A lot of people are under the impression that great marketing is an art, but of late, big data has introduced a scientific element to marketing campaigns. Smart marketers are now relying on data more than ever to inform, test, and devise their strategies.
And though data and analytics will never replace the creative minds behind the best marketing campaigns, it can provide the marketers with the tools to help perform better.
Consumers have 24-hour access to abundant product information, which has revolutionized the retail sector. With digital technology becoming ubiquitous, shoppers can make informed decisions using online data and content to discover, compare, and buy products from anywhere and at any time.
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For brands and retailers, information is also a game-changer. Retail data analytics can help companies stay abreast of the shopping trends by applying customer analytics to uncover, interpret, and act on meaningful data insights, including online shopper and in-store patterns.
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The retailers—both offline and online—are adopting the data-first strategy towards understanding the buying behavior of their customers, mapping them to products, and planning marketing strategies to sell their products to register increased profits.
Today, retailers attempt to find innovative ways to draw insights from the ever-increasing amount of structured and unstructured information available about their consumer’s behavior.
Big 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.
Become a Big Data Professional
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Big Data Engineer
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11 monthsPost Graduate Program in Data Engineering
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8 months
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Data Administrator, Seminole County Democratic Party
My instructor was experienced and knowledgeable with broad industry exposure. He delivered content in a way which is easy to consume. Thank you!
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I completed Simplilearn's Post-Graduate Program in Data Engineering, with Purdue University. I gained knowledge on critical topics like the Hadoop framework, Data Processing using Spark, Data Pipelines with Kafka, Big Data and more. The live sessions, industry projects, masterclasses, and IBM hackathons were very useful.
How It Works
Generating Recommendations:
Based on a customer’s purchase history, retailers can predict what the customer is likely to purchase next. Machine learning models are trained on historical data, which allows the retailer to generate accurate recommendations.
Making Strategic Decisions:
Companies will need to consolidate data, which will help in taking informed business decisions 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:
Retailers 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, retailers can now analyze more data.
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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 vast 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 the competition.
Predicting Trends:
Marketers are using what is called sentiment analysis. Sophisticated machine learning algorithms are used to determine context. The data gathered can then be used to predict the top-selling products in a specific category.
Enhancing Customer Experience:
Retail analytics will now be used to anticipate the demand of the shopper as well as produce a seamless customer experience. This will help improve the customer’s experience and loyalty.
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Conclusion
Big Data analytics will play a significant role in shaping the future of the retail industry. The big data revolution is here to stay. Certification in Big Data will help you upgrade your career in retail analytics and marketing.
