Cascading in Amazon and their Marketing Strategy

One of my favorite features of having the Kindle App is that when I finish a book or movie, I can go onto Amazon.com and expect a well put together list of other recommended books and movies based on the one that I just finished, but as well as previous purchases.

Normally, movie or book recommendations come from networks of friends or coworkers or any group of people who you are in frequent contact with. Then, this information would tend to spread in a cascading fashion, reaching many people due to ‘word of mouth’.

When it comes to the strategy of Amazon (as well as other companies such as Netflix) in theory, the network which recommends you what book to read comprise of complete strangers who we assume have nothing in common except the types of books they like to read. Amazon found a way to capture this phenomenon and use it to their benefit. Amazon gives personalized recommendations based on prior purchase patters.

When people recommend goods, by rating them and or writing reviews, purchases of that item will go up. However, I would think that purchases depend not only on recommendations, but also the number of recommendations, the number of people receiving those recommendations, how other people rate/ review the product, and the price of the product.

According to this article, http://webmarketingtoday.com/articles/viral-principles/, there are six simple rules to viral marketing which “encourages individuals to pass on a marketing message to others, creating the potential for exponential growth in the message’s exposure and influence.” At a quick glance I see that Amazon has definitely utilized most of these:

  1. Gives away products or services– its free to set up an Amazon account and when you make a certain amount of purchase, you get upgrades to more free products or free shipping
  2. Provides for effortless transfer to others– you can connect easily with other users and when buying movies/books/ music transfer occurs within the second to whatever device
  3. Scales easily from small to very large-
  4. Exploits common motivations and behaviors- targets tight knit communities with common interests but on a large scale
  5. Utilizes existing communication networks- Amazon indirectly connects those with common interests via recommendations and availability of product reviews
  6. Takes advantage of others’ resources.

YO

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2 thoughts on “Cascading in Amazon and their Marketing Strategy”

  1. It seems to me that Amazon is making use of all of these principles. The scaling is evident in that it doesn’t matter if it is making a few recommendations of a few million. On the low end it can recommend your next purchase based on your past purchase history alone. As more recommendations and network nodes enter into place it can use their information to produce even better results. Additionally, there is no better example of using others’ resources than the review system. No one is compensated yet Amazon generates a plethora of rating data to assist its users and its algorithm. Clearly there’s a reason for their massive success.

  2. According to the blog post only 6 simple rules are necessary to convince consumers to pass on their consumption behavior, sharing their preferences with other users. It is convincing that the offers Amazon makes encourage the users to share their Information, since they are benefiting from it and Amazon imposes the right incentives to do so. Overall, users are benefiting from these recommendations, paying attention to interest related products. Nevertheless, I would be concerned if it is a good idea to share personal information, simple as a book preference with People, who I only have a certain purchase behavior in common with.

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