Be Certain. Be Trillium Certain.

CRMUG SIGAvoiding Data Quality Pain in CRM The Impact on User Adoption

August 6, 2013

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Agenda

� Introductions & Expectations

� Trillium Software Overview

� Facts on CRM User Adoption

� Impact of Data Quality on User Adoption

� Steps to Avoid the Pain Associated with Poor Data Quality

� Questions & Answers

With over 25 years experience in the Information Technology industry, Dave has held numerous customer and partner-facing positions with Trillium Software for the past 17 years. He is a member of Trillium Software’s Executive Council and currently Vice President of Global Alliances.

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Trillium Software

A Division of Harte Hanks, Inc.

300 Concord Road, Suite 200

Billerica, MA 01821

978-671-6008

davep@trilliumsoftware.com

About Dave Pietropaolo

..with deep data quality expertise

• CRM, CDI & MDM

• Single Customer view

• Vertical applications

• Business Intelligence

Who is Trillium Software?

Best in class, proven technology leader…

• Gartner

• 2012 Magic Quadrant: Leader

• Rated as leader for over 10 years

• Forrester

• Forrester Wave – Leader

• Current Analysis: Very threatening to competition

• Bloor Research (UK):

• Best in Class

Trillium is a global provider and innovator of data quality solutions

• A business unit of Harte-Hanks (HHS-NYSE) - $1+B revenue & 6000 employees worldwide

• Over 2 decades in business with specific focus on data quality solutions market

• Solution platform (technology + domain expertise) addresses business critical, enterprise data

quality requirements

• Our Mission - “To enable our clients to develop data quality management programs that

support on-going improvements in business performance”

Trillium Software Customers

Insurance and Healthcare Manufacturing Technology

Financial Services Retail and Energy Pharma/Life SciencesHospitality/Transportation

Trillium/Microsoft Partnership

Courted by Microsoft

Used by Microsoft internally

Managed in “Top 200 ISVs”

Complimentary Technology

Expertise

� Recognized leader – Gartner Magic Quadrant & Forrester Wave

� Oracle & SAP compete

� Best in class solution for enterprise data quality leveraged internally by Microsoft for over a decade

� CRM Orion TAP Beta Participant

� “We are pleased to be working with Trillium Software to deliver

strong value to current customers while enabling expansion into

new growth markets.” – Mark Albrecht, Microsoft Dynamics Director, ISV Strategy

� Accurate data increase adoption rate of CRM & other Microsoft technologies

� Proven Enterprise Data Quality technology

� 30+ Years experience in data management

� Integration w/Dynamics CRM Online & On Premise

� Over 2,000 implementation around the globe

� Silver Application Development Partner

Data Quality Defined

� Data Quality Basics?� Data can be seen as high quality if it is fit for its intended uses

in operational, decision making/analytical and planning processes

� Factors that influence Data Quality?� The number of potential definitions of “the customer” defined by user communities;

departments, channels, business units, regions, etc.

� Business rules controlling cleansing and matching logic must be flexible and powerful

� Co-mingled, global data; diverse business standards, languages, character sets, addressing formats, naming conventions, business rules and expectations

� Integration within CRM must provide real-time interactive and high-volume batch processing

� Data Quality should be integrated as a natural part of the CRM user’s experience

Industry Research: Just the Facts

� Companies implement CRM systems so they can answer important questions about their customers.

� Many companies believe that investing in a CRM solution, in and of itself, will result in the much-sought-after 360° view of customer relationships.

� However 50% or more of companies with CRM programs are not satisfied with the customer views they get, citing distrust of the data among those who are supposed to use them.

� They are finding that investing in data integrity, reliability, and completeness is also critical—both for integrating diverse data for use in CRM systems and keeping that valuable information up-to-date.

Source:

Industry Research: Just the Facts

� At least 25% of most companies’ data is probably inaccurate, according to industry analysts at Gartner.

� If your data was cleansed at integration, you may breathe a little easier—but not much. Even clean data can degrade. Consider:

� 2% of all customer data becomes stale monthly, for an annual rate of 25%.

� 70% of people change at least one item on their business cards each year.

� 7-10% of consumers and businesses relocate every year.

� Given the data challenges, it’s not surprising that companies report having as many as 40 - 400 disjointed records for one corporate customer.

Source:

Sales Contact

John Nicoli

Alpha Imports, Inc.

