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© Absolutdata 2014 Proprietary and Confidential
Chicago New York London Dubai New Delhi Bangalore SingaporeSan Francisco
www.absolutdata.com
April 30, 2014
FAST facts
Customer Analytics
© Absolutdata 2014 Proprietary and Confidential 2
In Spring 2013, Alteryx and
Absolutdata surveyed industry
thought leaders to gather insight into
how organizations use Customer
Analytics, including adoption levels,
goals, usage, and relative maturity.
This document provides a fast
summary of our findings.
© Absolutdata 2014 Proprietary and Confidential 3
69%
69%
61%
49%
41%
31%
30%
17%
6%
Customer demographics
Primary/research data
POS/transaction data
Customer interaction data
Social media
Loyalty card data
Complaint data
Recorded voice calls
Others
Companies collect many different types of
customer data
Data captured from every customer
interaction has the potential to
provide deeper insight into their
behavior, attitudes, and opinions—
insight that can be leveraged to
improve customer relationships and
gain a competitive edge.
The survey results show that
traditional data sources still
dominate, but several new areas of
insight are emerging.
© Absolutdata 2014 Proprietary and Confidential 4
82%18%
Yes No
The vast majority of companies use
Customer Analytics today
Organizations are listening to what
customers say through their data.
They use this insight to implement
customer-driven marketing strategies
that improve revenue and customer
loyalty.
But, are they getting full value from
their data?
© Absolutdata 2014 Proprietary and Confidential 5
Customer
Focus
Channel
Focus
69%
63%
46%
62%
60%
49%
Customer
acquisition/retention
Enhanced customer
satisfaction
Increased loyalty
Improve product/service
design
Optimize
marketing/channel
Design/improve channel
strategy
Customer Analytics contributes significant
insight in support of strategic operations
Product
Focus
WHERE IS THE VALUE?
Customer Analytics is used primarily
for customer-focused Sales &
Marketing activities.
But, many also use this insight to
make product/service portfolio
decisions, and determine the optimal
distribution channels.
© Absolutdata 2014 Proprietary and Confidential 6
CHALLENGE #1:
Getting the Right Data
CHALLENGE #2:
Lack of Access & Skills
CHALLENGE #3:
ROI Assessment
Three Major Challenges Inhibit Analytic Decision Making
© Absolutdata 2014 Proprietary and Confidential 7
43%
39%
38%
37%
23%
Accessing data managed
by other departments
Integrating massive
amounts of data
Integrating disparate
data types
Converting data into
actionable insight
Collecting and storing
relevant data
CHALLENGE #1: Getting the Right Data
 Different departments use different
data sources in an attempt to answer
similar questions
 Time is wasted with tools that cannot
process
Big Data efficiently
 Unstructured, but valuable data such as
social media and call center logs cannot
be used
Massive volumes of disparate data types
and sources must become easier to
access, work with, and blend.
© Absolutdata 2014 Proprietary and Confidential 8
12%
38%
42%
8%
Industry leading, with a mastery of advanced analytics
Advanced, using predictive and spatial analytics
Basic, for modification of existing analytic workflows
Limited, for generating reports only
CHALLENGE #2: Lack of Access & Skills
 Limited IT staff/resources require line-
of- business users to perform their own
analytics
 Access to data and overly complex tools
remains a barrier to greater analytics
usage
 There is limited ability for new
analyses, especially in B2B companies
where basic skills dominate
The analytics required to answer complex
questions must be put into the hands of
users with the industry knowledge and
skills.
© Absolutdata 2014 Proprietary and Confidential 9
CHALLENGE #3: ROI Assessment
 Organizations struggle with defining &
calculating ROI for analytics
 Less than half can identify positive ROI
 Implementation of marketing best
practices can
be accelerated using specialized
support
ROI remains elusive so a new paradigm is
required that puts the right data and
analytics into the hands of those who drive
the business forward.
9%
10%
43%
38%
Return is less than investment
Return is equal to investment
Return is more than investment
Don't know or can't measure
© Absolutdata 2014 Proprietary and Confidential 10
RECOMMENDATION #1:
Massive volumes of disparate data types and sources must become easier to
access, work with, and blend.
RECOMMENDATION #2:
The analytics required to answer complex questions must be put into the hands of
users with the industry knowledge and skills.
RECOMMENDATION #3:
ROI remains elusive so a new paradigm is required that puts the right data and
analytics into the hands of those who drive the business forward.
© Absolutdata 2014 Proprietary and Confidential 11
71%
75%
95%
22%
12%
4%
7%
13%
1%
External
Resources
People
Technology
Positive No change Negative
Average Increase: 21%
Average Increase: 25%
Average Increase: 14%
Average Decrease: 10%
Average Decrease: 11%
Average Decrease: 12%
Analytics Investment Continues Despite these challenges, almost all
companies plan to increase their
investment in analytics
technology, people and external
resources.
© Absolutdata 2014 Proprietary and Confidential 12
Alteryx/Absolutdata will be publishing
a white paper in July 2013 to provide
more information about this survey
and a detailed review of the results.
