10 Data Science Tips & Tricks for Better Performance Marketing

For most companies, data is the new gold. They make plans and business strategies with the help of enormous data that is being created daily. This article will tell you about the best data science tips and tricks you can use to improve performance marketing.


Learning Of Blog

  • Why We Need Data Science in Marketing
  • Ways By Which Data Science Can Improve Performance Marketing
  • Conclusion 


The number of internet users worldwide has soared drastically. There are more than 2.4 million monthly active users on Facebook; the amount of data such users create is a feast for hungry marketers who are working on using data to develop targeted marketing strategies. However, decoding large amounts of data to come up with useful insights is a difficult task. This is precisely where data science comes into the picture.


Data science professional certificate courses have helped people boost their careers. Marketers who have opted for data science certification courses are in a better position to understand what data science is and how they can leverage the technology to up their marketing game.

Why We Need Data Science in Marketing

Previously, the generated data was mostly in a structured form and was easy to analyze with the help of data analysis tools. Modern-day data is usually unstructured or semi-structured (a significant portion of the information is unstructured). 


Sources of unstructured data:

  • Sensors and Electronic Equipment
  • Word Documents
  • Social Media
  • Webpages
  • Emails


Traditional data analytics tools are not capable of handling this heavy load, making it the need of the hour to use advanced analytics tools (data science tools) for better data processing decision making.


Ways By Which Data Science Can Improve Performance Marketing

The huge production of data on a daily basis has opened opportunities for data scientists to improve performance marketing. Below are some of the ways in which it can be done:


  • Product Pricing Strategy 


Many companies fail to create a product pricing strategy as they are not aware of customer preferences and their needs. Data science offers marketers with the right information, which will help them identify customers’ buying habits.

For example, they can see the number of sales when they offer discounts and compare the data to the normal days when the products are sold without any discount. This will help them identify customers who purchase only when a discount is offered; offering discounts to those customers only.




  • Social Media Marketing

The millennial generation is very active on social media platforms like Instagram, Facebook, LinkedIn, etc. Marketers can use this data to identify which users are viewing a particular content and design a marketing strategy around it.




  • Customer Communication 

Most of us check our emails during office hours only and are active on our phones in the evening. Data science can help marketers target leads using the right channel and at the right time.



  • Providing Better Customer Experience 

Great customer experience has always been a top priority for every organization. With data-driven marketing, marketers can understand what users want and how the customer experience can be improved.




  • Email Marketing Campaigns 

The process of sending emails to current or potential customers is called email marketing. With the right data, websites such as e-commerce platforms can create emails which are more personalized and relevant to the users. It will also make the customers know that they are being valued, thus increasing the chances of conversion.




  • Product Development

Data analytics can help companies build the right product. For example, people from a particular geography wish for a specific solution. This data can be used to create what people need, and highly targeted marketing campaigns can be created to focus on geography.



  • Content Creation 

Content is the backbone of every marketing campaign; it won’t be wrong to say that even if a page is ranking high on Google, it will not convert with bad content. With the introduction of data analytics in content strategy, the whole approach can be easily revamped.

For example, if a user does a Google search for a particular keyword, the marketer will know how to increase the frequency of that keyword in the content.




  • Sentiment Analysis 

Sentiment Analysis is the process of understanding the market sentiment of a brand. Data science helps companies to gain better insight into the customers’ thought process, beliefs, and opinions.




  • Customer Loyalty

Customer loyalty is something that comes with time and patience. Companies work very hard to build a customer base that trusts their brand and products. They will always try new products launched by the company, thus making them easier to convert than new customers. Data science offers valuable insights to marketers to create marketing campaigns to improve customer loyalty.

For example, if a person is going for a hike, companies can target him by offering discounts on hiking essentials. This will ultimately help them boost customer loyalty.




  • Marketing to Relevant Audiences 

Marketers usually fail to understand the market segment that is relevant to their products/services. If marketers leverage data science, they can segregate relevant and irrelevant audiences for a marketing campaign, helping them spend less and get better ROI.




Data science is set to minimize regular and monotonous marketing efforts and help marketers achieve their goals better. With more data being generated and collected, marketers will use it to improve their brand and build a loyal customer base.


With so much scope in data-driven marketing, it is the right time for marketers to consider a data science for beginners course. Later on, they can become a data science expert by opting for a data science professional certificate to learn more about data-driven marketing.