Why Traditional Methods Don't Work Anymore

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Retail is constantly changing. With the advent of online stores and mobile apps, customers have become more demanding and informed. Traditional business methods no longer provide the necessary flexibility and speed of response to market changes. According to a report by Deloitte, 62% of retailers admit that ineffective data management prevents them from making informed business decisions.

Big Data: The Key to Understanding the Client
Using big data allows you to collect and analyze huge amounts of information about customer behavior. This includes not only purchases and returns, but also the time of store visits, preferred communication chinese overseas australia data channels, and responses to marketing campaigns. Data analytics helps in:

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Forecasting demand and optimizing inventory.
Personalization of marketing offers.
Improving customer experience.
Demand forecasting and inventory management
Unsold goods are frozen funds. On the other hand, the absence of popular goods leads to loss of customers. Big data allows you to accurately forecast demand, taking into account seasonality, trends and even weather conditions. For example, Walmart uses analytical models to optimize stocks, which allowed them to reduce storage costs by 10%.

Marketing personalization
Modern shoppers expect a personalized approach. According to Epsilon, 80% of customers are more likely to make a purchase if a brand offers a personalized experience. Big data analytics helps segment audiences and create targeted offers, which increases conversion and average check.

Data-driven process automation
Routine operations take a lot of time and resources. Implementing automation based on data analytics allows you to optimize the following processes:

Managing prices and discounts.
Monitoring the market and competitors.
Manage employees and schedules.
For example, the Magnit chain of stores implemented an automatic price management system, which led to an increase in marginality by 5% and reduced the time for recalculating prices by 80%.

Cases of successful use of big data in retail
Let's look at a few examples of how major market players use big data to optimize their operations.