What Are Examples of Data Analysis Leading to Significant Merchandising Strategy Changes?
Retailing Central
What Are Examples of Data Analysis Leading to Significant Merchandising Strategy Changes?
In the ever-evolving world of retail, data analysis has become a cornerstone for strategic decision-making. We reached out to Merchandising Managers and Directors to share instances where data reshaped their approach. From leveraging seasonal sales trends to adapting to eco-friendly product demand, discover the four pivotal experiences that transformed their merchandising strategies.
- Seasonal Sales Trends Inform Strategy
- Data-Driven E-Store Assortment Planning
- Protein Flavor Selection Based on Sales Data
- Eco-Friendly Product Demand Shapes Merchandising
Seasonal Sales Trends Inform Strategy
Through detailed data analysis of our sales trends, we discovered a pattern indicating that certain products experienced higher demand during particular seasons. Armed with this insight, we revamped our merchandising strategy to emphasize these products more prominently during their peak seasons. By leveraging targeted marketing campaigns and optimizing product placement both online and in-store, we were able to capitalize on these trends and significantly boost sales. Additionally, this approach enhanced customer satisfaction by ensuring that the most sought-after items were readily available when customers were most likely to purchase them. Overall, data-driven decision-making played a crucial role in optimizing our merchandising strategy and driving tangible results for our business.
Data-Driven E-Store Assortment Planning
We use data analytics on an ongoing basis to inform the majority of our decisions regarding merchandising. One specific area where we found it had a significant impact was by utilizing sales data to plan the assortment on the e-store. Basically, what this means is that we look at the trends of which products are being sold and, based on this, choose to highlight certain products on our platform or promote other items at a discounted rate. This way, we can influence the sale of particular items, as well as better control existing stock and production schedules.
Protein Flavor Selection Based on Sales Data
Having owned numerous retail stores across various industries, one particular scenario stands out. In the protein category, brands are coming out with very wild flavors, yet our data analysis showed that 85% of purchases were for chocolate, vanilla, and strawberry. So, we changed our merchandising strategy by eliminating the wild protein flavors and replacing them with more of the top brands. Then, we added products that could be used with your standard chocolate and vanilla flavors to provide a more unique taste experience. It was one of the best decisions we made and helped us create a private-label brand that would further increase our profits.
Eco-Friendly Product Demand Shapes Merchandising
An instance where data analysis led to a significant change in our merchandising strategy involves the use of sales and customer behavior data to identify underperforming products and high-demand trends. By analyzing sales data, we discovered that eco-friendly products are outselling traditional alternatives. This led to a strategic shift toward stocking more sustainable goods, adjusting product placements to highlight eco-friendly options, and tailoring marketing messages to emphasize sustainability, resulting in increased sales and customer satisfaction.
