eCommerce. How digital is transforming retail

1. eCommerce
How digital is transforming
retail
II Aula Digital Business
Alex Rayón Jerez
@alrayon, alex.rayon@deusto.es
October 16th, 2014

2. iConsumer Global Research Initiative
1) Big Bang
2) New skills
3) Omnichannel
7) mCommerce
4) Marketing
analytics
6) sCommerce
5) Social
Intelligence

3. Índice de contenidos
● eCommerce Big Bang
● New skills
● Omnichannel
● Marketing analytics to drive growth
● Social Intelligence
● sCommerce
● mCommerce

4. Índice de contenidos
● eCommerce Big Bang
● New skills
● Omnichannel
● Marketing analytics to drive growth
● Social Intelligence
● sCommerce
● mCommerce

5. eCommerce Big Bang
eConomy
Source: http://www.theatlantic.com/business/archive/2011/11/the-8-trillion-internet-mckinseys-bold-attempt-to-measure-the-e-conomy/247963/

6. eCommerce Big Bang
eConomy (II)
Source: http://www.theatlantic.com/business/archive/2011/11/the-8-trillion-internet-mckinseys-bold-attempt-to-measure-the-e-conomy/247963/

7. eCommerce Big Bang
eConomy (III)
Electronic equipment, ecommerce, broadband
suscriptions, mobile Internet, hardware and software
0,1% 1,0%
Trade
Private
consumption
Public
expenditure
Private
investment
Spending and buying by government in software,
hardware and services
Telecommunications, extranet,
intranet and web sites
1,8%
Exports of Internet equipment
+ B2B services with overseas
companies
0,5%

8. eCommerce Big Bang
eConomy (IV)
Source: http://www.retailresearch.org/onlineretailing.php
Source: http://disruptors.mx/for-ecommerce-to-take-off-the-infrastructure-has-to-be-in-place-or-create-new-alternatives/

9. eCommerce Big Bang
Digital transformation of the economy
Transport
Utilities
Infrastructure
Finances
...
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* Scheduling and optimization
* Reduce consumption
* Saving time and cost for companies
* Efficient allocation of capital

10. eCommerce Big Bang
Digital transformation of the companies
Digital Digital
Digital

11. eCommerce Big Bang
Digital transformation of the companies (II)
Source: http://evigo.com/8570-mckinsey-digital-transformation-e-commerce-coming/

12. eCommerce Big Bang
eCommerce in Europe
Source: https://media.licdn.com/mpr/mpr/p/2/000/268/1b5/21f35eb.jpg

13. eCommerce Big Bang
eCommerce in Spain
Fuente: http://www.ipmark.com/pdf/CompradorOnline_ES.pdf
Fuente: http://www.hablandoencorto.com/2014/01/Perfil-internauta-Espana.html

14. eCommerce Big Bang
eCommerce in Spain (II)
Fuente: http://cnmcblog.es/2013/09/10/comercio-electronico-en-espana-it-2013-
facturacion-record-para-empezar-el-ano/

15. eCommerce Big Bang
Tipping point
● Traditional commerce and e-commerce are
merging
● Pervasive technology → useful
○ Already past the tipping point
Source: http://www.justintarte.com/2012/10/leadership-and-your-tipping-point.html

16. eCommerce Big Bang
Tipping point (II)
The Tipping Point (E-Commerce Version)
Fuente: http://jeff.a16z.com/2014/01/15/the-tipping-point-e-commerce-version/

17. eCommerce Big Bang
Tipping point (III)
● Implications?
○ Real-state
○ Showroom
○ Distribution centers
○ Local economies
○ Technology-enabled shopping
○ Different approach on how we engage with the
customer
○ ...

