There are a lot of group projects involved in the M.S. in Commerce Program, regardless of the track you are in. Being a Spanish major as an undergrad, I wasn’t used to working in groups; my workload back then was more along the lines of reading a book and analyzing it in an essay. That being said, learning to work in a team is by far one of the most important skills I’ve honed in these past few months and a topic that’s come up in every interview I’ve had. So without further ado, I’m going to talk about some of the projects Business Analytics (BA) students have been busy working on this semester in some of the classes that we took:
Advanced Quantitative Analysis: One major project this semester in this class was analyzing data from Hilton Worldwide, that’s right, the major hotel chain. We were given some of the company’s real data and were in charge of cleaning it up and getting it ready for analysis—changing variables, combining variables, you name it. Then comes the fun part—we were on our own to run any sort of tests we wanted, in SPSS, SAS or R, in order to glean valuable insights. We conducted a variety of tests such as one-way ANOVAs, linear regressions, clustering, and principal component analyses. After we found some interesting trends, we were in charge of creating tangible and actionable recommendations to present. We compiled everything in a slide deck, which was easy, given the variety of beautiful properties Hilton owns to use as backgrounds, and all the groups presented to Richard Netemeyer, Ralph A. Beeton Professor of Free Enterprise, and Doctor Dobolyi, post doc at McIntire Center for Business Analytics. Then, the eight slide decks prepared by the groups were sent to Hilton representatives, who chose the four they wanted to see presented. Finally, the four winning groups presented their analysis, findings, and recommendations to the VP of Human Resources and the VP of Total Rewards and HR Analytics, to name a few.
Digital Analytics: The first project in this class is social media-related. Falling in line with one of the big trends in data, we analyzed Twitter accounts and tweets. Each group picked a handful of accounts, the company they wanted to focus on, as well as a few competitors and then keywords related to those accounts. For example, one group analyzed Chipotle, Qdoba, and California Tortilla using keywords like “chipotle” and “burrito.” Then after collecting tweets for about a month, we used Tableau to analyze the tweets using graphs and created our own dashboards, which were used to visually support all of our findings. Then we developed specific recommendations to improve the companies’ social media presence, targeting metrics like engagement, impressions, and influencers. Finally, all the groups presented to the class and Professor Kitchens, who then voted for one group to present to the board of directors of the McIntire Center for Business Analytics at the Analytics Spring Symposium Friday, April 29.
The second project we’ve been working on in Digital Analytics is basically a real-life consulting project. Each group was partnered with one of three local businesses—Lumi Juice, Mudhouse Coffee, or King Family Vineyards—and given an issue to address such as online sales, wedding events, or driving online subscriptions (my group was assigned brand and tastings for King Family). We met with our clients to learn about their background and how the business works and then wrote a report outlining their value proposition, target consumer audience, and revenue sources. Then came the part where we got our hands dirty; we initially analyzed the website traffic and user demographics through Google Analytics after being given access to the company’s website. After determining which pages received the most web traffic, users’ geographic location and demographic information, and whether they used a desktop computer or mobile phone, we prepared our second presentation. This presentation included trends and recommendations for how to improve the website and drive traffic.
Finally, with a budget of $100 provided by the Center for Business Analytics, we all ran paid search advertisements using Google AdWords (you know, those ads that pop up on the top of the page after you search for something). We mocked up what we wanted the ad copies to look like, including links and descriptions; bid on the different keywords we thought users would be searching; and at the end of the week, analyzed the campaign using metrics like impressions, conversions, and CTR and CPC (click-through rate and cost per click). In the end, each group presented the outcome of their campaign to their clients (this included actual revenue that we generated through wine club and juice memberships for my group). It was great to see the actual value we could drive for businesses, and it’s pretty cool to see all of the changes we made to the websites come to life, such as adding new tabs or rearranging pictures.
Customer Analytics: March was a crazy month, and not just because we were trying to get reacquainted with school after spring break. As many sports fans know, the month was consumed by March Madness and college basketball teams competing for their chance to advance in the big dance. In our customer analytics class, each group was given a March Madness region to focus on—South, East, West, and Midwest—and all the 16 teams that competed in that region. We utilized Klear, a social intelligence platform that both the Marketing & Management and BA Tracks used this semester, to monitor the social media accounts of all the teams. We input their Instagram, Facebook, and Twitter accounts, and Klear collected the data related to posts, content, demographics, and new fans generated throughout the tournament. Each group then analyzed all the data to find out best social media practices for athletics departments in relation to March Madness. Some groups even ran regressions to find out how many new fans a team gained on social media for every round they advanced in the tournament. We found out which types of posts got the most engagement from fans (usually content that shows the players as real people), that Instagram is the best platform to leverage, and that the bigger teams weren’t always the best performing.
One of the reasons I have liked Business Analytics so much throughout this year is being able to see the value in the projects we’ve been doing. We’re generating real revenue for companies and they are actually taking our recommendations to heart, which is something that you’re not used to as a 20-something. We’ve had the opportunity to present to business owners, vice presidents of major companies, and C-level executives, and the confidence and sense of accomplishment are tremendous. I feel as though I’ve gotten a real look into the types of projects I’ll be faced with in the future, and I know that I am ready for whatever comes next!
-Written by Jordan Smith