MarTech

How to Use Data Analytics to Better Your Marketing Strategy

How to Use Data Analytics to Better Your Marketing Strategy
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Data is at the forefront of business operations today, leading critical decision-making processes. This is from intelligent insights gathered from reports and analytics.

In this manner, the field of marketing can also benefit from applying data analytics to the field. However, it must be utilized systematically.

Also Read: How MarTech Can Personalize Your Marketing in 2024

Discover how to utilize data analytics to improve your marketing strategy.

By leveraging data analytics, marketing teams can gain a fresh perspective on their customers’ behaviors and preferences.

What is Data Analytics and Which Data is to be Collected

Data analytics involves collecting data to process and then analyzing it to generate actionable intelligence. Marketing leaders can benefit by using this tool on various types of data depending on what their objectives are. They are:

  • Data on their Customers: Involves purchasing patterns, demographics, and more.
  • Sales Data: Involves volume of sales, rates of conversion and bounce, and other metrics.
  • Data on the Market/Industry: Involves competitor’s evaluation, trends, and more.

Gathering these types of data and more enables the proper application of data analytics.

Collecting and Processing the Data

Data analytics starts with data collection. To get better insights for better marketing, the appropriate data has to be collected. For websites and social media, the analytics tools given by the websites are the best. Externally, conducting surveys and gathering feedback gives their direct input on the product.

Data that is gathered will be raw data. It will contain some irregularities and anomalies. This must be processed and cleaned before it can be used to generate insights. It can be done by using a proper filtering and sorting method.

Studying the Data

There are four types of data analytics techniques that can be used:

  • Descriptive Analytics: Generates performance insights based on historical data. It helps detail the trends and relationships. For most businesses, it is revenue generated per customer, percentage growth over the year, and more.
  • Diagnostic Analytics: Identifies the reasoning behind past performance. For marketing, it can identify why a campaign failed or YoY percentage growth was less.
  • Predictive Analytics: Predicts and forecasts potential future trends and outcomes. For marketing, a shift in consumer behavior or demand could be an actionable insight.
  • Prescriptive Analytics: Generates recommended actions based on actionable insights from predictive analytics. For changing consumer demands, it can recommend the optimal time to launch a marketing campaign.

Once analytics is applied, it is time to develop targeted marketing strategies personalized for customers.

Grouping Customers

Customers should be grouped and segregated based on various factors such as demographics, their behavior, and various other attributes. This helps when developing targeted campaigns.

Creating Content and Launching Campaigns

Finally, it is time to generate content and launch those campaigns. Content generation should consider all insights from data analytics for a tailor-made campaign that is designed for success.

The campaigns should also be launched at the ideal time and manner so that they reach the selected customers.

About the author

Abhishek

Abhishek, as a writer, provides a fresh perspective on an array of topics. He brings his expertise in Economics coupled with a heavy research base to the writing world. He enjoys writing on topics related to sports and finance but ventures into other domains regularly. Frequently spotted at various restaurants, he is an avid consumer of new cuisines.