501 6th Avenue, Suite 700

New York, NY 10071

Direct: 212-345-5000,ext.101

Mobile: 917-625-4546

jnicoli@alphaimports.com

Customer Data Cleansing and Matching

Across Multiple User Communities

Service Contact

Jack Nicoli

Alpha Importers Co.

501 Avenue of the Americas

Manhattan, NY 10071

Direct: 212-345-5101

jnicoli@alphaimports.com

Service Id# 87005

Marketing Lead

John Nicole

AIC

501 6th Ave.

New York, NY

Main: 212-345-5000

jbn55@yahoo.com

Service Contact

John (Jack) Nicoli Direct: 212-345-5000, ext.2101

Alpha Importers, Inc. Mobile: 917-625-4546

501 Avenue of the Americas Service Id# 87005

Suite 700 jnicoli@alphaimports.com

Manhattan, NY 10071 jnicoli@yahoo.com

Industry Research: Just the Facts

� Changing data — An accurate, up-to-date, and integrated record for each customer is difficult to achieve because the facts themselves keep changing.

� Every transaction registers some change. In addition, about 2% of all customer data becomes stale each month.

� Integrated, clean data is what successful companies strive for, yet only 15% of businesses report full integration among their customer data systems.

� Analysts believe poor data quality is a primary reason that 40% of all CRM business initiatives fail to achieve their targeted benefits.

Source:

Why Tackle Data Quality

Along With CRM?

� Because Data Quality degrades due to normal, everyday CRM business processes

� Real-time data entry by diverse sets of users

� Different departments and channels have different data needs and standards

� Integration with other applications and systems, e.g. ERP

� Mergers/Acquisition require CRM integration

� List imports/external data

� Reference data feeds

Adoption Defined:

1. To take and follow by choice or assent: for example a course of action or a new technique

2. To take up and make one's own: adopt a new idea

3. To take on or assume: adopt as important

4. To vote to accept: agree to a resolution

5. To choose as standard or required: adopt a new line of thinking or process to pursue

CRMUG Whitepaper

Driving User Adoption, August 2012

Top Five Common Causes of Poor

User Adoption

1. Poor data accuracy and lack of a management plan

2. The application is not set up to work the way an organization does

3. Insufficient training

4. Missing executive sponsor

5. Several things can lead to confusion and frustration when learning new software

http://www.crmug.com/member-resources/crm-online/drivinguseradoption.pdf

Top Five Excuses

1. I don’t trust the data.

2. I don’t know how to use the software.

3. It takes too much time.

4. It doesn’t follow our business process or work the way we work.

5. Management doesn’t use

it, why should I?

Data Quality Impacts All Areas of CRM

Need to Involve all User Communities

Source: Forrester Research

Increase revenue per sales rep

Shorten sales cycleIncrease average

order size

Increase close rateIncrease conversion

rateIncrease revenue per customer

Increase campaign response rate

Decrease lead-generation cost

Decrease customer acquisition cost

Increase marketing sourced revenue

Improve targeted prospecting

Accelerate lead maturation

Increase customer retention

Increase customer service productivity

Reduce customer service costs

Decrease service response times

Decrease call waiting times

Decrease request solution time

CRM objectives

Sales

Marketing

Service

Business

function

Sales

• Data collection and content management

• Correspondence processing

• Opportunity management

• Pipeline tracking

• Sales team collaboration

• Task and activity management

• Order processing and delivery

• Proposal and sales history

• ………

Sales Operations & Management

• Pipeline Management

• Opportunity inspection & strategy

• Activity analysis and trending

• Revenue forecasting

• Reporting

• Analytics

• Channel Management

• Partner analysis, promotion and growth

• ……….

Marketing

• Target marketing and demand creation

• Data acquisition and management

• Lead nurturing and development

• Campaign management

• Multi-channel marketing

• Customer retention and growth

• Reporting & analytics

• Senior management dashboarding

• ……….

Services

• Customer care and lifecycle management

• Contact management and correspondence

• Case management and service history

• Escalation

• Collaboration with professional services

• Closed loop w/product management and development

• Reporting, trending and analytics

• ……….

Aberdeen Group Research Study

Leveraging Data Quality Best Practices and Technologies to Improve Sales Effectiveness

� Net result: better data created significant efficiencies and time is money, thus best-in-class had more opportunity to succeed.

� Data quality had direct impact on user adoption based on the realized value of being able to maximize “quality customer facing time”.

