Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.
Using Market Segmentation to
Track Program Success
Amanda Dwelley
AESP EM&V Online Conference
December 4, 2013
About Opinion Dynamics

Established in 1987
Leader in market research
for utilities
Offices in Massachusetts,
California &...
Key Points
 There are many ways to segment utility customer populations
 Some are more meaningful than others for progra...
Program implementers use segmentation all the time
Segmentation defines and divides a large population into identifiable g...
Historical approach of “equal access” to programs, and
undifferentiated marketing, hasn’t yielded equal impacts
For this u...
We’re leaving opportunity on the table, but don’t know where or how
much
“Our customers are
unique – So we can’t
reach sta...
Evaluators do report on differences by customer group, but sometimes
we only look within a program

Annual Percent
Savings...
Segment-level insights are useful across the program
lifecycle
Metrics

Measurement Opportunities

Awareness / Knowledge

...
So, what segmentation is “good” for EM&V purposes?
1
1. Segment membership must be identifiable ex ante for all customers
...
1

Identification: Tracking by segment requires defining segments
based on readily-available data – And we have a lot!
Sec...
2

Meaningful Differences: Segment membership should correlate with
savings opportunities, program propensity, barriers an...
Have AMI data? Clustering customers into Load Shape
Segments could enable long-term impact tracking
Best target for DR
and...
3

“Consumable” segments: Easy to explain and
interpret; manageable number

 Single dimensions (single-family / multi-fam...
We can start by reporting savings at a segment level

Segment

Percent of
Customers

Percent of Wx
Participants

Wx Saving...
End game: Identify and track program opportunities and
success metrics specific to each segment
Participation rate 
among ...
Thank You!

Amanda Dwelley
Associate Director
617-301-4629
adwelley@opiniondynamics.com

Visit us at www.opiniondynamics.c...
Using Market Segmentation to Track Program Success_ADwelley
Upcoming SlideShare
Loading in …5
×

