Case Study Analysis: Privacy Issues and Monetizing Twitter
All three Individuals held executive level sections at the time of the case study. Twitter created a relatively simple, but very popular social network consisting of short messages of 140 characters or less called “tweets”. Users could tweet using a variety of technologies ranging from the Twitter website to cell phone text messages and third party applications for mobile devices.
From its inception in 2006, Twitters user base grew quickly. While Twitter recorded an average of 500,000 tweets per quarter in 2007, that grew to four billion tweets in the first quarter of 2010.
The largest group of users was the 25-34 age group Twitter came a popular way for celebrities to keep in touch with their fans, and was even used by NASA astronauts to provide updates on shuttle repairs. Twitters potential business applications seemed promising. Dell started using Twitter and within 3 years was generating $6 million in sales from the channel.
Privacy concerns for users of various social media sites were a sensitive issue. Some users of Twitter, along with competitors such as Faceable, Google Buzz, and Namespace were concerned with how secure the personal data being provided to the social sites was.
Also concerning was owe a social media site may chose to sell user’s personal information for a profit to third parties. Most social media sites, Twitter included, had experienced negative publicity as a result of security breaches and unwanted features that used personal information in unwanted ways.
Politicians took notice and were working with regulatory agencies to provide guidelines for use of personal information. With Twitters user base exceeding 100 million users in early 2010, Twitter was still without a viable business plan.
Through several rounds of venture capital funding Twitter ad secured more than $57 million, but without a viable plan to generate revenue, Twitters long-term future was uncertain. One viable avenue was to leverage Twitters large user base for data mining purposes. Twitter possessed a large database of personal Information that could potentially be sold to companies looking to gain additional insight into the consumer market.
Competitors such as Faceable and Google Buzz had done this previously, often to negative feedback and publicly from their users and media alike.
In an effort to capitalize on the large Information database It held, Twitter signed a deal with Microsoft and Google In October of 2009 to allow tweets to appear In the search results of their search engines. This deal resulted In some increased exposure for Twitter, but was not lucrative financially for any of the companies involved. Even the Library of Congress announced plans to catalog Ana archive all puddle I Nils program was met Walt resounding criticism from users, citing privacy concerns.
The Library of Congress eventually revised and scaled back the program. Amid this environment of rapid growth in user base, Twitter was a company at a crossroads. Twitter needed to turn a popular free service into a viable revenue generating corporation. How does Twitter capitalize on their passionate user base? Is data mining the answer? If so, can Twitter sell user’s private information while maintaining their trust? Recommendation In an effort to create revenue generating channels, it is recommended that Twitter embark on several initiatives.
With respect to data mining, general, non-user specific information should be sold to marketing firms and other third-part companies interested in obtaining this information.
Second, explore the possibility of putting in lace a subscription-based account for any commercial users. This included companies, brands, products, celebrities, etc. These users are potentially profiting from the Twitter platform without any profit sharing going to Twitter. Lastly, explore the use of selling targeted advertisements to appear in the Twitter feeds of users.
Rationale There is a climate of great sensitivity to the protection of individual’s private personal privacy at the time of the case study.
Twitter has an avenue to profit while still maintaining individual user’s anonymity by selling demographic user data to third arties. Age, sex, interests, religious status, and other information could be very useful for marketers, and by not linking this data to individual people, potential kickback from the user base would be diminished.
Additionally, as the case study points out, Twitter had become a very useful tool for businesses and celebrities to promote their products, services, and public images. Look into creating a commercial subscription service for these types of users so that they are being charged for this form of advertising. It could be argued that these entities could switch too omitting social networking service, however when companies can have hundreds of thousands, if not millions of followers, it may be worth paying $50 or $100 a month to maintain contact with the Twitter network of users.
As Twitters user base grows, so does Twitters leverage to charge businesses and other commercial users higher subscription fees.
Lastly, the use of targeted advertising in user’s Twitter feeds could create another potentially lucrative revenue stream. It would be important to limit advertising in an effort to avoid annoying users, but 1 or 2 advertisements for every 00 standard twitter posts probably wouldn’t affect the user experience greatly. Implementation Tactics As indicated above, privacy rights are a chief concern for users, media, and politicians at the time of the case study.
Data mining is a touchy subject, as it has the potential to violate the privacy rights of millions of users if not done in a carefully thought out, ethical manner. As such should Twitter proceed with a data mining program to sell non-user specific data to third-parties, this program should be made clear to the general public and all Twitter users. Details should be provided guarding the safety measures being put in place by Twitter to protect user’s data in an effort to proactively address the privacy concerns.
Regarding the commercial-user subscription proposal, Twitter needs to develop a completing value proposition to offset the negative kickback that would inevitably result from converting what had Eden a Tree service Into a monthly crosscurrent service. Letter snouts create commercial marketing initiatives as part of the subscription service that would help commercial pay-users to more effectively promote their message and grow their follower base.
Additionally, a “Twitter Analytics” service could help commercial pay users to interpret the vast information related to their follower’s demographics and other data to allow them to refine their messages to maximize effectiveness. Twitter advertising could tap into the growing and lucrative online advertising budgets currently being devoted to Google, Yahoo! , Faceable, and other search engine and social networks. Modeling an advertising model after the very successful Google platform could generate huge long term revenue streams as Twitters user base continues to grow in the future.