WIMTACH’s Workshop Series: The Retail Analytics session proves to be useful in teaching industry professionals about data analysis

Competition for small and medium-sized retail businesses is steep. To be competitive, they must adapt to the customer’s growing and evolving needs. In order for any retail business to survive and grow, it is crucial to understand its customers, optimize marketing strategies, manage operations, and manage supply chain processes. Digital technologies and analytics are necessary today to achieve these goals. Retailers can make better, faster, real-time decisions with the integration of analytics and Artificial Intelligence (AI). To remain competitive in the market, retailers should take advantage of open source technology’s emergence and rapid growth. In the Centennial College Retail Analytics using Python workshop, Sreekumar Pillai, a CEDA Project Manager at WIMTACH, aims to arm industry professionals with the skills to efficiently use this technology.

During a recent workshop session, Sreekumar outlined how organizations require monitoring on different levels. “Approach and monitor factors that are crucial to your business,” he emphasized. Sreekumar also elaborated that it is essential to isolate the primary metrics of your business to improve your retail operation. However, monitoring all Key Performance Indicators (KPIs) can be conducted from a short list of access points, making the process much easier. These access points can include the Point of Sale (POS) for a business, entrance camera, restocking schedule, and more. Moreover, new technology like sensors are becoming much more popular now and will be very beneficial in the quick and adaptive monitoring of KPIs.

All attendees paid thorough attention throughout the workshop, but at one moment, one of the participants asked, “What would be an example of a KPI we can measure in the field?” In his reply, Sreekumar stated that one could measure many different KPIs, from visitor numbers to customer interest for different brands. He elaborated that since a retail organization needs to measure multiple KPIs simultaneously and conduct this process daily, it would be more beneficial to utilize AI-enabled devices. These devices will allow the organization to record and interpret the data on-site to have live access to all the metrics already presented in an understandable fashion. Participants of the workshop made many notes when Sreekumar started elaborating on how you can monetize retail analytics. Sreekumar said that retail organizations seek specialists who can benefit and improve their performance via data analysis.

Before starting the hands-on section of the workshop, Sreekumar sent all the participants a set of codes and data samples to be used for practice. Later, Sreekumar assisted participants in using freely accessible open-source Python tools to analyze retail data and understand the business performance.

After listening to instructions, participants would code different Python scripts in real life, enabling Sreekumar to provide feedback on the spot. To begin the activity, Sreekumar presented a prepared code sequence so the participants could understand the final goal of their work. This code enabled him to calculate and interpret data from simulated KPIs a company would typically monitor. The activity continued with participants working on creating the same code to perform analytical tasks. The main objective was to ensure that everyone had a solid understanding of how they would implement digital technology to measure and interpret data. The core idea behind this activity was to confirm that all the participants had required knowledge on analyzing, interpreting and understanding the data they were using.

The lecture went on with a presentation of several real-life cases of Python used in retail analytics. This part of the workshop enabled all participants to see the process and learn about potential issues organizations can encounter. Sreekumar also presented some independent learning resources like Google Colaboratory, an online platform created to run Python code for professional and educational purposes. He showed how it can be used with Python and how the participants could use the tool outside the workshop to practice their Python and retail analytics knowledge.

In the end, Sreekumar mentioned some freely accessible data sources, including those from the open data initiative, that would be integrated into the internal data to generate more meaningful insights that support the organization. “Retail Analytics will be a valuable skill that will benefit your professional work in any kind of retail.,” he concluded.

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