Welcome to the

Topic 1: Enhancing customer value using big data and actionable insights

Dr Julia Keddie and Goran Dragosavac

© BSG. All rights reserved CONSULTING | TECHNOLOGY

Big data has given businesses access to more customer behavioural data than ever before. To remain competitive and be seen as industry leaders, companies must turn this data into intelligence that will support business leaders in enhancing customer value

In an ever-changing digital world…

The world of today

Marketing automation and digital marketing

Real-time decisioning

Web-reporting and data

integration

Data mining and marketing optimisation Internet

Call centre

Centralised customer and contact data

Online and social media

TV

Email and post

Mobile

Collect inputs /

Responses

Collect inputs /

Responses

Collect inputs /

Responses

Collect inputs /

Responses

Use history in

in-boundmarketing

Use history in

in-boundmarketing

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The four Vs

Big data

Big data

01 Volume• Clickstream• Active / passive sensor• Log• Event • Printed corpus• Speech• Social media• Traditional

03 Velocity• Speed of generation• Rate of analysis

02

04

Variety• Unstructured• Semi-structured• Structured

Veracity• Untrusted• Uncleansed

Organisations must understand what insights they need to make good strategic and operational decisions

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Customer life cycle

Profit

Time

Cross-sell/Up-sell RetentionTermination / RecoveryAcquisition

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Voice of customer

Customer value

Product segmentation

Customer segmentation

Customer acquisition

Cross-sell / Up-sell

Next product offering

Customer retention /

Loyalty churn

Customer Lifetime value

Buy

CreativityDesire

Satisfaction

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Actionable insights

Big data

Actionable intelligence Profitability

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Data scientist

Hypothesis testing

Mathematics

Statistics

Modelling and prescriptive analytics

Data modelling

Big data solution engineering

Exploratory data analytics

Data Science

Pattern recognition

Data mining

Machine learning

Artificial intelligence

Neural networks

Data visualisation

SQL, R, SAS, Python, Matlab, Java, SPSS, Stata, Perl, Hive, Pig, Spark, Ruby, Ruby on Rails, XML, HTML, Javascript, C/C#

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Data science capability

http://www.kdnuggets.com/2015/11/different-data-science-roles-industry.html

Data ArchitectThe Contemporary Data

Modeller

Data AnalystData Detective

Data and Analytics Manager

Data Science Team Leader

StatisticianHistoric Leaders of Data

Data EngineerSoftware Engineers by

trade

Business Analyst

Change Agent

Data ScientistAs rare as unicorns

Database AdministratorDatabase Caretaker

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Conclusion

CONSULTING | TECHNOLOGY

“Customer expectations have evolved as well – they expect us to know who

they are and what they need.”Joan Dal Bianco

Senior Vice President, TD Bank

Fishbowl 1What do we need to set up to deliver to customer wants and needs?Greg Desilla

Fishbowl 2How can we address the challenges with Data Science skills in our organisations?Shiraz Amod

Topic 2: Driving innovation through customer insights

Jason Suttie

© BSG. All rights reserved CONSULTING | TECHNOLOGY

Organisations are embracing innovation and setting up innovation units to adapt quicker to changes in market demand, to embrace disruptive opportunities, and to have a positive impact on the bottom-line. New ideas and innovations must be practical and relevant to the market and attractive to the organisation’s customers. This topic looks at innovating and practically implementing innovative solutions in collaboration with customers; whilst protecting the intellectual property that is generated throughout the process. 

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Conclusion

CONSULTING | TECHNOLOGY

Fishbowl question:

How have you approached customer interactions while protecting IP?

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