How can you use retail sales data to understand the impact of seasonality on performance?

1 What is seasonality and why does it matter?

Seasonality is the variation in sales performance that occurs due to changes in weather, holidays, events, consumer behavior, or other factors that influence customer demand over time. This can affect retail sales by increasing or decreasing overall sales volume or revenue for a given period, changing the sales mix, affecting inventory turnover, and influencing pricing strategy. Therefore, understanding seasonality is important for merchandisers as it helps them plan and adjust their merchandising activities to expected demand and supply conditions. For example, analyzing seasonal trends can enable them to forecast sales and inventory needs for different periods and products, allocate their budget and resources to the most profitable products or categories, design and implement effective promotional campaigns or markdowns to stimulate sales or clear excess inventory, and monitor and evaluate their sales performance while identifying opportunities or challenges.

2 How to use retail sales data to understand seasonality?

To understand seasonality from retail sales data, it is essential to collect and organize the data in a way that allows comparison and contrast of sales performance across different time periods, products, categories, and markets. Data sources such as point-of-sale (POS) data, inventory data, pricing data, and external data can be used to gain insight. Descriptive analysis, trend analysis, seasonal adjustment, and decomposition analysis are some of the methods used to analyze the data. Descriptive analysis summarizes and presents the data using tables, charts, or graphs; trend analysis identifies and measures the direction and magnitude of sales changes over time; seasonal adjustment removes the seasonal effects from the data; and decomposition analysis breaks down the data into components such as trend, seasonality, cyclical, and irregular.

3 How to visualize and report your seasonal insights?

To effectively visualize and report seasonal insights, it is important to choose and create appropriate data visualizations and reports that clearly communicate your key findings and recommendations. Various tools and techniques can be used to achieve this, such as dashboards that display KPIs and metrics with interactive visualizations such as line charts, bar charts, pie charts, heat maps, or gauges. Reports can provide a detailed analysis of the data using descriptive and explanatory visualizations such as tables, histograms, box plots, scatter plots, or correlation matrices. Stories can tell a compelling narrative of the data using sequential and contextual visualizations like infographics, timelines, maps, or icons. When creating these visualizations and reports, there are some best practices to follow such as defining your purpose and audience to tailor your message and format accordingly. Additionally, clear and consistent labels, titles, legends, and colors should be used to make the visualizations easy to understand and compare. Appropriate scales, axes, and ranges should be used to show relevant and accurate data. Contrast, emphasis, and annotations can be used to highlight important or surprising data points or patterns. Lastly, simple concise language should be used while avoiding jargon or technical terms.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?