[MBA] Case Study: Zynga Wins with Business Intelligence

[MBA] Case Study: Zynga Wins with Business Intelligence

1.    It is said that Zynga is "an analytics company masquerading as a games company.” Discuss the implications of this statement.

2.    What role does business intelligence play in Zynga's business model?

3.    Give examples of three kinds of decisions supported by business intelligence at Zynga.

4.    How much of a competitive advantage does business intelligence provide for Zynga? Explain.

5.    What problems can business intelligence solve for Zynga? What problems cannot it solve?



Zynga's success has been example for video gaming industries. Zynga used the information available free for them i.e. the data of player frequency, preferences. It didn't interested much on short term income charging for customers but applied analytics to better improve users experience so that customers are retained more.

It maintained an eco-system of player, games and company data analysis system. Although Zynga's developers disliked the company's strategy of data analysis rather than game development it continued the way of retaining customers on simple games instead of plugging users on hard games.



Zynga have dedicated Vertica cluster for developing real-time graph of data on daily basis. Zynga's feeding and notification system is highly influenced by analysis of previous night's graph. It aims to better match level and type of gift for active players and lowering spamming inactive players.

When Zynga proposes and add certain feature to any game it can quickly get picture of its pro and cons, effectiveness by that day end graph so that they can improve or remove such feature.



Zynga have system to get day to day analytics graph that interprets terabytes of data. It determines user preference so that user preferences are measured more accurately. Depending upon user interest and involvement it can feed virtual goods likely to be purchased.

Zynga on the other hand have access to players profile, background and interest from their Facebook profile. Most users sharing things on Facebook so Zynga can make this profile a source for greater accurate information.

Zynga attempts to suffer inactive members less through spams but prioritize active ones offering limited edition offers which the gamers prefer much. Similar behavioral users group are detected and targeted for game-related promotions and activities.



Zynga accounted $91 million dollar profit in 2010 with revenue of $600 on same year jumping from the figure of $121 in 2009. Zynga followed different track than traditional business and have been role model for some running and some startup game industries. The revenue figure concludes its success of strategy. Zynga doesn't target revenue from original game but from virtual goods which are offered very precisely with detail analysis of available data.



Business Intelligent system can be used to reduce spam and promote active players interaction. Moreover it can use data analytics to get information of good and bad products so that they can trash rubbish piling up in their system. It can measure users' likelihood of accepting changes and upgrades on games by daily updates.

If Zynga underestimated requirement of creativity and only concern data analysis then they fail on success. They parallel should focus on both. Moreover its higher dependency on Facebook make it parasite to it so if Facebook raised some change in its strategies or policies then the direct effect is on Zynga.