This document summarizes a webinar about using a Contact Washing Machine (CWM) to clean marketing data and drive sales leads. The webinar will discuss how bad data impacts marketing returns, ways to measure and categorize bad data, types of CWM, and success stories. Attendees will learn how a CWM can clean, normalize, and enrich contact data to deliver more qualified leads for sales. The document also provides an overview of semi-automatic and fully-automatic CWM options and their features.

1. Leverage Contact Washing Machine
to Drive Sales Ready Leads
Webinar Details:
29th Jan, 2015 - 11am PDT / 2pm EDT

2. Few Pointers
• Dial in via phone or select "call using your computer"
• Tweet with us @Grazitti
• Chat your questions to the host
• Recording will be emailed to you on Monday
• For any more information, drop us a line at info@Grazitti.com

3. Quick Intro
Rahul Sachdeva
Data Analytics Manager
Isha Vohra
Web Marketer

4. You’ll learn about
• Insights on how bad data impacts your ROMI (return-on-marketing-investment)
• Ways to categorize your bad data
• Metrics to measure bad data impact
• Types of Contact Washing Machine (CWM)
• CWM Success Stories

5. @Grazitti

6. Who we are?
AutomationStrategy
Content Technology
AnalyticsOperations
85+
280+
Team of Marketing Experts
B2B Clients Served Since 2007

7. Marketing
Technology
Services
Online
Communities
Marketing
Operations
Salesforce
Web & Mobile
Development
Data Science
Demand
Generation
Our Services

8. Some of our Marketing Customers

9. 2015 Copyright © Grazitti Interactive. All rights reserved.
Let’s Start

11. 66%
80%
30%
54%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
MARKETING LEAD GENERATION FINANCE CUSTOMER
RELATIONSHIPS
% OF COMPANIES IMPACTED
Bad Data – Function-wise

12. Impact on Sales & Marketing
Grazitti Interactive Copyright 2014
Sales
• Lost revenue
• Wasted resources
• Lower productivity
• Damage to your credibility
• Failure of your marketing
automation initiatives
Marketing
• Delivering wrong message to
wrong customer/prospect
• Annoying customers/ prospects
with wrong and redundant
messages
• Failing to leverage multi-modal
marketing capabilities
• Distorting campaign success
metrics

13. Lead Sources
• PPC Ads
• Organic Web Traffic
• Social Media
• Partner Referrals
• List Purchase
• Tradeshows & Events
• Sales Cold Leads
• Web Listings & portals
• Content Syndication
• Inbound Calls
• Qualify
• Create
Opportunity
• Follow-up
Close
Opportunity
WON
LOST
Common Lead Flow

14. Lead Sources
• PPC Ads
• Organic Web Traffic
• Social Media
• Partner Referrals
• List Purchase
• Tradeshows & Events
• Sales Cold Leads
• Web Listings & portals
• Content Syndication
• Inbound Calls
• Qualify
• Create
Opportunity
• Follow-up
Close
Opportunity
WON
LOST
Here’s what brings Bad Data

15. 1. Missing Data: Empty fields that should contain data.
Example: A lead can not be assigned to a Sales rep because country and state field are missing.
Types of Bad Data in your Marketing System

16. 2. Wrong or inaccurate data: Information that has not been entered correctly or maintained.
Example: A junk or a 10-minute email ID, captured from a web form.
Types of Bad Data in your Marketing System

17. 3. Inappropriate data: Data that’s been entered in the wrong field.
Example: A promising lead doesn’t appear in regional reports because the city name is in the State
field.
Types of Bad Data in your Marketing System

18. 4. Non-conforming data: Data that hasn’t been normalized as per the system of records.
Example: A marketing segment of all U.S. leads doesn’t include clients with “USA” or “United States of
America” in the Country field.
Types of Bad Data in your Marketing System

19. 5. Duplicate data: A single Account, Contact, Lead, etc. that occupies more than one record in the
database.
Example: Sales reps in different regions unknowingly create three distinct IBM Accounts, wasting
valuable time, sowing confusion, and causing missed opportunities.
Types of Bad Data in your Marketing System

20. Do you have bad data
in your system?

21. 1. Duplicate Data %
Total Number of Duplicate Leads/ Total number on Known Leads
2. Lead Quality Score
Assign weightage to fields like Job Title, Country, City, State, Postal Code, Phone Number. Assess existing
lead database to measure quality score for each lead.
3. Email Deliverability %
Measure average email deliverability for last 180 days. Segment for new data and existing data in lead
database.
4. Unsubscribe %
Measure average email un-subscription for last 180 days. Segment for new data and existing data in lead
database.
5. Email Bounce Reasons
Monitor email soft bounces and hard bounces. Extract a report to see top reasons for bounced emails.
6. MQLs marked as Bad Data by Sales Team
Monitor leads which are marked by Sales Reps in Salesforce as Bad Data and return to marketing system
for clean-up or nurturing.
Measuring Impact of Bad Data

23. Cleaning & Normalization Only
• Series of Smart Campaigns for passing leads through
data filters
• Trigger when a lead is created and push it through
each campaign in a sequence, before sending it for
lead scoring
• Batch run old data through CWM campaigns for
better results
Contact Washing Machine(Semi-automatic)
inside your Marketing Automation System

24. Contact Washing Machine(Semi-automatic)
inside your Marketing Automation System
Filter Company Name
Filter Phone Number
Filter Lead Name

25. Contact Washing Machine(fully-automatic)
using External Data Application
Cleaning, Normalization & Enrichment

26. Built on the Alteryx platform, the Contact Washing Machine works in a three step process-
• Cleansing – In the first step, the raw data is scrubbed against a set of predefined bad values for the
fields, e.g. Name, Company Name, Email etc. The app flags bad data and separates it from the good
data stream. The bad data records are then separated from the good data ones.
• Normalization – This is the result from previous step, i.e. good data is normalized for
standardization of values such as country, state, city, job title etc.
• Enrichment – In the last step, the normalized data is enriched with third party business database to
help sales executives get extra information for qualifying and prioritizing their leads.
Working of The Contact Washing Machine

27. CLEAN
CONSISTENT
CORRECT
COMPLETE
The Contact Washing Machine
delivers DATA that is

28. Which CWM do you need?

29. Feature Semi-automatic Automatic
Setup in Marketing Automation Platform ✓ -
Integration with Marketing Automation Platform ✓ ✓
Data Cleaning ✓ ✓
Data Normalization ✓ ✓
Data Quality Assessment ✓ ✓
Data Enrichment X ✓
Contact Washing Machine
Semi-automatic vs Automatic

30. CWM Success Stories

31. CWM Impact
Leveraging the Contact Washing Machine, Alteryx got -
• More than 200K clean records processed per minute
• Over 40% improved lead quality with enriched information from external database
• Up to 37% Increase in the Sales Productivity
• 25% Improved Sales Qualification and Prioritization

32. With a seamless data cleaning process, Cloudwords got -
• 95%+ Delivery Rate on cold leads
• Clean lead segments for better customer engagement with targeted messaging
• Detailed account information by leveraging 3rd party sites like Zoom Info and Hoovers
• Increased campaign conversions by sifting the existing data to remove duplicates/junk data
• Functional lead qualification and lead scoring systems

33. Final Takeaways

34. Final Takeaways
Integrate
Data
Sources
Audit
Legacy
Data
Get Sales
Feedback
Integrate
CWM

35. Grazitti Interactive Copyright 2014

36. THANK YOU