In today’s data-driven world, data tracking and analysis are essential for staying relevant and driving growth.
Companies often fall into bad tracking habits, such as tracking excessive metrics or focusing on the wrong ones, resulting in poor decision-making and limited growth. Conversely, adopting good tracking habits involves tracking the right metrics, setting clear goals, and regularly analyzing data to make informed decisions that support success.
In this article, we will explore the root causes of event analytics mistakes and offer actionable steps that businesses can take to improve their tracking processes and avoid common pitfalls.
One of very common mistake (bad habit) is to have an event for every single activity. And that too with different name. For example, I have came across a company which have event for almost every song i.e. XYX_song_played. And there were about 150 events. This could easily be managed with a single event and event properties could be used for song details (name, duration, singer etc).
I am sharing my take on how to avoid the data tracking mistakes and be on the right path.
Step 1: Define clear objectives and KPIs
To focus your efforts and derive actionable insights from the data, it’s crucial to set clear objectives and key performance indicators (KPIs). Your objectives and KPIs should be specific, measurable, attainable, relevant, and time-bound (SMART). This will help you measure progress towards your objectives and track the effectiveness of your analytics efforts. For example, if your objective is to increase user engagement, you might set a KPI to increase the number of user sessions by 30% in the next quarter. To measure progress towards this KPI, you could track metrics such as the number of sessions per user, average session duration, and bounce rate.
Step 2: Identify relevant events and properties
Once you have defined your objectives and KPIs, it’s important to identify the relevant events and properties that will help you achieve them. Events are actions that users take on your app or website, such as form submissions, button clicks, or purchases. Properties, on the other hand, describe the characteristics of these events, such as the type of device used, the user’s location, or the referral source. By tracking the right events and properties, you can gain deeper insights into user behavior and identify areas for improvement.
Step 3: Implement a robust analytics solution
Implementing a robust analytics solution is critical to capturing and analyzing user behavior effectively. Your analytics solution should be able to track the relevant events and properties, integrate with your tech stack, and provide actionable insights that help you make informed decisions. For example, Google Analytics is a popular analytics solution that provides a wealth of data and insights, such as user behavior, traffic sources, and conversions.
Step 4: Ensure data accuracy and consistency
Data accuracy and consistency are essential for deriving accurate insights from event analytics. Inaccurate or inconsistent data can lead to incorrect insights and flawed decision-making. To ensure that your data is accurate and consistent, you should implement data validation checks, establish a data governance framework, and ensure that your analytics solution is properly configured. You can also use tools like Google Tag Assistant to verify that your analytics solution is collecting accurate data.
Step 5: Track “Decisions Made Without Data”
One of the most significant mistakes companies make is making decisions without data. This can happen when decision-makers rely on their intuition or past experiences rather than analyzing the data. To avoid this mistake, it’s important to track decisions made without data and assess their impact. By doing so, you can identify areas where data-driven decision-making could have improved outcomes and adjust your decision-making processes accordingly.
For example, if you notice that your team consistently makes decisions based on intuition rather than data, you could implement a process to encourage data-driven decision-making, such as requiring a data analysis report before making major decisions.
In conclusion, by following these steps, companies can avoid common event analytics mistakes and derive valuable insights that drive business growth. By defining clear objectives and KPIs, identifying relevant events and properties, implementing a robust analytics solution, ensuring data accuracy and consistency, and tracking decisions made without data, you can make informed decisions that improve user engagement, conversions, and overall business performance.