What Do Numbers Tell Us? Pizza Hut Facebook Figures Compared – Voice of an Intern

Followed posting is written by our intern, Junhee who worked with us for the last two months. He compared figures of Global Pizza Hut Facebook page with Korean page, such as fan number, Talking about this, etc.  
If you want to read his first article, click the following link

What Do Numbers Tell Us? Pizza Hut Facebook Figures Compared – Voice of an Intern

Written by: Junhee Lee

 In this information age of the Internet(‘Big Data’ ring a bell?) there is an ocean of data, raw, accumulating, and untapped sets of 1s and 0s screaming for attention that some of the highest paid jobs going to top Ivy League graduates have to do with number crunching.

As an intern untrained in the Matrix-like science of analyzing pages of excel spreadsheets, I wanted to see what I could come up with by sampling some data from two separate Facebook pages of Pizza Hut: Global and Korea.

Here’s a quick laydown of my methodology in sampling this dataset:

-          Period: January 23 – February 19 (4 weeks)

-          2 main datasets with 4 categories: posts, likes, comments, shares

-          1 subset of ‘posts’ with 5 categories: images, shares, text, polls, events

-          % of total likes: portion of ‘comments’ and ‘shares’ to the number of ‘likes’

 Below is a summary of the sampled data –


             Not exactly appealing to the eyes, I know. Makes you almost feel sorry for the guys who do this for a living. But hey, each to their own. So what exactly can we gleam from this? Pizza Hut Korea posts vastly different wall content (events: streaming videos, app promotion, discount offers) than its global counterpart, and its fans are much more keen on “sharing” (25.33% to a mere 3.11%). The global page is more focused on promoting brand-consumer interaction and developing a relationship by providing interesting content whereas the Korean page is more market-incentive-oriented alluring fans with attractive offers and lucrative discounts (in a sense, “buying” over fans).

This of course, leads to the question: SO WHAT? Upper management (decision makers) simply wants to know WHY this is happening and how to turn these business insights into $$$.

             Now I could tell you WHY, or at least form a hypothesis based on my prior working experience in the online marketing department of a MNC in Korea. For example, I know that Pizza Hut Korea’s celebrity endorsement change 2 years ago had an extremely positive impact on the brand and many of the Facebook image posts try and include this celebrity. I also know that online sales have been increasing in recent years and a lot more attention is being given to develop comprehensive online marketing strategies due to its potential for growth and low marginal costs. Cultural tendencies in Korea and the widespread popularity of SNS discount and sales promotions tend to lead many brands to focus on delivering a diversity of well-packaged and visually stimulating “events” that promote brand exposure by offering fans monetary incentives.

             To make this same argument using compiled datasets on the other hand, requires some fine-tuned excel spreadsheet know-how and shrewdness in data manipulation – classifying, predicting, linking, modeling, and analyzing to name a few – to ‘create’ the necessary (totally un-biased, of course) outcome.

Don’t get me wrong. I am not in any way trying to discredit the science of data mining and ‘Big Data’ analysis, but merely implying that although data is factual and may be wholly accurate in itself, the art of extrapolating relationships can be a fickle thing, and pursuing a data-driven business strategy may not always produce the expected results.


Conclusion: ‘Big Data’ most definitely has its merits, but it comes down to how effectively and objectively the data can be analyzed. There are also many limitations to drawing conclusions from datasets as it never shows a complete picture and may the product of a skewed and biased interpretation of an individual. That is not to say that businesses should shy away from this still-developing science of making data-driven decisions. I DO fully endorse it, as it WILL BE (excuse the highly opinionated and didactic tone of a 23-year old) the future to running businesses more efficiently – just remember that data can sometimes be misleading, and should be approached cautiously with a healthy dose of skepticism.



  1. http://www.facebook.com/PizzaHut
  2. http://www.facebook.com/enjoypizzahut
  3. http://www.nytimes.com/2012/02/12/sunday-review/big-datas-impact-in-the-world.html?pagewanted=all