Cloud isn’t just for geeks! Business students and entrepreneurs need to understand it’s potential impact as well. Find out how student entrepreneurs at Western University imagined Azure could help increase sales at a retail store.
Founders Network, the largest business technology club at Western University hosted a case competition. Their challenge: to help a retail store increase sales. Microsoft Student Partner, Zain Hemani, did a short presentation on the cloud and Azure Machine Learning to help the students understand how the cloud can fit into a solution.
180 students were challenged to come up with a proposal to increase sales in a retail store given a fixed budget. We spoke with the top three teams to find out more about their winning ideas and to find out how they as business students saw a technology like Azure affecting their future.
Why does a business student care about Azure?
We asked the winning team of Kelly He and Laban Lin why business students need to learn about technologies such as Azure.
Kelly: In regards to the case, knowledge of Microsoft’s cloud platform was definitely crucial for success. Having a better understanding of Azure’s capabilities allowed us to utilize it in the most effective way to bring feasible solutions to the issues on hand. In a broader context, since business and technology are now so intertwined, understanding how to implement the benefits of new innovations will certainly help businesses profit. Although I am pursuing future studies in business, I definitely recognize the importance of learning about technology and how it can be used across various areas.
Lin: We also considered other ways in which Azure could be helpful – for example, storing the POS data on Azure’s infrastructure, analyzing Twitter events with Stream Analytics and even using Azure’s CDN services to speed up the retail website loading times. If you pour over the features that Azure offers, I think you’ll find an extraordinary number of ways it can help any company, and it’s definitely more than just the machine learning we applied.
How can Azure Machine Learning help retail marketing?
Here’s how the top teams envisioned Azure Machine learning as a part of their solutions.
First place: Kelly He and Laban Lin
Our solution relies on the analysis of sales using Azure machine learning to identify trends. Based on those trends create suitable ad campaigns and use Azure Machine Learning to analyze the success of those ads. Over time this allows the company to create ads tailored to consumers on each outlet (Facebook, Twitter, Pinterest, etc..). what makes our proposal unique is it recognizes the applications of cloud computing, particularly in data mining. Retail stores sit on a mountain of data, and analyzing past transactions gives us a powerful understanding of what customers want. It can’t reliably predict future trends, but in a highly automated system, we can update inventories reasonably quickly to adapt to consumer preferences. Now, the real breakthrough is in the scale of Azure – because we can buy as much processing power as we want, we can almost mine data in real time. That means we can launch ad campaigns based on what the data tells us customers want, and analyze critical factors daily or weekly to see how well those ads are being received. In this way, we leverage the existing capabilities offered to us as a SaaS and use that to propel a store into the modern age of data analytics.
Second place: Pallav Bhavsar, Veronica Pang, Jeet Chakrabarty, and Alexander Li
We came up with a marketing campaign that targets the Do it Yourself retail store shopper. The target demographic would hear about an idea on YouTube, then from the video to a Pinterest wall of ideas, and once they have selected a project are brought back to YouTube to find a retail store video. Click through rates would be tracked and Twitter would be used to submit new DIY project ideas. Azure would be used to track parameters to measure campaign effectiveness including hashtags, mentions, follows, increase in views, and product click through rates.
Third place: Cathy Chen, Joanna Fu, Shirley Tan and Bobby Tzonev
We came up with the idea of creating a mobile app customers use within the store. The user can provide their gender and store area of interest. IBeacon devices (Bluetooth devices) in the store send signals to the phones as customers shop. The beacons track where customers go and can target shoppers with promotions. Machine learning on Azure could analyze the data collected to optimize inventory levels, and identify purchase patterns in the store.
Anyone can explore Azure for free
Whether you are inspired by the student suggestions above, or by the somewhat famous beer and diapers data mining story from 1992. You may want to explore cloud technology first hand to see what it can do for you: