Business Intelligence in Retail Customer Management

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Business Intelligence in Retail Customer

Management

Bringing Information Together to Build the Accurate Customer Profile

November 2006

Sponsored, in part, by:



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Aberdeen Group • i

Executive Summary

ndersatanding customer behavior has long been the elusive challenge of retailers
to unlocking the true potential of programs, promotion, product sales, and much
more. Stymied in the past by unruly data locked away in a data warehouses, the
art of mastering this challenge may be at hand with technology advancements of

late in the area of retail business intelligence. Historically, retailers have tended to look
at their customers in aggregate: that is they look at classes of customers, clusters of stores
and general target demographics. As a consequence, retailers would yield less than opti-
mal results when changing elements such as their messaging, marketing, merchandising
and pricing strategies.

Key Business Value Findings

• Best-in-Class retailers lead the way when it comes to managing customer product

interaction: 70% of these organizations track new product adoption; 100% track
promotion participation; and 91% of these retailers track product preferences/affinity.
The net result is that Best-in-class retailers have a sharper understanding of cus-
tomer/product behaviors.

• Eighty two percent of respondents are using BI on an enterprise-wide basis. How-

ever, only 16% of survey respondents, and 33% of Best-in-Class respondents, use
real- or near-real-time business intelligence-related data measuring techniques.

Implications and Analysis

The behaviors and activities of retailers utilizing business intelligence in retail customer
management directly affect bottom-line performance. For example:

• Eighty two percent of respondents are using BI on an enterprise-wide basis, however,

only 16% of survey respondents, and 33% of Best-in-Class respondents, use real- or
near-real-time business intelligence-related data measuring techniques.

• Fifty six percent of respondents use BI functionality to manage customer cross-sells

and up-sells, but only in a limited way (e.g. not typically done in real time).

Recommendations for Action

• Move to real-time BI-related data measurement.
• Prioritize the formal measurement of customer behavior analytics, such as the use of

customer conversion, acquisition, and retention measurement activities.

• Address the internal, non-technical challenges associated with BI, such as resistance

to trusting data generated by business intelligence systems, and the ability to BI to
replace existing functionality.

U

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Aberdeen Group

Table of Contents

Executive Summary .............................................................................................. i

Key Business Value Findings.......................................................................... i
Implications and Analysis................................................................................ i
Recommendations for Action.......................................................................... i

Chapter One: Issue at Hand.................................................................................1

Good Customer Service Comes From Good Customer Data ........................ 2

Chapter Two: Key Business Value Findings .........................................................4

Best in Class Keep their C-Level Executives Invested in
Business Intelligence.................................................................................... 7
Challenges and Responses........................................................................... 8

Chapter Three: Implications & Analysis...............................................................9

Process and Organization ........................................................................... 10
Data and Knowledge – Opportunity Missed................................................. 11
Measurement............................................................................................... 11
Pressures, Actions, Capabilities, Enablers (PACE)...................................... 12

Chapter Four: Recommendations for Action ......................................................14

Laggard Steps to Success........................................................................... 14
Industry Norm Steps to Achieve Best in Class Results................................ 14
Best in Class Next Steps ............................................................................. 15

Featured Sponsors.............................................................................................16

Sponsor Directory ..............................................................................................17

Appendix A: Research Methodology ..................................................................18

Appendix B: Related Aberdeen Research & Tools .............................................21

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Aberdeen Group

Figures

Figure 1: Cross-sells and Up-sells, Loyalty Programs Dominate BI Use..............3

Figure 2: Active BI Users More Likely to Have Traditional
Customer Measurements Available for Use .........................................................5

Figure 3: Best-in-Class Companies Focus on Traditional
Customer Buying Habits.......................................................................................6

Figure 4: C-Level Executives Using BI to Understand their Customers ...............7

Figure 5: Best in Class Measure Performance at the Enterprise Level ..............10

Figure 6: Retailers Miss Opportunities to Use Their Data .................................. 11

Figure 7: Traditional Store Sales Remains as Top KPI to Measure BI................12

Tables

Table 1: Top Pressures Driving In-Store Improvements .......................................1

Table 2: Business Intelligence: Retailer Challenges and Responses ...................8

Table 3: Business Intelligence in Customer Management
Competitive Framework .......................................................................................9

Table 4: PACE (Pressures, Actions, Capabilities, Enablers)...............................13

Table 5: PACE Framework .................................................................................19

Table 6: Relationship between PACE and Competitive Framework ...................19

Table 7: Competitive Framework........................................................................20

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Aberdeen Group • 1

Chapter One:

Issue at Hand

argeting and retaining in-store customers has never been an easy task for retailers,
especially in today’s rapidly expanding multi-channel selling environment. Tradi-
tionally, retailers have tended to look at their customers in aggregate: that is they
look at classes of customers, clusters of stores and general target demographics.

