Google shopping EU benchmark - Idealo · 2020-06-16 · Spain Idealo Sweden PriceRunner United Kingdom Prisjakt Findings • Prices in GSU for all offers were on average (mean) 13.7%

© 2019 Grant Thornton Sweden AB | Data analysis – Google shopping EU benchmark study | 2019-05-07

Google shopping EU benchmark Data analysis study

7 May 2019

© 2019 Grant Thornton Sweden AB | Data analysis – Google shopping EU benchmark study | 2019-05-07 2

Contents

Section Page

Background, scope and findings 3

Methodology 4 – 5

Outcome of the study 6 – 7

Transmittal letter 8


Background

Grant Thornton Sweden AB has been contacted by PriceRunner International AB to

collect data and analyse the difference in consumer value between Google shopping

Units (“GSU”) and major comparison shopping services sites (“CSS”) in selected EU

markets.

Scope

The study includes the 10 most popular products in the 10 most popular categories in

the 12 countries and CSS’s listed to the right. Total number of products included in the

study is 1,200.

The following parameters are included in the study:

• Mean (“average”) and median price in respect of: the first offer; top 3 offers and top

5 offers.

• Number of incorrect offers among five first offers.

• Number of properties (specifications) for each product.

Background scope and findings

Markets and CSS

Market CSS

Austria Idealo

Belgium Compare Group

Denmark PriceRunner

France Idealo

Germany Idealo

Ireland Prisjakt

Italy Idealo

Netherlands Compare Group

Poland Prisjakt

Spain Idealo

Sw eden PriceRunner

United Kingdom Prisjakt

Findings

• Prices in GSU for all offers were on average (mean) 13.7% higher compared to the

CSS. The median difference in price was 7.2%

• The price difference varies between markets. In some countries the difference is

around 30% whereas other countries have very small differences.

• The price differences vary between product groups. Toys and books and clothes and

shoes have the largest price differences whereas kitchen appliances and computers

have the smallest differences in price.

• The share of incorrect offers was in average 23% for GSU and 6% for CSS.

• Average (mean) number of properties for GSU was 4.2 and median number of

properties for CSS was 20.


Methodology

Preparations

Each CSS distributed a list of 100 products per country. We understand that the list

includes the 10 most popular products in the 10 most popular categories based on web

traffic data in each CSS.

The VPN software F-secure freedome was installed in order to collect data from each

market as a consumer in the specific market.

Data collection

The data collection was performed by three associates at Grant Thornton during the

period 22 February – 6 March. Data collection was performed for one country at a time

by searching for the products in Google and the CSS. F-secure freedome was used to

receive an IP-address connected to each country. Data was collected in the following way

for each parameter:

• The five first prices were collected in the order the products were presented at google

and the CSS (top to bottom or left to right). If fewer than five offers were displayed,

data was only collected for the number of offers displayed.

• The offer were verified at the merchant’s site if the price differed substantially from

other offers.

• Price information was collected from the merchant site if it was not displayed in the

CSS or GSU.

• Only prices excluding shipping costs or free shipping costs were collected. Prices

including shipping costs were ignored. Please see the exception and assumption

section for further comments.

• Prices for incorrect offers were ignored. Incorrect offers are discussed further down.

• The study includes only data from the first five offers. No offers below the first five

offers were included even tough prices from the first five offers were ignored (for the

reasons listed below).

• If no offers were found at either the GSU or the CSS the product was removed from

the study altogether. 111 products were removed for this reason (most of them were

removed since no GSU offers was displayed).

• Only the first price offered by a merchant was collected. If the search results showed

several offers from the same merchant, the latter offers from that merchant were

ignored and not included in the first five offers.

• Offers were classified as incorrect for the following reasons:

- Wrong product

- Refurbished or used product

- Products as a part of a subscription arrangement

- Non-existing products

- Non-functional links to merchants

- Product not deliverable to the specific country

• When counting the number of properties from the CCS’s and GSU’s, all existing

product information such as dimensions, ratings, etc. was included.

• Number of properties was capped at 20; i.e. search results for offers with more than

20 properties were collected as 20.

