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SWOTT Analysis for Netflix

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Using netflix as the organization with products Eco Friendly Disks (EFD) This service will be the basis for your Marketing Plan Paper. Marketing Plan Outline for the general framework of the Marketing Plan.

A SWOTT (Strengths, Weaknesses, Opportunities, Threats, and Trends) analysis on the service.

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Solution Summary

Founded in 1997 by Reed Hastings and Marc Randolph, Netflix began offering daily DVD rentals to customers via the mail. Seeking to differentiate itself from its competition, Netflix created partnerships with companies selling a complementary good (i.e.) a DVD player (Chiu, Doroudi, Haussler, Khosla and Maltingly, 2007). Netflix therefore offered free rentals with every DVD player purchased. Presently, Netflix is the world's largest online movie rental service with more than 20 million members (http://ir.netflix.com/). The company provides not only online movie rental service but subscription service streaming movies and unlimited TV episodes via the internet. The company also offers free in home delivery with no due dates, late fees or return charges. This winning strategy and user friendly service has made Netflix extremely successful over the years.

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SWOTT Analysis
Strengths
Market Entry
Netflix entered the market for DVD rentals with minimal competition which allowed the company to establish its brand whilst providing a large variety of DVDs to customers at their convenience. Thus customers are able to rent and return DVDs at their convenience without the hassle of rushing to avoid late fees.
Partnerships
By partnering with stakeholders in the movie, electronic and retailer industries, Netflix was able to promote its services and product and increase profits. For example according to Gallaugher (2008) found that Studios partnered with Netflix because they earn a percentage of the subscription revenue per disk sent to each Netflix customer, whilst Netflix gets to by the Studio's DVD at cost.

Website
Netflix's website boasts many features. Netflix's CineMatch implements an award-winning algorithm which predicts with consistency the movies an individual would prefer to watch based on rental history, planned future rentals and past movie ratings ...

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