Plus, this paper will provide insight
about how to put data to work to
predict customer behavior, and create
targeted offers that drive critical
improvements in sales, customer
retention, and loyalty.
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Customer analytics fast facts v3

  • 1. © Absolutdata 2014 Proprietary and Confidential Chicago New York London Dubai New Delhi Bangalore SingaporeSan Francisco www.absolutdata.com April 30, 2014 FAST facts Customer Analytics
  • 2. © Absolutdata 2014 Proprietary and Confidential 2 In Spring 2013, Alteryx and Absolutdata surveyed industry thought leaders to gather insight into how organizations use Customer Analytics, including adoption levels, goals, usage, and relative maturity. This document provides a fast summary of our findings.
  • 3. © Absolutdata 2014 Proprietary and Confidential 3 69% 69% 61% 49% 41% 31% 30% 17% 6% Customer demographics Primary/research data POS/transaction data Customer interaction data Social media Loyalty card data Complaint data Recorded voice calls Others Companies collect many different types of customer data Data captured from every customer interaction has the potential to provide deeper insight into their behavior, attitudes, and opinions— insight that can be leveraged to improve customer relationships and gain a competitive edge. The survey results show that traditional data sources still dominate, but several new areas of insight are emerging.
  • 4. © Absolutdata 2014 Proprietary and Confidential 4 82%18% Yes No The vast majority of companies use Customer Analytics today Organizations are listening to what customers say through their data. They use this insight to implement customer-driven marketing strategies that improve revenue and customer loyalty. But, are they getting full value from their data?
  • 5. © Absolutdata 2014 Proprietary and Confidential 5 Customer Focus Channel Focus 69% 63% 46% 62% 60% 49% Customer acquisition/retention Enhanced customer satisfaction Increased loyalty Improve product/service design Optimize marketing/channel Design/improve channel strategy Customer Analytics contributes significant insight in support of strategic operations Product Focus WHERE IS THE VALUE? Customer Analytics is used primarily for customer-focused Sales & Marketing activities. But, many also use this insight to make product/service portfolio decisions, and determine the optimal distribution channels.
  • 6. © Absolutdata 2014 Proprietary and Confidential 6 CHALLENGE #1: Getting the Right Data CHALLENGE #2: Lack of Access & Skills CHALLENGE #3: ROI Assessment Three Major Challenges Inhibit Analytic Decision Making
  • 7. © Absolutdata 2014 Proprietary and Confidential 7 43% 39% 38% 37% 23% Accessing data managed by other departments Integrating massive amounts of data Integrating disparate data types Converting data into actionable insight Collecting and storing relevant data CHALLENGE #1: Getting the Right Data  Different departments use different data sources in an attempt to answer similar questions  Time is wasted with tools that cannot process Big Data efficiently  Unstructured, but valuable data such as social media and call center logs cannot be used Massive volumes of disparate data types and sources must become easier to access, work with, and blend.
  • 8. © Absolutdata 2014 Proprietary and Confidential 8 12% 38% 42% 8% Industry leading, with a mastery of advanced analytics Advanced, using predictive and spatial analytics Basic, for modification of existing analytic workflows Limited, for generating reports only CHALLENGE #2: Lack of Access & Skills  Limited IT staff/resources require line- of- business users to perform their own analytics  Access to data and overly complex tools remains a barrier to greater analytics usage  There is limited ability for new analyses, especially in B2B companies where basic skills dominate The analytics required to answer complex questions must be put into the hands of users with the industry knowledge and skills.
  • 9. © Absolutdata 2014 Proprietary and Confidential 9 CHALLENGE #3: ROI Assessment  Organizations struggle with defining & calculating ROI for analytics  Less than half can identify positive ROI  Implementation of marketing best practices can be accelerated using specialized support ROI remains elusive so a new paradigm is required that puts the right data and analytics into the hands of those who drive the business forward. 9% 10% 43% 38% Return is less than investment Return is equal to investment Return is more than investment Don't know or can't measure
  • 10. © Absolutdata 2014 Proprietary and Confidential 10 RECOMMENDATION #1: Massive volumes of disparate data types and sources must become easier to access, work with, and blend. RECOMMENDATION #2: The analytics required to answer complex questions must be put into the hands of users with the industry knowledge and skills. RECOMMENDATION #3: ROI remains elusive so a new paradigm is required that puts the right data and analytics into the hands of those who drive the business forward.
  • 11. © Absolutdata 2014 Proprietary and Confidential 11 71% 75% 95% 22% 12% 4% 7% 13% 1% External Resources People Technology Positive No change Negative Average Increase: 21% Average Increase: 25% Average Increase: 14% Average Decrease: 10% Average Decrease: 11% Average Decrease: 12% Analytics Investment Continues Despite these challenges, almost all companies plan to increase their investment in analytics technology, people and external resources.
  • 12. © Absolutdata 2014 Proprietary and Confidential 12 Alteryx/Absolutdata will be publishing a white paper in July 2013 to provide more information about this survey and a detailed review of the results. Plus, this paper will provide insight about how to put data to work to predict customer behavior, and create targeted offers that drive critical improvements in sales, customer retention, and loyalty.