Big data - illusion or opportunity (Miha Vogelnik, Valicon)

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This document discusses big data and how it can provide opportunities for businesses. It outlines key components of big data including data, analytics, and action. It also discusses potential sources of customer data both internal and external. The document suggests that big data analytics can help businesses optimize marketing efforts through more targeted and personalized campaigns compared to traditional general advertising. It provides examples of how big data can help with customer profiling, predictions, evaluations and improving sales over time through smarter follow up campaigns. Finally, it recommends that businesses looking to utilize big data should start with a simple problem, identify relevant data sources, analyze the data, take action and continuously improve through measurement and iteration.

Big data –
illusion or opportunity
Miha Vogelnik, Valicon

Key components of big data

Data

SMARTER
DECISIONS

Analytics

Action

TECHNOLOGY

Source: Nakupna pot 2012/2013, Valicon/IPROM
WEB

WOM
26%

EVENT
TV
OUT

STIMULATION

PRINT
CATALOG

ONLINE
21%

RADIO

OFFLINE
53%

WOM
WOM

WOM
21%

WEB SEARCH

OFFLINE
16%

WEBSITE

RESEARCH

SOCNET
CONTACT

ONLINE
63%

WEB PRICE
MOBILE
WEB RESEARCH

WEBSITE

ONLINE
15%

CONTACT

PURCHASE

MOBILE
STORE
STORE PROMO & PUSH

OFFLINE
85%

STORE MOB
WEB RESEARCH
SURVEY

WOM
WEBSITE

POST
PURCHASE

SOCNET

0%

20%

40%

60%

80%

100%

Potential sources of customer data

POS
Transactions

Facebook

VOLUME

VELOCITY

VARIETY

Twitter

Company
web portals

OTHER
SOURCES

SOCIAL
MEDIA

Blogs

Call-centre
logs

INTERNAL
DATA

VERACITY

Surveys

Winning
games

Marketing optimization – less investment in
„traditional“ marketing with higher utilization
TRADITIONAL MARKETING

TRADITIONAL MARKETING

General image
advertising
Segmented
communication
IDENTIFICATION

IDENTIFICATION

profiling
direct

8

1to1 MARKETING

1to1 MARKETING

Advanced analytics helps find meaning
in vast quantity of data
Classification

Grouping customer based
on their common
characteristics
demographic, behavioral

Associations

Understanding relationship
between customers in
social network or product
in shopping basket

Predictions

Finding what differentiate
buyer from not
buyer, churner from not
churner and make a
prediction

Cust_1

Cust_2

Cust_3

WEB
EVENT
TV

STIMULATION

OUT

AQUISITION

PRINT
CATALOG
RADIO
WOM
WOM
WEB SEARCH
WEBSITE

RESEARCH

SOCNET
CONTACT

AQUISITION

WEB PRICE
MOBILE
WEB RESEARCH
WEBSITE
CONTACT
MOBILE

PURCHASE

STORE
STORE PROMO &…
STORE MOB
WEB RESEARCH

PERSONALISED SELLING
CROSS-SELLING
UP-SELLING

SURVEY
WOM

POST
PURCHASE

WEBSITE

SOCNET

RETENTION

Cust_1

Cust_2

Cust_3

WEB
EVENT
TV

STIMULATION

OUT
PRINT

• Testing which ad/video /tweet will
have better impact

CATALOG
RADIO
WOM
WOM
WEB SEARCH
WEBSITE

RESEARCH

SOCNET
CONTACT

WEB PRICE
MOBILE
WEB RESEARCH

• Click-stream analysis to present most
suitable ad-content to display
• Lead scoring and managing in order
to achieve best conversion

WEBSITE
CONTACT
MOBILE

PURCHASE

STORE
STORE PROMO &…
STORE MOB
WEB RESEARCH
SURVEY
WOM

POST
PURCHASE

WEBSITE

SOCNET

• Most probable next product
recommendation
• Combination of most suitable
products for cross-sell
• Retaining customers by predicting
most probable churners
• Campaign evaluation

Sales

Traditional campaigns

Days/Weeks
13

Sales

Traditional campaigns

Days/Weeks
14

„Smart“ optimized campaigns

Sales

Smaller more targeted
campaigns

Days/weeks
15

„Smart“ optimized campaigns

Sales

Smaller more targeted
campaigns

SMART follow-up campaigns

Days/weeks
16

„Smart“ optimized campaigns
Smaller more targeted
campaigns

Sales

Increase of Sales

SMART follow-up campaigns

Days/weeks
17

How to start with BigData?
1.
2.
3.
4.
5.
6.
7.
8.

Clearly identify simple problem
Identify suitable data
Use existing data
Analyze data
Decide on action
Action!
Measure the outcome
Improve and do it again!

Presentation given at the Internet Retailing Customer Experience Jumpstart event on 19th June 2013. The presentation explains how @SDL_CMA can help retailers improve the customer experience of their customers. By using a combination of data, analytics and marketing, retailers can deliver improvements to ROI A video of the presentation can also be found on the Internet Retailing you tube channel at http://www.youtube.com/watch?v=rOmpghu8AUU

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