Application of Data Science in Marketing

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The consumer is changing. The mindset of buyers does not have a specific way. Every day, Companies are trying to read the consumer’s mind and are always eager to explore what is going inside the mind of a consumer while making a purchase decision. The market place has changed now. The conventional marketing techniques are becoming obsolete. The first set of changes in product marketing came when the culture of supermarkets emerged. Many traditional shopkeepers had rejected the supermarket concept then, but when reality hit them hard, then the corner grocery stores also allowed customers to choose and pick the product on their own. The same thing repeated when the e-commerce portal started selling the products online. No one had ever imagined that one could buy anything on a click while sitting in the comfort of his or her own or while moving.

Data Science is one of the areas, which is helping the marketing department of every company. Whether one is selling the product or services, both are getting tremendous help in every decision they make from data science techniques. The companies are collecting and storing the data every second. This data is producing valuable information using data science techniques and tools. From product inception to product decline, everything is changing with the help of data science. Marketing research and consulting firms who are the most crucial supplier of consumer data to large organizations are generating insights from these data sets. The data is present in many formats and broadly classified in two types: structured and unstructured data. Nowadays, there are many techniques and tools available to analyze both types of data and provide real-time information for decision-making. We have highlighted some of the primary applications of data science techniques in the critical area of marketing decision making.

Customer Segmentation – If, as a company, you know who is buying your product, then you will never have to worry about your bottom line. Understanding the different segments of buyers can help in many ways. You can create a customized product for different types of consumers. Your marketing strategy can be shaped and reach to the relevant consumer. Data Science can help create a segment of your consumer based on their buying patterns and demographic information. Customer Relationship Management systems can provide secondary data and online methodology to collect primary data about the customers, which can help data scientists build the segmentation model. Cluster Analysis techniques are data science techniques that help define the segment of consumers for any products. Behavioural data plays an important role apart from demographic information while creating a segment of consumers.

Pricing Strategy – Data Science helps in defining the appropriate price of a particular product. It is essential to know how much a consumer will pay for a specific product. One of the crucial techniques is conjoint analysis. In this analysis, a consumer is shown a different combination of attributes of a product, and then they select which one he will prefer to buy and on what price. Post that, the data science algorithm analyzes the data to provide the optimal amount chosen by a set of consumers.

Competition Benchmarking– Market is a battleground where there are so many opponents who want to attract consumers. There is no shortage of options for any product. The age of monopoly is almost gone. Therefore, it is essential to know whom you are fighting. The completion benchmarking can help the company to win this. A company compares themselves with their competition by this process. There are several methods available under data science that can help analyze the performance of the product, representation of channel, and reach. Social Media Analytics is highly used these days for improving the benchmarking process.

Supply Chain Management – This is one of the critical areas for any business, especially for a product-based company. Nowadays, the whole process of Supply chain management is automated using data science algorithms and tools. Some companies have built a zero manual intervention model for their supply chain management. In the past, the supply chain function was an operation process purely, but with the help of the latest data science techniques, blockchain, artificial intelligence, it is an emerging strategic advantage. Demand forecasting, procurement, distribution is using various modelling techniques and real-time data.

Target Marketing – The dimension of marketing has completely changed now. In the past, a banner or posters were placed on various locations where maximum people can see, and the company used to believe that the product information has reached the right consumer that is not true anymore. Nowadays no one cares what is displayed until it is essential information for him or her. The predictive modelling techniques in data science is helping companies to create target based marketing campaign. The online advertisement is fully algorithm-driven. The data science algorithm running behind knows whom to show what. These automated techniques provide a maximum reach of any product to the right consumers.

The above mention examples show that it is essential for every marketing person to know about data science. The decision based on gut filling may not always help, but the decision based on the right data will still help. There are many resources available to educate in the field of data science. The prerequisite for enhancing the knowledge in the file of data science is basic mathematics and statistics, along with computer science. A marketer who has expertise in his domain and basic understating of data science can generate gold for any organization. Remember that in the upcoming time, only data will be the truth rest everything will be an illusion.

(The Above article has been published in the Second Edition of PHD-Chamber Journal of Ideas Innovations)

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