What Is Customer Analytics?

Customer analytics, also known as customer data analytics, is the study of a company’s customer data and behavior to discover, attract, and keep the most profitable customers.

Why does customer analytics matter?

Customers in the digital world have access to information about where to buy goods and services, what to buy, and how much they should expect to pay. They can discover the ideal products for their needs. Thus businesses must do all possible to provide the correct products and marketing campaigns to their target market.

Organizations can achieve this by using customer analytics technologies to better understand their customers. Customer analytics aims to generate a single, accurate picture of a company’s customer base that can be used to help us facilitating the decision making process about how to effectively attract and keep new customers. It can also recognize high-value customers and recommend proactive ways to communicate with them.

Organizations that have a thorough understanding of their consumers’ purchasing behaviors and lifestyle preferences can better forecast their behavior and, as a result, optimize the customer experience. Large amounts of precise data are required for accurate analysis. Without this, analysis insights could be wholly inaccurate and useless.

How does customer analytics work?

Customer analytics is frequently managed by a cross-functional team of executives from marketing, sales, customer service, IT, and business analysts. The group should agree on which business metrics can provide a comprehensive view of the customer experience to get helpful information.

Customer analytics begins with raw data and concludes with sound business decisions. Data must go through three steps before it can be used to make decisions: collection, organization, and analysis.

Collection: To begin, businesses must collect raw customer data from various sources, including marketing tools, CRM systems, and third-party sources. The following are examples of such information:

  • demographics
  • advertisement engagements
  • survey responses
  • contact center interactions
  • purchase history
  • web and social media activity

Organization: Following that, businesses must structure customer data to be used in a customer analytics platform, as unorganized data might lead to an erroneous customer profile. Inaccurate findings might be caused by several CRM instances, fragmented enterprise resource planning platforms, or insufficient customer data integration. A customer data platform (CDP) can assist businesses in centralizing and organizing their data.

Analysis: A customer analytics tool assists businesses in making sense of their data and can illustrate trends that are in the form of charts and graphs.

Customer analytics best practices

The best practices and customer experience metrics listed below can help businesses develop successful customer encounters.

  1. Analyze how to deliver a product or service to clients through various channels.
  2. Assess and comprehend clients’ attitudes toward the brand and whether they are satisfied.
  3. A combination of quantitative and qualitative surveys can be used to accomplish this.
  4. Engage customers at the appropriate time and through the right channel.
  5. Predict the turnover rate and take steps to increase a customer’s lifetime value.
  6. To enhance sales, spot trends in extensive data, and evaluate online behavior.
  7. Optimize the customer experience with targeted selling and market segmentation by determining which customers are more likely to buy one product over another.

The future of customer analytics

When users use the internet, the websites they visit can send a text file to their browser called a cookie containing identifying information. Cookies enable websites to collect information about a user’s session for personalization. But not all cookies are created equal. First-party cookies are only used by the website that received them and is used to improve the user experience on the site.

For example, they allow a website to remember what goods users have in their shopping carts. On the other hand, it is concerning that third party cookies come from various websites other than the one a user views. Advertisers can use them to monitor a user’s session across several websites and serve tailored ads based on their behavior.

Since the 1990s, third-party cookies have been a significant source of data used in customer analytics to generate marketing insights. Due to privacy concerns, Apple Safari and Mozilla Firefox had removed third-party cookies since 2013, while Google had kept them until June 2021, when it revealed its plan to phase out third-party cookies from its Chrome browser by mid-2023.

Instead of waiting for Google to reinvent the third-party cookie, businesses should take the following proactive steps:

Utilize first-party data: Unlike third-party cookies, first-party cookies are here to stay. To turn the data, they collect from their sources into marketing insights; companies should invest in CDPs and analytics tools.

Collect zero-party data: Companies can collect voluntary information from their customers using innovative online quizzes, social media surveys, and loyalty cards.

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