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Ep #46: Using Retirement Plan Data To Target Benefits Prospects – With Mark Smith

Today on The ShiftShapers Podcast, the founder and CEO of MiEdge, Mark Smith, returns to the show to continue our conversation about Big Data. In this episode, Mark focuses on the use of retirement plan data to create opportunities and deliver value to prospects and clients.

Mark describes new ways that benefit advisors can easily visualize potential prospect relationships from massive amounts of publicly-available data. We also discuss how you can interface your data findings with LinkedIn to help create offensive and defensive strategies that deepen and strengthen existing client relationships.

What You’ll Learn From This Episode:

The type of information the government collects.
How this data can be used to play offense and defense.
How large the data set is.
How employers react to this type of research.
Whether it is easy to see the relationships by just looking at the data.
The important data points for advisors.

Featured On The Show:

www.MiEdge.biz
Ep #24: Using Big Data as a Differentiator – With Mark Smith

Listen To The Full Interview:

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Ep #24: Using Big Data as a Differentiator – With Mark Smith

Today, we welcome the founder and CEO of miEdge.biz, Mark Smith, to ShapeShifters. The miEdge application is an affordable and easy to use service that combines an intuitive interface to a database and search engine of Department of Labor Health/Welfare Employee Benefits information.

I invited Mark to the show to discuss how data can be an effective prospecting and service tool while also serving as a differentiator for benefits advisors. Tune in to learn how the miEdge system helps level the playing field by making even the “average” benefits advisor a subject mater expert, able to tailor client solutions based on their unique datasets.

What You’ll Learn From This Episode:

What “Big Data” is and why it matters.
How data can be a differentiator for advisors.
How data can be used in prospecting.
Whether this is accessible to the “average” advisor.
Why DOL datasets are not practical for the average person to use.
How advisors can use data to help clients.