Head of Market Insights Google Spain

Presentación del tema: "Head of Market Insights Google Spain"— Transcripción de la presentación:

1 Head of Market Insights Google Spain
Consumidor actual Cobertura y frec Branding ventas Laura Ludeña Head of Market Insights Google Spain Nuevos usos de la estadística en la sociedad del conocimiento y de la red Eustat. Donostia Julio 2013

2 Uso de la estadística para conocer el mundo digital
Agenda Uso de la estadística para conocer el mundo digital Uso de la estadística para mejorar los productos publicitarios Uso de la estadística para medir la efectividad de los productos publicitarios

3 Agenda Uso de la estadística para conocer el mundo digital
Estadísticas globales y para España Representatividad y continuidad Uso de dispositivos Herramientas públicas a disposición de los estudiantes: OurMobilePlanet y ConsumerBarometer Uso de la estadística para mejorar los productos publicitarios Google Analytics True View Retargeting lists Herramientas públicas a disposición de los estudiantes: Google Trends, y Google Insights for Search Uso de la estadística para medir la efectividad de los productos publicitarios Medición de Reach Medición de Branding Medición de ROI

4 1. Usos de la estadística para entender el mundo digital

5 Estadísticas globales y para España

6 Uso de dispositivos 1. How many Mobile users are there vs other devices users? 2. Who is the Mobile user? When, where and why is it Mobile used? 3. How is the Mobile used within a Multiscreen context? 4. What is the Mobile role in the Purchase Journey Consumer Connected Survey TNS Our Mobile Planet Ipsos Multiscreen Survey Ipsos Mobile Purchase Journey Ipsos

7 Global consumers move to multi-screening
Number of connected devices per household average: 1.5 Source: TNS, Global Enumeration Study, 2012 Base: All respondents 16+; 1,000 per country Q: Which, if any, of the following devices do you currently use? (Smartphone, PC, laptop Webbook, Tablet, Internet TV)

8 PC / Laptop usage is high in most countries
Q PC or laptop usage average: 70% Q: Which, if any, of the following devices do you currently use? Source: TNS, Global Enumeration Study, 2012 Base: All respondents 16+; 1,000 per country

9 Strong growth for Smartphones worldwide
Smartphone usage X1.33 Q: Which, if any, of the following devices do you currently use? Source: Global Enumeration Study, Ipsos 2011, TNS 2012 Base: All respondents 18+; 1,000 per country

10 Strong growth for Tablets worldwide
Tablet usage X1.6 Q: Which, if any, of the following devices do you currently use? Source: Global Enumeration Study, Ipsos 2011, TNS 2012 Base: All respondents 18+; 1,000 per country

11 Hihger Intent to use tablets (except in Africa)
In Africa, smartphones are expected to grow faster than tablets Question: Which, if any, of the following devices do you currently use? Question: You are currently not using a so called [device]. How likely are you to buy or use a [device] within the next 12 months? Source: Global TNS Infratest enumeration study Q1 2012 Base: All respondents 16+; 1,000 per country

12 Africa: mobile connections more important than fixed connections
Index on total population Question: What type of internet connection is your main internet connection at home, i.e. how is your home connected to the internet ? Source: Source: Global TNS Infratest enumeration study Q1 2012 Base: All internet users with home connections 16+; Africa 8639 Asia 4,897; Europe 16,456; NA 1,673; SA 716; Oceania 1,728

13 Smartphones tend to be solitary devices, tablets and PC/laptops are shared more
Distribution of people using devices Question: How many people in your household use [Device] in addition to yourself? Source: Source: Global TNS Infratest enumeration study Q1 2012 Includes all countries, Base: Device users; Mobile phone/smartphone 33,680, PC/laptop/webbook 27,070, Tablet 3,216)

14 Tablet users go online mostly through wifi and particularly at home
Tablet and Smartphone internet access Question: Now thinking about internet access with [Device], how do you connect to the internet with [Device] Source: Global Enumeration Study, Ipsos 2011, TNS 2012 Bases: Device users for at least some personal reasons; Tablets, 2,950; Smartphone, 8,707

15 Tablet usage appears to be complementary to other devices
Header: Relation Internal/Identier/File name 15 Source: Spain Consumer Connected Survey Q1 2013 Base: All respondents 16+; 1,000 15