Using Market Segmentation to Track Program Success_ADwelley

508 views

Published on

Published in: Marketing, Business, Technology
  • Be the first to comment

Using Market Segmentation to Track Program Success_ADwelley

  1. 1. Using Market Segmentation to Track Program Success Amanda Dwelley AESP EM&V Online Conference December 4, 2013
  2. 2. About Opinion Dynamics Established in 1987 Leader in market research for utilities Offices in Massachusetts, California & Wisconsin Energy Efficiency Evaluation Energy Advising Smart Grid, DR, and Behavior Market Research Custom approach — We work with utilities and implementers to use all available data to develop tailored solutions AESP EM&V Online Conference 2
  3. 3. Key Points  There are many ways to segment utility customer populations  Some are more meaningful than others for program design, portfolio planning and/or EM&V  Implementers are already using segmentation to improve program targeting (and uptake)  The EM&V community (us!) does analyze results by customer group/segment  …But often not in a cohesive or consistent way  Consistently integrating segmentation in to EM&V will:  Deliver insights that help programs improve faster  Get stakeholders thinking about (a) how results can be used/extrapolated, and (b) if/how programs should be tailored/targeted to different segments AESP EM&V Online Conference 3
  4. 4. Program implementers use segmentation all the time Segmentation defines and divides a large population into identifiable groups based on similar characteristics Summer kWh 25% 20% 15% 10% 5% 0% • High summer usage targeted for HVAC rebate • High annual usage targeted for behavioral programs Experian Mosaic Segment Multi-family middle-income targeted for audits / weatherization 1 AESP EM&V Online Conference Urbanites targeted for HEMS / IHD
  5. 5. Historical approach of “equal access” to programs, and undifferentiated marketing, hasn’t yielded equal impacts For this utility, there’s a strong relationship between wealth quintile (measured three ways) and long-term EE program participation: 10% 8% 6% 4% 2% 0% 1 2 3 4 Income Quintile 5 12% Cumulative EE Participation vs. Assessed Home Value (among the 50% of customers with assessor data) EE Participation Rate 12% Cumulative EE Participation vs. Pct of Neighborhood with Income >$75k (from secondary data) EE Participation Rate EE Participation Rate Cumulative EE Participation vs. Per Capita Income as % Poverty Line (modeled value) 10% 8% 6% 4% 2% 0% 1 2 3 4 Income Quintile 5 16% 14% 12% 10% 8% 6% 4% 2% 0% 1 2 3 4 5 Home Value Quintile What were the drivers of these differences? Targeted marketing? Awareness/knowledge? Qualification criteria? Interest? AESP EM&V Online Conference 5
  6. 6. We’re leaving opportunity on the table, but don’t know where or how much “Our customers are unique – So we can’t reach statewide goals” Three-Year Plan vs. Statewide Goals 3.5% 3.0% 2.5% 2.50% 2.55% 2.60% PY 2013 PY 2014 Segmented program evaluation and opportunity studies can uncover how/why: • Moderate income status? • House type (SF/MF)? • Seasonal/vacation homes? • Channel preferences vs. implementation channels? • Baseline efficiencies already high? PY2015 2.0% 1.5% 1.0% 0.5% 0.0% AESP EM&V Online Conference 6
  7. 7. Evaluators do report on differences by customer group, but sometimes we only look within a program Annual Percent Savings 2.5% Annual Percent Savings by Consumption Tertile 2.0% 1.5% 1.6% 1.8% 1.2% 1.0% 0.5% 0.0% Low Medium High Consumption Consumption Consumption Top 2030% Top 1020% • Misleading to report, because the program targeted high users! • Difficult for planners/evaluators to understand how to use findings Top 10% Make sure segment “membership” we report is relative to the customer population; use the same data source AESP EM&V Online Conference 7
  8. 8. Segment-level insights are useful across the program lifecycle Metrics Measurement Opportunities Awareness / Knowledge  General population and non-part surveys Intention  Inquiries, leads, incomplete applications that link to customer database by account # Qualification  Ex ante: Filter database by qualifying criteria  Ex post: Program qualification rates Participation  Program participation rates  Portfolio-level participation: What % of all segment members have participated in any EE? Engagement  Online / HEMS / IHD device tracking  Participant surveys Impacts  Realization rates by segment  Savings “depth” by segment (% savings)  Measure mix by segment AESP EM&V Online Conference 8
  9. 9. So, what segmentation is “good” for EM&V purposes? 1 1. Segment membership must be identifiable ex ante for all customers  Rate code (Low income, SF/MF, Small/large commercial)  Psychographic “lifestyle segment” available through data providers (e.g., Experian)  Usage characteristics (L/M/H; summer load; load shape) 2 1. Segments should distinguish between meaningful differences that affect program outcomes  Energy opportunity  Barriers to participation (own/rent; income)  Motivation to participate  Channel/communication preferences (on-bill, web, phone)  Impacts! 3 1. Segments should be “consumable” by readers/regulators:  Easy to understand / well-named  Manageable number AESP EM&V Online Conference 10
  10. 10. 1 Identification: Tracking by segment requires defining segments based on readily-available data – And we have a lot! Secondary demographic/ housing data – e.g., age, income, home value Past program participation – DSM and non-DSM TOU Account Rate A  B C Energy Audit Ref. Rebate   Customer characteristics from CIS data – e.g., rate class, time-as-customer New Customer engagement – e.g., online activity, payment preferences Energy indicators – e.g., seasonal usage, load shape 1-4 yrs 5-9 yrs 10-19 20+ yrs yrs 0 2 4 6 8 10 12 14 16 18 20 22 AESP EM&V Online Conference 11
  11. 11. 2 Meaningful Differences: Segment membership should correlate with savings opportunities, program propensity, barriers and preferences Demographically-Based “Lifestyle” Segmentation Custom Psychographi Segmentation Energy Usage Patterns Past Participation Highest Medium Dim. 1 Lowest Dim. 2 • May correlate well with: • Ability to participate • Channel/ marketing affinity • Heterogeneous in terms of: • Savings opportunities • May correlate well with: • Ability to participate • Motivation • Heterogeneous in terms of: • Savings opportunities • Channel/ marketing affinity 0 2 4 6 8 10 12 14 16 18 20 22 • May correlate well with: • Savings opportunities • Heterogeneous in terms of: • Ability to participate • Channel/ marketing affinity
  12. 12. Have AMI data? Clustering customers into Load Shape Segments could enable long-term impact tracking Best target for DR and conservation programs? cluster similar  patterns Relatively high baseload - many EE/Wx opportunities Whole‐House Load Shapes 4000 3500 High Peak / Low Baseload 3500 3000 3000 2500 2500 Extended Peak High Baseload Low Users Non-HVAC EE and behavioral interventions 2000 2000 1500 1500 1000 1000 500 500 0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 0 0 1 2 3 4 5 6 7 8 Low-cost conservation and 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23behavior Identify highest-impact equipment, envelope and behavioral opportunities for each segment AESP EM&V Online Conference 13
  13. 13. 3 “Consumable” segments: Easy to explain and interpret; manageable number  Single dimensions (single-family / multi-family) or 2X2 matrices have merit  But they leave a lot of heterogeneity undescribed  Complex segmentation schemes quickly go un-used  Reviewers don’t have background/knowledge of approach  Imagine 70 Experian lifestyle segments!  Cost implications to what we choose  Segment quotas AESP EM&V Online Conference 14
  14. 14. We can start by reporting savings at a segment level Segment Percent of Customers Percent of Wx Participants Wx Savings per Household (kWh) Wx Savings Total (MWh) A 25% 28% 180 81.0 B 15% 14% 150 33.8 C 40% 34% 100 56.0 D 20% 24% 80 32 Total 100% 100% 124 202.8 AESP EM&V Online Conference 15
  15. 15. End game: Identify and track program opportunities and success metrics specific to each segment Participation rate  among encouraged Savings depth or  realization rate n Targeted for Wx Wx Uptake (among those targeted) Wx Savings per Household (kWh) Wx Opportunity per Household (kWh) % of Opportunity Achieved 28% 5,000 9% 180 200 90% 15% 14% 3,000 7.5% 150 300 50% C 40% 34% 8,000 7% 100 150 75% D 20% 24% 4,000 10% 80 100 80% Total 100% 100% 20,000 8.2% 124 172 72% Segment Percent of Customers Percent of Wx Participants A 25% B AESP EM&V Online Conference 16
  16. 16. Thank You! Amanda Dwelley Associate Director 617-301-4629 adwelley@opiniondynamics.com Visit us at www.opiniondynamics.com AESP EM&V Online Conference 17

×