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Applications of Big Data Marketing Analytics

Big data is an evolving term, and it consists of high volume of structured, semi-structured and unstructured data that has the potential to be mined for information.

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Applications of Big Data Marketing Analytics

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  1. Applications of Big Data Analytics

  2. Introduction Introduction • Big data is an evolving term, and it consists of high volume of structured, semi-structured and unstructured data that has the potential to be mined for information. • Big data increases the quantity of sales, it also improves the quality of sales, lead data, territory planning etc. These are the areas where big data is making enormous contribution to sales and marketing today. • Big data also provides insights into how to lower the Customer Acquisition Cost (CAC) and Customer Lifetime Value (CLTV) is it's the newest trend and we don’t have to give second thought on it. • By providing various opportunities, big data is changing the marketing and sales in various ways some of them are

  3. Review Program Performance Big data basically focuses on performance. It allows the marketers to review their programs for benefit. Marketers make data, center of sales and marketing decisions which in return increases the investment of their companies. It allows the marketers to leverage data to capitalize on what works, while discarding wasted efforts on what doesn’t. It also affiliates with more real time information and this allows to make better marketing decisions and enhances customer experience online, by increasing brand image and brand loyalty.

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  5. Gain Consumer Insights Big data will always search for new opportunities for your program. It gives marketers the opportunity to gain insights about customers that was never possible before. It also permits the marketers to tailor personalized marketing campaigns and upgrade the customer’s experience.

  6. Analyse Consumer Behaviour Big data also expands customer intelligence. It examines various range of onsets that include structured information such as purchase histories, CRM data as well as unstructured data information such as social media etc. Sorting from this information would surely help in expanding customer’s intelligence.

  7. Improve Operational Efficiency Big data also improves operational efficiency. It frames the value chain that helps the companies to drive more operational efficiency from existing investments. Big data is moving from the sphere of data scientists into business transactions. Various firms like insurance companies and others are getting benefit from this introduction big data for reduction of costs.

  8. Need For Resources There has been an increase in demand for hiring new people. As technology automates big data collection, there has been an increased need for hiring people.Computer scientists, statisticians are needed to filter big data.

  9. Forecasting Predict your customer’s needs before the customers say it. Big data helps in forecasting the future needs of the customers.

  10. Personalization We all know that every customer is different and their needs and wants are different, and presenting the same deals to all the customers will not work ever. Big data can deliver insights into customer’s locations, needs and contact information. Personalization can be built by converting customer data from social media, customer’s review and insights that target customer’s individual needs. But big data allows you to study the different trends in the market of almost every customer and then each time show them something new. And when the customer will be satisfied by your presentation and planning he would surely come back to you.

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