This analysis can often result in an incomplete picture of customer behavior and buying
patterns. As a consequence, retailers would yield less than optimal results when changing
elements such as their messaging, marketing, merchandising and pricing strategies. Lack
of internal systems that allow retailers to effectively evaluate and act on customer behav-
ior trends has stood in the way of progress.

Providing a higher level of customer performance has been center stage for retailers for
some time. On the one hand, retailers feel constant pressure from Wall Street and other
stakeholders to maximize earnings per share, predictability, and performance against
their peers. On the other hand, these same retailers recognize that these metrics alone,
achieved in isolation without understanding, are short lived.

Recent Aberdeen research confirms these challenges and the priority retailers place on
providing increased customer performance. For example, in

The Empowered Store: De-

lighting Customers, Motivating Employees, and Pleasing Shareholders

, as well as

The

Empowered Point of Service: The Customer Reclaims Her Kingdom

, eroding customer

loyalty and improving customer service were two of the top three pressures for opera-
tional improvements.

Table 1: Top Pressures Driving In-Store Improvements

Pressures Within the Store Environment

91% — Inconsistent store execution
87% — Product or service differentiation on factors besides price
73% — Eroding consumer loyalty
92% — Improve customer service without increasing labor costs
80% — Improved employee productivity

Source:

Aberdeen

Group

, November 2006

R

Key Takeaways

• Retailers tend to look at their customers in aggregate: classes of customers, clusters of

stores and general target demographics.

• Fifty six percent of respondents use BI functionality to manage customer cross-sells and

up-sells. Other top areas of BI use include loyalty rewards programs, sales analysis, and
identification and targeting of specific households.

T

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2 • AberdeenGroup

Good Customer Service Comes
From Good Customer Data

Good customer service is heavily dependent
on how well a retailer knows its customer.
However, most retailers still manage mes-
saging, marketing, merchandising and pric-
ing strategies, independent of understanding
the impact on individual customer behavior.
Left uncoordinated, retailers will find them-
selves challenged to make optimized deci-
sions to truly impact the bottom line.

As a response to the challenge business in-
telligence application are being deployed
and are changing the way retailers manage
customer data within their enterprises. Fal-
ling hardware prices and increased process-
ing power, coupled with advances in ana-
lytic engines, are coming together to raise
the value of a next generation business intelligence offerings. Business intelligence
functionality has evolved beyond simple dashboards that show red, yellow, and green
flags for exception reporting, to simple but sophisticated systems capable helping retail-
ers understand future trends based on past performance and missed opportunities.

Theoretically, the “Holy Grail” of retailing is the prospect of establishing a single view
of manageable data across the enterprise. When it comes down to coordinating en-
hanced customer performance strategies, this mantra could not be truer. Although the
retail industry has a long way to go to hit that goal, the vendor community is moving in

the right direction. Best in Class retailers, defined as having
annual store sales growth of more than 3%, improved cus-
tomer retention, and decreased shrink rates are seeking new
and improved solutions to managing this process.

Retailers Utilize BI for Increased Customer
Touches

Between March and November of 2006, the Aberdeen
Group surveyed more than 175 respondents on their BI
strategies. Fifty three percent of these respondents indicated
that they have active Business Intelligence implementations
in place for their customer management processes – the most
popular category of BI use (along with BI in Merchandising)
among survey respondents. (See

Business Intelligence in

Retail Merchandising: Harnessing Advanced Data Manage-
ment to Address Today’s Merchandising Challenges

) Ac-

cording to these executives, cross-selling/up-selling, loyalty
rewards programs and sales analysis were the top three uses

PACE Key — For more detailed descrip-

tion see Appendix A

Aberdeen applies a methodology to benchmark
research that evaluates the business pressures,
actions, capabilities, and enablers (PACE) that
indicate corporate behavior in specific business
processes. These terms are defined as follows:

Pressures —

external forces that impact an

organization’s market position, competitiveness,
or business operations
Actions —

the strategic approaches an organi-

zation takes in response to industry pressures
Capabilities —

the business process competen-

cies required to execute corporate strategy
Enablers
— the key functionality of technology
solutions required to support the organization’s
enabling business practices