16 PCs for productive activities, mobile for intimate usage
PCs for productive activities, mobile for intimate usage. Tablets still to be defined (enterteinment now) Leisurely Curious Friendly Versatile Productive Intense Dependable Sexy Quick Efficient Fast Powerful Accessible Casual Impulsive Important Smart Spontaneous Social Intimate Essential

17 Preferred Device is related to the activity
Working Enterteinment Commuting Lunch % Relative Uses by 24 hours /day Source: Multiscreen Survey Ipsos 2013

18 Uso de smartphone Nuevos modos de presentación y distribución de la información La información que no se procesa no es efectiva: y los informes no se procesan. Los hábitos de lectura han cambiado. Los informes han de ser comprensibles, “personalizables”, intuitivos, usables, significativos,… Source: Our Mobile Planet Ipsos 2013

19 - 85% 78% 22% Interacción entre las distintas pantallas
Not at the same time 85% 1. Sequential Usage Moving from one device to another at different times to accomplish a task (ie. booking a summer travel) - At the same time 78% 2. Multitasking Usage Using more than one device at the same time for an unrelated activity (ie. Watching a TV show and playing Angry Birds with a smartphone app) 22% 3. Complementary Usage Using more than one device at the same time for a related activity (ie following a soccer match on TV and getting other matches updates on a website in the tablet) Universe of reference: 19.7 Mill of Smartphone, PC & TV users aged 16 or more Source: Multiscreen Survey Ipsos 2013

20 89% of smartphone users have looked for local information 19,248,624 ind 77% 14,821,441 ind have taken action as a result 32% 6,159,560 ind have visited the business 27% 5,197,129 ind have called the business or service How often do you look for information about local businesses or services on your smartphone? (Ever) Base: Private smartphone users who use the Internet in general and who look at least less than once a month for information on their smartphone, Smartphone n= 891 Which of the following actions have you taken after having looked up this type of information (business or services close to your location)? Source: Our Mobile Planet Ipsos 2013

21 41% 91% Mobile research to Desktop purchase Researched on smartphone
Mobile users 41% Researched on smartphone and purchased on desktop Mobile, PC & TV users Start shopping on smartphone and continue or finish on desktop 91% 6.7 M started an online purchase via smartphone, 6.1 M converted via PC; 5 M started planning a trip via smartphone, 4.5 M finally converted via PC Source: Our Mobile Planet Ipsos 2013 Source: Multiscreen Survey Ipsos 2013 For the 41%: Listed below are various products or services. For each of these products or services please indicate which statement applies to you. “Research on smartphone then purchased via computer” Source: OurMobilePlanet Fort the 91%: Base: Have Started Activity on One Device & Continued on Another (488). Q. For the activities listed below, think about the last time you started each activity on one device and then continued or finished the same activity on another device. Please select which device you started and then continued on. If you have not done this, select “I have not done this”.

22 94% 88% 82% Search dominates the sequential usage
Search again on the second device 88% Directly navigating to the destination site 82% Via / sending a link to myself Universe of reference: 19.7 Mill of Smartphone, PC & TV users aged 16 or more Source: Multiscreen Survey Ipsos 2013 Base: Have Started Activity on One Device & truly Continued on Another: Searching (249); Browsing (296); Shopping (224), Watching a Video (181). Q. You mentioned that you have started each activity below on one device and then continued it on another device. For each activity (column), please indicate the way(s) in which you did this.

23 Conclusiones 1 La representatividad, consistencia y continuidad es clave en el análisis estadístico de tendencias sociales. 2 La investigación de mercados basada en datos declarativos sirve para entender el pulso social, las tendencias de los mercados, y comparativas entre países (pues son metodologías al alcance de casi todos) 3 Para cuantificar la realidad del uso de dispositivos, consumo de medios y audiencias de medios deben desarrollarse mediciones más sofisticadas basadas en “datos comportamentales” (y no “declarativos”) en la medida que las nuevas tecnologías lo ponen cada vez más al alcance del investigador.

