Adjusting prices in real-time based on factors such as demand, seasonality, and competitor pricing is known as dynamic pricing. Leveraging data analytics and algorithms enables you to optimise prices to maximise revenue and capitalise on market fluctuations.
For instance, a commercial farmer dealing with perishable crops like strawberries or tomatoes might implement dynamic pricing during peak harvest times when supply is abundant and demand might not match it. They could adjust prices based on factors like inventory levels, demand forecasts, and competitor pricing to ensure they sell their produce efficiently and avoid waste.
During slower seasons or when there's excess inventory, offering targeted discounts or promotions could help stimulate demand and move inventory before it spoils, thereby preventing potential losses and improving overall profitability. This strategy allows farmers to manage their inventory effectively while maximising revenue throughout the year.
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