Competitive Framework

Key

The Aberdeen Competitive
Framework defines enter-
prises as falling into one of
the three following levels of
practices and performance:

Laggards — practices that
are significantly behind the
average of the industry

Industry norm — practices
that represent the average
or norm
Best in Class — practices
that are the best currently
being employed and signifi-
cantly superior to the indus-
try norm

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Aberdeen Group • 3

of BI for customer management within the enterprise. Other top uses of BI in customer
management included sales analysis, identification and targeting specific households as
potential customers, and prediction of spending patterns (Figure 1).

Figure 1: Cross-sells and Up-sells, Loyalty Programs Dominate BI Use

Use of BI for Customer Management

25%

27%

27%

37%

51%

54%

56%

0% 10% 20% 30% 40% 50% 60%

New customer acquisition

One-on-one marketing

Predict spending patterns

Identify and target specific households

as potential customers

Sales Analysis

Loyalty rewards programs

Cross-sells and up-sells

Source:

Aberdeen

Group

, November 2006

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4 • AberdeenGroup

Chapter Two:

Key Business Value Findings

Key Takeaways

• Best-in-Class retailers are on the cutting edge of quantifying customer behaviors: 73% of

these organizations measure customer conversion, and 100% of Best-in-Class retailers
measure retention and acquisition.

• Best-in-Class retailers also lead the way when it comes to managing a customer’s prod-

uct interaction: 70% of these organizations track new product adoption, 100% track pro-
motion participation, and 91% of these retailers track product preferences/affinity.

• Lack of data management centralization was the top challenge associated with business

intelligence in customer management (according to 49% of respondents), and data
cleansing projects to improve data quality was the top response to existing challenges
(according to 61% of respondents).

n the Aberdeen Group BI benchmark report,

Business Intelligence in Retail: Bringing

Cohesion to a Fragmented Enterprise,

it was reported that 76% of respondents indi-

cated they use or have active, budgeted plans to use business intelligence in some

form within their organizations. Although such high metrics are promising news for the
retailers themselves, understanding the role of business intelligence in the organization is
essential to its success. For example, retailers need to consider:

What executive-level support is required to ensure successful BI implementations?

Should business intelligence be measured in real time, batched, or ad-hoc to achieve
balanced results?

How will BI data be viewed and applied?

What role does BI have beyond customer management and how will this impact cus-
tomer performance?

In addition to understanding and answering these key questions, retailers should also
look to understand the advantages of using BI to empower customer relationship man-
agement (CRM) or marketing automation applications, and measuring such traditional
customer metrics as acquisition, retention and conversion. In addition, there is the pos-
sibility of using BI to strengthen “sales floor” decision-making and track customer buy-
ing behavior such as product preference/affinity, promotion participation, and new
product adoption
.

I

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Aberdeen Group • 5

Acquisition, Retention and Conversion:
Best-in-Class Customer Management BI Users Know Them Well

Respondents who currently use of BI for customer management have demonstrated a
specific willingness to use customer metrics such as retention, acquisition, and conver-
sion to monitor their customer base, in comparison to those who are still planning for this
specific use of BI. In two of those three metrics (and extremely close in the third), those
who are already using BI for customer management were more likely to actively conduct
these measurements. In addition, in all three metrics, Best-in-Class were much more
likely then either of the previous two groups to use such metrics in their business process.

Traditional CRM functionality can be a crucial first step into collecting and managing
customer conversion, retention, and acquisition data. In addition, Knowledge Manage-
ment functionality may bolster this data to provide consistency through out the organiza-
tion. Providing top-line decision-making based on advanced customer data management,
however, can be achieved by combining measurement of traditional customer manage-
ment parameters with business intelligence functionality. Customer management business
intelligence solutions that utilize these metrics allow for a more holistic picture of the
customer, and provide the specificity decision-makers need to increase potential cross-
and up-sells on a per-customer basis, versus a per demographic basis. While the analysis
cannot guarantee respondents’ actual utilization of these metrics with BI, their shear
availability puts retailers in a position to strengthen existing BI functionality with this
data, already available for use.

