Network Marketing Leverages Relationships And Improves Monitoring

I started this blog in part to earn income through affiliate marketing channels. A lot of companies like Uber, Lyft, Dollar Shave Club, Nozbe, and others offer referral incentives. If you use my Uber or Lyft codes for your first rides, I get a $20 discount on a future ride. If you sign up for Nozbe on my recommendation, I get a few dollars. If you sign up for Dollar Shave Club, I get credit toward my next sleeve of blades. And so on.


So will this create a world of unscrupulous shills hawking products in cynical ploys to separate friends and audience members from their money? I don’t think so. Why? Reputations are riding on it. If I recommend a product you don’t like, my credibility suffers, people are less likely to buy and use the things I recommend, and ultimately my plan to earn income through affiliate marketing is compromised and I’m less able to fund the worthy causes I’m supporting with the money I’m earning from the blog (see here for my money-back guarantee).


Affiliate marketing leverages existing relationships and gives the marketers themselves incentives to monitor products and services for quality. That so many people—the manufacturers, distributors, and affiliates—have so much on the line provides a powerful check against opportunism.


Ride-sharing is an example. If I recommend that you use Uber or Lyft, there are several layers at which people have incentives to provide quality recommendations and services. First, I have an incentive to recommend only things you will find useful or you’ll go elsewhere for recommendations. If I’m not reliable, I lose my audience.


Second, Uber and Lyft have incentives to monitor their products, their drivers, and their riders. Bad experience with Uber? I can use Lyft instead with two taps on my phone. Finally, drivers have incentives to provide quality service in pursuit of those coveted five-star ratings.


That’s a lot of screens. Given the sheer enormity of the world and the number of people involved. Are the filters perfect? Of course not: nothing is. In my experience, however, they are extremely effective.

About the Author: artcarden


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