Once our 'members' have registered, we are now in the trusted position of delivering relevant and valuable information (push vs. pull) to the somewhat anonymous member. The challenge then is to ensure that what we send to you and how we engage are relevant and valuable to you. We plan to localize content based on various mechanisms at our disposal like asking for zip code for example. We know that not everyone has a smart phone with a willingness to share location. I also have a mechanism for establishing an initial location with members based on their phone #.
In the Healthy Families Community Network, 80% of the digital registrations came from mobile vs. 20% via web/email.
Feedback Loop
Included with the welcome message, approximately 50% of all users have subsequently shared at least zip code with the community network when interacting via mobile device. This is in stark contrast to email which gets fewer than 10% of member data beyond email address. Forms sign-ups have traditionally delivered the best startup data with zip code provided in more than 90% of all registrations. Just with the enhancement of zip code the Network is able to exponentially increase the relevancy of information shared with the member.
Managed Community Blogs
- past editor and contributor for the Challenge Diabetes Blog (final post & list of all posts)
- editor and interviewer for 2011 World Masters Athletics Championships (main site)
Designed, Implemented, Promoted & Managed Community Webinars
- evaluated commercial options and selected Adobe ConnectPro
- editor for all agendas and content
- moderated webinars and kept less experienced speakers on track and on message
- included follow-up content management, video editing and modular reuse of recorded webinars
Developed Proprietary Engagement Tools
- cost calculators that allow people via phone or web to quickly understand Total Cost by asking a few simple and personal questions which are inputs to a series of calculations and stated assumptions which return relative cost to the user of going with option A vs. option B.
- predictive modeling tool that considers manual or streaming data inputs, stored personal profile data, clarifying questions resulting in a forecasted value as well as a calculated recommendation for the individual to intervene and change the forecasted value. (eg - a tool used to predict future costs based on machine or manually input data representing existing patterns and the ability to recommend simple changes which would result in achieving a desired target cost).
- member de-identified peer group comparisons (How am I doing vs. my peers?)
