O2S Effect: a Reality

Google Confidential and Proprietary Google Confidential and Proprietary

Think Retail, Paris le 28 juin 2011 Mark Riseley, Market Insights Manager, EMEA

The O2S Effect, a quantified reality


Online to Store Matters

7.3%

48%

2

Estimated Online Sales as % of total France retail sales 2011*

% of Internet users recently researching a retail product online before buying off-line**

*Source: Fevad Juin 2011, **Source: IAB/Google/TNS Consumer Commerce Barometer 2010


Source: Longitudinal Economic Study Series, IRI Attitude Link, n = 1,000+ shoppers. CPG Purchase Decisions. IRI, 2009.

In store

Before visiting store

3

% of consumers who decide what to buy…

Impulse buying is declining

60%

83%

40%

17%

2007 2009


Base : Acheteurs en magasin ayant consulté Internet avant ou après achat Q15 : Pour quelles raisons n’avez-vous pas acheté les produits directement sur le site de l’enseigne ?

C'est compliqué de retourner le produit 44%

Pour le plaisir de flâner dans les magasins 45%

J'avais besoin rapidement des produits 50%

Le magasin est à proximité de chez moi 50%

Le coût de la livraison est trop élevé 51%

Essai du produit / conseil

Proximité immédiateté

Plaisir

Je ne suis pas sur(e) d'avoir les mêmes conseils que si j'achete en magasin 37%

Je préfère voir ou essayer les produits avant de les acheter 55%

Source : TNSInfratest, Consumer barometer 2010

Why do people still buy in store ?


O2S customers search almost as actively as online buyers

Source: GfK MEP, Allemagne - Base: Buyers who have researched online

Average number of queries

Online buyers

O2S buyers

9,2

7,6


Top E-commerce and Top O2S products are different

Source : TNSInfratest, Consumer Barometer 2010

Top E-commerce Top O2S

1 Computer Software/Video Games Digital Camera/Camcorder

2 Mobile Phone Visual Devices

3 Audio Devices Audio Devices

4 Digital Camera/Camcorder Home Furnishings/Furniture

5 Computer Hardware Domestic Appliances

6 Computer Peripherals Mobile Phone

7 CDs/DVDs/ Books Computer Hardware

8 Visual Devices DIY, Tools, Garden Equipment

9 Domestic Appliances Computer Peripherals

10 Clothing & Accessories Sport Equipment


How to measure the online to store effect

7

Experiments Tracking Modelling

Attribution of offline sales

Prove incremental effect

Correlation+ of online ads and offline sales

Consumer insights

Surveys


incremental spend from in-store buyers who researched online.

33% average

€701

RESEARCHED ONLINE DID NOT RESEARCH ONLINE

Basket size amount Spent

in-store

Surveys: Online researchers spend more

Source: Online2Store Research - Quantifying the role of the web on in-store TV purchases @ FNAC Spain; Sep 2010

€526


Tracking: Cross-channel measurement embedded in Argos business model

25%

48% multi-channel

10%

9% 2%

2%


Experiments: Vodafone example

10

Objective: Create a measurable difference in Adwords spending between test and control regions and determine the impact on in-store sales

* Test ran for 8 weeks, beginning 1 April 2010


Experiments: Vodafone example

11

« Vodafone’s additionnal investment in generic and upper funnel keywords was an effective way to drive incremental in-store sales. We now have a better understanding of the impact of online research on retail purchase behaviour and we’ll have to rethink the way our current attribution model works. »

-Mike Durbridge, Head of Direct Sales, Vodafone UK


Halo effect

Impact of online advertising on offline sales in non-tested categories

Up to 3.5%

Offline sales lift

Increase in offline sales revenues in tested categories

1.5% – 4.4%

12

Experiments: Online advertising drives offline sales

Source: Google client studies in Europe & USA


Mobiles & Contracts

4:1 ROAS

Apparel

3:1 ROAS

Source: Google client studies in Europe & USA

Consumer Electronics

12:1 ROAS

Home & Garden

6:1 ROAS 13

Experiments:…delivering strong ROI across different categories


Modelling: explaining sales with equations system

14

0

1000

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Lapt

op S

ales

(Uni

t)