Figure 2: Active BI Users More Likely to Have Traditional Customer Measure-
ments Available for Use

Use of Traditional Customer Management

100%

100%

73%

73%

77%

47%

51%

54%

48%

0%

20%

40%

60%

80%

100%

120%

Acquisition

Retention

Conversion

Best-in-Class

Active BI User

Planned BI User

Source:

Aberdeen

Group

, November 2006

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6 • AberdeenGroup

Customer Preferences, Promotions, New Product Adoptions:
The Pattern Continues

Traditional ways of tracking customer behavior, such as acquisition, retention and con-
version are helpful in gaining a good understanding of the customer and his or her overall
touch points with the retail enterprise. However, by themselves, they may not provide the
specificity to accurately qualify a customer’s exact behavior when it comes to the spe-
cific interaction with that particular retailer. Thus, more specific metrics, such as an un-
derstanding of customer adoptions, promotion participations, and what types of product
preferences they prefer may provide retailers with a more approximate level of customer
characteristics. If this data is collected, the ability to generate more intelligent BI deci-
sions becomes that much greater.

Figure 3: Best-in-Class Companies Focus on Traditional Customer Buying Habits

Use of Traditional Customer Buying Habits

91%

100%

70%

78%

73%

63%

60%

52%

48%

0%

20%

40%

60%

80%

100%

120%

Product

Preferences/affinity

Promotion

Participation

New product

adoption

Best-in-Class

Active BI User

Planned BI User

Source:

Aberdeen

Group

, November 2006

Case Study Quote

“Extremely large companies (Safeway, Albertsons, Wal-
Mart, etc.) obtain information so massive they cannot
interpret it on the micro level of the individual store that
[it was] generated [from].The larger the organization,
the harder and slower the information flow to the pro-
duce clerk and courtesy clerk, where it is needed for
direct impact on the customer base.”

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Aberdeen Group • 7

Best in Class Keep their C-Level Executives Invested in Business
Intelligence

In the original Aberdeen Group business intelligence benchmark report, it was reported
that 58% of average performers, and 70% of Best-in-Class performers noted that their BI
endeavors were driven by top management, including C-level executives. In the case of
business intelligence specific to customer management, however, respondents were
slightly more inclined to have this C-level support. Indeed, Best-in-Class C-level execu-
tives may be using Corporate Performance Dashboards, in addition to and augmented by
operational BI, to monitor customer activity. The focus on customer management has
thus proven itself to be a concern driven from the top of an organization downwards.

Figure 4: C-Level Executives Using BI to Understand their Customers

Highest Enterprise Level Using BI

0%

8%

8%

83%

17%

11%

8%

63%

0%

20%

40%

60%

80%

100%

VP

Director

Manager

C-level

Best-in-Class

All Respondents

Source:

Aberdeen

Group

, November 2006

Case Study Quote

“…the business and IT departments can-
not seem to prioritize the utilization of
real-time or near real-time customer
data. Business intelligence is essentially
underused because the analytics and as-
sociated reports are not tied directly to
the user experience. Uptime is easier to
produce than true cross-selling.”

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Challenges and Responses

Data cleanliness and lack of organizational control of customer management data metrics
were highlighted by retailers as top challenges associated with managing business intelli-
gence implementations within the enterprise. These challenges remain obstacles to retail-
ers of all sizes and success levels, and proves that while retailers are good at collecting
data, their analysis and decision-making skills need work.

Thirty percent of respondents also indicated that their organizations are somewhat un-
willing to use information generated by BI functionality. This type of challenge was con-
sistent among retailers of all types, such as laggard, industry average, and Best-in-Class
respondents. This is explained by that fact that advanced BI that uses predictive analytics
is a relatively new concept, as well as the cultural trust and reliance executives often
place on existing systems and functionality. Those who have completed advanced BI
processes may have to lead the way in addressing this challenge.

Table 2: Business Intelligence: Retailer Challenges and Responses

Challenges

% Selected

Responses to Challenges

% Selected

Data is scattered throughout the
organization; not centralized

49%

Data cleansing projects to improve
data quality

61%

Data is not clean enough
for analysis

46%

Executive mandates for change

44%

Business processes do not lend them-
selves to making use of this informa-
tion

40%

Small projects in pilot departments to
measure ROI

44%

Not enough customer-specific informa-
tion to generate valid results is avail-
able

35%

Select small cross-functional team to
implement

38%

Not have enough time to make use of
any more information - already drown-
ing in data.

33%

Bring in outside help to change busi-
ness processes

31%

Organization is unwilling to use the
information generated by the system.

