Archive | September 15, 2013

The Power of Customer Data

US-based retailer Target was one of the first companies that used customer purchase data in order to strategically influence buying behavior – with major consequences for their PR department. The New York Times article “How Companies Learn Your Secrets” [1] describes the developments of the now world-famous case in detail: How the management decided to target pregnant women with customized advertising, how statisticians developed a model that accurately predicted if a customer was pregnant, and how an angry father of a high school girl filed a complaint about the coupons for baby clothes that his daughter received, just to learn that she was actually pregnant.

Surely, the short-term consequences for Target’s image were disastrous. Customers felt that they had been spied on and women were shocked to find out that a supermarket knew about their pregnancy before they did themselves. However, I believe that the strategy itself was an ingenious step to take which turned out to be highly profitable. That is because it was based on an important theory of human habits: Usually, we follow our daily routines such as grocery shopping without thinking about our choices and alternatives which makes it hard for companies to intervene and get us to divert from our habits. However, these habits become flexible when we go through major life events, such as a pregnancy or a change of jobs. Target recognized this and made pregnant women build new habits of buying child-related items at their store by offering coupons at an early stage of the pregnancy. When Target was forced to see that customers do not like to feel spied on, they combined their pregnancy-related coupons with unrelated items to make their customers think that the advertisement was sent to them randomly. The result of this campaign: an increase in revenues of 52% between 2002 and 2010 [1].

This case shows that customer data provides a great opportunity for retailers to intervene at important points in their clients’ lives and make sure to influence new shopping habits accordingly. What if started tracking customers who just moved out of their parents’ places to start university with a simple algorithm that analyzes age, address changes (close to a university?), and purchases? With the right coupons and offers, these students might be inclined to buy their study books on Amazon – and not only their first books, but all of them.

I believe that more and more companies will recognize this opportunity in the future and I am wondering how consumers will react to it – after all, would you feel comfortable being analyzed like that?


LinkedIn changes its privacy policy to open up for teenagers

Most of you have heard of LinkedIn and belong probably to the 4 million registered users LinkedIn has in the Netherlands [1]. Recently LinkedIn changed its privacy policy in the Netherlands. The age limit is lowered from 18 to 16 years. This change opens op LinkedIn for teenagers, in line with the vision of LinkedIn to focus more on teenagers and students. In America the age limit is even lowered from 13 to 12, which could also happen in the nearby future in the Netherlands [2].

LinkedIn is trying to encourage these teenagers and students to sign up to LinkedIn, so that the can prepare themselves better towards a future job, an internship or more in general their carrier. These profiles are slightly different in a way that it is not possible to get a hit on their profile picture, function or date of birth through Google. A second change is that universities and other educational institutes are able to create pages, so that teenagers are more likely to use LinkedIn in the search for a school or university [2].

In my eyes the strength of LinkedIn always has been the professional attitude. Professionals can search for a job and expand their network, as well as other professionals try to find the right person for their (future) job application. There was no room for advertisements, spam or other unwanted contact [2]. LinkedIn was in my eyes the professional step that you made when you graduated high school and started you further career on a university.

With the change that is recently made, I can see troubles for LinkedIn. In my opinion, letting teenagers register on LinkedIn, the professional attitude of the site diminishes. It could be possible that the true professionals can have problems with finding the right person. Lowering the age limit of LinkedIn could also cause it to be a second Facebook in the future. The separation between the ‘work side’ and the ‘private side’ was in my eyes the strength of LinkedIn. I think teenagers from 16 till 18 (or maybe in the future even from 12 onwards) are not the ones who need to expand their network and look for a job on LinkedIn at that age. I think they are not of an added value, and could possibly diminish LinkedIns value by not being able to handle the more professional guidelines of LinkedIn that they are not familiar with at that age. This could lead to a switch of professionals to other sites as for example, which lowers the truly important network effect of LinkedIn of connecting many professionals.[2].

[1] Jeffrey Weller,, 15 september 2013.