Modeled

Actual

98% Le modèle explique des variations dans les ventes


Modelling: PC City ecosystem

15

Offline Sales

Online Sales

Rainfall

Holiday

Sporting Events

Store Refurbishment

Competitive Media

Traditional Media

Web traffic

Online Display

SEM (Paid Search) Email

Online Search

Online world Offline world Business Outcome

+ Driver

- Driver

Legend

15

Price, Base Sales & Seasonality

Short term Promo days

Width of line indicates size

of driver


Modelling: Understand in-store sales drivers

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Base Sales

Seasonality Regular price

Price promotio

n

TV Advertising

Catalogues Press Radio & OOH

Other Web traffic to pccity.es

42%

12%

8%

2% 5%

15% 11%

3% 1% 1% 62% of PC City sales are

non marketing drivers

38% of PcCity sales are influenced by

Marketing

Catalogs and website traffic are the two key in-store sales drivers

PCcity.es explains 11% of offline sales – which means nearly 1/3 of all driven by marketing offline sales


4,100

4,200

4,300

4,400

4,500

4,600

4,700

4,800

- 50,000 100,000 150,000 200,000 250,000 300,000 350,000

Wee

kly

Sale

s (U

nits

)

Weekly Media Spend €

Increase spend in

4,300

4,400

4,500

4,600

4,700

4,800

- 10,000 20,000 30,000 40,000 50,000 60,000 70,000

Wee

kly

Sale

s (U

nits

)


Modelling: Understand Marketing investments efficiency

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4,100

4,200

4,300

4,400

4,500

4,600

4,700

4,800

- 100,000 200,000 300,000 400,000 500,000 600,000

Wee

kly

Sale

s (U

nits

)


Historical spend

Optimal spend

Historical spend

Optimal spend

Optimal spend

Historical spend

4,400

4,500

4,600

4,700

4,800

- 10,000 20,000 30,000 40,000 50,000

Wee

kly

Sale

s (U

nits

)


Historical spend

Optimal spend

An optimal mix of PC City would induce a reduction in TV Investment and an increase in other media

catalogues

TV

Paid search

Press

Increase spend in

Increase spend in Decrease spend in


€1.40

Modelling: Apply the optimal media mix

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Paid Search 9%

Catalogues 42%

Outdoor 3%

Press 3%

TV 43%

Paid Search

1%

Catalogue 32%

Outdoor 1%

Press 2%

TV 64%

Last year 23 Aug – 11 Oct 2009 (8 weeks) Optimal Mix for 24th Aug – 12 Oct 2010 (8 weeks)

Aggregate Marketing ROI

Aggregate Marketing ROI €1.10

With the same global budget, an optimal mix would bring 6% of additionnal revenue

Note : Understanding of ROI of display within the media mix was compromised by a lack of data relating to Display investments over the period analysed.O


Campaign impact on store sales: Instead of this….

The Dutch brand Aviko did this


50% of Aviko TV budget into pre-roll on YouTube

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Aviko (NL): Cost GRP Pre-roll targeted usage

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1,0

0,2

1,00,5

1,0 0,8 1,01,4

1,0

3,2

0

1

2

3

4

5

6

7

8

9

10

TV YT TV YT TV YT TV YT TV YT

Net Cost/GRP (indexed against TV)

Male 20-‐30 20-‐34 20-‐49 Female 20-‐49 13+

~ 1:16

Source: Gfk Media Efficiency Panel + Carat Media facts booklet (TV net cost based on 70% average market discount)


Aviko (NL): Pre-roll targeted usage (size within

inventory) Efficiency in driving store purchase

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1,00,6

1,01,4

1,0

2,5

1,0

3,7

1,0

8,5

0

1

2

3

4

5

6

7

8

9

10

TV YT TV YT TV YT TV YT TV YT

Source: Gfk Media Efficiency Panel + Carat Media facts booklet (TV net cost based on 70% average market discount)

Efficiency in driving sales (indexed against TV)

13+ 20-‐49 Female 20-‐49 20-‐34 Male 20-‐34


40+ Studies to quantify the O2S Effect

§ 40+ studies in Europe and in the United States

§ Methodologies : econometrics, geo-testing, coupons,

tracking, single source panels

§  Instore sales driven by the retailer website traffic : 10%-13%

§ Case studies : PC City, Auchan, Vodafone, Cadbury, Aviko

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O2S effect parameters

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1 Product categories affinity with O2S effect

2 Store network coverage

3 O2S functions on your websites (ex. Store locators, in-store stock availability etc.)

4 Conversion efficiency on your website

5 Your customers’ increasing comfort with e-commerce

O2S is amplified by:

O2S is minimised by :


Conclusions

•  Online to store is much bigger than e-commerce

•  O2S shoppers are high value

•  Economic benefit is measurable with several methods

•  Online ads can deliver 1.5-4.4% offline sales lift

•  Online to offline ROAS has been measured from 3:1 to 20:1+

•  We can help you with measurement challenges

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O2S Effect: a Reality

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