cleaner data, higher adoption, better leads
DESCRIPTION
How accurate is your business data? Do you have duplicate records? Keeping data clean and relevant for your users is no small task. Join us for a session dedicated to data cleansing and de-duplication and learn techniques for better managing your data. We'll focus on Excel and file import, Web-to-lead, de-duplication, creation of validated fields, lead scoring with formula fields, and using Jigsaw to create automated data cleansing. Take home all the methods, tools, and best practices you need!TRANSCRIPT
Cleaner Data, Higher Adoption, Better Leads
Marketing Professionals
Jorge Villamariona: salesforce.comJennifer Taylor: SunGard Data SystemsJon Miller: MarketoJames Cleveland: salesforce.com
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Jorge Villamariona
Sales Engineer,
salesforce.com
Agenda
Why you need to have a data quality policy and strategy?
Techniques for managing the quality of your leads
How SunGard is keeping their data clean and relevant to increase CRM adoption
Learn how to leverage Jigsaw to obtain new contacts and maintain existing contacts
How Marketo is leveraging Jigsaw to create better leads
Why Data Quality Matters
Understand your customer
Increase customer loyalty
Obtain correct metrics
Make the right decisions
6 Consequences of Bad Data“Analysts rate bad data as one of the top 3 reasons for CRM failure”
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3
4
5
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Inaccurate report metrics
Users get frustrated. You lose valuable buy-in and adoption
Marketing wastes money and effort pursuing bad prospects
Understanding your “customer” is impossible
IT wastes time sifting through information
Operations has difficulty reconciling data against finance and other back end systems
75% of commercial businesses believe that they are losing as much as 73% of revenue due to poor data quality
Experian - QASU.S. Business Losing Revenue Through
Poorly Managed Customer Data
Importance of Data QualityThe Cost of Bad Data
75% ofrespondents
41% ofrespondents
“
”
Poor data quality costs U.S. businesses more than $600 billion annually
Data Warehousing Institute ”“
How Do We Manage Data Quality?
Data Culture
Analyze
Establish a mindset that data quality is everyone’s responsibility
Analyze and understand your data
Set goals and map your path to get there
Implement data management processes to improve your data quality
Leverage integrations and automation to drive data quality
Deploy mechanisms to protect and track data quality against goals
Standardize, Enrich & Clean
Integrate & Automate
Maintain
Plan
Instilling a Culture of Data Quality
EducateAnything goes, adoption before data integrity
EducateAnything goes, adoption before data integrity
UnderstandRecognize usage trends,Adapt standards to reality
UnderstandRecognize usage trends,Adapt standards to reality
StandardizeTrain to common « best practices »
StandardizeTrain to common « best practices »
Rewards / DisincentivesReinforce best practices,with a carrot AND a stick
Rewards / DisincentivesReinforce best practices,with a carrot AND a stick
IntegrateBuild tools to help multidepartment tasks / processes
IntegrateBuild tools to help multidepartment tasks / processes
AutomateMake everybody’s job easier,and make the company more efficient
AutomateMake everybody’s job easier,and make the company more efficient
1 2 3
456
Analyze: Data Profiling
Data Sources Data weaknesses Mapping & Usage
Data Quality Analysis Example: Phone Numbers
Not valid
Not standardized
Not complete
Plan: Data Quality Management Strategy
Create your data quality plan Identify and prioritize goals
Define reports and dashboards
Find sponsors and owners
Establish budget
Select tools (i.e. for de-duplication)
Commit resources
Create communication plan
Standardize, Clean, and Enrich
Names Load to Sandbox
Find & Replace
1 2 5
StandardizeStandardize CleanseCleanse ValidateValidate
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
Enrich/Integrate/Automate
Acme Inc HQAcme UK
Hierarchy Data
Demographics
4
Postal Standards
Identify, Match & Score
3
De-dupeDe-dupe
J. Smith, John Smith – 80%
Re-parent Child Records
Account: Division, Opportunity, Contact
Merge
J. Smith, John Smith -> John Smith
Archiving & Filtering
Validate & Modify
Load to Production
Standardize
Accounts names: Inc vs. Incorp., INC, incorporated; Ltd vs LTD, Limited
Opportunity names: i.e. Name – Product: “Acme – 250 Tschotchkes”
Country/State: use validation to standardize TX vs Texas, USA vs. U.S.