[2] Dennis Mons,, 15 september 2013

Technology of the Week – Team 5 – Netflix and Amazon

In our Technology of the Week assignment we decided to compare the business models of Netflix and Amazon. Netflix is now the biggest online movie rental company, and Amazon the biggest online bookseller. They both made this happen through the smart use of information systems in their business model. 

Both industries at the time were vulnerable for new entrants according to the 3 conditions of Granados et. al.(2008), and both Netflix and Amazon were able to tap in the long tail of the market. This was only possible because of the up rise of internet. They were the first so succeed in both their endeavors which made it able for them create network effects which added to their success.

Their business models made smart use of the databases they created over time. They both ask their customers to give reviews of the movies or books, and with that data they are able to link the interests of those customers and recommend new products which they might like. The study of Chen et al.(2011) calls this observational learning.

In the future both companies have opportunities and threats that have to be taken in account. Amazon can focus more on their ability to predict demand through their database, and Netflix could become the new way of watching television, with everything ‘on-demand’.  A big weakness for both companies is that they do not make the content they sell. Netflix is changing this by making its own shows and Amazon by publishing their own books, but that content will always be a small part of their total collection.

With E-commerce still being a ‘young’ subject however we can’t be entirely sure which business models are the best practices. We just  have to wait and see (or read).

Chen, Y., Wang, Q., and Xie, J. (2011). Online Social Interactions: A Natural Experiment on Word of Mouth versus Observational Learning. Journal of Marketing Research 48(2) 238-254.


Granados, N., Kauffman, R.J., and King, B, (2008), How Has Electronic Travel Distribution Been Transformed? A Test of the Theory of Newly-Vulnerable Markets. Journal of Management Information Systems 25(2) 73-96.


Can social media monitoring prevent suicide?


It is not always easy to predict the effects of social media, especially the negative ones. 33% of all teenagers have been the victim of cyberbullying[1], and sometimes cyberbullying plays a big part in suicides. After recent suicides the Glendale Unified School District in Los Angeles has hired the company Geo Listening to monitor thousands of its students’ online activities. Chris Frydrych, the CEO of Geo Listening says that a probable new suicide has been prevented because of their monitoring![2]

I believe this shows how much potential the monitoring of social media has. We have already seen in class that firm equity value can be predicted by social media and social media predictions of elections have proven to be the most accurate.[3] And now we try to predict individual behavior based on social media. There is the obvious privacy concern, but Geo Listening only monitors public posts and by now users of social media should know information you post on the internet is accessible to the public. Monitoring social media may be able to disrupt not only cyberbullying, but also help depressed students whose only outlet is on the internet.

There are already a lot of social media monitoring services out there, most of them available as a service to companies. But CEO Listening provides a social network monitoring service specialized in students, this makes me wonder what other niche markets are still out there to exploit. Is it possible to predict traffic jams and the duration and intensity of the rush hour based on social media? What else do you think can be predicted because of social media? And would you care if the university was monitoring your facebook and twitter?






Tech of the week – Team 1 – SaaS vs SoP

Our technology of the week revolves around two Innovative business models: Software as a Service (SaaS) and Software on Premise (SoP).

A precursor of SaaS was used by IBM in the 1960’s to rent out its mainframe computers. From here out it evolved together with the advent of the internet into SaaS. Currently SaaS evolved into a multitude of forms. Mnay evolved into a subscription model, with different pricing models, hosting options and even different products (software, storage, entertainment). Examples of SaaS are: Office 365 and Adobe.

Online application markets are an evolution from brick and mortar shops. With the coming of the internet some changes in the distribution models of software companies were bound to happen. Especially with software which can be digitally distributed the advantages brick and mortar companies cannot compete with advantages of online application markets for instance: the reduced search costs. The most popular app stores are the IOS App Store and the Android Live Store.

SaaS vs SoP
As a consumer, as well as a distributor, factors such as Security, Ownership, Costs are important to consider and each model utilizes these factors differently, with both having their pros and cons.