Exceptions and assumptions

• All prices are including shipping for two of the CSS whereas the GSU always includes

prices excluding shipping. In order to have comparable prices, we received a

complete excel list of prices excluding shipping directly from the CSS. One product in

each category (total 10 products) was randomly compared to the CSS site in order to

verify that the prices in the excel list were correct. The deviation between the excel list

and the CSS was low and is in line with a normal freight cost. Hence, we consider the

data received from the CSS as reliable and included it in our study.


Methodology

Exceptions and assumptions (cont.)

• For some products sizes or volumes were not specified. This may impact the

comparability as products of different sizes or volumes are compared with each other.

For example, sizes and volumes were not specified for some perfumes or TV’s which

could impact comparability as the price will differ when comparing a large (50 ml)

perfume bottle with a small (25ml) one. In such cases, a specific volume/size was

determined and added to the product name when searching for the products.

Quality check of collected data

The collected data was quality checked by analysing all outliers. A second search was

made for all products with an average difference in price between CSS and GSU of +/-

60%


Outcome of the study


• For all offers, the GSU prices were on average (mean) 13.7% higher compared to the

CSS. The median difference in price was 7.2%.

• The difference in prices was higher for the first offer compared to the top 3 and 5

offers. The higher price difference is partly explained by the fact that the CSS always

displays the cheapest product first whereas the GSU offers are not arranged by price.

• The price difference varies between the markets. In some countries the difference is

around 30% whereas other countries have very small differences.

• All 100 products are not included in the price comparison as some products did not

have any offers when adjusting for incorrect offers.

• The share of incorrect offers was on average (mean) 23% for GSU and 6% for CSS.

The higher share of incorrect offers for GSU is mainly related to wrong or used

products. The most common reason for incorrect offers in the CSS was non-

functional links to merchants.

• Average (mean) number of properties for GSU was 4.2 and median number of

properties for CSS was 20. GSU has only a few properties such as rating and price

drop whereas the CSS has a more comprehensive summary of the properties for each

product. Please note that that number of properties is capped at 20. As such, the

actual median and mean for CSS is significantly higher than 20 as some products had

more than 50 properties at the CSS.

Outcome by countryNo. of prod.in

price comp. Mean Median 1st offer Top 3 offers Top 5 offers Max offers* 1st offer Top 3 offers Top 5 offers Max offers* GSU CSS GSU (mean) CSS (median)

Country A 94 447 294 17.5% 11.6% 9.8% 12.3% 11.8% 7.6% 7.2% 7.4% 21.3% 20.6% 5.3 20.0

Country B 92 457 304 13.0% 8.2% 6.0% 9.3% 7.8% 6.7% 4.1% 6.1% 16.8% 2.9% 5.9 20.0

Country C 89 281 123 29.9% 20.6% 16.3% 24.1% 16.5% 16.1% 11.9% 15.6% 37.4% 1.5% 1.3 11.0

Country D 96 408 167 24.1% 18.0% 17.0% 20.5% 13.3% 12.5% 11.2% 14.5% 16.6% 2.5% 3.1 20.0

Country E 96 352 284 22.6% 15.6% 11.2% 14.7% 15.5% 10.0% 7.3% 9.0% 9.4% 6.9% 2.2 20.0

Country F 84 493 312 20.6% 16.1% 11.5% 14.2% 13.6% 9.7% 6.0% 9.0% 34.9% 10.2% 4.4 20.0

Country G 95 279 129 32.3% 26.2% 22.7% 26.7% 19.0% 14.4% 11.3% 14.0% 15.3% 9.0% 5.5 12.0

Country H 93 415 343 4.5% 0.3% (1.7)% (0.3)% 0.6% 0.0% (0.1)% 0.0% 24.8% 0.0% 5.5 20.0

Country I 96 281 151 23.9% 16.7% 11.4% 18.4% 14.9% 11.0% 7.3% 12.9% 14.8% 5.6% 3.4 20.0

Country J 98 575 429 5.8% (0.3)% (1.5)% 1.7% 1.9% 0.0% (0.4)% 0.4% 34.2% 0.0% 3.4 19.5

Country K 89 346 242 23.5% 12.3% 9.3% 15.7% 16.9% 6.6% 5.8% 6.9% 11.7% 2.8% 5.7 20.0

Country L 67 326 244 8.3% 3.5% (0.1)% 4.8% 3.9% 1.6% (0.2)% 0.9% 34.0% 4.4% 4.1 20.0

Total 1 089 390 254 19.0% 12.6% 9.5% 13.7% 10.0% 7.0% 5.1% 7.2% 22.6% 5.5% 4.2 20.0

*Compares the maximum number of offers collected for GSU or CSS. I.e. if 4 offers are collected for GSU and 3 for CSS the top 3 offers for GSU and CSS are compared.