Postal Code: use validation rules for proper format in US/CAN: xxxxx-xxxx
Contact info: use pick lists for roles, titles, department: Marketing vd. Mktg
Look for useful validation rules in Help & Training!
Cleanse your Data
Correct inaccuracies and inconsistencies
Find and replace bad or missing data
Remove or merge duplicates
Leverage all users to fix data (it’s their data)
Archive irrelevant and old data
Leverage automated routines/tools
Routinely reconcile Salesforce data against other data
points/systems
Cleanse your Data
Prioritize your data control process Fix high visibility/usage information first (duplicates, addresses,
emails)
Fix business specific information next (opportunity types,
stages etc)
Remove duplicate fields (don’t repeat account info on contact)
Remove irrelevant fields
Enrich: Data Augmentation
Add missing information from 3rd party sources
Understand what data would provide additional value
Add internally available account intelligence
Integrate
Understand your masters
Avoid stale and bad information
Make information read only
Create a 360 view
4 Resources to Help Automate
Workflow Jigsaw
Force.comIntegration points
list not all encompassing
Data Management ApplicationsForce.com Appexchange app considerations
Sample Tools
Composite Apps• Enterprise Mash-ups• Rich user interface
Application Integration• Real-time integration•Multi-step integration• Human workflow
Data Integration• Data migration• Data replication• Bulk Data Transfers
Data Cleansing• Data de-duplication• Data assessment
4
Tools for Managing Data Quality
Web-to-X
Leverage tools to prevent duplicates before passing to Salesforce real-time
Import data from various file sources
Validation Rules
Use Validation Rules and Workflow
Data Quality Analytics
Use reports and dashboards to measure data quality
Analyze and cleanse data
Excel Connector Data Loader
Web to X
• Prevent duplicates leads when using W2L
• Visit our AppExchange for more information
Validation Rules
• Enforce your standards before you save the record
Excel Connector
• Analyze• Cleanse• Enforce your standards
Data Loader
• Extract• Analyze• Cleanse• Import
Reports & Dashboards
Use reports & dashboards to measure quality
Tools & Resources
AppExchange - Data Quality tools and offerings– Data Quality Analysis Dashboards
– Integration & Data Management
– Data Cleansing
– De-duplication Tools - Search term “Data Quality”
Salesforce.com Data Tools– Apex Data Loader and Excel Connector
Salesforce Professional Services– Data Quality Assessment and Cleansing Solutions
Additional Dreamforce Sessions– Data Quality for Beginners
– Data Nirvana
– Data Done Right
Jennifer Taylor
Marketing Operations Manager,
SunGard
All About SunGard
After 25 years of developing software and managing the systems that help financial services institutions run their business, SunGard is still a leader. Our prestigious track record of industry awards is a reflection of our deep understanding of the specialized, mission-critical business processes that lie at the heart of the banking, securities and investments, and insurance industries. From the beginning, we have applied our expertise to better serve our customers.
• INDUSTRY: Software & IT Services• EMPLOYEES: 16,000 • GEOGRAPHY: Global• # USERS: 2000+• PRODUCT(S) USED: SFA, Marketing, Service & Support, 5
downloaded AppExchange applications
Com
Overview
What is a lead?
How we manage lead imports through cases and
DemandTools
How we use SPOT to get a holistic view of “genuine”
duplicate leads
Sales tools to research and validate leads
What is a Lead to SunGard?
Leads are an extension of the sales funnel – “above the
funnel” information
Leads are potential opportunities (with contact
information)
Just as a contact can be associated to multiple
opportunities, the same contact information can be on
multiple leads
Leads are only de-duped within a segment/product line
What is a Lead to SunGard?
