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Showing posts with the label independent insurance agent

The Endowment Effect - Why We (Agents) Keep Bad Business

If you could “divorce” one of your clients who would it be? ...people attach some strange value to what they own, simply because they own it, and are reluctant to let go even when trading makes economic sense. Every time I ask an agent that question, they immediately have an answer, and it’s usually more than one client. My next question is, “Why?” The answers include they have a ton of losses, they’re always rude to our team, they require constant service, they never pay their bills on time, etc. The list goes on. I then ask, “Why don’t you divorce them? Why not advise you can no longer be their agent?” Usually, the answer is in the form of body language. Looks of surprise, shock, or confusion. The concept of dropping a client is foreign to almost every agent I speak with. Richard Thaler’s “Endowment Effect” is the concept that people attach some strange value to what they own, simply because they own it, and are reluctant to let go even when trading makes economic sense. Agen...

The 80/20 Rule and the Law of Small Numbers

"Twenty percent of our insurance clients create eighty percent of our work." Have you heard this line before? I’ve spent a decade in the insurance industry in both the carrier and agency worlds. In my experience, the 80/20 rule seems to be almost universally accepted, and the majority of resources are spent on a small number of needy clients. What’s not universally accepted is this: How much of the resources should be spent on the 20 percent? How can an agency service these clients differently? And, how much stock should an agent put in what these clients say they need? When pressed, many agencies share that the accounts needing the most service are the type of business they don’t really want anyway. So why do they continue to serve those accounts? For some agencies, it simply comes down to pride in providing excellent service to all clients. For most, it’s a symptom of a larger operational problem - lack of data analytics. Spending precious time and resources ...