Who are these people? And why aren't they using our library?

Friday January 30, 2009
[1025] Who are these people and Why aren’t they using my library?
Don Mills, CEO, Mississauga PL, Rupen Seoni, VP, Environics Analytics
Don.Mills@mississauga.ca, Rupen.Seoni@environics.ca
discussed ways to find out why people aren’t using their public library.

Goal = we want to be relevant to the greatest number of our service area residents.
Tool = Geodemography
-->add neighbourhood level demographic information to library’s client data

Library Client Data

• limited demographics (age, gender)
• transaction data
• postal code and city/town information

PLUS

Environics Neighbourhood Data

• much more demographic info (from census)
• growth trends
• lifestyle segmentation
• social values
• purchase behaviour
• media use

= GeoDemography

Benefits: Adding Environics’ demographic and social values data to library’s information about its existing clients, and the neighbourhoods where they live allows the library to see
- what it does well, i.e. where it already has lots of members
- what it does not do, i.e. where it has few or no members
- what it does not do well, neighbourhoods where its actual membership is much lower than potential membership, based on patterns in other areas

The Process: Environics used demographic, social value and urbanity (i.e. urban, suburban, rural etc) data to come up with 66 consumer segments – e.g. grey power, mini vans and vin rouge, newcomers rising, big sky families.
These segments are used – mostly by commercial enterprises – to understand and target lifestyles, purchase preferences, media use, mindsets/motivators. But can be used by non-profits and public sector organizations, too.
Each neighbourhood (i.e. census dissemination area) is described in terms of the consumer segments which are dominant.

MPL partnered with Recreation Services, to share costs – had similar goals.
MPL worked with 12 segments, dropped ones with very few members

MPL looked at which segments had the highest membership rate:
South Asian Society (suburban upscale ethnic) 54.2% have MPL cards
Blue-Collar Comfort (exurban midscale) 51.6% have MPL cards
Asian Influence (suburban upscale ethnic) 51.1% have MPL cards

Highest non-membership rates were in
Cluttered Nests (urban upscale ethnic) only 40.3% had cards
Grey Pride (suburban midscale) 37.5% had cards
New Italy (urban upscale ethnic) 30.8% had cards

For Non-Users

Summarized the demographic characteristics of non-user clusters:
• Empty-nesters and older families
• Below-average incomes
• Mixed houses and apartments
• Below-average presence of immigrants; Southern European where present

Summarized the social characteristics of non-user clusters:
• Emotion, Intuition & Connection
• Looking for emotional experiences; trust their intuition
• Seek to connect with others; connected to the world at large
• Conflicted about work
• Enjoy their careers, but want to spend time on other things
• Low need for control and creativity
• Paternalistic towards children

Looked at BBM (Bureau of Broadcast Measurement) info about non-user segments, to get ideas about which channels they listened to, what events they patronized – in other words, where & how best to reach them.

All these give ideas about how to reach non-users.
Follow up with focus groups, based on postal code, to investigate these ideas.

For users: look at geodemographic info to get ideas about new services they might like.

Potential vs Actual
PRIZM profile of library members shows “expected” or average rate of membership for that cluster
Next, look at neighbourhoods with that cluster, and see if they are above, below or at expected rate of membership

For RWL : very exciting prospects, a way to discover if there are potential users of online services in our “neighbourhoods”. Could perhaps partner with other Regional departments, or Township recreation departments?