Step 1: Understanding Your Goals Before Collecting Data
The first step in any data analytics process isn’t collecting data—it's defining what you want to learn. Many businesses jump into data collection without a clear purpose, which often results in an overwhelming amount of information that doesn’t align with their objectives. This lack of focus leads to confusion about how to effectively leverage the data in the first place.
To clarify your goals, start by asking yourself what you hope to learn or what specific questions you want the data to answer. For example, I often aim to uncover insights about what people are searching for when they land on my website and how they navigate from initial interest to deeper exploration. I might define this goal as "understanding how users first interact with my brand." By setting this clear objective, I remain focused on the insights I hope to gain before diving into the collected data.
When setting your goal, ensure it’s something the data can directly influence. While data can support a wide range of objectives, it's important to be specific. Instead of a vague aim like "increasing sales," try reframing the goal to ask how the data can guide strategies that drive future sales. This approach keeps your analysis purposeful and actionable, ensuring the insights you gather support to goals.
Before analyzing any data, I work with teams to establish clear, specific questions they want to answer. Instead of vague objectives like "I want to understand my customers better," I guide them toward focused queries such as "What time of day do most of our customers make purchases?" or "Which products have the highest return rates?" These targeted questions act as micro-goals that contribute to achieving larger business objectives, such as increasing sales.
For instance, a smaller goal toward boosting sales might involve understanding how customers find your business and what decisions they make before contacting you. Similarly, I might focus on identifying what content users engage with first when visiting a website. Another example of a micro-goal could involve optimizing email outreach. By setting a goal to increase email open rates through testing different formats, you're more likely to connect with potential clients who have significant needs.
Each business's goals will differ, but they must remain specific and tied to actionable outcomes that data can influence. Data can drive meaningful changes, such as increased sales, without relying on manipulated metrics. By ensuring your goals for leveraging data are precise and purposeful, you significantly enhance the likelihood of achieving success. Clear, focused objectives make it easier to align efforts with desired outcomes, leading to impactful results.
Step 2: Setting Up Data Collection
Now that I have clear, actionable goals I want to address and achieve using data, the next step is determining how to collect that data effectively. Like goal-setting, data collection is a broad and complex topic. To keep this article focused, I’ll highlight two key elements for setting up and standardizing data collection; specifically for my website and primary social media account.
In the next section, I’ll dive into strategies for aligning data collection with your goals and important considerations for auditing data to drive better outcomes. If you already have a data collection system in place, feel free to skip ahead, as this section serves as a foundational guide to getting everything properly connected and operational for effective audits.
Let’s start with my website. I’ve noticed that many clients rely on basic data insights provided by their platform, such as SquareSpace or Wix, which often include built-in visualizations. While these tools aren't inherently wrong, they can limit your ability to make well-informed decisions if the data isn’t robust enough.
For my website, I prefer using Google Analytics for several reasons. It offers far more detailed insights into my audience, including who they are, where they’re coming from, and which content they’re engaging with. This level of detail helps me better understand and optimize my site’s performance. Installing Google Analytics can be relatively straightforward, depending on your platform. To offer a quick overview, I’ll guide you through the process of integrating GA with your website.
If you’re already collecting data but want deeper insights, Google Analytics might be the right choice for you. While there are other tools available for auditing web data, Google Analytics is my go-to platform due to my extensive experience with it and its powerful capabilities.
1- Visit analytics.google.com and sign up using your business Google account. It’s best to use an established business account or create a new, business-focused Gmail account to manage team access effectively.
2- Create your account and property by naming them after your business or brand. While the name doesn’t impact performance, keeping it relevant to your business ensures clarity.
3- Enter your business details, including selecting an appropriate category. This step is crucial as Google uses this information to align your business with relevant search intentions, so choose a focused and accurate category.
4- Define your business objectives. I recommend selecting "Leads" or "User Engagement & Retention" since other options are tailored for ad metrics like cost-per-outcome, which isn’t the focus of general data auditing.
5- When it’s time to start collecting data, choose the "Web" option and input your website's URL and domain information. Ensure the "Enhanced Measurement" feature is enabled—this provides robust insights without compromising user privacy.
6- Once your domain appears, click on it and select "Installation Instructions."
