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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.
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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.
Customer demograph-ics
Primary/research data
POS/transaction data
Customer interaction data
Social media
Loyalty card data
Complaint data
Recorded voice calls
Others
69%
69%
61%
49%
41%
31%
30%
17%
6%
Companies collect many different types of customer
data
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82%18%
Yes No
The vast majority of companies use Customer
Analytics todayOrganizations 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?
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Customer Focus
ChannelFocus
Customer acquisition/retention
Enhanced customer satisfaction
Increased loyalty
Improve product/service design
Optimize marketing/channel
Design/improve channel strategy
69%
63%
46%
62%
60%
49%
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.
Customer Analytics contributes significant insight in support of
strategic operations
ProductFocus
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CHALLENGE #1:Getting the Right Data
CHALLENGE #2:Lack of Access & Skills
CHALLENGE #3:ROI Assessment
Three Major Challenges Inhibit Analytic Decision Making
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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 processBig 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.
Accessing data managedby other departments
Integrating massiveamounts of data
Integrating disparatedata types
Converting data into actionable insight
Collecting and storing relevant data
43%
39%
38%
37%
23%
8
12%
38%42%
8%
Industry leading, with a mastery of advanced ana-lytics Advanced, using predictive and spatial analytics Basic, for modification of existing analytic work-flows 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 toolsremains 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.
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CHALLENGE #3: ROI Assessment
• Organizations struggle with defining & calculating ROI for analytics
• Less than half can identify positive ROI
• Implementation of marketing best practices canbe 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
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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.
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Despite these challenges, almost all companies plan to increase their investment in analytics technology, people and external resources.
ExternalResources
People
Technology
71%
75%
95%
22%
12%
4%
7%
13%
1%
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
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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.