1. Accenture Analytics
Customer Analytics Survey
May 2011
Copyright © 2011 Accenture All Rights Reserved. Accenture, its logo, and High Performance Delivered are trademarks of Accenture.
Copyright © 2010 Accenture All Rights Reserved. Accenture, its logo, and High Performance Delivered are trademarks of Accenture.

2. Summary of key findings
• Accenture’s Customer Analytics Survey of 800 directors and senior managers at blue chip
organizations in Brazil, China, Germany, Italy, Japan, Spain, United Kingdom & Ireland and the
US and Canada showed that more than half (55 percent) of respondents felt their methods for
segmenting customers and providing relevant experiences are either “ideal” or “very good
However, more than half of the organizations surveyed do not take advantage of analytics to help
them target, service or interact with customers. Most organizations accept they could benefit from an
improved use of customer analytics
•When making decisions about what customers want, many organizations are just as likely to rely on
personal experience as analysis of data and facts
•Even amongst organizations actively using analytics in marketing, sales and service, most are not
applying it broadly across the full spectrum of marketing and customer activities such as pricing,
product/service delivery, and product development
•Less analytically mature firms are much more likely to perceive their data sources as accurate and
reliable than organizations with more developed analytic capabilities
• Corporate culture also poses challenges. While almost 70 percent of respondents said their senior
management was totally or highly committed to analytics and fact based decision making, corporate
culture still presents a major barrier
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3. Extent to which organizations are taking advantage of analytics to
target, service or interact with customers
60
%ages
50
70% us analytics for just 2 of the
functions or fewer.
40
36
33
30
20 17
10
10
3
1 0
0
Using analytics for Using for any 1 Using for any 2 Using for any 3 Using for any 4 Using for any 5 Using far all 6
none of the 6
The 6 areas or functions are Sales, Marketing, Customer service, Product/service
pricing, Product/service delivery and New product/service development
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4. Areas in which organizations would benefit, and by how much,
from a greater or more sophisticated use of analytics
Would benefit at all (1+2) % Would benefit greatly (1) %
Market profile/company image 50
18
45 Most organizations accept they
Competitive position 16 could benefit from an improved
use of customer analytics
New product/service development 45
17
Product/service delivery 43
14
Product/service pricing 44
12
Customer service 57
32
Marketing 57
23
Sales 55
27
0 10 20 30 40 50 60 70 80
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5. Extent to which even analytically minded organizations are missing
opportunities.
Proportions of major users of customer analytics not using for……………..
New product/service development 59
Product/service delivery 77
Product/service pricing 86
Customer Service 56
Marketing 35
%ages not using analytics
Sales 61 in each area
0 10 20 30 40 50 60 70 80 90 100
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6. Extent to which customer and prospect data and analytics provides
Sales and Marketing functions with an important asset from which
new ideas and opportunities are regularly generated
%ages saying to a great extent
70
60
50
40
32 32 33
30
20
10
0
Total Most analytically mature Least analytically mature
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7. Extent to which analytics has been beneficial in understanding…..
Proportions saying very beneficial
Speed/level of customer activity 26
Speed of customer return 23
Sales team management 27 %ages saying very
beneficial
Individual customer revenue 21
Determining reasons for losing customers 28
Customer service performance 29
Marketing campaign performance/ROI 25
Customer activity by channel 32
0 5 10 15 20 25 30 35 40
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7

8. Resources used by senior managers when making decisions about
what their customers want
Very important %
Consultation with colleagues 15
When making decisions about what
Personal experience 23 customers want , many organizations
are just as likely to rely on personal
experience as on analysis of simple data
and facts
Intuition 12
More complex data analysis 17
Simple data and facts 22
0 5 10 15 20 25 30 35 40
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9. Frequency of use of customer analytics in each area
%age saying very frequently
40
35
30
25 23 23
21
20
15
10
5
0
Sales Marketing Customer service
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10. Perceived quality of customer and prospect data taken
as a whole
Proportion describing data as “extremely clean” in each aspect
Most analytically mature
companies %
Least analytically mature
Accessibility 15 companies %
16
Ease of use/understanding 11
24
Level of integration 13
9
27 In many areas poor analytical users
Consistency 22 say their data is cleaner. This
probably reflects a lack of awareness
Completeness 16 of its poor quality caused by limited
30 use - “blissful ignorance”
Format 9
26
Accuracy 19
45
0 10 20 30 40 50 60
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11. How well organizations claim to segment and manage different
types of customers and prospects
Ideal or close to it % Very good % Quite good % Pretty poor % Not very well at all %
80
More than half (55 %) of respondents felt their methods for segmenting customers and providing
70 relevant experiences are either “ideal” or “very good.
60
50 45
40
40
30
20
10
10 5
1
0
Total
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12. What is holding organizations back?
Perceived barriers to improving customer management activities
and driving better decision making
Most analytically mature
companies %
Least analytically mature
companies %
Staff skills limitations 33
22
Data quality limitations 25
25
Technology limitations 35
36
47 Corporate culture at the
Budget limitations 29 organization, departmental and
senior management level,
Lack of senior managment support 45
31 poses a real challenge
Culture within sales, marketing and customer service 40
29
Corporate culture 33
42
0 10 20 30 40 50 60 70
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13. Commitment of the senior Sales and Marketing management teams
to analytics and fact-based decision making
Totally committed % Highly committed % Somewhat committed % Not very committed % Not at all committed %
70
68 per cent of senior S+M teams are at least highly
committed so this is not a major barrier to improved
60 use of analytics in most companies
50
50
40
30 26
18
20
10 6
0
0
Total
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14. Extent to which organizations use customer data as a predictive
tool for…………
%ages saying to a great extent
70
Again only between approximately one quarter and one third of
companies use analytics as a predictive tool in any of these areas
60
50
39
40 36
32 31
30 26 26
20
10
0
Sales growth
Competitor performance/activity arket trends
M Price movement Product life cycle product/service opportunity
New
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15. How beneficial the use of analytics has been for understanding (By
customer type)
Marketing campaign performance/ROI
100
Very benefical % (1) Quite benefical % (2) At least quite % (1+2)
90
80
73
71
70 68
60
50 45
43
39
40
34
30 25 25
20
10
0
Total Primarily B2B Primarily B2C
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16. Which of the following are barriers to improving your customer management
activities and driving better decision making?
B2B
Yes %
Staff skills limitations 25
Data quality limitations 32
Technology limitations 32
Budget limitations 34
Lack of senior management support 26
Culture within the sales team,
marketing and customer service 41
function
Corporate culture 34
0 5 10 15 20 25 30 35 40 45 50
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17. Which of the following are barriers to improving your customer management
activities and driving better decision making?
B2C
Yes %
Staff skills limitations 36
Data quality limitations 26
Technology limitations 44
Budget limitations 38
Lack of senior management support 36
Culture within the sales team,
marketing and customer service 39
function
Corporate culture 40
0 5 10 15 20 25 30 35 40 45 50
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