Prices in € all top 5 offers Mean difference in price Median difference in price Share of incorrect products Mean and median properties




• The price differences vary between product groups. Toys and books and clothes and

shoes have the largest price differences whereas kitchen appliances and computers

have the smallest differences in price.

Outcome by product groupNo. of products in

price comparison Mean Median 1st offer Top 3 offers Top 5 offers Max offers* 1st offer Top 3 offers Top 5 offers Max offers*

Clothes and shoes 111 114 100 45.8% 35.4% 28.8% 36.5% 37.2% 29.0% 23.6% 31.7%

Computers (including accessory 's) 80 830 788 9.2% 5.3% 4.2% 6.5% 4.3% 2.2% 0.9% 2.5%

Games and consoles 42 252 286 16.3% 11.5% 9.5% 12.5% 8.1% 7.5% 5.4% 6.9%

Headphones and speakers 160 187 157 17.0% 10.5% 6.8% 11.7% 11.1% 7.0% 4.2% 7.4%

Kitchen appliances 38 436 376 10.7% 5.2% 3.8% 5.1% 3.9% 2.1% 1.0% 1.0%

Mobile Phones and tablets 60 453 425 12.7% 7.2% 4.8% 8.6% 7.5% 4.9% 4.0% 6.9%

Perfumes 85 53 50 15.1% 10.3% 6.1% 12.6% 6.6% 7.6% 3.9% 7.7%

Sports equipment 154 246 232 24.6% 14.9% 11.1% 13.2% 17.8% 14.1% 8.7% 9.3%

Toy s and books 157 128 68 37.9% 18.7% 14.3% 28.1% 26.3% 13.9% 10.7% 16.8%

TV and monitors 202 1 013 859 11.9% 9.3% 7.3% 9.6% 4.8% 5.1% 3.4% 5.1%

Total 1 089 390 254 19.0% 12.6% 9.5% 13.7% 10.0% 7.0% 5.1% 7.2%

*Compares the maximum number of offers collected for GSU or CSS. I.e. if 4 offers are collected for GSU and 3 for CSS the top 3 offers for GSU and CSS are compared.

Mean difference in price Median difference in pricePrices in € all top 5 offers


Grant Thornton Sweden AB is a limited liability company registered in Sweden. Company Registration nr. 556356-9382. Domicile:

Stockholm. Member of Grant Thornton International Ltd

8

Google shopping EU benchmark study

In accordance with your instructions set out in our engagement agreement dated 18

February 2019, we have pleasure in enclosing a copy of our report. Details of the scope

and process of our work is set out in the Engagement Agreement which you should also

read.

Period of our work

Our work was performed in the period between 22 February and 6 March. We have not

performed any work since 6 March and our report may not take into account matters

that have arisen since then. If you have any concerns in this regard, please do not

hesitate to let us know.

Yours faithfully

7 May 2019

Transaction Advisory Services

Grant Thornton Sweden AB

Sveavägen 20

P.O. Box 7623

SE-103 94 Stockholm

T +46 (0)8 563 070 00

F +46 (0)8 563 070 04

www.grantthornton.se

Our reference:

Nicklas Storåkers

PriceRunner International AB

Kungsbron 21 8 tr

111 22 Stockholm

If you have any questions in respect of this report or its contents, please contact:

David Ramm

Partner

T +46 (0)8 524 674 08

E [email protected]


© 2019 Grant Thornton Sweden AB. All rights reserved.

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Grant Thornton Sweden is a member firm of Grant ThorntonInternational Ltd (GTIL). GTIL and the member firms are nota worldwide partnership. GTIL and each member firm is aseparate legal entity. Services are delivered by the memberfirms.

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Documents

Google shopping EU benchmark - Idealo · 2020-06-16 · Spain Idealo Sweden PriceRunner United Kingdom Prisjakt Findings • Prices in GSU for all offers were on average (mean) 13.7%