29%

Select process areas that are easier
to install with simpler algorithms

31%

The use, integration, and complexity of
the algorithms of business intelligence
engines is daunting

29%

Align compensation incentives to BI
system results

22%

Source:

Aberdeen

Group

, November 2006

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Aberdeen Group • 9

Chapter Three:

Implications & Analysis

s shown in Table 2, behaviors and activities directly affect performance for busi-
ness intelligence ROI recognition. Survey respondents in each of the three Com-
petitive Framework categories – Laggard, Industry Average, or Best in Class —
exhibited different characteristics in five key categories: process (consistency

across the enterprise); organization (corporate focus/philosophy, level of collaboration
among stakeholders); knowledge (visibility into and timing of results); technology (scope
of automation and productivity tools) and measurement (frequency of measuring per-
formance).

In each category, survey results show that firms exhibiting Best-in-Class behaviors and
characteristics also enjoy Best in Class sales improvements:

Table 3: Business Intelligence in Customer Management Competitive Framework

Laggards

Industry Average

Best in Class

Process

Process is different for
each store.

Process is consistent
across departments.

Process is standardized
company-wide, across
all banners or store
brands.

Organization

Business intelligence
programs, if existent,
measure enterprise or
departmental
performance.

Business intelligence
programs measure
departmental
performance.

Business intelligence
measures enterprise
performance, enabling
multi-departmental deci-
sions to be made.

Knowledge

Sales and receipt data
reviewed on an ad hoc
basis.

Business Intelligence
data on sales and re-
ceipt data reviewed
daily.

Business Intelligence
data on sales and re-
ceipt data reviewed in
near real-time.

Key Takeaways

• Eighty two percent of respondents are using BI on an enterprise-wide basis. However,

only 16% of survey respondents, and 33% of Best-in-Class respondents, use real- or
near-real-time business intelligence-related data measuring techniques.

• 100% of BIC organizations measure customer retention. However, retailers have noted a

specific difference between data collection and actual utilization. Only 33% of all respon-
dents use this measurement as a top BI-related KPI.

• Comparable same store sales and gross margin were the top two KPIs in which BI data

was used to measure performance.

A

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10 • AberdeenGroup

Laggards

Industry Average

Best in Class

Technology

Business Intelligence
data is driven through a
spreadsheet.

Business Intelligence
data is driven through a
spreadsheet.

Business Intelligence
data is driven either
through portals or a
dashboard.

Measurement

Comparable store sales
by department, store
rank as top KPIs for data
measurement.

Gross margin, compara-
ble store sales by store
rank as top KPIs for data
measurement.

Gross margin, compara-
ble store sales by store
rank as top KPIs for data
measurement.

Source:

Aberdeen

Group

, November 2006

Process and Organization

Business processes and organizational structures for business intelligence are often
closely associated with overall sales success levels. For process and organization, how-
ever, some interesting correlations can be made between average and laggard retail per-
formers. While Best-in-Class retailers were focused on enterprise-related BI functionality
(100% of responses), a majority of both average (81%) and laggard responders (100%)
focused on departmental-based BI data. None of the three groups mentioned above were
focused solely on individual-based BI decision systems. This may indicate a step in the
right direction for retailers looking to increase the scope of their overall BI implementa-
tions.

Best in Class respondents (100%) indicated widespread use of BI across the enterprise
(Figure 5). Merchandise planning, distribution, store operations, customer experience,
and multi-channel selling efforts are all coordinated for increased visibility. Considering
that the activities of a vast majority of business departments have some effect or another
on customer management, it is logical for retailers to use BI on an enterprise-wide basis.

Figure 5: Best in Class Measure Performance at the Enterprise Level

What is the Scope of BI Within Your Organization?

100%

58%

0%

82%

79%

31%

0%

20%

40%

60%

80%

100%

120%

Enterprise

performance

Department

Performance

Individual

Performance

Best-in-Class

Active Implementations

Source:

Aberdeen

Group

, November 2006

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Aberdeen Group • 11

Data and Knowledge – Opportunity Missed

Only 33% of Best in Class and 16% of all survey respondents take the opportunity to
review BI-related information in real- or near-real-time (Figure 6). Given retailers’ objec-
tives to create a more dynamic and fast-moving supply network capable of interdepart-
mental data management processing, this remains an area that needs attention.

