Creating a content scorecard is essential for any brand looking to measure the effectiveness of its content. It combines both quantitative and qualitative metrics to provide a comprehensive assessment. While metrics like page views and engagement give insight into performance, they don’t tell the entire story. A content scorecard steps in to bridge this gap by providing a detailed evaluation, offering a nuanced understanding of what works and what doesn’t.
A content scorecard marries qualitative and quantitative assessments. Quantitative evaluations are based on metrics such as views, engagement, and SEO rank. Qualitative evaluations are derived from criteria like readability, accuracy, and voice consistency. This dual approach allows for a well-rounded view of your content’s performance, helping you to make informed decisions about what content to keep, update, or discard.
1. Define Key Metrics
To begin creating a content scorecard, the first step is to define the key metrics that will be used for evaluation. Understanding the objective of each content piece is crucial for determining what to measure based on its purpose. For instance, consider a landing page: if a high amount of time is spent on a landing page, it might indicate that users are struggling to find what they are looking for. On the other hand, a long time spent on a detailed article or white paper is a positive reflection of user engagement.
Metrics you might consider include exposure (content views, impressions, and backlinks), engagement (time on page, clicks, ratings, comments), conversion (purchases, registrations for gated content, return visits), and redistribution (shares, pins). It is important to be specific with your content asset’s goals and to align these goals with the chosen metrics. This tailored approach will allow for more accurate and useful assessments.
After determining which metrics to focus on, you will need to set up a system to track these metrics. This may involve using tools like Google Analytics for web traffic, social media dashboards, or email marketing software. The key is to ensure that these tools can provide consistent, reliable data that can be used for ongoing assessments.
2. Establish Benchmarks
Once the key metrics are defined, the next step is to establish benchmarks. Benchmarks are essential as they provide a point of reference against which content can be measured. You can identify industry standards by looking at data available from sources like the Nielsen Norman Group. Additionally, social media and email marketing tools often provide engagement benchmarks by industry. Internal benchmarks, based on your organization’s marketing history, can also be valuable.
Creating a benchmark reference chart involves listing the key metrics and the parameters that define different levels of performance. For example, for the metric ‘page views,’ you might create a scale of 1 to 5, with ‘1’ representing less than 2% page views and ‘5’ representing more than 5% page views. Each metric should be broken down in this way to create a comprehensive benchmark reference chart.
With these benchmarks in place, you will have a clear understanding of what constitutes good, average, or poor performance. This will make it easier to compare individual content pieces and identify areas for improvement.
3. Build Quantitative Analysis Worksheets
Next, it’s time to build quantitative analysis worksheets. These worksheets will be used to track the quantitative metrics defined earlier. Start by creating a “quantitative benchmarks” worksheet. This worksheet will serve as a reference sheet, listing the key metrics and ranges for each score from 1 to 5, based on the benchmarks established.
The second worksheet to create is the “quantitative analysis” worksheet. This should include columns for the content URL, topic, and type, followed by columns for each quantitative metric (e.g., page views, clicks, engagement). Populate this worksheet with details for each piece of content and calculate the scores for each metric using the benchmark reference sheet.
With the quantitative analysis worksheets complete, you will have a clear, data-driven understanding of how each content piece performs. This quantitative evaluation will form one half of your content scorecard, providing a solid foundation for further qualitative analysis.
4. Formulate Qualitative Success Criteria
After establishing a quantitative framework, the next step is to formulate qualitative success criteria. These criteria will be used to assess each content piece on factors that are not easily quantified. A 5-point scale is typically used for this qualitative assessment. Key areas to evaluate include consistency, clarity, accuracy, discoverability, engagement, relevance, and authenticity.
Consistency looks at whether the content is in line with the brand voice and style. Clarity and accuracy check if the content is understandable, accurate, and current. Discoverability evaluates if the layout supports key information flows, making essential information easy to find. Engagement assesses whether the content employs techniques to influence or engage visitors. Relevance determines if the content meets the needs of its intended audience. Authenticity ensures that the content is original and genuinely reflects the brand.
