% 91,7% 0,0% 0,0% 0,0% 61,3% 70,0% 0,0% 0,0% 0,0% 0,0% 0,0% 54,8% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 72,2% 0,0% 48,7%

HU 65,9% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 93,3% 82,6% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 74,7% 0,0% 0,0% 0,0% 51,1%

LV 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 87,0% 0,0% 64,3% 72,1% 0,0% 0,0% 91,7% 0,0% 0,0% 0,0% 0,0% 0,0% 76,4% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 65,4%

LT 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 75,0% 72,5% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 77,8% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 63,8%

LU 64,7% 72,9% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 49,4% 65,7% 0,0% 0,0% 0,0% 0,0% 0,0% 69,4% 0,0% 70,4% 0,0% 68,7% 0,0% 0,0% 0,0% 0,0% 0,0% 47,4%

IE 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 68,5% 63,0% 0,0% 0,0% 0,0% 0,0% 0,0% 93,7% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 66,7% 0,0% 50,0%

IT 68,3% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 67,6% 63,6% 0,0% 0,0% 0,0% 0,0% 0,0% 65,9% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 59,2% 0,0% 54,9%

MT 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 71,0% 78,1% 0,0% 0,0% 0,0% 0,0% 0,0% 72,6% 83,8% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 74,7% 0,0% 86,4%

NL 0,0% 60,3% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 71,8% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 77,8%

PL 0,0% 0,0% 0,0% 0,0% 82,4% 0,0% 0,0% 0,0% 0,0% 0,0% 70,1% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 62,3%

PT 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 69,7% 60,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 55,1% 0,0% 60,8%

RO 79,5% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 80,0% 64,7% 0,0% 98,7% 0,0% 0,0% 0,0% 0,0% 81,8% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 60,5% 0,0% 63,3%

SK 75,6% 0,0% 0,0% 0,0% 75,4% 0,0% 0,0% 0,0% 0,0% 0,0% 59,5% 0,0% 98,7% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 83,8% 0,0% 0,0% 0,0% 0,0% 0,0% 68,9%

SL 78,5% 0,0% 0,0% 71,8% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 70,3% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 67,6% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 66,7%

ES 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 77,4% 61,1% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 57,6% 0,0% 0,0% 0,0% 81,0% 0,0% 0,0% 0,0% 0,0% 50,7%

SE 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 73,0% 0,0% 0,0% 0,0% 50,7% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 62,2%

UK 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 46,2% 62,2% 0,0% 0,0% 0,0% 0,0% 0,0% 52,9% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 61,4% 0,0%

Source: Q25 – Can enter payment details; N=10537


2.8 Prevalence by direction of trade – EU15 and EU13

In addition to comparing the incidence of geo-blocking by EU region, the availability of

data on the origin of both the retailer and the shopper allows for a comparison of geo-

blocking practices based on the direction of the flow of cross-border e-commerce. The

figure below presents a breakdown of the incidence of geo-blocking at each stage of the

shopping process by the direction of trade between EU15 and EU13, as well as within the

regions themselves.

Overall, geo-blocking is least prevalent when online shopping takes place within the EU15

(63%). Interestingly, geo-blocking is most prevalent when trade occurs from an EU13 to

another EU13 country (84%). Retailers based in the EU15 are less likely to geo-block

shoppers residing in the EU13 (71%) compared to trade flowing in the opposite direction,

from EU13 to EU15 (82%). Differences in geo-blocking based on the direction of trade

are small at the access stage (4% for EU13 to EU13 vs. 7% for EU13 to EU15). Geo-

blocking at the registration stage is most likely to take place when trade flows from EU15

to EU13 (33%). The biggest differences can be observed when considering the delivery

and payment stages. Overall retailers based in the EU15 are less likely to impose delivery

restrictions to cross-border shoppers residing within the EU15 (32%) compared to

shoppers residing in the EU13 (40%). Online retailers based in the EU13 are, overall,

more likely to impose delivery restrictions and, interestingly, this happens more often

when shoppers reside within the EU13 (53%) compared to outside this region (47%).

This could be due to EU13 online retailers addressing more consumers from larger, more

affluent cross-border markets within the EU15.

When it comes to geo-blocking during the payment stage, the overall trend remains that

EU15-based retailers are less likely to geo-block based on payment restrictions, with

payment issues being less likely when trade flows towards the EU15 (23%), compared to

the EU13 (26%). Regardless of whether they reside in the EU15 or the EU13, shoppers

attempting to make a cross-border online purchase are more than twice as likely to be

blocked by EU13 retailers (53% for EU13 shoppers and 52% for EU15 shoppers).

EUROPEAN COMMISSION

39


direction of trade (EU15 and EU13 regions)


2.9 Prevalence by sector

The breakdown of geo-blocking practices per sector shows that the overall prevalence of

geo-blocking varies substantially depending on the individual sector and even more so

when comparing tangible goods with online services. In the Electrical household

appliances sector 86% of the mystery shopping assessments ended prematurely because

of geo-blocking practices compared to only 60% of the assessments within the Books

sector. Looking at online services to be used offline, geo-blocking practices were not as

common, resulting in incomplete purchases in only 33% and 40% of the websites

assessed for Travel services and Online reservations of offline leisure, respectively. The

overall prevalence of geo-blocking is at least double for most tangible goods sectors

compared to the Travel services sector.

The breakdown per shopping stage reveals an even wider variability based on the type of

geo-blocking practices observed at each stage. Most notably, service providers were

more likely to geo-block mystery shoppers at the access stage of the shopping process

(9% for Travel services and 7% for Online reservations of offline leisure) compared to

most of the tangible goods markets where the range was between 3-6% amongst online

sellers. It appears that the following 3 stages contribute to the difference in the overall

geo-blocking prevalence between services and tangible goods sectors. The most

5%

4%

6%

7%

29%

28%

33%

29%

32%

53%

40%

47%

23%

53%

26%

52%

EU15 to EU15

EU13 to EU13

EU15 to EU13

EU13 to EU15

Direction of trade

Access

Registration

Delivery

Payment

63%

84%

71%

82%

Overall

EUROPEAN COMMISSION

40

pronounced difference was the prevalence of geo-blocking during registration (40% for

Electrical household appliances vs. only 10% for Travel services) and right after

registration (58% for Electrical household appliances vs. only 7% for Travel services),

when entering one’s delivery address in order to proceed with the specific online

purchase. When it comes to payment-related issues, the Books sector scored particularly

high, with 39% of online retailers blocking shoppers due to their payment method not

being accepted or for other payment-related errors (after the electrical household

appliances sector where the proportion was as high as 44%).


sector

Source: Q11, Q13, Q15 - Access, N = 10537; Q19 - Registration, N = 10382; Q20 – Delivery, N = 7628; Q24, Q25 – Payment, N = 5180; weighted data.

2.10 Prevalence by product category

The breakdown presented in the previous section already revealed some significant

variability per sector in retailers

Documents

Mystery shopping survey on territorial restrictions and geo … · b) Does volume of trade have an impact (e.g. more geo-blocking for countries with a low level of cross-border trade