Data analytics is now being applied at every step of the retail process – right from predicting the popular products to identifying the customers who are likely to be interested in these products and what to sell them next.
Generating Recommendations: Based on a customer’s purchase history, we can predict what the customer is likely to purchase next. Machine learning models are trained in historical data which allows the retailer to generate accurate recommendations.
Making strategic decisions: We will consolidate data which will help in taking informed business decisions by using a single and trusted source of information about products and customers. Retail dashboards will give a high-level overview of important competitive performance metrics, including pricing promotion and catalog movements.
Forecasting trends: We can understand what the market demands are using economic indicators and demographic data.
Utilizing Market Basket Analysis: A standard technique used by retailers, the market basket analysis helps figure out what products customers are most likely to purchase together. Using Hadoop, we can analyze more data.
Optimizing pricing: The big retailers like Walmart are spending big on real-time merchandising systems. Walmart is currently working on a private cloud that will be able to track millions of transactions every day. Inventory levels, competitors, and demand can be tracked and market changes can be responded to automatically.
Listening to Social Media: Listening to what customers have to say on social media is an important activity especially for the retail industry. Platforms like Hadoop facilitate the analysis of huge amounts of unstructured data. NLP or natural language processing is used to extract information from social media sites. Machine learning is then used to make sense and give the retailer an edge over competition.
Predicting trends: Marketers are using what is called sentiment analysis. Sophisticated machine learningalgorithms are used to determine context. The data gathered can then be used to predict the top selling products in a specific category.