Although customer analytics as a tool has been available to marketers for several years, many fail to understand or use it correctly. This results in numerous missed opportunities due to incorrect sales projections, poor product management decisions, and the necessity to keep prices low to retain customers. The inevitable result is financial losses for businesses and slow customer acquisition, both opposite of the goals marketing departments want to achieve.

While this may sound dismal, the good news is that more businesses than ever understand the need to truly get to know customers. By learning to use data analytics efficiently, companies of all sizes can remain competitive and hit their financial targets.

Understanding Customer Analytics

This term refers to a process rather than a single action. Businesses employing customer analytics collect and analyze data from a variety of sources to better understand their behavior. The goal is to learn customer preferences well enough to make the most appropriate strategical decisions on behalf of the business. This strategy also helps online marketers create automatic product recommendations for customers based on their purchase and browsing history. Several categories of customer analytics exist, including the following:

  • Descriptive analytics: This provides a clear picture of the customer’s typical online researching and shopping behavior.
  • Diagnostic analytics: Delving into a specific business problem helps marketers understand where it came from and what to do about it.
  • Predictive and prescriptive analytics: These analytics categories use machine learning and data science to suggest sales forecasts and specific actions marketers can take to reach them.

Customer Metrics All Marketers Should Track

Anyone new to tracking online customer behavior should first establish an account with Google Analytics. This free tool goes far beyond tracking how many people visit a company’s website. It also provides them with the following useful and actionable insights:

  • Acquisition: How customers found the website.
  • Audience: Demographics of website visitors.
  • Behavior flow: This shows the actions visitors took on a website.
  • Bounce rate: Number of people who left the website after looking at only one page.
  • Conversions: This can be however the company defines it from completed sales to requests for more information.
  • Exit percentage: This displays the number of people who leave the website after viewing a page with or without making a purchase.
  • Landing pages: This stat shows how customers arrived at the landing page and whether they spent time on it.
  • Pages per session: The average number of pages each website visitor viewed.
  • Session duration: How much time customers spent on each page of the website.
  • Site speed statistics: How fast pages on the website loaded compared to similar sites.

Analytics data makes it much easier to know customer intentions and understand behavior. With this information, marketers can tailor their approach to each customer to make it more efficient and personalized.

Salesforce Merges Its CRM with Google Analytics

The industry leader Salesforce recognized some time ago that its clients weren’t using or understanding the wealth of information available to them with Google Analytics. Salesforce integrated its own customer relationship management (CRM) software with Google Analytics to provide its clients with a 360-degree view of online customer behavior and intentions.

Part of the challenge that marketers face is pulling together customer data from more than a dozen platforms. The new Salesforce product tackles this dilemma by bringing big data analytics from multiple sources together in a single location.