This document summarizes a presentation on leveraging data for demand generation. It discusses using pre-campaign analytics to refine target lists and messaging by validating data, aligning expectations with available prospects, and enhancing prospect profiles. Real-time analytics are used to optimize campaigns by measuring key metrics and adjusting targeting and messaging. Post-campaign analytics provide insights for future initiatives by analyzing results based on variables like event timing and data sources. Modeling techniques like an "ideal prospect" algorithm are also discussed for developing highly targeted lists. Case studies demonstrate how these data-driven strategies improved results.

1. Leveraging Data for
Demand Generation
Success

2. Background:
Since 1990, Winn Technology
Since 2001, WaveLength Market
Group has supported over 800
Analytics: Specializing in combining
technology firms with thousands
knowledge of technology markets,
of demand generation solutions.
products and services with data
management & quantitative analysis
for strategies & programs that
deliver superior results.

3. Speakers:
Geoffrey Swallow
President
Winn Technology Group
Kate Healy
32 years experience in technology
Principal
marketing
Wavelength Analytics
19 years experience in technology
marketing

4. •
Challenges:
Need to optimize marketing and sales budgets
• Data feast or data famine
• Prospect quantity vs. prospect quality

5. Agenda:
• Data Analytic Strategies
• Pre-Campaign
• Real Time
• Post-Campaign
• Data Strategies to Drive Quotas
• Using Intelligence from Data
• More about the “Ideal Prospect” Algorithm
• Strategies for Sourcing and Managing Data

6. Pre-Campaign Analytics
Target Universe Data Strategies
• Validity
• Aligning expectation
• Refining
• Modeling

7. Pre-Campaign Case 1
Fortune 500 Software Firm
User Conference Event Promotion Impact of Data Validity
• Program Objective: Telemarket to 200,171 contact records to promote User Conference.
• Pre-campaign data analysis identified 1,996 invalid records (1% of total database)
• Based on cost per dial, >$3,700 of campaign budget would have been spent calling invalid records.
• Total dials placed:! ! ! 249,138
• Cost per dial:! ! ! ! $1.86
• Post campaign analysis identified 56,171 invalid records representing 28% of total database.
• Cost of calling invalid records: >$104,478
Strategies
•Develop on-going nurturing process, integrating lead cultivation with a regiment for data re-validation.
•Leverage lower cost maintenance procedures leveraging a funnel concept for data validation.
•Map internal data to third party for re-validation and or raising of confidence in existing prospects.
•When using third party data - pilot multiple sources (measure invalidity cost vs. data costs) (3.5% - 30%).
•Scrub data for duplication, competitors, customers, contact validity, bad fits (out of industry scope).
•Overall, minimize wasted dollars spent on activity due to irrelevant and inaccurate data.

8. Pre-Campaign Case 2
Leading Virtualization Firm
Aligning Expectation With Available Universe for > 20 City Road Show
Strategies
•Develop realistic goals based upon expected % conversion and available universe.
•Compare existing data coverage on target universe with actual universe.
•Too small universe: Re-align expectations where universe is limited.
•Too large universe: Look for ways to stratify database based upon key attributes and BI to optimize.

9. Pre-Campaign Case 3
Fortune 500 Collaboration Firm
Refining Target Universe for Demand Generation and Lead Nurturing Initiative
• Program Objective: Develop demand generation/lead nurturing initiative to 525 target accounts.
• Developed scoring model to measure suspect value and lead status.
• Deployed several strategies to enhance data prior to campaign launch:
• Mapped target firms to Winn Enterprise Database for contact, demographic, and technology data.
• Conducted Internet Research to further enhance account knowledge,
• Identified > 3500 related entities linked to target accounts.
• > $800,000 booked opportunities converted to sales - additional 100 nurture leads in funnel.
What we learned
•Developing intelligence prior to program launch can enhance messaging, targeting and prospect stratification.
•Intelligence gained prior to program launch also provided better territory alignment.
•Developing corporate relationship profiles assisted with cross and up sell opportunities.

