What Are the Benefits of Google Analytics Remarketing for Your Business?

Limitations of Google Analytics Goals: What Data Can't Be Tracked

While Google Analytics Goals is a powerful tool for tracking specific user actions and conversions, it does have some limitations in the data it can track:

• Customer lifetime value (CLV/LTV): Goals cannot directly measure the total value a customer brings over their entire relationship with your business. CLV requires analyzing purchase history, retention, and other factors beyond a single conversion that Goals tracks. Tools like Kissmetrics specialize in calculating and tracking customer LTV.
• Post-conversion events: Goals only track up until a conversion event like a purchase or signup. They don't monitor how customers interact with your product, additional purchases, or retention after the initial conversion.
• Offline conversions: If a user converts offline, such as by calling a phone number on your site or visiting a physical store, Goals can't automatically track those conversions. Offline conversion tracking requires importing that data separately into Google Analytics.
• Qualitative insights: Goals provide quantitative data on conversions, but not qualitative insights like why a user converted, what almost stopped them from converting, or how they feel about your brand and products. Gathering this \\"why\\" behind conversions requires user research, surveys, and feedback tools in addition to Goals data.

So while Goals excel at tracking online conversions tied to specific user actions, they can't give you the complete picture of a customer's lifetime value and ongoing experience. Combining Goals with other analytics and customer feedback fills in those gaps.

Tracking Customer Lifetime Value Outside of Google Analytics Goals

Since Google Analytics Goals is unable to track customer lifetime value directly, businesses need to use other methods and tools to measure this crucial metric. Here are a few approaches:

1. CRM data analysis: Customer relationship management (CRM) software like Salesforce or HubSpot CRM tracks individual customer interactions and purchases over time. Analyzing this data can provide insights into customer LTV.
2. Cohort analysis: Grouping customers by acquisition date (cohorts) and comparing their behavior and value over time can reveal trends in LTV. Tools like Mixpanel simplify cohort analysis.
3. Predictive modeling: Using historical customer data and machine learning, predictive models can estimate the future value of a customer. Platforms like Optimove specialize in LTV modeling and prediction.
4. Customer surveys: Asking customers directly about their likelihood to purchase again, refer friends, or upgrade can provide qualitative insights to supplement quantitative LTV data. Tools like SurveyMonkey or Typeform make it easy to gather this feedback.

By combining data from CRMs, cohort analysis, predictive models, and customer surveys, businesses can piece together a more comprehensive view of customer lifetime value — going beyond what Google Analytics Goals can track on its own.

Remember: while Goals is fantastic for tracking individual conversions and user actions, it's just one piece of the analytics puzzle. A robust tracking setup incorporates Goals alongside other methods to measure the complete customer journey and lifetime value.

Filling in the Gaps: Supplementing Google Analytics Goals Tracking

To recap, while Google Analytics Goals is a robust tool for tracking online conversions and user actions, it has some notable limitations:

• Inability to directly measure customer lifetime value (CLV/LTV)
• Lack of tracking for post-conversion events and customer retention
• Difficulty tracking offline conversions without manual data imports
• No qualitative insights into the "why" behind conversions

As a marketer or business owner, it's crucial to understand both the capabilities and limitations of your analytics tools. Knowing what data you can reliably track with Goals — and what gaps you need to fill with other methods — empowers you to build a more comprehensive tracking strategy.

To paint a complete picture of your customer journey and lifetime value, supplement Google Analytics Goals with:

• CRM data analysis to track individual customer interactions and purchases over time
• Cohort analysis to compare behavior and value of customer groups over time
• Predictive modeling to estimate future customer value based on historical data
• Customer surveys to gather qualitative feedback and insights

By combining these techniques with the conversion tracking power of Google Analytics Goals, you can gain a well-rounded understanding of your customers and how to optimize your marketing efforts.

The key is to view Goals not as an all-in-one solution, but as one essential part of a broader tracking ecosystem. Embrace the strengths of Goals while also leveraging other tools and strategies to fill in the customer data gaps it leaves behind. With this holistic approach, you'll be well-equipped to make data-driven decisions and drive long-term business growth.