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Technology Infrastructure Breakout Session How to Obtain a 17:1 ROI Using a Next Evolution Approach to Global Data Quality
Welcome
2
Session Objective:
• Why data quality is a key component of cCRM
• Managing big data on an international level and optimizing it to support overall marketing strategies
• How to build a business case and gain buy-in from key stakeholders
• Implementing a data quality initiative in a way that reduces risk and ensures success
• Measuring the impact by creating a meaningful ROI
Evan Kent Global Vice President
Chandos Quill Vice President, International Solutions
To prepare for digitization, you must have a technology set to deliver this across all channels.
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Name
Cookie
Phone
IP
Address
Session
User ID
Device ID
Offer
Content
Personal
Determine Strategy
Resolve Identities
CC DM EM Display Search Social Mobile Site Retail TV Print Radio
Data Insights
Map Events
Deliver Experience
Offer Media
Experience
Product Distribution
Price
Cross-channel technology delivery
Schneider Electric
4
Moving a Fortune 354 company
one data source at time
Schneider Electric
billion € of sales in 2012
employees in 100+ countries
of sales devoted to R&D
Global Specialist in Energy Management:
of sales in new economies
Residential
Utilities & Infrastructure
Industrial & machines
Data centres
Non-residential buildings
North America
25% 28,300
9%
25%
22%
15%
29%
Diversified end markets FY2012 Sales (b€)
Western Europe
30% 44,200
Asia Pacific
27% 42,600
Balanced Geographies FY 2012 sales & YE emp
Rest of World 18%
22,000
Proliferation of data has provided us with granular & specific information on customer and prospect behavior
The combination of traditional marketing, digital marketing and analytics are the new compliments
Sophisticated data management is the path to organic growth
What a unique time in history to be in marketing…Our day has come!
From digital exoskeleton to nervous system
© Edd Dumbill, Strata, Aug. 29, 2012
Digital exoskeleton
Nervous system
In 2012 (that’s 31 zeros!)
Corporate emails daily
Tweets daily Facebook posts daily
Mobile subscribers
Smart phone users
Is the customer really at the center?
Result: A disjointed brand experience, a sub-optimal sales cycle, wasted resources.
Are you listening to me?
Integrate and automate the inbound/outbound to mirror the buying cycle
It’s a win-win!
Digitization enables marketing to offer the right content at the right time. Customers are not bombarded, sales doesn’t waste their time.
• Remove duplicates • Address standardization • Contact history • Contact subscriptions • Data overlays
GMDB Merge/purge
Rules
First Logic
Hygiene/Std. Q coding
Solution
Schneider Electric Merkle
37 Global Source
Systems Bar
Napkins Social
Rebate Warranty
Call Center
XLS
Micro sites
Web
Siebel Reg
Forms
Customer Master
SFDC
Event Portals
So why data hygiene?
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• Global is blind without local • Efficiency & ROI • Complex CDIs – 1.65M records per update • Recover records • Combine digital actions to drive print support
And for Schneider Electric, the starting point was improving the data quality in the global database
Meaningful: • What are we solving for? • Usage • Enrich data set
Cleaning: • Standardization • De-duplication • Accuracy of info • Eliminate waste
Data Hygiene and Governance
Data Validation, Enrichment
and Sourcing
Contact Strategy
Speed to
market
Marketing action layer
Information-driven insight
layer
Foundation layer
Merkle’s Approach Schneider’s Implementation
Speed: • Real-time decision making • Cross-sell, up sell • Course correct
Most common issues include: • Missing data • “Stale” data • “Bad” data • Duplicate data
On a global basis, these issues are even more prevalent: • Dual language keyboards • Fantasy street names • Unique naming conventions
The Data Quality “Issue Matrix”
Data quality issues are not the result of any “one” thing and become even more complex when dealing with data from multiple countries
GMDB
Cleansing, standardization, verification, correction, suppression
Local Data Quality Solution
#1
Local Data Quality Solution
#2
Local Data Quality Solution
#3
Merge/purge
First Logic
Solution Schneider Electric Merkle
First-pass -- or -- Quarterly Net New
37 Global Source
Systems
GMDB
Present the Findings Run the Data Forecast Final
Results Run a Pilot
• Involve all stakeholders • Publish findings broadly • Ask for more $$$
• Pull the data • Run the data • Analyze results
• Update calculator • Update scorecard • Communicate
• Pull the data • Run the data • Analyze results • Make recommendations
Obtaining buy-in through a business case
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Schneider Electric Merkle
Ask for permission Or beg for forgiveness?
Identify Stakeholders
Forecast Test Results
• Identify the Top X “dirty data” countries.
• Match with the Merkle country partnerships
• Determine test qty • Determine eligible
attributes • Decide methodology
• Design a calculator • Create scorecard • Communicate
expectations w/teams
• Stakeholders • Influencers • Approvers
Sample Admit a Problem
Schneider Electric The impact
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Netherlands: key findings
Data Quality Components Impact Records Submitted 58,250
Number of records with mailable = Y 42,102
Number of records with mailable = N 16,148
Number of records with Q4, Q5 and Q6 8,378
Number Q4-Q6 of records corrected to “Y” after cleansing 1,081 12.9%
Number Q1-Q3 records suppressed after cleansing 7,477 15.0%
44%
27%
1% 1%
12%
5%
10%
Data Quality Flags 1 2 5 6 7 8 10
72%
28%
0%
20%
40%
60%
80%
100%
120%
%Mailalbe
Mailable Distr.
N
Y
Netherlands: key findings
Verification and Standardization:
Correction and Suppression:
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pages of paper saved Savings over 3 years Trees conserved
Key Takeaways
Decide build or buy
Identify “dirty data” countries in relation to your strategic objectives
Create a baseline through business case
Develop standard quality codes for your MDB
Test > Roll out > Quarterly updates (or as needed)
Demand samples of corrected records
Document your findings
Thank you Evan Kent Global Vice President Customer Retention Schneider Electric [email protected] @evankent22 linkedin.com/in/evankent Chandos Quill Vice Presiddent, International Solutions Merkle Inc. [email protected]
