How to Filter Signals From Noise in Social Listening Data

In 2025, marketers will have more data than ever before, thanks to various tools available, including social media analytics, third-party tools, and AI tools. However, this also means that they are more likely to face information overload. According to one study, poor-quality data costs businesses at least $12.9 million annually. The study notes that only 5% of your target audience is actively looking to make a purchase.

For optimal results, brands need to disregard insufficient data and instead focus on accurate, actionable, and timely signals that lead to informed decisions. Good data is usually relevant, correct, complete, and consistent. Such data helps to harness the power of social listening. This article will help you sort out the essential signals from the noise in your social listening data.

Understanding the Differences Between Good Data and Bad Data

Data is only as valuable as its quality and how well it can be implemented. However, poor-quality data remains one of the biggest hurdles, with 46% of digital strategists suggesting that it's their biggest challenge when trying to leverage advanced analytics. Good data can be defined as: 

• Complete and accurate. It's essential to ensure that the information is comprehensive and error-free. 
• Consistent. The data should be able to align across different systems while ensuring there are no discrepancies. This is necessary as multiplatform cohesion is key.
• Relevant and timely. The data should be updated and applicable to the current customer needs.

On the other hand, poor-quality data is usually marked by:

• Reports with conflicting results.
• Incomplete or missing fields.
• Outdated information that is no longer applicable.

It is worth noting that insufficient data doesn't just happen but occurs as a result of specific errors, which can be a result of human mistakes and poor management practices. For instance, in Cook County, Illinois, data on dog licensing contained over 250 misspellings of the word "Chihuahua." This was a result of the free-text entry used instead of a standardized dropdown menu. There are several contributors to insufficient data, such as: 

• Manual entry of data leading to human errors.
• No standardization, resulting in wrong formats or measuring units.
• Bias in sampling. Leads to key groups being excluded from the data.
• Confirmation bias. Data interpretation to find out if there are any pre-existing biases.

Risk of Using the Wrong Data

If you use incorrect data, your business can face various risks, including financial losses, customer dissatisfaction, and operational inefficiencies. According to Gartner data, poor-quality data costs businesses approximately $12.9 billion annually. Some of the risks associated with poor-quality data include:

• Budgeting and forecasting errors.
• Low efficiency and productivity.
• Low customer retention and trust
• Regulatory and legal implications

Tips For Ensuring Quality Data in Social Listening

After collecting data through social listening, focus on the key signals that matter. This will enable you to cut the noise and focus on insights that bring meaningful results. If data signals cannot produce measurable outcomes, they cannot provide essential insights. Therefore, check out data signals that are actionable to show you trends and the clear direction. For data to meet your time, it should meet three criteria:

• Actionable. You should be able to collect and measure your data.
• Trendable. The data should exhibit a consistent pattern over time.
• Directional. The data should indicate whether sentiments are positive or negative.

These characteristics should help you identify the factors and transform raw data into critical insights to guide your decision-making.

Steps in Ensuring Quality and Accurate Data in Social Listening

It's essential to choose the right social media listening tool to ensure data accuracy and quality. Many software and platforms can help users collect, analyze, and organize data from different sources. However, some tools will yield better results than others. When finding a good tool, consider various factors such as reliability, cost, usability, coverage, and functionality. Ensure that the tool also aligns with your objectives for collecting the data.

Define Your Goal

Before defining your queries and keywords, you will need to determine the role of social listening. Is it for threat detection, customer feedback, or brand health? After identifying your objective, you can proceed to find keywords tailored to that goal. 

Define the Correct Queries and Keywords

You will also need to define your social listing queries and keywords, which you plan to track on social media. After finding the keywords, filter them to refine your search. When selecting the keywords and queries, ensure they are specific, relevant, and comprehensive. Also, ensure that the keywords aren't too vague, broad, or ambiguous.

Data Cleaning and Validation

Before you start the data analysis process, you will need to clean and validate the data by removing any duplicate, irrelevant, or spammy comments and posts. To validate the data means it should be complete, accurate, and consistent. By cleaning the data, you can ensure that you only work with reliable data that reflects your target audience and market. 

Choose the Method and Sources

It is essential to utilize various sources and methods for your social media listening. These are the approaches and techniques you will use for data analysis, including topic modeling, sentiment analysis, and network analysis. The sources refer to the platforms and channels used for data collection, such as Facebook, Instagram, and Twitter. Ensure that you employ various methods to capture the complexity and diversity of social media behaviors and conversations. 

Data Interpretation and Finding

You will need to interpret and report the findings from the social media listening. Your goal in analyzing the data is to make sense of it and the generated analytics. It will help you to identify the insights, trends, implications, and patterns they find. 

To report your findings, you will need to communicate your results and recommendations to various stakeholders, including colleagues, managers, and clients. These findings should be interpreted in a clear and actionable way. Use data, evidence, and examples to support your conclusions. 

Optimize and Update the Strategy

Based on the insights you gather from social listening, you can now refine your strategy. This should involve revising your goals, objectives, and research questions in light of the new information or knowledge gained. You can also optimize the social listening strategy by refining your keywords, queries, tools, sources, and methods based on the evaluation and feedback you receive. The strategy optimization will ensure that you always gain new insights into improving social media listening. 

Final Thoughts

Social media listening is a crucial step in monitoring and analyzing online conversations about your brand, competitors, and industry. This can provide you with essential insights into the customer’s opinions, preferences, needs, and feedback. However, for the best results, you need to ensure the accuracy and quality of the data obtained from social media listening. By following our guide, it should be possible to do so.