Last updated on January 20th, 2022 at 10:01 am
With the increased competition and customer demands, retailers have to toil hard for merchandise planning. Retailers are facing challenges in stocking their stores according to customer demands. Data analytics is used in the retail industry to know more about customers. Data analytics is used for numerous other processes in the retail industry. One such process is assortment planning. With assortment planning for numerous stores, a retail agency can boost its ROI (Return on Investment). Retailers that know data science will be in huge demand for better assortment planning and increased customer conversions. Read on to know more about the role of data analytics for better assortment planning in the retail industry.
Understanding assortment planning
With assortment planning, a store decides the ideal store layout and visual merchandising that can attract customers. Product placements in a store are decided via assortment planning to maximise conversions. Retail companies usually conduct assortment planning at fixed intervals like weekly, monthly, or daily. Assortment planning decides which products should be highlighted at a given time. For example, a store can highlight its umbrellas and raincoats during the rainy season. The store can highlight its sweaters during the winter season.
If a retail company has multiple stores, assortment planning can differ for each store. Assortment planning is also done based on the preferences of the local or daily customers. Many young retailers are looking for data analytics courses online to get a raise by offering assortment planning services to their stores.
What makes assortment analytics important?
It is hard to determine the preferences of customers and perfect product placements manually. It is why you need data analytics to fine-tune assortment planning. A retail company can know about the driving factors that compel the customers to make a purchase. The driving factors can then be implemented in physical stores to boost sales. The processes involved in assortment planning are as follows:
- Customer/sales data is collected and cleaned for advanced analytics. Redundancies in the customer data are removed for better assortment planning.
- Walk-in rates are determined via high-end data analytics. Sensors and cameras are used to determine how many pedestrians passed through your shop and how many entered. Based on the walk-in rate, you can modify product placements.
- Assortment analytics can help retailers in identifying customer loyalty. You can know which products are preferred by customers again and again.
- You can rank products based on their sales with assortment analytics. Retail companies use data analytics to identify which products are not generating substantial revenue.
- Assortment analytics also includes identifying the space productivity index of different stores. The space productivity index helps in knowing how much selling space is occupied by different products.
How to learn data analytics for better assortment planning?
Due to the numerous benefits of assortment analytics, retail firms are recruiting professionals who have a data analytics certification. To learn more about assortment analytics, you can go for the PG Program in Data Analytics & Machine Learning offered by Imarticus Learning. This course will cover all aspects of data learning along with 25 real-world projects. Various programming languages like SQL, R, and Python will be covered in this data analytics course. Imarticus is well-known in India for its data/business analytics courses that follow an industry-designed curriculum. At the end of the data analytics course, Imarticus will help you in getting a job offer.
Conclusion
With better assortment planning, stores can maximise their revenue. Assortment analytics can be the key to determine customer demands and optimise stores accordingly. The online course of Imarticus can make you job-ready by teaching several data analytics skills. Start learning assortment planning now!