Figure 6: Retailers Miss Opportunities to Use Their Data

Time Frame for Measuring BI

33%

33%

17%

16%

48%

18%

0%

10%

20%

30%

40%

50%

60%

Real or near-real

time

Day

Week

Best-in-Class

All Survey Reciepients

Source:

Aberdeen

Group

, November 2006

Measurement

Comparable store by store sales volume was the number one way retailers are measuring
the successes of their business intelligence implementations. Gross margin was not far
behind, with 51% of respondents. Surprisingly, customer retention was indicated as a top
success measurement only by 33% of respondents.

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Figure 7: Traditional Store Sales Remains as Top KPI to Measure BI

Top KPIs to Measure BI Success

25%

29%

33%

37%

51%

52%

0%

10%

20%

30%

40%

50%

60%

Logistics

performance

Merchandise Turn

Customer

Retention

Comparable Store

Sales by

Department

Gross Margin

Comparable Store

Sales by Store

Source:

Aberdeen

Group

, November 2006

Pressures, Actions, Capabilities, Enablers (PACE)

Aberdeen’s research has consistently shown a clear relationship between the pressures
companies identify and the actions they take, and their subsequent competitive perform-
ance. In other words, retailing excellence is not just an accident, a function of convenient
store locations, or the result of a merchant with a “hot hand”. We encourage all readers to
examine the prioritized PACE selections in Table 3. Comparing their own priorities to
those of Best in Class retailers can provide valuable insight into performance improve-
ment opportunities.

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Aberdeen Group • 13

Table 4: PACE (Pressures, Actions, Capabilities, Enablers)

Priorities

Prioritized

Pressures

Prioritized

Actions

Prioritized

Capabilities

Prioritized

Enablers

1

Rapid response
ability to con-
sumer demand

Improve cus-
tomer service

Centralize
data in the
organization

Data cleansing projects to
improve data quality

2

Become more
operationally effi-
cient

Improve back-
office productiv-
ity

Clean existing
data

Small projects in pilot de-
partments to measure ROI

3

Manage demand
across multiple
channels

Sharpen pricing
life cycle capa-
bilities

Make use of
business in-
formation

Executive mandates for
change

4

Improve store
performance

Improve in-
store productiv-
ity

Generate spe-
cific customer
information

Select small cross-
functional team to imple-
ment

5

Stem the tide of
price deflation
and eroding gross
margins

Improve mer-
chandise as-
sortments

Make time to
use informa-
tion

Select process areas that
are easier to install with
simpler algorithms

Source:

Aberdeen

Group

, November 2006

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14 • AberdeenGroup

Chapter Four:

Recommendations for Action

Key Takeaways

• Move to real-time BI-related data measurement.
• Prioritize the formal measurement of customer behavior analytics, such as the use of

customer conversion, acquisition, and retention measurement activities.

• Address the internal, non-technical challenges associated with BI, such as resistance to

trusting data generated by business intelligence systems, and the ability to BI to replace
existing functionality.

usiness Intelligence, especially when it comes to customer management, is neither
a monolithic business process, nor is it always supported by the same technology.
Solutions once considered “advanced” may be little more than glorified spread-

sheets. Whether a company is trying to gradually move from Laggard to Industry Aver-
age, or Industry Average to Best in Class, the following actions will help spur the neces-
sary performance improvements:

Laggard Steps to Success

1. Move to more frequent BI-related KPI measurements.

Seventeen percent of Laggard respondents indicated that they measure data only
on an ad-hoc basis, compared to zero Best in Class respondents. Measuring data
without a formal, repetitive plan prevents good data comparison. The more fre-
quent t the measurement, the better optimized the decision.

2. Use customer retention as a business intelligence success metric.

Seventy seven percent of respondents who used business intelligence in customer
management indicated they measure customer retention. However, only 33% of
these retailers indicated they use this KPI as a measurement of how successful
their business intelligence implementation is. Retailers should consider integrat-
ing this data with traditional comparable store sales information to get a more ac-
curate read on whether a technological implementation that directly affects cus-
tomer centricity is a success or failure.

Industry Norm Steps to Achieve Best in Class Results

1. Prioritize the formal measurement of customer behavior analytics, such as the

use of customer conversion, acquisition, and retention measurement activities.

Forty three percent of industry average respondents indicate that they currently
measure customer conversion metrics, versus 73% of Best-in-Class retailers. This
trend was similar in customer acquisition and retention, as well as product pref-
erences/affinity, promotion, and new product adoption. Industry average
retailers should consider focusing their success metrics around existing busi-
nesses intelligence functionality to gain a better understanding of the customer.