Both models differ greatly from each other. When applying SaaS, the end user is basically ‘renting’ the software and is hosted off-premise. SoP on the other hand uses online application markets, where software is bought, owned and kept on-premise. This one difference already has multiple implications for both consumer and business.

SaaS allows a consumer to lower the barrier of entry and remove the initial purchase costs of the consumer. Security-wise, however, the data is managed on a distant server and is thus exposed to digital theft.
SoP, on the other hand, requires a high upfront costs as well, but security is within the consumer own hands.

From a distributer point of view, SaaS gives the software vendor a lot of responsibiliy to protect its client data. It also cuts up and divide the incoming cash flows, since smaller amounts will be exercised over a longer period of time.

These are minor examples of the differences and how they influence multiple parties. All factors that deserve consideration are being evaluated and compared in our report,  from both a consumer perspective and a business/distribution perspective.

Technology of the Week – Apple Touch ID vs. Intel IPT (Team 2)

Since more and more commerce and financial activities are performed online, the demand of new technologies that would aid to secure confidential digital information is growing.

Our report analyses two relatively new technologies:

– Apple Touch ID (a fingerprint scanner);
– Intel Identity Protection Technology (two-factor authentication technology).

Apple Touch ID          

The iPhone 5S is the first phone with a built in sophisticated fingerprint scanner. Since Apple has taken over a rather large part of the market, it is also the first time that a fingerprint scanner becomes widely available to the mass market.

+ Time saving;

+ Hardware based technology;

+ Extra Safety;

+ Multitude of opportunities in the market;

–  Limited performance;

–  Limited capabilities for the time being.

Intel Information Protection Technology

Intel Information Protection Technology (Intel IPT) is a two-factor authentication which adds an extra layer of security to the identification process. Intel’s IPT uses CPU as authenticator which allows tying a physical PC or laptop to an online account. An algorithm in CPU generates a six-digit code every 30 seconds.

+ Embedded in computer;

+ Hardware-based technology;

+ Automated dynamic password;

+ Secure VPN login;

+ Secure money transfers;

+ No security questions, no password changes;

–  Limited compatibility for the time being;

–  Limited to support digital environment.

Both technologies, if implemented on a large scale, would have effects for many markets that rely on online interaction. Personal finance services, online payment and e-commerce are all sectors that could benefit from better identification systems. Also, transactions would be safer, encouraging more people to trade, do shopping and conduct business over the internet. Both technologies might in fact be able to reach the status of business process standard being an integral part in securely connecting businesses and consumers around the world.

Technology of the Week (team 3): Netflix & Blendle

New applications

Netflix has been recently introduced in the Netherlands. For only 7.99 euros per month, Dutch subscribers can have online access to thousands of movies and TV-series at Netflix, using practically every device with an Internet connection.

Blendle, a new online newspaper/magazine platform, has been announced by its developers to enter the Dutch market soon. Blendle is developing a platform where customers can buy single digital articles from different newspapers and magazines. With article prices ranging from 10 to 89 euro cents, it provides a way to compose a personal set of articles of high quality journalism.

Subscription-based vs fee-for-service based

As stated Netflix uses the subscription-based business model, which means that users are charged a fixed monthly fee. Blendle, on the other hand makes use of the fee-for-service-based model. This model charges a fee for every service obtained and contains a pay-as-you-go system.

Recommendation systems

A similarity between the companies is making use of a recommendations system, which can be seen as a competitive advantage for both. Netflix is able to provide its customers with personal recommendations for movies and series through the use of advanced algorithms and collecting big data. Blendle on the other hand will construct a recommendation system with the use of social media. Blendle will suggest articles based on recommendations of your social network.

Uniqueness of Netflix and Blendle

Netflix and Blendle deal with many competitors offering similar services. However, both of the companies are quit unique for their kind. Netflix is the only company offering such a large amount of series and movies for a very low monthly fee without any advertisements. As for Blendle it is expected to be the only application offering a high volume of digital newspapers and magazines in combination with the ability to buy articles per unit.