Standardizing these criteria allows for a systematic review of each content piece. Using a set scale and consistent questions helps in making fair comparisons across different types of content, ensuring a balanced evaluation.
5. Standardize Qualitative Assessment
To ensure the qualitative assessment is consistent, you will need to standardize the process. Create a “qualitative questions” worksheet that includes columns for the content URL, topic, and type. Add additional columns for each category and its corresponding questions. The final column should be used for calculating the average score based on the responses.
For each content piece, answer yes-no questions based on the established criteria. For instance, under clarity and accuracy, you might ask, “Is the content understandable to all user types?” and “Does it use appropriate language?” One point is awarded for each “yes” answer. The scores are then averaged for each category to provide a clear qualitative evaluation.
Having a standardized set of questions ensures that all content pieces are evaluated evenly, reducing the risk of bias. This step is crucial for generating reliable qualitative data, which will later be combined with the quantitative metrics to form the content scorecard.
6. Assemble Qualitative and Quantitative Data
After gathering both qualitative and quantitative data, the next step is to assemble this information into a comprehensive scorecard. Create a new spreadsheet that merges the qualitative and quantitative scores. This will allow you to see a side-by-side comparison of each content asset’s performance.
Arrange the spreadsheet so that each content piece has its own row, with columns for the average qualitative score and the average quantitative score. This setup provides a holistic view of how each asset is performing, making it easier to identify strengths and areas for improvement.
With this complete scorecard, you will have a detailed, data-driven overview of your content. This comprehensive approach allows for more nuanced decision-making, ensuring that both the quality and performance of content are considered in future strategy planning.
7. Analyze Results and Determine Next Steps
With the assembled data at hand, it’s time to analyze the results and determine the next steps for each content asset. Compare the qualitative and quantitative scores for each piece to understand its overall performance. For example, if a content asset has a high qualitative score but a low quantitative score, it may indicate that while the content is good, its distribution plan needs improvement.
Decide on actions based on these insights. For content with higher qualitative than quantitative scores, reconsider the distribution plan. This might involve trying new channels, different posting times, or even repurposing the content in alternative formats. For content with higher quantitative scores but lower qualitative performance, revisit the content to improve its quality through rewrites or additional data-backed research.
Low scores in both areas usually indicate that the content should be removed and avoided in the future. Conversely, content with high scores in both areas should be promoted and reused as much as feasible. Regular updates to the content plan will ensure that successful content types are replicated in future efforts.
8. Utilize AI Assistance (Optional)
If you’re looking to streamline the process further, consider using AI tools to assist with content scoring. Machine learning can help by extrapolating scores for additional content based on patterns identified in the original scorecard sample. Show the AI tool a series of content pieces along with their respective scores. The tool can then score similar content using the same logic.
However, it’s important to validate these initial AI-generated scores with an expert review. This ensures that the scores are accurate and reliable before any actions are taken. While AI can save time and provide valuable insights, human oversight remains crucial to maintaining the quality and accuracy of the assessments.
9. Implement and Refine the Process
If you want to make content scoring more efficient, think about leveraging AI tools. By using machine learning, you can extrapolate scores for new content based on patterns identified in an initial set of scored materials. To do this, show the AI tool various content pieces and their corresponding scores. The tool will then use this information to evaluate and score similar content using the same criteria.
While AI can significantly reduce the time and effort it takes to score content and provide valuable insights, it’s still essential to validate these AI-generated scores. Have an expert review the initial scores to ensure they are accurate and reliable before making any decisions or taking action based on them. This step helps maintain the quality and accuracy of the assessments.
AI tools can be incredibly powerful in improving efficiency, but the importance of human oversight cannot be overstated. The expertise and judgments of human reviewers are indispensable in ensuring that the AI’s outputs align with the expectations and standards of your content evaluation process. This combination of advanced technology and expert human review creates a balanced and effective approach to content scoring that optimizes both speed and accuracy, ensuring your end results are dependable and actionable.