7- You’ll see two installation options, but I recommend choosing "Install manually." Based on experience, the "Install with a website builder or CMS" option can sometimes cause issues depending on your website's hosting platform. Don’t worry about the code presented for manual installation—it’s straightforward.
8- Copy the code provided and paste it into the "head" section of your website. This area is part of your website's foundational code and ensures data is captured whenever a user visits or interacts with your pages.
9- Save the changes and republish your website. There should be no visible errors or code on your website. If issues arise, contact Google support or reach out to me—I’m happy to help at no charge.
10- Allow 24-48 hours for the connection to finalize. While Google Analytics will begin displaying data after 24 hours, I recommend waiting 5-7 days before reviewing the metrics. Initial data may seem inflated due to a lack of historical context, but after a week, you’ll have more accurate insights to guide your content and actions based on user interactions.
What if you don’t have a website and rely solely on social media?
This is a critical area of data insights that you don’t want to miss out on in the future. While many social platforms offer built-in analytics, they are often limited and lack depth. However, this doesn’t have to be the case.
With the right tools, such as third-party analytics or post-level insights, you can monitor social media performance and guide your next steps based on traffic and engagement. Tools like Google Analytics can even connect to social platforms or track backlinks to provide insights into who is engaging with your content and taking action.
That said, I recommend establishing a website first to create a central hub for tracking and then integrating social media analytics as a secondary measure. Either way, social platforms should provide high-level analytics that still offers value. Let’s dive into how to identify and leverage these insights more effectively below.
Step 3: Identifying Relevant Data Sources
Now that we've established the importance of collecting data and insights, the next step is to identify which data sources will provide the most meaningful information. These could include traffic analytics, sales records, customer feedback, or social media engagement metrics.
The focus should be on selecting sources that align directly with the objectives outlined earlier, rather than gathering data indiscriminately.
Taking this a step further, it's crucial to establish clear parameters for data collection. This involves defining:
- Deciding on the timeframe for data collection
I often find that teams become eager to see their metrics and data immediately after establishing the proper connection. However, as noted in the instructions for setting up Google Analytics, it's important to allow at least 5-7 days for data to populate and align with the platform being used for insights. This timeframe helps build a preliminary data history before diving into key metrics and analysis.
Beyond initial setup, it’s crucial to establish a clear timeline both before and after any data change or audit. For instance, if I want to determine whether a page revision improves follow-through rates, I first need to understand the previous metrics. Then, I would create a timeline to measure the success of the changes. While there’s no universal timeline I can recommend, patience is key during this process. Whether you’re testing over 14 or 30 days, allowing for a longer testing period often leads to more reliable and impactful results.
- Determining the frequency of data gathering
While this may appear similar to the previous practice, there’s an important distinction to clarify. In the first point, I discussed setting a timeline for data collection, such as one month. Here, the focus shifts to determining how frequently the data will be gathered.
For instance, while tools like Google Analytics collect data continuously, it’s essential to narrow the focus to the specific item being tested. This might involve checking the analytics daily or every other day to track changes or trends. These observations can then be documented in a secondary system for easier access and deeper analysis later. However, I wouldn’t recommend checking the data too frequently, such as every hour or even every 12 hours, as this depends on the volume of traffic your site receives. Monitoring too often may lead to unnecessary noise in the data without providing meaningful insights.
- Establishing data quality standards
Not all the data I collect is of high quality. There are anomalies within certain parts of the dataset that I need to identify and address. For example, I once tested whether key mobile app features influenced a user's likelihood to engage with the app over time. Feedback suggested that the feature could be impactful with a few minor adjustments. However, some individuals stated that their likelihood of engagement would not increase, regardless of any changes made. These anomalies likely stem from participants who were already dissatisfied with the solution and had either found a better alternative or an ideal workflow elsewhere.
I believe it's important to approach such anomalies with caution, as they provide insights that, while valuable, do not represent the majority of the data. This highlights the need to establish a standard for data quality to stay focused and ensure the insights I gather are reliable and actionable.
- Identifying who will be responsible for data oversight
Auditing and streamlining data collection can be challenging without the help of automation. Manual efforts to gather and analyze key insights can be time-consuming and inefficient. If automation isn’t a priority for a business owner, I recommend designating one trusted team member to oversee and analyze the data. This individual should follow an established framework for evaluating insights, ensuring they document the source and timeline for each data point collected.