10. Real-Time Analytics
• Drive campaign success via the measure of key metrics
• Develop front-loaded metrics that can be measured during campaign.
• Develop key questions in call guide to help drive BI and key metrics.
• Leverage those metrics for innovative practices:
• Messaging - message testing
• Targeting
• Tracking
• Lead / Suspect scoring (Suspect Value / Sales Status).
• Overall and comparative demand center productivity by rep.

11. Real-Time Case 1
VAR 500 Firm
Appointment Setting / Lead Generation / Lead Nurturing Program
• Program Objective: Develop sales-ready opportunities and nurturing leads for on-going initiative.
• Challenge: too much data (number of prospect contacts to company ratio).
• Winn analyzed the type of functions and titles that were driving higher lead rates.
• Winn pre-coded and isolated higher level target contacts and stratified the database.
• All other contacts were made viewable in account rep portal for use when referred.
What we learned
•Reps were better focused on key accounts vs. canvassing too large of an audience.
•Campaign lead rates improved by 4X after re-aligning the data.

12. Real-Time Case 2
Emerging Technology Software Firm
Cross-Industry Lead Generation Campaign
• Program Objective: Develop sales ready opportunities and nurturing leads for on-going program.
• Client unaware of best market to focus on at program launch.
• Winn pre-loaded key data metrics including industry classification for all prospects selected for
the campaign.
What we learned
•Relative to resolved records, three industries represented 5X greater lead rate.
•Campaign adjusted to focus on remaining prospects in Manufacturing, Services, and Construction.
•The more coded data you can pre-load in a campaign, the more opportunities you have to analyze and shift
program to drive results.

13. Post-Campaign Analytics
• Leveraging knowledge gained from programs
• Key metrics established up-front
• Value of data collection and codification of
tactical data
• Business / competitive intelligence
• Re-alignment of messaging and targeting

14. Post-Campaign Case 1
Fortune 500 Technology Distributor
Post-Campaign Analytics to Multiple Events
• Objective: Analyze results of 21(on-site) events covering similar technologies over one year.
• Analysis of event success by:
• Event timing (day/time/season)
• Venue type
• Lead time for event promotion
• Technology Theme
• Based upon analysis, leverage knowledge gained to drive future initiatives.
What we learned
•Special events had the lowest cost per registration (4:1).
•Events promoted with a 15+ day lead time out performed those with < days over 50%.
•Technology theme dramatically effected cost per registration (as high as 10 X).

15. Post-Campaign Case 2
Global 100 Technology Firm
Post-Campaign Analytics for Appointment Setting / Lead Generation Program
• Objective: Analyze results of demand generation initiative.
• Analysis of program conducted by:
• Data source lead rates
• Data source validity rates
• Opportunities generated vs. areas of interest
• Based upon analysis, leveraged knowledge gained to drive future initiatives.
What we learned
•Although the average cost of an actionable lead = $151, list sources ranged from < $100 to > $1000.
•Re-focus of campaign and future targeting of higher yielding list sources.
•Messaging altered to focus on areas resonating with target audience.

16. Modeling
• Data Strategies to Drive Quotas
• Using Intelligence from Data
• More about the “Ideal Prospect” Algorithm
• Strategies for Sourcing and Managing Data

17. Cost-effective & Successful Customer
Acquisition Using Intelligence from
Data - Why It’s Important
Targeting the RIGHT prospects within the organization
Making sure the Knowing and Understanding
message is going to understanding motivators and
resonate with the trends and buying concerns of your
target persona transitions target buyer

18. More about the “Ideal Prospect”
Algorithm
• The Ideal Prospect algorithm is based on the relationship between revenue growth and
employee growth.
• Developed based on primary research that segmented the enterprise market using some
key attitudes and behaviors about enterprises technology needs, how they use it, and
what they expect it to do for them.
• Leading segment in new technology & adoption, termed “Strategic IT Spenders”:
• On average, higher revenue growth & profitability, composing approximately 24% of the global
enterprise market & existing in all countries and industries.
• Buy IT for productivity gains more than cost savings.
• Perceive their organizations to be highly dependent on real-time transactions in daily operations, and
involve many different channels for both IT information and sales.
• Always on the lookout for new technologies that make them more efficient.""

