Tripadvisor: a case study to think why bigdata variety matters


The recent scandals about fake reviews has put the reliability of TripAdvisor under discussion (see The Guardian).

Such a bad quality of service is not useful for consumers, entrpeneurs as well as in the long run for the reputation of TripAdvisor. So, where is the problem?

Clearly it’s a question of reliability of the sources of information and specifically for TripAdvisor is a question of assessing the reliability of the user that post a new review. Nice and easy…like discovering the hot water. However, thinking also at the practice of the so-called Negative SEO, that is not only an issue of web sites like TripAdvisor but also for all the companies that have to promote theirs brands in the social networks (who think doesn’t need it, raise up the hand).

In order to fix the issue, Tripadvisor developed the service Report Blackmail that tracks and eventually bans the users that are using Negative SEO tactics. For example, 100 user managed by a restaurateur that are reporting cases of colitis and runs in the reviews of the competitor near the corner. Such a solution try to catch fake users when they’ve already done the “attack” as well as, if not properly working, it might ban by mistake honest users. It sound reactive rather proactive, isn’t it?

So, are there other approaches that can fix the problem of malicious reviews proactively? An idea could be use new IT bigdata technologies and re-think the business model. How? (see also MIT Sloan Management Review: technology as a catalyst for change).

An approach could be associating the Tripadvisor user with a unique ID, for example a TripAdvisor idetity card, while to restaurateurs and hotel managers have an ID card reader (RFID, infrared,etc.). Thus, once the consumer eat the meal and goes to pay the restaurateur track the consumer ID that univocally identify the user, plus time and position. Finally, the user have just to fill the form for his\her review that now can be fully validated. Potentially, once the users sign in the TripAdvisor website, a list of pending reviews not already filled might be also provided in order to facilitate the process and thus creating the so-called “customer experience”. Moreover, by tracking precisely the date, it is also possible to provide evaluations that are more meaningful for the customer by giving less importance to aged reviews.

With the technology currently available actually even a smart phone could be a card reader since it might equipped with a RFID or a magnetic stripe reader and, by developing a specific app, the restaurateur could easily and quickly transmit a transaction with the TripAdvisor ID of the customer.


Apart from the solution proposed, that is an example that stresses the importance, when defining a bigdata strategy, to identify first the information that is really meaningful (user, time, position) as well as having a Variety of sources in order to validate the reliability of the data. In the case of Tripadvisor is crucial to correlate the data coming from the restaurateurs with the reviews of the couple customer\user (together!!!).

Thinking about the definition of BigData by Gartner:

Bigdata is high-volume, -velocity and -variety information assets that demand
cost-effective, innovative forms of information processing for enhanced insight and decision making

So, Variety is one of the “Vs (Volume, Velocity and Variety) and the Volume of data is only what is up to the sea level of the iceberg called BigData.

Do you think that variety matter? I think yes, it matters!

If you think so as well and you have the opportunity to visit Italy I would you recommend (personal advice) to enjoy meals in restaurants where are shown logos such as the following and relying on the word of mouth, an evergreen.


They are not implementing Variety like TripAdvisor as well but reviews are made by professionals and they do not have social media and WEB2.0 visibility risks. Of course, I would recommend to find other sources (use variety!).

Have a nice journey and enjoy the meal!

Feelink – Feel & Think approach for doing life!


IT, I, WE: A Framework For Assessing the Consumer Behavior

How the consumer behaviours should be inferred? Or, is the brand proposition consistent with the targeted culture? These is the issues to address for defining a marketing strategy.

Along my MBA experience, I had the both the opportunity to study some insights regarding the behavior of a Chinese customer and living a cultural experience in China within an exchange program (Sun Yat-sen University). So, how is possible to create a framework that measure the consistency (correlation) between the culture and the relative inferences about the decision making process of the consumer? That was what stimulate my curiosity during my permanence in China so much that was also the question I have chosen as a final essay for the exchange [2]:

IT, I and WE

Briefly, in order to evaluate the consistency between the culture and the inferred consumer behaviours the idea is to use the IT, I and WE paradigm initially developed by Daniel Ofman [1] within the Core Qualities where are mainly three areas that represent three different ways to see the world and the reality:

  • IT: IT is the world of science, truth and objective reality as well as of tasks and goals to achieve.
  • I: I is the inner world and is about arts and also self-understanding, self-consciousness and self-awareness.
  • WE: the “sense of WE”. Solidarity, inclusion and sense of being part of a group\community are the main values for such a WE personality.

Since the IT, I and WE model by Daniel Ofman has been applied also for managing diversities and conflicts among people (See Blue, Green and Red model by Diversity Icebreaker) [3], why not applying it also for asessing cultures and consumer behaviors? Let’s see how.


The model IT, I and WE in the methodology proposed has been implemented as follow:

  1. First, identify the main topics that in general can assess a culture.
  2. For each topic, given 6 points available, distribute the points among the three areas IT, I and WE.
  3.  Sum all the points obtained respectively for the IT, I and WE areas.
  4. Collects all the findings that describe the decision making process of the customer.
  5. As it has been done for the culture at point 2, assign per each characteristic of the consumer behaviors 6 point distributed among the area IT, I and WE.
  6.  Sum the scores obtained respectively for the IT, I and WE areas regarding the consumer behaviour.


IT, I, WE: A Framework for Assessing the Consumer Behaviour (Infographic)

The result obtained from the analysis of the Chinese consumer behaviors has shown:

  • A consistent preference to the WE area: 45% and 38% from the Cultural and consumer behavior respectively. The result suits the high context mark of the Chinese culture where trust is based on relationships rather that tasks and facts.
  • Divergences between IT and I areas. In fact, with the selected items, the Chinese Culture has shown a preference to the IT area (35%) rather than to I (20%), while the Chinese behaviors has shown a balance between them, 25% and 37% respectively for the IT and the I.

For further details see the references.


  1.  Ofman Daniel. (2004). Core Qualities: a Gateway to Human Resources. Cyan Communications.
  2. Gruer Ivan. (2013). ” IT, I, WE: a framework for the consumer behaviour“. (Slideshare).