Applications of Data Science in the Marketing Domain

For the last decade, data consumption has drastically shot up due to the availability of the World Wide Web. It is estimated that a person generates 1.7 Megabytes every second and around 2.5 Million terabytes of data is generated every day. This data alone shows the impact of data on the lives of the people.

For the professionals in the marketing field, the data which reveals the activities of a particular Netizen is a gold mine. The reason that this data holds an emphasis from them is due to the fact that this data not only reveals interests n particular products but it also helps in analyzing the trends in their spending as well. However, decoding huge chunks of data is a mammoth task. This is where Data Science can immensely help.

Data Science is quickly becoming a standard for Marketers around the world to help with not only their day to day activities but also for achieving their required targets. The insights through Data Science can be on various marketing aspects such as customer intent, experience, behavior, etc that would help them in efficiently optimizing their marketing strategies and derive maximum revenue.

Let’s take a look at 15 ways through which Data Science can be implemented in Marketing:

1. Marketing Budget Optimization

Return on Investment (ROI) has always been critical for any marketing company because they want to maximize it as much as they can within their allotted budgets. 

By developing a budget model, Data Scientists can help marketers with distributing their budget across locations, channels, mediums, and campaigns to optimize their key metrics.

2. Marketing to the Right Audience

In the yesteryears, Marketers didn’t have any tool for targeting the right audience to get the most of their marketing campaigns and had to use the hit and trial method to marketing the products. As a result, marketers had to face problems with excessing the budget for the campaigns and which often led to ROI being on the negative side.

Fortunately, with the progress in Data Science, it has become easier for the campaign bearers for analyzing the locations and demographics much better and investing in only those via the help of relevant data points.

3. Analyzing the Channels for the right fit

Data Science can be used to analyze different channels for the campaigns via the help of relevant time series models. It helps in revealing the right channel for maximum ROI.  

4. Right Strategies for Right Customers  

Devising the right marketing strategies for different segments of customers is very important, especially when you have a tight budget. While targeting new customers via different strategies is important, retaining the highly profitable accounts is beneficial for the markets is as well.

By developing a clustering model, a customer can group and retain the customers by offering the highly valued ones with discount vouchers and giving them a chance for being in a relevant promotional campaign.

5. Lead Target

Marketers can analyze and narrow down the leads by looking at their historical data, marketers can determine their business requirements and the type of brands they’ve been associated with, in the past year.

6. Segmentation of Lead Scoring

Data science enables marketers to create a predictive lead scoring system. This system is an algorithm that is capable of calculating the probability of conversion and segmenting your lead list. The list can be categorized into the following: eager customers, curious prospects, and not interested customers.

7. Profiling of Customers

When it comes to targeting the right kind of customers, Data Science has made the lives of marketers much easier. Different models help the marketers creating these personas by the inclusion of specific characteristics.

8. Content Personalization 

Marketers are fond of delivering relevant information to their customers. Fortunately, Data Science has a plethora of models, tools, and algorithms which help them in enabling them towards personalization based on the searches and history of browsing of the customers.

9. Product Development

Product development has been a prime responsibility for the professionals in the marketing domain as it enables them in delivering a product with just the right ingredients which the customers love and always look forward to. Algorithms based on the Data Science plays a key part in it by analyzing the data based on gender, occupation, and even demographic locations of potential customers.

10. Pricing Strategy

Data Science has been a forerunner when it comes to not only developing but also altering the pricing strategy of their products which is based on several attributes like purchase history, economic situation, and buying habits of the customers.

11. Customer Feedback

Improving product or services is an important and essential job of marketers. Data Science can make use of visualizing tools like Tableau and Power BI by creating easier to interpret charts and graphs to help marketers in analyzing the feedback data and enhance the functionality of the products or services they offer.

12. Social media marketing

Nowadays, customers are highly active on social media sites like Facebook, LinkedIn, and Twitter. Marketers can use data science to see which leads are exploring their social media page, what content they clicked on, and more. With insights such as these, they can formulate a proper social media engagement strategy.

13. Targeted Ad Offerings

Marketers can use Data Science to specifically targeted ads to relevant customers based upon their profile and even measure clicks and results of their campaigns.

14. Email Campaigns

As marketing, while using Business Development professionals is slowly fading out, Marketers are using Data Science excessively for their marketing campaigns by sending out Emails related to the profile of their leads and earning new customers very easily and conveniently.

15. Digital Marketing

As we know, Digital Marketing thrives on Data. Data Science improves Digital Marketing by providing the cleaned, preprocessed, and right data for the relevant professionals and enabling them to achieve their marketing goals.