Analyzing Digital Marketing Data: A Guide to Informed Business Growth through Analysis.
Let’s take a look at the fundamental elements of data analysis that can help you improve your business’s digital marketing efforts. This process is essential for converting a collection of numbers into actionable steps and insights that can truly benefit you. Having data is obviously critical. If you truly want to grow your business, relying on instincts, ideas, or educated guesses is not a viable or effective strategy. You can’t make informed decisions about what’s effective or what will be in the future unless you have data. However, simply having data isn’t enough. A spreadsheet full of numbers will not help you run a more efficient business, improve customer experiences, or make meaningful changes.
The sheer volume of numbers may cause you to feel overwhelmed. That is why it is not just about gathering data; it is also about turning data into action. So, what bridges the gap between data and action? It’s analysis. Analysis is the process of converting raw data into concrete strategies and plans that can improve your business, attract more traffic, and increase your conversion rate, among other benefits. Let me quickly walk you through the tools you’ll need to go from raw data collection to meaningful insights that can help your business grow.
Analysis is crucial because it translates data into actionable insights. It transforms data into improved or useful patterns. Additionally, it helps eliminate biases and outliers. There will be instances in your business when you observe sudden changes in metrics like a tripled average order value or a skyrocketing conversion rate. In such cases, there’s a possibility that these abrupt shifts result from tracking errors or issues with your website. The analytical process provides a strategy to identify and rectify these anomalies, ensuring that the trends and patterns you notice may be used effectively.
Furthermore, analysis is important because it contextualizes your data. Viewing data in isolation may lead you to believe that something is wrong, such as a decrease in average order value or website visits. However, contextualizing the data reveals seasonal patterns or the impact of new strategies, competitors entering or exiting the market, and other natural changes in your business. Understanding these contextual factors allows you to make more informed decisions and avoid errors based on incorrect assumptions or isolated data.
Now, let’s discuss the tools you need for effective digital marketing data analysis.
- Firstly, data acts as the tripwire, identifying anomalies and providing insights into what is happening in your business. Key metrics serve as tripwires, while drill-down metrics help explain why specific events occurred.
- Next, you need a question — a formalized query that helps you understand or explain a phenomenon. For instance, if your average order value doubled, your question might be, “What caused my average order value to double?” This sets the framework for breaking down and addressing the issue.
- Following the question, you create a hypothesis — a proposed explanation for the observed phenomenon. The goal is to use collected data to either prove or disprove the hypothesis. For instance, if your email newsletter open rate drops, a hypothesis might be that people are not interested in the topics or there’s a technical issue affecting deliverability.
- Lastly, the Analyst Toolkit provides various methods to question and break down the numbers, helping you contextualize your data and gain a deeper understanding of your business context, these tools assist in breaking down and analyzing your data comprehensively and they include:
Historical Contextual Questions -
- What does history tell us to expect?
- Have we seen seasonal dips?
- How have promotions performed in the past?
External Contextual Questions -
- What changes outside of our control might influence our metric?
- Have referring sources changed?
- Has Technology Change?
- What Has Changed with Our Competitor?
Internal Contextual Questions — and
- Am I Comparing Raw Numbers or Percentage?
- Is my baseline skewed by outliers?
- Is my data correctly pulled?
General Contextual Questions -
- Have we made changes to our strategy?
- Have we made changes to our site?
- Have we made changes to the offer?
- Are we driving new audiences?
Armed with these tools, you can transform your data into actionable insights, allowing you to observe trends, identify influencing factors, and implement strategic changes to drive business growth. This, in essence, serves as the foundation for transforming your data into useful actions and insights. Understanding data analysis is critical for converting raw business numbers into actionable insights that drive growth.
With the right tools, you can navigate data complexities and uncover meaningful patterns, such as having the right data, formulating the right questions, developing hypotheses, and using the Analyst Toolkit. Analysis not only closes the data-to-action gap, but it also protects against misleading outliers and provides essential context for informed decision-making. With these insights, businesses can confidently adapt, improve, and thrive in the ever-changing world of data-driven strategies.