B

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Aberdeen Group • 15

2. Take Business Intelligence Functionality to the Enterprise level with Corporate

Performance Management.

Obtaining a high level of customer transparency involves the utilization of many
metrics. Marketing information, supply chain movement, CRM data, and other
metrics all play a hand in true customer business intelligence. Industry norm re-
tailers must take this to heart, as only 57% of these executives use enterprise-
wide business intelligence (compared with a full 100% of Best-in-Class retail-
ers).

Best in Class Next Steps

1. Address the internal, non-technical challenges associated with BI, such as resis-

tance to trusting data generated by business intelligence systems, and the ability
to BI to replace existing functionality.

A consistent theme in Aberdeen’s research is the prohibitive internal challenges
associated with advanced BI functionality (See Table 1: Business Intelligence:
Retailer Challenges and Responses). Although these challenges are consistent
among all retailers, Best-in-Class show strength in other areas of BI use, such as
data measurement, and must now manage these other issues to increase their
overall process efficiency.

2. Extend business intelligence beyond traditional customer management opera-

tions.

Customer management and merchandising processes came across as the two
most popular uses of BI among all respondents. But for Best in Class retailers,
the focus of BI should not be limited to these specific niches of the enterprise. In-
stead, the entire business should benefit from good interdepartmental communi-
cations. Best-in-Class respondents indicated they measure customer management
data at the enterprise level. They should now extend these processes beyond cus-
tomer management, and into such processes as back-office, and loss prevention
BI strategies.

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16 • AberdeenGroup

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Aberdeen Group • 17

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18 • AberdeenGroup

Appendix A:

Research Methodology

etween March and November 2006, Aberdeen Group examined the business in-
telligence practices, initiatives, procedures, experiences, and intentions of more
than 165 retailers, 78% of which indicated active or planned use of BI within the
enterprise. Of that 78%, 53% of respondents are actively using business intelli-

gence for retailer customer management, and an additional 43% are actively budgeting or
planning for BI in this area.

Responding executives completed an online survey that included questions designed to
determine the following:

• Methods of business intelligence-related deployment and management within the

organization (Business intelligence is defined as using data to harness the power
of massive customer and transaction data warehouses into a set of manageable
performance metrics);

• Current and planned use of various applications defined as “advanced” by their

use of sophisticated mathematical algorithms; and

• Business challenges and pressures these retailers face that drive adoption of new

initiatives.

Our intention was to determine whether and how each of the above created competitive
advantage for retailers that use them and a disadvantage for those that do not. From there,
we identified emerging best practices and provided a framework by which readers could
assess their own capabilities and ways to improve effectiveness.

Responding enterprises included the following:

Job Titles/Functions:

The research sample included respondents with the following

job titles: Senior management, including CEOs, CFOs, CEOs and CIOs (32%), Vice
Presidents (7%); directors (17%), managers (27%) and internal consultants and staff
(9%). Functional areas represented included planning, allocation and/or replenish-
ment, merchandising, logistics, finance, information technology, marketing, product
development, and others.

Retail Segments:

The research sample included respondents from across the retail

spectrum. Fast-moving consumer goods companies represented 33% of the respon-
dent base, including supermarket, convenience stores, chain drug, and warehouse
stores. More than 51% were from general merchandise and apparel, including large
and small footprint specialty stores, mass merchandisers, and department stores. The
other 19% came from hardware and “do it yourself,” furniture, and restaurant and
hospitality.

Geography:

Fifty-three percent (53%) of respondents were from North America,

including the U.S., Canada, and Mexico. Twenty-three percent (23%) were from
Europe, the Middle East and Africa; and 20% were from the Asia/Pacific region.

B

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Aberdeen Group • 19

Remaining respondents were from South and Central America and the Caribbean
(5%).

Company Size:

About 29% of respondents were from large enterprises (annual reve-

nues more than $1 billion); 39% were from mid-size enterprises (between $50 mil-
lion and $1 billion); and 33% from small businesses ($50 million or less).

Solution providers recognized as sponsors of this report were solicited after the fact and
had no substantive influence on the direction of Business Intelligence in Retail Customer
Management: Bringing Information Together to Build the Accurate Customer Profile.
Their sponsorship has made it possible for

Aberdeen

Group

to make these findings avail-

able to readers at no charge.

