Manchester's Psychographic Segmentation Analysis
Segmentation Analysis Highlights
Manchester High Needs Areas
Demographics
Lifestyle and Interests
Self-Care
Media Preferences of High Needs Households
- High needs households are heavy television users who tend to binge-watch.
- They are also heavy YouTube watchers and stream on free platforms.
- This group actively uses popular social media platforms and is likely to have Facebook and/or Instagram accounts.
- They are avid music listeners on Spotify and radio.
- This group consumes ads regularly, listening to and watching ads on online radio, mobile apps, websites & social platforms.
Medical Preferences
- Comfortable accessing mental health & relationship counseling online.
- Have received medical information from a patient support group or pamphlets/ brochures.
- Refilled prescriptions or had a doctor’s appointment within the past 12 months.
- Prefer brand-name medication and are likely to ask their doctor about medications.
- Likely smokers.
Financial Profile
These are careful spenders who only buy essentials and shop at low-end retailers. They are unlikely to have credit cards nor bank cards and are uninterested in long-term planning.
Psychographic Segmentation for Eastern Winnipesaukee, Western Winnipesaukee, Laconia, and Greater North Country
Segmentation Groups
Utilizing Esri Tapestry psychographic data, PAP identified the dominant market segments by Needs location for each area.
The following is the identified LifeMode consolidated list for all locations.
- Heartland Communities
- Home Improvement
- Retirement Communities
- Rooted Rural
- Front Porches
- Rustbelt Traditions
- Small Town Simplicity
- Old and Newcomers
- The Great Outdoors
- Parks and Rec
- Emerald City
LifeMode categories provide details regarding household demographics, socioeconomics, and preferences.
Goals for Psychographic Analysis
Psychographic segmentation will allow us to reach and motivate residents in the highest needs areas.
Our focus will include media channel selection and personalized messaging development, ensuring prevention efforts have maximum impact.
Key Areas:
- Optimizing community engagement
- Targeted prevention messaging
- Resource and infrastructure allocation
- Marketing of prevention opportunities
References
- [2] Little Rock Child Maltreatment: Predictive Analysis, 2020. Grant Drawve, Shaun Thomas, and Jyotishka Datta.
- Daley D., Bachmann M., Bachmann B.A., Pedigo C., Bui. M.T., & Coffman J. (2016). Risk terrain modeling predicts child maltreatment. Child Abuse Neglect. 62:29-38. doi:10.1016/j.chiabu.2016.09.014. https://www.sciencedirect.com/science/article/pii/S0145213416301922
- Predict Align Prevent (2019). Richmond, Virginia Technical Report. https://b9157c41-5fbe-4e28-8784-ea36ffdbce2f.filesusr.com/ugd/fbb580_2f1dda2ff6b84f32856bc95d802d6629.pdf