Aberdeen Group Research Study

continued

� The study included strategies for integrating, standardizing and cleansing customer data

� For more details, download the study from our website

Industry Research:

Recommendations

1. Recognize the value of 360°customer view

2. Define data business rules across lines of business to establish a

360°customer view

3. Implement customer data integration (CDI) tool to cleanse, de-duplicate,

merge and manage customer data

4. Employ clean data to integrate sales, marketing and customer service

standards

5. Increase user adoption rates through confidence in your data

6. Data Quality Management is not a one-time event, it is a journey

Forrester Research:

Data Management

Fundamentals for CRM

What are enterprises doing to

realize value from CRM?

Source: Forrester Research

10 Steps to Ensure

Data Quality Adoption

1. Establish clear objectives you can measure and are aligned with organizational goals – outline your vision, e.g. single customer views

2. Recognize that data quality is not just an IT issue, business involvement and ownership required

3. Really understand the technology and how it will fit short and long term

4. Senior management sponsor along with project (and data) champions

Excerpts from: Nigel Turner, Strategic Consulting Services, Trillium Software

10 Steps to Ensure

Data Quality Adoption

5. Remember, Slow and Steady Wins the Race; Change must occur - process, culture and behavior…and don’t forget data will change!!

6. Ensure high quality data for both operational and analytical purposes… and fit-for-purpose for each constituent group

7. Training is vital, not only how…by why are we doing this?

8. Establish a governance approach

9. Apply intentional energy to adoption

10.Track and measure ROI

Excerpts from: Nigel Turner, Strategic Consulting Services, Trillium Software

CRM Adoption = Strategic and

Operation Usage

� CRM must be core to business process

� Every day/hour/minute usage

� Must provide significant, recognized value to the user’s every-day role, activities and responsibilities

� Must be embraced by the user community based on value, usability and purpose

Data Quality Value to CRM

• Deliver a complete understanding of total customer value and total household value across accounts, products, and divisions

• Reduce risks and errors in data consolidation and data migration for a CRM package through data discovery and integrated cleansing

• Resolve customer data anomalies before they enter operational systems and impact relationship management decisions

• Form the basis for accurate analytics, reporting, forecasting, profiling, scoring, segmenting, and targeting

• Enforce your definition of customer, prospect, household, contact, etc. and how that information is to be recorded and reflected within your organization

Data Quality Helping Deliver Business Value to

CRM Programs will Foster User Adoption:

Factors that Influence Successful

Data Quality Management

� Business Rules and Processes – robust, best practice business rules delivered with the software to leverage for rapid results

� Tunable rules with traceable results – adapt to specific business requirements & defend why results were produced

� Deep data quality subject matter knowledge – provide thought leadership, independence and over 30 years of experience

� Context-sensitive processing – superior approach for cleansing and matching data regardless of data domain

� High performance for real-time and high volumes deployments – designed from inception for complex, operational deployments

� Global reach – wide & deep worldwide coverage

� Architecture - Enterprise scalability & availability – single, fault-tolerant platform to support all business processes, applications and platforms

Data Quality Management

When & Where

Data Quality Processes Applied to:

1. New CRM Implementations

• Data Migration and Conversions

• Initial Cleanse

2. Existing CRM Implementations with Data

Challenges

• Data Assessments & Analysis

• Initial Cleanse

• Integrated within the CRM application

3. Integrated within the CRM Application

• DQ processes embedded as filters within batch

and real-time CRM processes

CUSTOMER

DATA

Dynamics

CRM

Cleanse &

Migrate

Cleanse &

MigrateCUSTOMER

DATA

CUSTOMER

DATA

Ideal Resource & Activities

Mix for CRM Initiatives

� User Adoption has its own program track with major focus and effort to drive value, usage and adoption

� Adoption is derived from strategy definition, objective setting and defining of new processes

Data Quality Management and CRM

In Summary:

• CRM is highly data centric and requires data quality management to fully realize program potential

• Clear objectives must be established in order to set expectations, manage change and measure success

• Collectively CRM & data quality must be leveraged at all levels

• Natural Progression =

� Data Accuracy and understanding

� Trust & Confidence

� Derived Business Value

� User Adoption!!

Recommended Reading

� CRMUG Whitepaper, Driving User Adoption

� Gartner, The Eight Building Blocks of CRM: Data and Information

� Aberdeen Research, Leveraging CRM in the Pursuit of the Elusive “Single View of the Customer”

� Forrester Research; Best Practices: Getting The Most From Your CRM Deployment

Questions?