3 Tips for Retailers Navigating the Holiday Shopping Season
This holiday season, businesses are bracing for the unknown.
“The economic fallout from the coronavirus pandemic has made it difficult for sales teams to set forecasts — at the same time they’re under increased pressure to hit their targets.” –Harvard Business Review
This year’s unique economic challenges have left many businesses unsure of how to approach the upcoming holiday shopping season. Businesses can prepare by creating a well-crafted and accurate retail forecast to anticipate many consumer demand scenarios.
“Demand forecasting in retail is the act of using data and insights to predict how much of a specific product or service customers will want to purchase during a defined period of time. This method of predictive analytics helps retailers understand how much stock to have on hand at a given time,” – StitchLabs.
Demand forecasting combines the business’s historical transactions with market and industry data. Several different forecasting methods can be applied to forecast demand, the two most popular being qualitative and time-series.
Qualitative forecasts combine historical data analysis, research, and expert opinion. These forecasts offer the best results when a business expects to see a rise in revenue.
Time series forecasts are typically more involved and work to identify and extrapolate trends from historical cash data. These forecasts are better suited for seasonal businesses that see cyclical spikes in demand, like the retail industry.
Discover which forecast is best for your organization by reading our blog, Forecasting Techniques Overview, which summarizes four popular forecasting approaches.
Retail forecasts predict consumer behavior and product popularity to help businesses anticipate demand. A well-developed forecast can help businesses ensure that they are making an appropriate investment in inventory.
Spending too much money on inventory would tie up the organization’s working capital, ultimately hinder spending on expansion, and reduce the business’s ability to create a cash cushion.
Spending too little inventory would leave the business at risk of not being able to meet customer demand, losing business, and driving customers to competitors.
Retail forecasting has never been more important, as many businesses operate on a razor-thin error margin. COVID-19 has presented business owners with a myriad of new challenges. As a result, there is little historical data to support this year’s forecasts, leaving them more susceptible to error.
How Can Businesses Increase Their Forecast’s Accuracy?
- Start with clean and aggregated data
- Regularly adjust forecasts
- Leverage automation technology
Start with Good Data
Having easy access to high-quality, real-time cash data has become crucial to maintaining a high level of forecast accuracy. When it comes to retail forecasting the more data, the better. When combined with growth rates and other external metrics, the business’s historical data can be used as a benchmark for future performance. Properly tracking and storing transactional data ensures that the business has the data it needs to create a forecast and that all members of the business are working from the same data set.
Regularly Adjust Forecasts
It is important to think of a retail forecast as a living document, as regular adjustments are necessary to successfully anticipate demand. This year, the lack of relevant historical data has forced businesses to rely more heavily on actual, real-time data vs predictions.
Supplementing forecasts with current sales metrics allows businesses to increase the accuracy of their projections. For example, while it may have been difficult to anticipate Black Friday sales this year, businesses will be able to use their 2020 Black Friday data to better predict the level of demand in December.
Leverage Automation Technology
Automation can increase the efficiency and accuracy of forecasting efforts. Artificial intelligence (AI) and machine learning algorithms are being leveraged to sort through vast amounts of data to quickly identify relevant patterns. These algorithms work to reduce the level of human error that results from the manual aspects of creating and maintaining a cash forecast. By allowing automation technology to do the heavy lifting, you can spend your valuable time and expertise analyzing forecast results and applying them to the business. For example, if the projection shows that you will have excess inventory, analysts can then spend their time re-allocating budget to the marketing department to promote the surplus inventory.
Looking to supercharge your retail forecasting efforts with AI and automation technology?
Trovata Platform makes it easy for businesses to automate cash workflows like cash reporting, analysis, and cash forecasting. By bridging the gap between banks and accounting systems, Trovata is helping companies gain powerful insights into their cash flows that drive better and quicker business decisions. With our direct API connections to most major banks, new clients can get set up in just a few hours.