Table 5: PACE Framework

PACE Key

Aberdeen applies a methodology to benchmark research that evaluates the business pressures, actions,
capabilities, and enablers (PACE) that indicate corporate behavior in specific business processes. These
terms are defined as follows:

Pressures

external forces that impact an organization’s market position, competitiveness, or business

operations (e.g., economic, political and regulatory, technology, changing customer preferences, competi-
tive)
Actions

the strategic approaches that an organization takes in response to industry pressures (e.g., align

the corporate business model to leverage industry opportunities, such as product/service strategy, target
markets, financial strategy, go-to-market, and sales strategy)
Capabilities

the business process competencies required to execute corporate strategy (e.g., skilled

people, brand, market positioning, viable products/services, ecosystem partners, financing)
Enablers
— the key functionality of technology solutions required to support the organization’s enabling
business practices (e.g., development platform, applications, network connectivity, user interface, training
and support, partner interfaces, data cleansing, and management)

Source:

Aberdeen

Group

, June 2006

Table 6: Relationship between PACE and Competitive Framework

PACE and Competitive Framework: How They Interact

Aberdeen research indicates that companies that identify the most impactful pressures and take the most
transformational and effective actions are most likely to achieve superior performance. The level of com-
petitive performance that a company achieves is strongly determined by the PACE choices that it makes
and how well it executes.

Source:

Aberdeen

Group

, June 2006

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20 • AberdeenGroup

Table 7: Competitive Framework

Competitive Framework Key

The Aberdeen Competitive Framework defines enterprises as falling into one of the three following levels of
retail practices and performance:

Laggards (30%) — Retail practices that are significantly behind the average of the industry, and result in
below average performance. For this study, Laggards were defined as those retailers with similar or in-
creasing year-over-year levels of shrink, and similar or decreasing year-over-year levels of customer reten-
tion.

Industry norm (50%) — Retail practices that represent the average or norm, and result in average industry
performance. For this study, Industry Norm was defined as those retailers with improved customer reten-
tion.

Best in Class (20%) — Retail practices that are the best currently being employed and significantly superior
to the industry norm, and result in the top industry performance. For this study, Best-in-Class was defined
as fulfilling three requirements: (1) Better than average year-over-year comparable store sales increases
(2) Improved shrink, and (3) Improved customer retention.

Source:

Aberdeen

Group

, June 2006

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The Business Intelligence in Customer Management Benchmark Report

Aberdeen Group, Inc.
260 Franklin Street
Boston, Massachusetts
02110-3112
USA

Telephone: 617 723 7890
Fax: 617 723 7897
www.aberdeen.com

© 2006 Aberdeen Group, Inc.
All rights reserved
December 2006

Founded in 1988, Aberdeen Group is the technology-

driven research destination of choice for the global

business executive. Aberdeen Group has over 100,000

research members in over 36 countries around the world

that both participate in and direct the most comprehen-

sive technology-driven value chain research in the

market. Through its continued fact-based research,

benchmarking, and actionable analysis, Aberdeen Group

offers global business and technology executives a

unique mix of actionable research, KPIs, tools,

and services.

The information contained in this publication has been obtained from sources Aberdeen believes to be reliable, but
is not guaranteed by Aberdeen. Aberdeen publications reflect the analyst’s judgment at the time and are subject to
change without notice.
The trademarks and registered trademarks of the corporations mentioned in this publication are the property of their
respective holders.

Appendix B:

Related Aberdeen Research & Tools

Related Aberdeen research that forms a companion or reference to this report include:

The Proactive Merchant: Anticipating Consumer Demand

(December 2004)

The Empowered Store Benchmark Report: Delighting Customers, Motivating Em-
ployees, and Pleasing Shareholders

(September 2004)

The Empowered Point of Service Benchmark Report: The Customer Regains Her
Kingdom

(June 2005)

The Business Benefits of Advanced Planning and Replenishment

(December 2005)

Perspective: Retail Business Intelligence Drives Top and Bottom Line Growth

(March, 2006)

Customer Intelligence Management Benchmark Report: Converting Data to Profits

(December, 2005)

Chasing the Holy Grail: A Unified Planning Process for Retailers

(February 2005)

Information on these and any other Aberdeen publications can be found at

www.Aberdeen.com

.

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AberdeenGroup

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on its Web site.

This publication is protected by United States copyright laws and international treaties. Unless otherwise
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Group, Inc., and may not be reproduced, stored in another retrieval system, or transmitted in any form or
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The trademarks and registered trademarks of the corporations mentioned in this publication are the
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All information contained in this report is current as of publication date. Information contained in this
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