Best Practices for Keeping Your Data Clean

Best Practices for Keeping Your Data Clean

Marketing Professionals

Dave Hughan: JigsawGreg Malpass: Traction Sales & Marketing IncRenee Gellatly: NetApp

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Agenda

Why you need to have a data quality strategy?

Best practices for data cleansing and data quality

Q&A

How NetApp is keeping their data clean and relevant and the results

Good Data is the Lifeblood of Sales & Marketing

Critical for Prospecting

Required for Customer Analysis

Marketing Lists

Sales Reps

Business Cards

Web Forms

All Companies Struggle in Some Way with Data

Average Dirty Data Found in Customers Before Jigsaw

90%Incomplete

74%Need Updates

21%Dead

7%Duplicate

$10+ Billion Annual Market

We Spend $10B+ Buying, Managing, Cleaning It

$4 Billion MarketCRM Data &

Marketing Lists

$0.5 Billion MarketSales & Marketing Research, Intelligence

$6 Billion MarketData Integration,

Management / Hygiene

There’s a Real Impact on Marketing Organizations

65% of titles incorrect42% of addresses incorrect43% of phone numbers incorrect37% of email addresses incorrect

1Coe, John M. “B2B Data Decay – The Untold Story.” Sales & Marketing Institute. 2002 http://www.b2bmarketing.com.

2009

2010

70% of Contact Data Outdatedafter 12 Months1

And a Real Impact on Sales Organizations

One sales rep calling 12 wrong numbers a

day wastes 20+ hours a month.

Average Dirty Data Found in New Jigsaw Customers:

90%Incomplete

74%Need Updates

21%Dead

7%Duplicate

1Coe, John M. “B2B Data Decay – The Untold Story.” Sales & Marketing Institute. 2002 http://www.b2bmarketing.com.

Having Clean Data Requires a Plan

Names Load to Sandbox

Find & Replace

1 2 5Standardize Cleanse Validate

US, U.S, U.S.A -> USA Acme-Widgets-453

Hot HighCold Low

Data Transformation

acme incorp.-> Acme Inc

Naming Conventions

Addresses

Mergers, acquisitions, spin-offs

Company Name & Address

Enrich/Integrate/Automate

Acme Inc HQAcme UK

Hierarchy Data

Demographics

4

Postal Standards

Identify, Match & Score

3De-dupe

J. Smith, John Smith – 80%

Re-parent Child Records

Account: Division, Opportunity, Contact

MergeJ. Smith, John Smith ->

John Smith

Archiving & Filtering

Validate & Modify

Load to Production

Greg MalpassTraction

Best Practices Overview

Building the plan Data Quality – Who/How Getting required buy-in

Data Quality Planning/Strategy

Where is quality data mandatory

Data Quality Planning/Strategy

Where is quality data mandatory What is the business doing to workaround

Excel ReportingOther tools/dBOutlook Notepads

Data Quality Planning/Strategy

Where is quality data mandatory What is the business doing to workaround How will you define quality data

Guideline: Expect perfection, expect infinite effort

What fieldsMeasures of qualityAcceptable variance

Getting from Mediocre to Great

Not all at once Eventually, you are going to need to spend money Strategy

– Easy wins first– Build value in data– Make the ask

Consider All Data Levers

Users

Data Change Tools

Customers Web/Static Lists

Internal dB

Subscription Services

Consider All Data Levers

AutoClean: Standardize/Normalize your bad data

Goal: Standardize your existing data

Clean Tools: Jigsaw Clean, Excel Connector/Data Loader

Maintain Tools: Validation/Workflow

Sources: Salesforce and Std Values(ISO)

Process:- URL matching- State standardization- Country ISO

Clean

Consider All Data Levers

Leverage the Web: Free data, resources, partners etc

Goal: Fill in the blanks with what you can find

Clean Tools: Excel Connector/Data Loader, ListGrabber Pro, Jigsaw Clean

Maintain Tools: Same – schedule reminder

Sources: Jigsaw Free Company File, Linked in, Wikipedia for stdized values, YellowPages

Process:- Find, Compare, Match, Append

Consider All Data Levers

Integration: Is not Impossible – Crawl, Walk, Run

Goal: Link into other sources, single version of truth across the enterprise

Tools: Integration – Informatica, CastIron, Boomi, Pervasive, Jitterbit

Systems:ERP, Backoffice, Warehouse other

Process: Start simple, don’t boil the ocean

Consider All Data Levers

External Data Quality Service Providers

Goal: Link into the cloud

Tools: Jigsaw, Hoovers, D&B, Onesource or consider Industry Specific via Integrators ie: Astadia and McGraw Hill

Considerations:- Standardize first to optimize match- Don’t open the gates up right away- Don’t expect perfection

Consider All Data Levers

Tools: Get what you need, become an expert

Goal: Once you perfect manual, apply muscle

Tools: CRM Fusion, Excel Connector, Data Loader

Considerations:- Build your own routines- Forwarn users - Add exclusion fields for users

Consider All Data Levers

Users: the obvious choice. Easily angered

Goal: Make it worth their while

Tools: Anything that saves time, and improves conversion: - SFDC Quotes- Conga – PPT generator- EchoSign - Esignature-Validation Rules – force quality-Workflow – fill in the blanks realtime

Process: Get a plan, sequence it out, follow the user

Consider All Data Levers

Customers: Closest to the truth, most effort to engage

Goal: Expose Salesforce data to customers

Tools: E-Sign, Clicktools, Service Portal, Customer Portal

How: Use Salesforce data to generate contracts, ask for updates,

Process: 1. Surveys 2. Quotes 3. Portals 4. E-Sign

Executive Buy-in

Show progress Make Salesforce your system of record Work around the warehouse Make exec reporting, the focal point of your implementation Expose the true cost of poor data Real time all the time

Renee GellatlyNetApp

About NetApp

NetApp creates innovative storage and data management solutions that deliver outstanding cost efficiency and accelerate performance breakthroughs. Discover our passion for helping companies around the world go further, faster at www.netapp.com.

The Company

Data Quality • Database Loss• Incomplete Records• Missing Processes

The Problem

• 25% Database Loss

• Incomplete Account and Contact Records

• Missing Processes• Standardization• Cleanse• Append

Data Quality

Key Challenges

The Solution

• Build the Solution

• Secure Executive Sponsorship

• Test

• Rollout

Defining Our Data Management Strategy

Marketing Database

Management

Integration

Process

Objectives

Data Quality – A Recent Snapshot of Activity

The Results

Integrating Jigsaw into NetApp Strategies and Systems• Complete Contact Profiles

• Quarterly Database Cleanse

• Automation - API Integration

• Account and Contact Master Complete

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