APPLICATIONS OF DATA SCIENCE IN MARKETING

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1. APPLICATIONS OF DATA SCIENCE IN MARKETING RAHUL SAVIO JOSHY 2237018 MA APPLIED ECONOMICS
2. DATA SCIENCE & MARKETING • Marketing refers to activities a company undertakes to promote the buying or selling of a product or service. • Marketers have to fight with competitors to grab the attention of their target customers if they want to be successful in the field of business. • Data science is a process that involves studying and analyzing a huge amount of data by using modern tools. • Data science is used to identify the influences that may have direct or indirect effects on business operations and revenue. • Many sources like web databases and social media provide an incomprehensible amount of big data to choose from. • If this data can be processed and analyzed properly, it can give great insights into the target customers and thus become a great tool in the business venture. • Data analytics and data science can be employed to predict market trends. • Thus you can use them to make marketing strategies that will work for the business.
3. NEED OF DATA SCIENCE IN MARKETING • With the huge amount of data in the palm of our hands, it is only natural for it to be used for marketing strategies. • Businesses incorporate data science into their marketing strategy to make informed decisions based on actionable insights derived from vast quantities of data. • Successful marketing requires a deep understanding of customers’ needs, wants, and pain points. Data science provides the tools and techniques needed to collect, analyze and interpret customer behavior. • Data science can help businesses understand the needs and demands of their customers much better and also help them attract more customers with great marketing strategies. • It can also help businesses figure out which shipping model will be the best for them, whether overtime helps their revenue, and much more depending on the available data. • If businesses do not start taking advantage of the opportunity to use data science techniques now, they will be left far behind their competitors who do so. • In 2023, using data science in marketing has become a necessity.
4. DATA SCIENCE MECHANISMS FOR MARKETING  DATA VISUALIZATION : • It attracts attention and helps marketers change their actions according to customer behavior. • Data visualization can tell marketers about the type of customers that live in or frequent the store’s neighborhood. • Based on that, they can use different marketing strategies to attract more customers.  AUTOMATION OF CUSTOMER SUPPORT : • Most of the routine processes can be automated through bots. • This has also cut down the costs of manual customer support.  REGRESSION ANALYSIS : • This is a very useful tool in marketing that helps make more accurate predictions. • It also analyzes a specific behavior of your customer and predicts what they are likely to buy next and advertise it to them.
5. DATA SCIENCE APPLICATIONS  Optimizing Marketing Budget • Data science can make a spending model based on the data they acquire that makes sure that the budget gets evenly spread throughout channels, locations, and campaigns.  Matching Customers with the Right Strategies • With the help of data science, marketers can identify the demographics and locations that provide them with the most ROI and design their campaigns accordingly.  Customer Profiling • Data science can help them make the customer experience more holistic and personalized, which will earn them more loyal customers.  Communication with Customers • Data science can help marketers understand which customers are more receptive through which channels – SMS, emails, and more. Social Media Marketing • The ads and campaigns over different social media platforms can make data scientists understand the success of each campaign and they can design their future ads accordingly.
6.  Predictive Analytics • The data with businesses is analyzed through machine learning algorithms that can predict the course of the market with high accuracy. Based on that, the marketing team can change its tactics.  Lead Scoring • Lead scoring is the process of identifying the customers who have the highest probability of buying products and making sure to target them at the right time.  Sentiment Analysis • Sentiment analysis is a part of data analysis that ensures that your marketing strategy has empathy to reel people in.  Optimizing Channels • Data Science can help in identifying the right channels which bring around the most ROI.  Product Development • Data science helps marketers and businesses identify what types of products get the most revenue and positive customer feedback for the company.