Reposted from i.e., the Center for Energy and Environment's Innovation Exchange blog -- http://mncee.org/Innovation-Exchange/ie/

 

Today when you search Google or browse items on amazon.com, advertisements and recommendations appear to be personalized specifically to your interests or buying history. The fact is, they are. The same thing happens when companies like Targetsend you coupons in the mail. In the age of the Internet and big data, marketers have more access to our purchasing history and personal information. They’re able to use this information to tailor their messages specifically to us as individuals, increasing influence over our consumer preferences and choices.

Some energy institutions and utilities have successfully adopted market segmentation approaches to promote their energy products and services to their customers. Segmentation entails:

identifying homogenous sub-populations within larger heterogeneous  populations ... The technique is a response to the need to effectively communicate with, and motivate to action, an increasingly diverse population of individuals, families and businesses, who rely on a rapidly multiplying set of communication channels.


The first step is to define the segments. The UK Department Department for Environment, Food and Rural Affairs (Defra) conducted interviews with over 3,600 people to identify the seven clusters described in their environmental segmentation model:

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Similarly, the Bonneville Power Administration (BPA) used a survey of about 2,000 customers to perform residential segmentation research on energy efficiency in the Pacif... and develop eight segments:

bpa.png

And at the 2012 E Source ForumPG&E and Progress Energy described how segmentation efforts helped them increase participation in their residential programs.

Developing a segmentation model is expensive, and many of us managing efficiency programs don’t have the resources to formally segment our own customer base. However, a number of available tools could provide enough insight into our market to develop targeted messaging and improve recruitment.

Nielsen Claritas
 provides a handy (and free) online resource. On a zip code level, you can obtain the top five most common segments for households in those neighborhoods determined for each of the three Nielsen segment models: PRIZM (lifestyle and consumer behavior), P$YCLE (financial behavior and wealth), and ConneXions (communications behavior). A paid subscription provides even greater granularity. You might be able to infer the segment for a particular house by using available assessor data (or Zillow). The number of bedrooms can be a clue of the size of the household. The value of the house might hint at the household income. Both of these might then identify the Nielsen Claritas segment for that house. Here are the results for a Minneapolis suburb where we are currently delivering our residential energy program:


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We could compare our Nielsen segments with Defra's or BPA’s segments, then match our general messaging approaches to the types of households represented in the target zip code.

It’s also important to consider how energy efficiency aligns with our audience’s cultural values. For example, perceptions of the need for energy efficiency can be informed by the issue of anthropogenic climate change. This can be an emotional, hot button topic. As Andrew Hoffman pointed out in his keynote address at BECC 2012, climate change is a cultural issue governed significantly by political ideology. So the messages that resonate with the cultural values of a Democratic supporter could fall flat with a Republican supporter. Energy independence might be a preferable hook to recruit him or her to an efficiency program. Frank LuntzGeorge Lakoff, and Drew Weston have written extensively about the types of messaging one could employ.

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Following the market segmentation thread, anyone can access online resources with voting results for various U.S. precincts. Minnesota’s maps are here. We could use them as a general guide to anticipate customer responses to different communication strategies.

Our Community Energy Services Program found that new homeowners (in current home five years or less) and homeowners likely to have paid off their homes were the majors groups that perform energy efficiency programs after our home visits.

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Knowing that people are more open to changing behavior after a life-changing event, we expect that new homebuyers, empty nesters, and retirees would be three groups that would be worthy of targeting for a retrofit program.

On one hand, market segmentation can be viewed as a slippery slope with respect to customer privacy. The information is in the public domain, but is it ethical for us to adopt these practices? On the other hand, we invest significant time and resources to sell energy efficiency. Could these approaches help us serve our community more effectively? We would love to hear about your thoughts or experiences with segmentation and targeting in home energy retrofit work.

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