Wrapping Up

As Dr. Knapp and I are wrapping up in our final month of research, it is interesting to look back and see the progress of our project thus far. At first, we had such a broad topic and did not know what exactly our scope was in terms of what we want to zone in and really focus on. Through much research, we finally broke it down to looking into customer based research. Since the last post, the interviewers in which we spoke with really helped. It is very beneficial to have people in the industry have in depth conversations to us about what we are simply reading about. One very important aspect that I learned throughout this process is that no matter how many technological advances predictive analytics has come upon within the past years, this idea of looking at consumer behavior and making business decisions is something that will never die out. The whole idea of capturing customer information, reviewing trends and developing models that identify what a customer might like is something every organization needs to look at on some level in order to run a successful business. I am very  interested to see how the progress of this goes throughout the years.

Our next steps include putting our research together in a paper, as well as preparing our presentation for the final showcase. I can’t express how much this research has impacted me from teaching me various techniques on to conduct basis research to actually learning about the context itself. Being in a business based profession, it is interesting to see how customer analytics plays such a heavy role in the business world. Interviewing the professors as well as the people who work with a predictive analytical tool really showed me how useful this practice is and how widely used it is. I am excited to use this research to better brand myself and to be more knowledgeable about such an extensive topic. I am looking forward to see everyone else’s presentations as well!



Blog #2

As Dr. Knapp and I are both in roughly the third month of our research, we are finding out more in depth just exactly what data mining in customer analytics really is. In my last post I talk about how broad the topic is and how we want to define our scope. At first, we thought it would be interesting to focus on financial markets because it ties directly with my field and my future employment, however, upon our research we found that although financial markets is interesting, we thought our audience would find it more appealing to look into customer-based research in which companies makes business decisions based on data findings. We also decided it would be a good idea to interview many of the professors in both marketing and economics here at Pace because many of them have worked in these fields and have performed research similar to our topic.

Something that an interviewee told me that helped put this very broad topic into context was the well-known Beer and Diapers example. Researchers have found that when men go to stores to purchase diapers, they are also likely to buy beer simultaneously. From examining this, organizations have started to place their beer near the diapers in the supermarkets to push this predicted outcome. It goes to show that companies use research methods to make better business decisions that will ultimately create greater revenue. Many questions arise as we focus on these points during our research. For example, we want to look more into how companies use date on customers to make suggestions to them based on their interests. We want to explore the approach to the pool of data researchers go in to to extract the information about customers based on their previous purchases, location, interests, etc. I hope to work with Dr. Knapp in looking into our unanswered questions before this semester ends through more research from databases as well as interviews with professors and other specialists in marketing research that will be beneficial to our study.

Data Mining in Customer Analytics

Hello Everyone,

My name is Hannah Cherian and I am a senior double majoring in Information Systems and Quantitiative Business Analysis with a minor in Spanish. This year I have the privelage of working with Dr. Constance Knapp in our research program. We are focusing on Data Mining in Customer Analytics. This concept deals with looking at customer behavior or trends to help make key business decisions through predictive analytics. There is such a broad range of techniques when it comes to predictive analytics, some of which including satistics, modeling, and what will be the bulk of our research, data mining.

With such a broad topic in something that almost every major organization uses, Dr. Knapp and I decided to really focus on the financial markets and how they use predictive analytics. Our objective is to fully understand how companies utilize quantitative sets of data to predict what products to produce and how to advertise them. We also want to look into financial markets and also see how they predict stock investments in addition to their portfolio as a whole. We will research papers focusing specifically in large amounts of data and how exactly descriptive and decision models are used to reach optimization in predictive analytics for these companies.