Finding a client can be the hardest part of selling life insurance. But one technology can lead you directly to the clientele you’re after.
Furs and Station Wagons, Shotguns and Pickups; it might sound like the title of reality TV shows but in fact are geocoded demographics advisors should be targeting.
Geocoding has long been used in other industries to great effect but the uptake for life insurance has been slow.
“This is a mature technology, it’s been around a long time and I would say health and life have been slower to adopt it than retailers and property and casualty insurance have been and I think there’s a big opportunity to really and deeply understand the customer base that are in these industries,” said Berk Charlton, global portfolio director in customer data/location intelligence, Pitney Bowes Software.
But gradually life insurers and advisors are seeing the technology’s potential for direct marketing and targeting demographics.
“Let’s say you have 15 different policies,” said Charlton. “You can geocode each one of them and determine the geographic segmentation of each one of those. If you look at some of the segmentation categories you’ve got the classic descriptors that kind of transcend the raw demographic variables. They have these cute descriptors to describe [the neighbourhood].”
That’s where you get your shotguns and pickups, which would be for a more rural neighbourhood. There could be one called blue collar overachievers; another would be called furs and station wagons.
Once there’s a profile then advisors can compare the demographics between neighbourhood to another or even one city to another and market products or have more agents in specific areas.
For example, after looking at the data you realize there are similarities between the demographics in one neighbourhood in Toronto and another one in
Montreal. But your advisor network isn’t as strong in Montreal. There would be opportunities for more sales by building up the agent network in Montreal.
“Then it really becomes a planning tool and a marketing tool,” said Charlton. “Then you can identify specifically all the households that are in those areas and just pinpoint market to just those households that match a description of who your most successful customers. It really all started with geocoding them and matching them to their neighbourhoods so you know who they are.”
Also for site selection, you may find when you geocode your customers there’s a whole bunch of customers in the western suburbs of Vancouver and the closest office to a lot of them is miles away. By putting offices closer to them “you can start building some loyalty and repeat business in that area where you’ve already got customers. Sometimes it’s shockingly easy to see what’s happening.”
Geocoding has long been used in other industries to great effect but the uptake for life insurance has been slow.
“This is a mature technology, it’s been around a long time and I would say health and life have been slower to adopt it than retailers and property and casualty insurance have been and I think there’s a big opportunity to really and deeply understand the customer base that are in these industries,” said Berk Charlton, global portfolio director in customer data/location intelligence, Pitney Bowes Software.
But gradually life insurers and advisors are seeing the technology’s potential for direct marketing and targeting demographics.
“Let’s say you have 15 different policies,” said Charlton. “You can geocode each one of them and determine the geographic segmentation of each one of those. If you look at some of the segmentation categories you’ve got the classic descriptors that kind of transcend the raw demographic variables. They have these cute descriptors to describe [the neighbourhood].”
That’s where you get your shotguns and pickups, which would be for a more rural neighbourhood. There could be one called blue collar overachievers; another would be called furs and station wagons.
Once there’s a profile then advisors can compare the demographics between neighbourhood to another or even one city to another and market products or have more agents in specific areas.
For example, after looking at the data you realize there are similarities between the demographics in one neighbourhood in Toronto and another one in
Montreal. But your advisor network isn’t as strong in Montreal. There would be opportunities for more sales by building up the agent network in Montreal.
“Then it really becomes a planning tool and a marketing tool,” said Charlton. “Then you can identify specifically all the households that are in those areas and just pinpoint market to just those households that match a description of who your most successful customers. It really all started with geocoding them and matching them to their neighbourhoods so you know who they are.”
Also for site selection, you may find when you geocode your customers there’s a whole bunch of customers in the western suburbs of Vancouver and the closest office to a lot of them is miles away. By putting offices closer to them “you can start building some loyalty and repeat business in that area where you’ve already got customers. Sometimes it’s shockingly easy to see what’s happening.”