18. eCommerce Big Bang
Technology and its effects
The technology has transformed the retail industry
Coase Theorem
Online channels reduce transaction costs

19. eCommerce Big Bang
Technology and its effects (II)
From
Consumer-oriented Internet
towards
Company-oriented Internet
Source: http://antoniotoriz.blogspot.com.es/2013/08/internet-de-las-cosas.html#sthash.hAa2ha7K.dpbs
Source: http://pame95.wordpress.com/2012/11/03/mi-ensayo-planeta-web-2-0-la-intercreatividad-y-web-2-
0/

20. eCommerce Big Bang
Technology and its effects (III)
● Internet
○ Tool for automation + market expansion
● Cloud computing
○ Reduce the need for hefty investment in IT systems
● Online marketing
○ Target specific consumer segments
● eCommerce
○ Instant and direct access to consumers
○ Support services such as payment and logistics
● Online price transparency
○ Pressurce on margins

21. eCommerce Big Bang
Shopping experience
● Shopping is no longer
only an utility activity
○ It is also an
entertainment and
engagement
● Is a social experience
● New shopping
experience
○ Just-in-Time
○ Service
Source: http://arstechnica.com/staff/2012/08/op-ed-apple-store-may-be-shifting-from-customer-experience-
to-profit-machine/

22. eCommerce Big Bang
Shopping experience (II)

23. Índice de contenidos
● eCommerce Big Bang
● New skills
● Omnichannel
● Marketing analytics to drive growth
● Social Intelligence
● sCommerce
● mCommerce

24. New skills
Introduction
Where is our client?

25. New skills
Digital competencies
● Understand how to take advantage of the
technology and how it works in order to be
able to:
○ Search for information
○ Filter it
○ Organize it
○ Synthesize it
○ Generate knowledge
○ Communicate our knowledge
○ Interact with our stakeholders

26. New skills
Social networks
Source: http://sisobproject.wordpress.com/2011/07/27/social-networks-social-media-and-social-network-analysis/

27. New skills
Quantitative reasoning
Source: http://serc.carleton.edu/NICHE/examples_qr_programs

28. New skills
How to optimize
Source: http://www.attilasystems.com/search-engine-optimization-seo/

29. New skills
How to engage
The Attention Economy

30. Índice de contenidos
● eCommerce Big Bang
● New skills
● Omnichannel
● Marketing analytics to drive growth
● Social Intelligence
● sCommerce
● mCommerce

31. Omnichannel
Source: https://media.licdn.com/mpr/mpr/p/2/000/268/1b5/21f35eb.jpg

32. Omnichannel (II)
Source: http://www.i95dev.com/understanding-omni-channel-and-multichannel/
Experience
Transaction

33. Omnichannel (III)
1. Refine Your Brand’s Digital Presence
2. Search Strategies Should Come First
3. Target Existing Customers Using Site
Retargeting
4. Search Retargeting Will Help You Gain
New Customers
5. Use Mobile To Connect The Dots

34. Índice de contenidos
● eCommerce Big Bang
● New skills
● Omnichannel
● Marketing analytics
● Social Intelligence
● sCommerce
● mCommerce

35. Marketing analytics
Introduction
Source: https://media.licdn.com/mpr/mpr/p/2/000/268/1b5/21f35eb.jpg

36. Marketing analytics
Introduction (II)
Source: http://www.accenture.com/us-en/Pages/insight-cmo-digital-transformation-summary.aspx

37. Marketing analytics
Big Data
Source: http://de.nr-apps.com/blog/2014/01/09/zukunft-des-handels-big-data-und-bitcoins/

38. Marketing analytics
MROI
● MROI: Marketing Return on Investment
○ McKinsey review: an integrated analytics approach
could save up to 15-20% total budget
■ That’s $ 200.000.000.000 worlwide
Source: http://www.thecmosite.com/author.asp?section_id=1137&doc_id=234474

39. Marketing analytics
MROI (II)
Source: http://www.marketingsherpa.com/charts/roi020409-1.gif

40. Marketing analytics
Small data
“More data does not mean more knowledge”
[Jenkins2013]
Searching for the evidence in a mass of data
requires knowing what kind of evidence is
needed
Knowledge of the domain and understanding
and interpretation of the patterns we see

41. Marketing analytics
Anchoring analytics to strategy
● How do we allocate marketing resources?
○ Previous years’ budgets or products/lines that worked
well
○ This situation produces “Beauty contests”
Source: http://www.thefinancialphilosopher.com/2008/05/weekend-wisdom.html
Coolest proposals
Loudest shouts

42. Marketing analytics
Anchoring analytics to strategy (II)
● But is should be focused on
○ Most need to grow
○ Defend current position
● How to measure it?
○ Strategic return
○ Economic value
○ Payback window

