1. A Toolkit of Technologies and Tactics
for Successful Community‐Based
Initiatives
Melanie Coen, National Grid
Kessie Avseikova, Opinion Dynamics
October 1, 2013
AV sponsored by:

2. 2
Presentation Overview
 Efficient Neighborhoods+SM (EN+SM) Background
 EN+SM Design
 Involving Evaluation Early
 Community Selection - Microtargeting Approach
 Key Takeaways

3. Initiative Background
 Efficient Neighborhoods+SM born
from the Appreciative Inquiry
Summit led by National Grid in the
spring of 2012.
 Stakeholders interested in
environmental justice and equity
in service
 Main issue is difficulty reaching
lower to moderate income
customers, typically who earn
between 60-120% of state median
income
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4. 4
Barriers to Higher Residential
Participation
41% of Massachusetts
housing stock is multi-
unit structures Split Incentives
Higher Job Costs
No point
of
contact
Pre-Weatherization
Barriers
Income
verification
screening

5. Initiative Design
 EN+SM included in the
Massachusetts Joint Statewide
Three-Year Electric and Gas
Energy Efficiency Plan
 Extension of the Mass Save®
Home Energy Services (HES)
initiative
 Statewide effort – most
Program Administrators (PAs)
implementing EN+SM from
June through November 2013
5
LEANLow-Income Energy
Affordability Network

6. Initiative Design (Cont.)
 Open to the entire community, but targets lower to
moderate-income energy customers in designated
neighborhoods
 Low-income customers and customers in 5+ unit structures
do not qualify and are referred to other programs
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7. 7
Enhanced Incentive Description
Enhanced EN+ SM
Incentives
Existing Incentive
Common Area Lighting (LED or CFL
depending on fixture) $120 $0
Pre-Weatherization Barrier Incentive Up to $800 $Up to $800
90% up to $3000 Insulation per unit/single
family $1,980
$1,650
(Based on historical
costs)
2-4 Family Landlord Whole House
Insulation with Adder
(50% of Customer Contribution)
(Based on historical job
costs)
2 Family $5,130 $4,000
3 Family $7,695 $6,000
4 Family $9,500 $7,500
Early Retirement Refrigerator
(ENERGY STAR® labeled) $200 $150
EN+ SM Boiler & Furnace Incentive Adder $100 $0
Early Boiler Replacement (EBR) Rebate
with Additional $500 Incentive for Non-
owner Occupied Properties
($4,000)
Unrestricted Timeline
($4000)
Restricted Timeline
EN+ SM Whole House $500 Incentive Adder
Package
Insulation + Heating Equipment $500 $0
Enhanced Incentives

8. Involving Evaluation Early
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9. 9
Community Selection – Big Questions….
How do we select the communities that have
high concentrations of target customers?
How do we identify customers that are most likely
to fall into the desired customer segment?
How do we avoid customers who do not qualify for the
program or who already participated in the program?
How do we find communities with city/town support?
Are there other initiatives that are going on in that
community?

10. 10
Community Selection – Effective Solution
Microtargeting
A strategy that uses
demographic, geographic,
household, psychographic,
and other data to identify
customer segments of interest
for purposes of marketing,
targeting, and outreach.

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Community Selection – Effective Solution
Multiple sources of data:
 Census
 Past program participation
 Utility customer
 Other (secondary segmentation data,
GIS shapefiles)
Easy to Use
Efficient
Flexible
Microtargeting=Data+Mapping

12. 12
Community Selection – Process
 American Community Survey (ACS) data for 2007-2011
 Data fields of interest available at the census block group level
 Core data fields (housing count, population count, income, housing stock, home ownership status)
 MassGIS data
 Maps of towns and census block groups
 Maps of Massachusetts PA service territories
 Program tracking data
 Utility customer data
Census block group –between
600 and 3,000 people, with an
optimum of 1,500 people.
Census Block group
Income
Housing stock
Ownership status
AddressTown
Program
Administrator
Participant Flag
Audit Flag
Address
Low Income Rate
Code
Multi-family indicator
Census Data Utility Customer DataMass GIS Data Program Tracking Data
Microtargeting database
Perfect for our purposes!

13. 13
Community Selection – Process (Cont.)
Step 1 Step 2
Initial data
analysis to
narrow the set of
communities to
target
In-depth
community
analysis and final
community
selection
Three-step approach
Step 3
Customer
Targeting List
Development

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Step 1 – Approach
Step 1 - Initial data analysis to narrow the set of communities to target
 Target communities have a higher
than average number of households
with:
 Incomes falling between 61% and 100% of
median income
 1 – 4 unit buildings
 Also want to avoid communities with
high concentrations of:
 Low-Income Program eligible customers
 Multi-family (5+ units) buildings
In setting optimal thresholds, it was
important to substantially narrow down
the set of communities while still
providing PAs with enough
communities to meet their goals

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Step 1 – Results
Qualifying communities:
• 30% of households or more have
income between 61% and 100%
of the state median income
• 30% of units or less are in 5+ unit
structures
Qualifying communities:
• 311 census block groups
• 112 towns with at least one
qualifying census block group
• 43,253 households

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Step 2 – Approach
Step 2 - In-depth community analysis and final community selection
 In-depth analysis of qualified
communities
 Prior participation in PA-administered energy
efficiency programs
 Percentage of renters vs. owners
 Building stock and characteristics (age, size,
etc.)
 Other characteristics

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Step 2 – Results
Town of Townsend

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Step 2 – Results (Cont.)

19. 19
Step 2 – Results (Cont.)

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Step 3 – Approach
Step 3 – Development of Customer Targeting Lists
 For selected communities, mapped customer addresses
and rate codes to support custom marketing and targeting
 Identification and removal of the low-income rate codes, past participants,
customers in multi-family structures

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Step 3 – Results

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Key Takeaways
 Customize program design and delivery
to account for the specific
characteristics of the target audience
 Community selection is one of the
critical design components
 Targeting can be done efficiently and
cost-effectively
 A wealth of data available at fingertips
 Engage evaluation early on in the
process – they can help!

23. Save the Dates
AESP’s National Conference
San Diego, CA
AESP’s Spring Conference
Baltimore, MD
AESP’s Summer Conference
San Francisco, CA
Jan. 27-30, 2014
For more information - www.aesp.org
May 12-14, 2014
Aug. 4-6, 2014