The very first place to start when measuring or initially benchmarking the image of your community is with internal stakeholders, the people who live in your city or county. This will require teaming with experts.
Don’t be so sure your community has a strong self image or sense of pride. You can see some averages in the chart comparing Durham results with a Gallup project. Some of the most “boosterish” communities I know have a relatively low sense of pride among residents as a whole. Actually, seemingly cocky, pretentious and overreaching communities are often disguising an inherent insecurity or lack of pride among residents.
- Try to find team with experts, preferably based outside your community for both objectivity and credibility purposes. It is best if they have expertise in “diffusion” studies in short, studying the way information moves through a population. One of these experts has helped DCVB update this information annually since the early ‘90’s. That consistency is important, but the key background is going to be scientific public opinion polling.
- In Durham’s case we started with individual interviews of a good cross section of the community, then used the anecdotal responses to determine issues and then shape questions to determine the opinions of the general population.
- Make sure the people interviewed are not just boosters or politicians etc. Include activists, neighborhood leaders, cultural/arts leaders, small and large business executives, university leaders, students, newcomers, tourism sector and businesses that have recently relocated to your community etc. Ethnic and gender balance is also important as is a good mix of front line people.
- What’s learned from the interviews needs to be used to inform questions for scientific, random, public opinion polling to compare what the general resident population thinks about your community. Be prepared to track these same questions over many years. You’ll also want to include some demographic questions for later analysis, e.g. gender, ethnicity, time they have lived in your community etc.
- The questions will be best as statements so they aren’t “leading.” The subjects will be asked if they strongly agree, agree, disagree or strongly disagree or are uncertain or undecided or neither agree or disagree. Each of these responses is given a number, 1-5 which is a likert scale.
- The general statements to be measured may be something like:
- I am proud of my community
- I am pleased with my community as a place to live
- I have a positive image of my community
- Depending on what surfaces in the prior, personal interviews, you may want to probe certain areas like personal safety, student achievement, overall appearance, ratings for various parts of the tourism sector compared to other places, e.g. things to do, places to each, places to stay, places to shop etc.
You’ll also want to include questions to benchmark awareness of your organization and perceptions of the job your organization is doing. When you get the results, you’ll want to analysis ratios for each of the responses as well as some cross-tabbing (more on that in another blog.) You’ll note in the results in the chart shown above that in some cohorts there is a significant “uncertain.” Uncertain is better than negative but it reveals an ambivalence that isn’t good. Mostly you’ll want to look at ratios of positive responses to negative responses for each question.
Once you know your community’s self-image, you can decide on strategies to improve the results or as in Durham’s case, if the community’s residents as a whole have strong levels of pride and self image of the community and they are pleased, then you move on to external audiences.
But one warning. Never, ever assume you know what your residents truly think and feel about their community. All of the information in the world about what external audiences think about your community won’t matter a whit if you don’t know what internal audiences feel.
Remember, it is your internal stakeholders or residents as a whole who have to deliver most on your community’s brand.
I’ll deal in future blogs on some strategies to deploy based on the results.
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