24 Usos de la estadística para mejorar el marketing

25 ¿Cómo hace dinero Google?
Companies pay Google for advertisements that appear on the Google search results page Companies pay Google for the best possible ranking in the search results Companies pay for information that Google collects about you Companies pay Google to place their advertisements on other pages across the web Google makes money in a different way I don’t know how Google makes money 56% 60% 59% 53% 51% 44% 45% 41% 30% 35% 28% 26% 19% 34% 39% 42% 11% 10% 7% 6% 29% 27% In France of those 35% who believe Google makes money by selling information on users, over half (51%), still rate Google as trustworthy Substantially less concern about Google selling personal data in Italy Ipsos MediaCT January to February 2012 Source: Q24a. In your opinion, which, if any, of the following best describes how Google makes money? Base: All respondents n=2,991 25 25

26 Esto es el impacto global actualmente: internet llega a todos

27 Push

28 Pull How much you’re willing to pay (bids)
How “good” your ads are (relevance) Competition

29 La estadística aplicada a la comprensión de las necesidades del consumidor: Search

30 La estadística aplicada a la comprensión de las necesidades del consumidor: Google Analytics

31 La estadística aplicada a la comprensión de las necesidades del consumidor: True View
Preroll vs. TrueView at equal efficiency 2.8x Source: GfK (randomised experiment with 18 brands and n = respondents) Connected Life Panel Germany 2012 (n = panelists)

32 La estadística aplicada a la comprensión de las necesidades del consumidor: Retargeting

33 Herramientas públicas: Google Trends

34 Herramientas públicas: Google Trends
DIETA

35 Herramientas públicas: Google Trends
DUKAN

36 Herramientas públicas: Google Trends
-DUKAN

37 Herramientas públicas: Flu Trends

38 Herramientas públicas: Bank of England
Real time insights – find the predictive query set you don’t have to wait for a big econometric model update to get the pulse of changing consumer demand trends.

39 Conclusiones 1 La libre elección de información ha cambiado el modo en el que el consumidor está dispuesto a acceder al contenido publicitario. 2 La estadística tiene un papel clave para conectar las necesidades del consumidor al contenido y formato publicitario que está dispuesto a aceptar y valorar en última instancia. 3 Existen herramientas públicas accesibles para todos que permiten entender y optimizar nuestra oferta, y ejemplos que nos inspiran al uso de la estadística para mejorar la gestión de múltiples productos y servicios.

40 Uso de la estadística para medir la efectividad del marketing

41 La escalabilidad es clave
Building Scalable Tools Improving research standards Improving marketing products Rolling out externally

42 El consenso también Esta es la situación a la que aspiramos

43 Tres dimensiones fundamentales
To demonstrate & empower digital effectiveness within Media Mix Reach Branding Sales

44 Reach: via fusión de datos fija
KANTAR MEDIA TV PANEL (n: ) Official Spain TV currency Exposure to TV based on fusion to TV currency panel (Kantar Media) FIXED FUSION KANTAR WORLPANEL households (n: 8.400) KANTAR WORLDPANEL individuals (n: 4.863) Exposure to Online based on impression tags Fusion process is based on similarities among Kantar Media (TV) and Kantar Worldpanel (online) panelists. “Twins” are created based on sociodemographics, attitudes, TV chanel profile, day band profile (multidimensional reduction) and 200 additional exclusive clusters. 44

45 Reach: via fusión de datos fija
Only YouTube added an average of 2.9 extra reach points to TV Average TV reach (1+) 79.1% Average YT reach (1+) 14.3% Only TV 67.7% Overlap TV + YouTube 11.4% Exclusive Youtube reach: +2.9 p% Source: Kantar Worldpanel cross media analysis– internet users Base: 10 YouTube campaigns in 2012/2013 45

46 Reach: via fusión de datos fija
More than 20% of total YouTube reach is not doubling up with TV . YouTube share of incremental reach goes higher while looking at effective TV reach Media Reach by different levels of TV OTS (%) YouTube share of incremental reach (100= Total YouTube reach) 20.2% 41.2% 55.9% Source: Kantar Worldpanel cross media analysis– internet users Base: 10 YouTube campaigns in 2012/2013 46

47 Reach: via fusión de datos fija
WEB media is particularly effective at delivering additional GRP´s among lower TV exposed audience Almost 75% of online GRPs delivered out of high TV exposed Source: Kantar Worldpanel cross media analysis– internet users Base: 12 campaigns in 2012/2013 47

48 Reach: via Single Source Panel
What we did: Analyzed 80 TV campaigns for different products of leading advertisers TV media plans by Ebiquity, YouTube media plans simulated by Google Data source: Single-source panel: Measurement of individual TV & online behavior from same consumers in 5,000 households within GfK Media Efficiency Panel This share-shift analysis is based upon a decent data base (80 TV campaigns) to find out the effect of adding online (YouTube in this case) to a TV-only campaign. Data comes from individual contacts with TV and YouTube from German Media Efficiency Panel. Analysis will be repeated with a larger sample to allow for more granular results.