43. Marketing analytics
Anchoring analytics to strategy (III)
1) Marketing-Mix Modeling (MMM)
● Big Data to determine the effectiveness of spending by
channel
Marketing
investments
● Include external variables such as seasonality, and
competitor and promotional activities to uncover
○ Longitudinal effects: changes individuals and
segments over time
○ Interaction effects: differences among offline, online
and Social Media activities
Marketing
investments
Statistical
links

44. Marketing analytics
Anchoring analytics to strategy (IV)
2) Heuristich RCQ (Reach; Cost; Quality)
● Disaggregate touchpoints into its component paths
○ target consumer Reached
○ Cost per unique touch
○ Quality of engagement
● More limited; but the best one when limited
data is available

45. Marketing analytics
Anchoring analytics to strategy (V)
3) Attribution modeling
● Set of rules or algorithms that govern how credit for
converting traffic to sales is assigned to online
touchpoints
○ Email campaign
○ Online ad
○ Social-networking feed
○ Website
● Statistical modeling regression techniques

46. Marketing analytics
Anchoring analytics to strategy (VI)
● Integrate capabilities to generate insights
○ DSS tool to integrate the results from MMM, RCQ and
AM
Source: http://water.usgs.gov/watercensus/delaware-dss.html

47. Marketing analytics
Anchoring analytics to strategy (VII)
● Analytical approach at the heart of the
organization
○ Data scientists
○ Marketing researchers
○ Digital analysts
● Question assumptions, formulate hypotheses,
and fine-tune the math

48. Marketing analytics
Data as competitive advantage
● Data is both an art and a science
○ Science
■ A lot of research
■ ¡But never make Data Mining alone!
○ Art
■ Critical reasoning
■ Business judgement
■ Domain knowledge

49. Marketing analytics
Data as competitive advantage (II)
Source: Data Mining with WEKA MOOC (http://www.cs.waikato.ac.nz/ml/weka/mooc/dataminingwithweka/)

50. Marketing analytics
Data as competitive advantage (III)

51. Marketing analytics
Data as competitive advantage (IV)

52. Marketing analytics
Knowledge discovery methods
1. Prediction methods
2. Structure discovery
3. Relationship mining

53. Marketing analytics
1) Prediction methods
Source: Data Mining with WEKA MOOC (http://www.cs.waikato.ac.nz/ml/weka/mooc/dataminingwithweka/)

54. Marketing analytics
1) Prediction methods (II)
Source: Data Mining with WEKA MOOC (http://www.cs.waikato.ac.nz/ml/weka/mooc/dataminingwithweka/)

55. Marketing analytics
1) Prediction methods (III)

56. Marketing analytics
1) Prediction methods (IV)
Source: Data Mining with WEKA MOOC (http://www.cs.waikato.ac.nz/ml/weka/mooc/dataminingwithweka/)

57. Marketing analytics
1) Prediction methods (V)
Source: http://lawprofessors.typepad.com/legalwhiteboard/important-research/

58. Marketing analytics
1) Prediction methods (VI)
Source: Data Mining with WEKA MOOC (http://www.cs.waikato.ac.nz/ml/weka/mooc/dataminingwithweka/)

59. Marketing analytics
2) Structure discovery
Clustering
Source: http://inside-bigdata.com/2013/12/18/tech-tip-power-pitfalls-clustering/
Source: http://www.cs.bilkent.edu.tr/~saksoy/research.html

60. Marketing analytics
2) Structure discovery (II)
Factor Analysis
Source: http://www.mathworks.es/machine-learning/examples.html?file=/products/demos/machine-learning/cluster_genes/cluster_genes.html

61. Marketing analytics
2) Structure discovery (III)
Social Network Analysis
Source: http://rs.resalliance.org/2010/11/03/reading-list-using-social-network-analysis-sna-in-social-ecological-studies/

62. Marketing analytics
3) Relationship mining
Association rule mining
Source: http://aimotion.blogspot.com.es/2013/01/machine-learning-and-data-mining.html

63. Marketing analytics
3) Relationship mining (II)
Correlation mining
Source: http://www.bain.com/publications/articles/Growing-brands-by-understanding-what-Chinese-shoppers-really-do.aspx

64. Marketing analytics
3) Relationship mining (III)
Sequential pattern mining
Source: http://www.mdpi.com/1424-8220/10/8/7496

