messaging for utilities - center for resource...
TRANSCRIPT
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Messaging for Utilities
Renewable Energy Markets Conference
October 2010
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Data Marketing Inc.
Founded in 1976
Located in Silicon Valley
Creates and administers direct market campaigns across US and Canada
Verticals include green energy, government, financial, retail, and non-profit organizations
Data Marketing, Inc.160 East Virginia St #100 San Jose, CA 95112408.275.8300www.datamarketing.com
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Our Approach to Direct Marketing
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Messaging for Utilities
Knowing Your Customers
Capturing Customer Information
What We’ve Done
What We’ve Learned
Response Analysis
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Knowing your Customers
Your Local Region
Geographic, Demographic, Weather/Climate
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Knowing your Customers
Relationship Between the Utility and the Customer
Trust and Transparency
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Knowing your Customers
Cost Sensitivity
Purchasing Power, Ability/Willingness to Pay Extra
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Capturing Customer Information
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Capturing Customer Information
![Page 10: Messaging for Utilities - Center for Resource Solutionsresource-solutions.org/images/events/rem/presentations...Data Marketing Inc. Founded in 1976 Located in Silicon Valley Creates](https://reader034.vdocuments.mx/reader034/viewer/2022050110/5f47f910be87ee4a194ae793/html5/thumbnails/10.jpg)
Capturing Customer Information
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Capturing Customer Information
Modeling helps to identify best customer targets and identify
displayed behaviors to craft a relevant message
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What We’ve Done
Generated 28 separate participation models across 6 states
Applied to 23 separate direct mail campaigns
Selected 1,000,000 of the most likely respondents
Result = 12,500+ new green energy buyers
Each of the 28 models are:
generally unique to the utility
specifically unique to the campaign
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What We’ve LearnedSimilarities
Three main census variables:
Education
Age
Children
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What We’ve LearnedSimilarities
Key selection variables for household-specific data
Home/Property ownership
Non-apartment residence
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What We’ve LearnedDifferences
One small utility's model showed that smaller households were more likely participants
A West Coast utility's model showed that participation was correlated with donations to a low income program
A State-Wide Utility’s model showed that lower usage
indicated a higher likelihood of participation
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Response Analysis
Measure Results
Validate/Invalidate Methods
Update and Enhance Modeling
Total Mailed: 100,000 Device Responses DMI Match Percent
BRC 697 509 73.03%
Prospects Mailed: 90,006 Bill Insert 430 134 31.16%
Email 252 156 61.90%
Total DMI Responses: 1,166 Incoming Call 983 501 50.97%
Outbound 2 0 0.00%
Total DMI Response Rate: 1.30% Other/Unknown 1 0 0.00%
Total 2365 1300 54.97%
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Aligning Your Message
Be aware of your local issues, politics, weather
“… data driven marketing reduces cost, increases effectiveness,
and has environmental benefits.”
Jim Burke, SMUD
Recognize and incorporate similarities
Use response information to track results
Direct your appeal to a specific modeled segment