How SunGard Manages Lead Imports
All lead import/de-dupe requests are submitted via internal
salesforce.com case with an attached import spreadsheet
using a provided template
Lead imports offered as a centralized serviced (not viewed as
a user limitation)
The standard turnaround time for a lead import/de-dupe is
24 – 72 hours
We use Demand Tool’s People Import to de-dupe on
segment/product line, email address, and last name when
importing
How SunGard Manages Lead Imports
How SunGard Manages Lead Imports
SPOT – Single Point of Truth
SPOT joins all leads/contacts with the same email
address for a holistic view of:– Subscription preferences
– Campaign activity
– Email results
SPOT helps eliminate concerns of “genuine” duplicates
providing a holistic view
SPOT – Single Point of Truth
“LinkedIn” from Lead or Contact
Updates from Jigsaw from a Lead or Contact
VP Marketing, Marketo
Author Modern B2B Marketing
Jon Miller
About Marketo
Revenue Performance Management solutions (marketing automation, sales insight, ROI analytics) that significantly increase marketing and sales success for more than 800 mid-sized and enterprise worldwide
• Salesforce• Jigsaw for Salesforce• Salesforce Community• Marketo Lead Management / Marketing Automation• Marketo Sales Insight• Marketo Revenue Cycle Analytics
Marketo’s Revenue Cycle
All
Nam
es
Pro
spec
t &
R
ecyc
led
Lea
d
AW
AR
EN
ES
S
En
gag
ed
Opportunity Customer
Sal
esL
ead
MQLSQL
SAL
Marketing SDR Sales
All
Nam
es
Pro
spec
t &
R
ecyc
led
En
gag
ed
Need Quality Information about Prospects
Lea
d
Opportunity
Sal
esL
ead
MQLSQL
SAL
By Industry: 82%By Role: 67%
Doers vs. BuyersJob FunctionBy Company Size: 49%By Geography: 29%
Generating Names and Prospects
Problems With Self-Submitted Data
Short Forms Outperform Long Forms
Short Form (5 fields)
Conversion rate: 13.4%
Cost per: $31.24
Medium Form (7 fields)
Conversion rate: 12.0%
Cost per: $34.94
Long Form (9 fields)
Conversion rate: 10.0%
Cost per: $41.90
Progressive Profiling
Data Augmentation
Real-Time & Batch Import (Weekly)
Jigsaw Results
Matches for 39% of leads and 70% of accounts
Industry, Revenue, and Employee count populated on all
fields
Graveyard leads and contacts moved to unsubscribe
Early but seeing improvements in nurturing quality and
scoring relevance
Manager Corporate Sales, Jigsaw
Jim Cleveland
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
The Cloud Shows Us a Better Way to Manage Data
12,568,906 users made…395,177,595 edits to…20,676,516 articles
xxx
Socially Aggregated
The data you need finds you…right away
xx
Real Time
*Source: Shaugatuck Technology 2010 Cloud Business Solutions
2014: 50% of software
deployments in the cloud*
No Software
Stock Data
Weather Data
Restaurant Data
Traffic DataMovie Data
The Crowd is More Precise
70% Direct Dial Numbers
100% Complete Contacts
10xMore Titles
NameTitle Ext. 3415
Director of… Marketing…
Viral Marketing…Enterprise Marketing…
Social Media…Email Marketing…Dept
EmailPhone
Address
Leverage the Cloud with Jigsaw
1.4 million + members200,000 updates/month
Name Phone
Bob Johnson 415-536-6000
Bob Johnson 650-205-1899
Rob Johnson 415-536-6100
Bob C. Johnson
408-209-7070
Bob Johnson 415-536-6000
Rob Johnson 650-205-5555
Bob T. Johnson
650-780-9090
Robert Johnson(415) 536-2283
Improve Productivity with Clean Services
Access Clean Data Within the Sales Cloud
Instant source of 24M+ new leads
Unlimited, free research into 4M+ new accounts
Reps are productive with clean data
for Salesforce
Jigsaw Delivers Across the Complete Plan
Names Load to Sandbox
Find & Replace
1 2 5
StandardizeStandardize CleanseCleanse ValidateValidate
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
Enrich/Integrate/Automate
Acme Inc HQAcme UK
Hierarchy Data
Demographics
4
Postal Standards
Identify, Match & Score
3
De-dupeDe-dupe
J. Smith, John Smith – 80%
Re-parent Child Records
Account: Division, Opportunity, Contact
Merge
J. Smith, John Smith -> John Smith
Archiving & Filtering
Validate & Modify
Load to Production
Jorge Villamariona
Sales Engineer
Jennifer Taylor
Marketing Operations Manager
James Cleveland
Corporate Sales Manager
Question & Answer
Jon Miller Vice President of MarketingTWITTER @jonmiller2
Action Plan
Data Culture
Analyze
Establish a mindset that data quality is everyone’s responsibility
Analyze and understand your data
Set goals and map your path to get there
Implement data management processes to improve your data quality
Leverage integrations and automation to drive data quality
Deploy mechanisms to protect and track data quality against goals
Standardize, Enrich & Clean
Integrate & Automate
Maintain
Plan
Cleaner Data, Higher Adoption, Better Leads
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