19. Strategies for Sourcing and
Managing Data
Project Goals, Budgets, & Timelines •Variety of possible places
• POS data from the channel
• CRM data
• Financial data
Internal Data
External 3rd Primary Manually Modeled • Harte-Hanks
Party Data Research Collected Data
• Jigsaw
• D & B, Hoovers
• US census
• Postal zip maps

20. Case Study 1
Data Center Switch Vendor
• Problem: Build sales funnel
• Solution: Create highly targeted list of enterprises
with 800 company names based on Ideal Prospect
Algorithm, developed using primary research
segmentation model.
• Focus 4-quarter demand generation program using
demand center tactics to nurture list of OWNED names.

21. Case Study 1
Program Specifics
• Filling the sales funnel tightly couples data
and outbound marketing programs.
• The process begins with defining and building a highly
targeted Enterprise target list to nurture.
• In partnership with the Demand Center, populate the
contact list, and deliver a set amount of A, B and C leads.

22. Case Study 1
Results
WaveLength Standard
Approach eDM Approach
List Size Requirements based on a 1800 names 50,000 names
2% response rate
Cost Per Name for Rental 0.90
Total List Rental Fees $45,000
1 Inside sales rep to qualify leads 12.5 days @ $320/day or $4.57/
based on 80 calls per day call = a total of 4000.00
WL Program $32,000
Sales-accepted leads 99 22.7
Cost per qualified sales lead $323.23 based on 80% of the $2,158.75
project being completed- cost will
go down as reach our final lead
goals
TOTAL COSTS $32,000 $49,000

23. Collaborative Case Study
Winn-WaveLength Cloud Computing
Primary Research
• Goal: Gain an in-depth understanding of the fast
evolving cloud marketplace. We looked at buying
trends, buyers and influencers personas, and the
role of the channel.
• Some results: Nearly 42% of sample of
medium to large enterprises (n=151) are
deploying or testing some type of cloud model.

24. Collaborative Case Study
Cloud Computing Primary Research
• Cloud buying habits of the early market: Target the right persona
• Internal IT plays largest role – from creating the strategy to developing, migrating and
managing application.
• Top business management is highly involved for current cloud users.
• Role of trusted, third party partners in enterprise buying currently very limited among
early cloud adopting enterprises.
• Systems Integrator and Consulting Partners.
• Software vendor partners.
• And NOT telco service providers or hardware vendors.

25. Collaborative Case Study
Cloud Computing Primary Research
• Created demand generation message based on motivators in
why the cloud transition is happening:
• Operating cost reduction
• Rapid application deployment/more nimble IT
• Addressed concerns about deploying cloud services in demand
generation campaign:
• Security breaches for applications and for stored data (a.k.a at rest)
• Perceptions of high start-up costs
• Lack of “trusted” 3rd party relationship

26. Summing it up...
• It takes a whole lot of leads to get to a few sales, so make sure
you’re targeting your RIGHT market, in the RIGHT way and
getting the most out of your efforts.
• Data is key to your success in your campaign - for targeting,
messaging, and addressing concerns in an evolving market.
• Enterprise Migration to the Cloud study is a perfect example of how
research helps:
• Target top IT executives
• Mitigate adoption concerns, e.g., security issues, and high start-up costs
• Demonstrate how cloud solutions results in cost savings and faster application deployment

27. Thank you very much for joining us today!
Q/A
winntech.net wlanalytics.com