A retirement-focused advisor along the New Jersey shore encountered a production problem that Bill Poll said data analytics helped solve. After five years of high production, sales started dropping, seemingly out of the blue.
It happened before Hurricane Sandy in 2012, so the devastation was not the cause.
Poll said a ZIP code study of the area the advisor had been targeting found that the market had changed dramatically from five years previous. The prime buyers of annuities and other retirement products were leaving the area, Poll said, so “the hosting of steak-and-lobster dinners wouldn’t work there anymore.”
But the report also found that a market ripe for annuity and retirement-related sales lay in another ZIP code farther inland, so if the advisor wanted to refocus there, the advisor might see production pick up again.
That is an example of how data analytics can help, and is helping, advisors grow their business, said Poll, who is managing partner at Information Asset Partners (IAP), a Metuchen, N.J., analytics firm.
Analytics is often viewed as something for use by insurance carriers, broker/dealers (B/Ds) and insurance marketing organizations (IMOs) in designing marketing and sales strategies. LIMRA confirms that life insurers are definitely stepping up to the plate in using analytics, including predictive analytics.
But some producers are benefitting from analytics too, according to Poll. Typically, the carriers, IMOs and B/Ds provide salient findings from analytics studies to producers whom they believe will benefit from the data.
However, advisors like the one from New Jersey sometimes seek out analytics data too. “They need a snapshot, usually for a specific need or purpose,” Poll said, “but they probably don’t need to get reports regularly.”
Types of data developed by analytics firms vary by researcher, firm, industry, target markets and other factors. At Poll’s firm, the focus is on analytics by ZIP code or other geographic codes where annuity production lags or excels compared with market potential.
To do that, the firm takes its own national survey data on current retail annuity buyers and relate it with U.S. Census Bureau “block group” data and with the annuity sales data gathered by a unit of the Depository Trust & Clearing Corp. From that, the firm produces various reports, including those that identify performance benchmarks and trends for various regions down to the ZIP code level.
Annuity production opportunities vary between states and between ZIP codes within each state, Poll pointed out.
For instance, an area within a 10-mile radius of a ZIP code may have 65 producers (advisors and agents), 45 of whom are working with annuities. If that area has close to the highest annuity production in the state, that signals a highly competitive environment for annuities, and it may mean that opportunity for significant future growth may be comparatively limited.
But if a nearby ZIP code area in the same state has only 30 producers, 10 of whom are working with annuities, and if production there is well below the state benchmark, that bears some study. If the data show that there are lots of households in this area with strong similarities to households having made a recent annuity purchase, that might signal an underperforming marketplace that has opportunity for greater sales, Poll said.
Put another way, this second area may be an “overlooked ZIP code” that annuity marketers may want to consider for targeting more frequently, Poll said. It could may provide annuity wholsalers, IMOs and B/Ds with meaningful information to share when consulting with advisors.
Analytics can identify state trends as well. For instance, the map accompanying this article shows the states that represent the most opportunities for selling annuities in 2014, according to IAP research.
The advantage of data analytics like this is that it can reveal the scale of retirement income product opportunity in particular markets, Poll contended, adding that this can help everyone involved in production “to address potential opportunities more efficiently” with campaigns, products or other methods.