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Swaths of the population aren’t the right fit for your clients’ insurance...

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發表於 2024-3-7 14:21:51 | 顯示全部樓層 |閱讀模式
They leverage the power of sentiment.Consider the type of insurance your client sells and the various emotional responses to scenarios in which someone would need to purchase it. Think of how the idea can be framed, both positively and negatively (testing doesn’t hurt!), and get ready to stand out! Even if site visitors don’t convert, inciting a click gives you the ability to remarket to prospects.Insurance Marketing Tip  Control Lead Quality Using Income TargetingA few realities People without boats don’t buy boater’s insuranceYou’re not going to sell a $10k burial policy to a billionaireYou’re probably not going to sell variable life insurance to a 26-year-old living in a janky apartment My point is this.

Income targeting is one way to focus ad spend on areas in which searchers are likelier to Benin WhatsApp Number fall within your target demographic.This basically functions in the same way you used RLSA’s target and bid function to prioritize bidding on your most expensive keywords only after someone has visited your client’s website. If right out the gate you can draw a geofence around an area using average household income as the distinguishing factor.





You cut superfluous impressions.Obviously this is a less effective tactic for something like car insurance, but if you notice that most of your clients’ prospects and policyholders are of a certain income, use that data to your advantage.targeted locations insurance marketing tacticsAnd the best part? You can layer income-based targeting with the RLSA you implemented two tips ago to virtually guarantee rich, smiling clients. In marketing, we call this “the dream.”Insurance Marketing Tip .4: Use Demographic Data to Inform Your Ad CreativeKnowing what an objectively “good” lead looks like is the key to maximizing the value of every dollar your insurance-industry clients spend on Google Ads. The “Audiences” tab in the Google Ads UI is often used as a tool for adjusting bids based on gender and age.




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