Amazon Affiliates

Rather than chasing after niches, I have always searched within broad networks or groups of people such as within associations, professions and specific demographics. This can span hundreds of highly profitable niches, and marketing to them is a matter of matching relevant products to an engaging funnel system. It has nothing to do with ranking, SEO, Google, product competition, etc.

Focusing on marketing by developing an affinity within specific groups of people who share a commonality of interests can open up a broad spectrum of lucrative niches and opportunities for referrals and cross-sales. Typically, people with common interests, vocation, members of organizations, clubs, etc tend to have similar and often predictable buying patterns. For me, this single marketing method has worked astoundingly well for over 16 years.

For example, I targeted medical professionals, legal specialists, accountants, mechanical/electrical/aerospace engineers, managers in business/industry, academia faculty/researchers, trade associations, churches, civic groups, etc. People are multi-dimensional, and have a wide variety of interests which can often be monetized with effective online/offline list segmentation.

The idea idea behind this marketing concept comes from the "affinity approach" used for many decades among marketers, also known as "market basket analysis". Purchase behavior was analyzed for cross-promotions and capturing new buyers who share similar demographics. In more recent years, it has evolved into "data mining" - using advanced statistical analysis.

A superb example of data mining and market-basket analysis is Amazon's ingenious algorithm for suggesting "other" products, which has no readily apparent similarity to the original search or purchase. This is a common experience for Amazon affiliates, where the cross-over purchase is made in addition to (or sometimes instead of) the original product being promoted. Amazon keeps a history of purchases made (and even interests from search results) which is used in their data-based marketing algorithm and rigorous email promotions.

Follow Amazon's example, which over the years has been finely tuned to become a very formidable marketing machine. Build lists of your initial buyers and their interests, then you can promote (ie recommend) progressively higher end products on the strength of your affinity and relationships with your subscribers.

Consider that as much as 65% of Amazon's sales are from their own in-house promotions to existing customers (which are so generously given away by unknowing affiliates). Most affiliates are leaving huge piles of money on the table by not collecting contact information for repeat sales.

Very good point, here. Designing/producing things for humans rather than for search engines tends also to produce better SEO results than trying to design/produce things for Google. SEO is increasingly about quality and relevance, these days (like most other things in internet marketing, really).

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