49 Reach: via Single Source Panel
For illustration only reallocation of wasted TV OTS to unexposed audiences

50 Reach: via Single Source Panel
Benefits of Share-Shift from a Budget-Point of View Share Shift TV ONLY TV + YOUTUBE Stable Reach NET REACH: 69% NET REACH: 69% The second analysis scenario takes out TV and adds YouTube to a media plan while keeping overall net reach stable. On average for 80 campaigns, the overall campaign costs can be reduced by share-shift by 7.4%. Cost Reduction: -7.4% COSTS COSTS Source: Share shift analysis Google, based on GfK MEP and Ebiquity data

51 Brand Impact: ejemplo preroll vs skippable
Looking at recall, awareness and recognition no major differences in impact can be seen between the two formats. If any, prerolls perform sligthly stronger. % of respondents per cell Source: GfK / nurago 2011, n = interviewss. Audi and Redbull Ads Nurago Impact Panel Germany (n = panelists) indicates differences at 90% significance level to control

52 Brand Impact: randomized experiments
IMPACT PANEL ( panelists, used for ad effectiveness research). Unique methodology: nurago technology allows experimental study designs for ad effectiveness in a real live campaign setting Full control over reach and frequency of campaign delivery Experiment embedded into the panelists‘ natural online usage Campaigns can be fully simulated or boosted if needed within the panel Survey Panelists (representative for onliners years) Random pre campaign assignment into test and control groups, e.g. # only allowed to see skippable # only allowed to see preroll Panelists fall into groups depending on their natural online behaviour # did not see advertising # exposed to skippable # exposed to preroll

53 Brand Impact: eficiencia preroll vs skippable
However, in terms of efficiency (impact per GRP) skippable prerolls clearly outperform standard prerolls by factor 2.4 on average across brand metrics Uplift to control per GRP Efficiency Index 234% Efficiency Index 248% Efficiency Index 234% Source: GfK / nurago 2011, n = interviewss. Audi and Redbull Ads Nurago Impact Panel Germany (n = panelists)

54 Ventas: Econométricos “online to store”

55 Ventas: Econométricos “online to store”
1. Need to collect all the variables that may influence the sales 2. An analyst uses judgement and SAS to produce different regresion models until best combination is identified 3. So he is able to identify each variable influence to the sales 4. Final check: the blue line is the reality (sales); the red line is the model (how it fits the sales)

56 Ventas: Econométricos “online to store”
12% of visit to dealer are influenced by media. Visit to dealer Web visits Paid Search Purchase Repeated ealer visit Organic Search Dsplay Other Media

57 Paid search is the most cost-effective.
Ventas: Econométricos “online to store” Paid search is the most cost-effective. ROI: Visits to dealer by 1€ invested Online ROI Offline ROI Monetary value of an application and actual returns not shown due to client confidentiality – ROI data indexed Visit to dealer Web visits Paid Search Purchase Repeated ealer visit Organic Search Display Other Media

58 Ventas: Econométricos “online to store”
*Historical Media Mix *Improved Modelled Media Mix

59 Conclusiones 1 La integración de la medición de audiencias y coberturas desde múltiples dispositivos y plataformas es el principal reto actual en la medición de efectividad publicitaria. 2 El desarrollo de las nuevas tecnologías en la emisión de contenido publicitario permite la optimización y escalabilidad de la medición del impacto publicitario en notoriedad e imagen de marca. 3 Es fundamental explorar la medición del ROI de las diferentes actividades de marketing de un modo integrado y comparable entre ellas. La creación de modelos econométricos es una vía sólida aunque costosa en tiempo, dinero e infraestructuras de gestión de la información interna.

60 ¿Preguntas?