65. Marketing analytics
3) Relationship mining (IV)
Causal data mining
Source: http://www.ciberconta.unizar.es/leccion/INTRODUC/485.HTM

66. Índice de contenidos
● eCommerce Big Bang
● New skills
● Omnichannel
● Marketing analytics to drive growth
● Social Intelligence
● sCommerce
● mCommerce

67. Social intelligence
Introduction
● Social Media
○ Insights and how consumers think and behave
● Social Intelligence literacy
● How social technologies can augment the
intelligence-gathering approaches
○ How information is sourced, collected, analyzed and
distributed

68. Social intelligence
Social Media approach
Source: http://www.mckinsey.com/insights/high_tech_telecoms_internet/how_social_intelligence_can_guide_decisions

69. Social intelligence
Social Media approach (II)
1) From identifying data to mapping people
and conversations
● Social Media → new information map
○ Primary and secondary information sources
Source: http://tedescostwocents.com/social-media-models/

70. Social intelligence
Social Media approach (III)
2) From data gathering to
engaging and tracking
● Tools to pinpoint where
information and expertise
reside and track data in
real time
○ i.e. General Electric,
@ecoimagination + # key
topics

71. Social intelligence
Social Media approach (IV)
3) From analysis and synthesis to structuring
and mining
SWOT
Porter 5 forces
Analytic methods
to structure and
derive insight from
complex
information

72. Social intelligence
Social Media approach (V)
3) From analysis and synthesis to structuring
and mining (cont.)

73. Social intelligence
Social Media approach (VI)
4) From reporting to curating and embedding
● Automatically curate highly pertinent
information
○ Flipboard
● Visual mapping

74. Índice de contenidos
● eCommerce Big Bang
● New skills
● Omnichannel
● Marketing analytics to drive growth
● Social Intelligence
● sCommerce
● mCommerce

75. sCommerce
Introduction
Source: https://media.licdn.com/mpr/mpr/p/2/000/268/1b5/21f35eb.jpg

76. sCommerce
Social Networks
Social networks play the
simultaneous role of portal
and link with retailers,
providing a source of
information prior to purchase

77. sCommerce
Categories
1. Options to share on the website
2. Social infused onto site
3. A View Into Individual Activity
4. Site as it’s Own Social Network
5. Six Degrees of Separation
6. Social-Sourced Shopping

78. sCommerce
Categories: 1) Options to share on the website
Source: http://www.fluid.com/e-commerce/social-commerce

79. sCommerce
Categories: 2) Social infused onto site

80. sCommerce
Categories: 3) A View Into Individual Activity
Source: http://www.fluid.com/e-commerce/social-commerce

81. sCommerce
Categories: 4) Site as it’s Own Social Network

82. sCommerce
Categories: 5) Six Degrees of Separation

83. sCommerce
Categories: 6) Social-Sourced Shopping

84. sCommerce
Tools
Source: http://comunidad.iebschool.com/iebs/redes-sociales/social-commerce-redes-sociales-ventas-comercio-electronico/

85. Índice de contenidos
● eCommerce Business Models
● Current situation of retailing
● New skills
● Marketing analytics to drive growth
● Social Intelligence
● sCommerce
● mCommerce

86. mCommerce
Source: https://media.licdn.com/mpr/mpr/p/2/000/268/1b5/21f35eb.jpg

87. mCommerce (II)
● Reaching the tipping-point
○ Technology-enabled screens
○ Connected screens of all sizes
Source: http://www.slideshare.net/TNSGlobal/mobile-commerce-reaches-the-tipping-point

88. mCommerce (III)
The number of searches on mobile phones is
booming and there is a direct impact on
purchasing behaviour
65% say that they postpone their purchase or
change suppliers according to this research

89. Copyright (c) 2014 University of Deusto
This work (but the quoted images, whose rights are reserved to their owners*) is licensed under the
Creative Commons “Attribution-ShareAlike” License. To view a copy of this license, visit http:
//creativecommons.org/licenses/by-sa/3.0/
Alex Rayón Jerez
October 2014

90. eCommerce
How digital is transforming
retail
II Aula Digital Business
Alex Rayón Jerez
@alrayon, alex.rayon@deusto.es
October 16th, 2014