The process of collecting, auditing, and leveraging data is incredibly valuable for any business. However, if done poorly or without attention to detail, it can lead the business down the wrong path. Personally, I rely on data to make informed decisions about the best course of action, and this mindset should apply to anyone managing key data points. Proper engagement with data is essential to streamline future efforts and drive meaningful results.
Step 4: Using Data for Future Outcomes
Let’s take a closer look at my final point: using data to predict and influence future outcomes. As mentioned earlier, data should play a key role in guiding strategic business decisions, whether it’s improving customer relationships or boosting the company’s bottom line. It’s a common misconception that one can collect data without acting on the insights it provides. For instance, even if the data points to a specific metric or course of action, some founders may dismiss it because it doesn’t align with their personal preferences for the business. This mindset can limit growth and innovation.
As a founder, I understand my business better than anyone else. However, ignoring the insights derived from collected data would be a mistake. If the data has been gathered correctly, directly from customers—it should reflect valuable feedback, whether it’s a need for change or an indication to remain consistent. Acting on this information ensures that the business remains relevant and aligned with customer needs.
I strongly encourage anyone investing in data collection to use those insights for strategic decisions actively.
Otherwise, the effort put into gathering data is wasted, and opportunities for growth are likely missed.
When analyzing collected data, I focus on identifying trends that reflect the impact of specific changes I’ve tested. For example, I might change a button color from dull to bright to determine if it increases clicks to the next page.
I also look for insights in areas I may not have previously explored. For instance, while regularly posting blogs on my website, I’ve noticed that some older posts consistently rank among the top pages, driving traffic. This insight encourages me to create more content around those successful topics and to update them regularly, ensuring they continue to provide value to readers.
Ultimately, my goal is to let the data guide my decision-making, whether I’m validating a hypothesis or striving to achieve an ideal outcome like improving click-through rates with a simple design change.
The same principles apply when analyzing social media metrics. I might post daily, but not every post will perform well. By reviewing a month’s worth of data and posts, I can clearly identify which content resonates with my audience and which falls flat. Understanding what my audience values and engages with allows me to refine my approach, keeping their preferences at the forefront. This helps me optimize my content for stronger engagement and deeper connections.
Some may argue that they only post about topics they personally want to discuss, and while I don’t disagree with this mindset, I see it more as a starting point. From there, leveraging data and insights can guide you toward better results over time. By paying attention to what metrics and algorithms reveal about your audience’s interests, you can move beyond guesswork and create content that is both meaningful and effective.
For me, data-driven strategies are invaluable. They eliminate uncertainty and help me focus on delivering what my audience wants, ensuring my efforts are impactful and aligned with their needs.
Building the Foundation for Analysis
Investing time in the initial planning phase lays a strong foundation for all subsequent analysis. This preparation ensures that every piece of collected data has a clear purpose and directly contributes to a deeper understanding of the business. The importance of this step cannot be overstated—it’s like creating a map before embarking on a journey. Without this clarity, businesses risk amassing large volumes of data that offer little practical value. By starting with well-defined objectives and a thoughtful plan, I ensure that my data analytics efforts lead to meaningful insights and actionable outcomes.
Data is an invaluable tool for businesses, enabling founders and teams to make informed decisions based on customer needs rather than assumptions or guesswork.
I believe that data will continue to be a decisive factor in the success or failure of businesses. Neglecting its potential only works to the advantage of competitors who pay attention to what their customers truly want. At the end of the day, it is the customer who ultimately decides which business to support.
There are many factors influencing this decision, but by identifying the key drivers behind customer choices, I can consistently refine strategies to better serve them. Understanding these critical “make-or-break” points allows me to anticipate customer needs and ensure the business delivers value, time and time again.
Key Takeaways:
- Define clear, specific questions before collecting data - replace vague goals like "understanding customers better" with focused queries like "what time do customers make purchases?"
- Allow proper time for data validation - wait 5-7 days after setting up analytics before drawing conclusions to ensure reliable insights.
- Look for patterns in your collected data - track high-performing content and user behaviors to identify what resonates with your audience and drives engagement.
- Let data guide strategic decisions rather than personal preferences - analyze metrics objectively to identify customer preferences and adapt accordingly.
