Introduction to Content Analytics

Transcript

Hi, this is Michelle. Join me for this introduction to content analytics. Measuring content performance isn’t always straightforward. Too often, teams rely on guesswork, leading to inefficient use of time and budget. That’s where content analytics makes a difference. Our focus is on two key questions. How can we measure and understand content performance more effectively? And what specific aspects of content are driving engagement? Content analytics helps us uncover why content works, whether it’s the marketing language, tone, imagery, or even subtle elements like color choices or subject matter. By revealing what resonates with your target audience and why it converts, content analytics unlocks deeper insights to drive smarter content strategies. Generative AI plays a major role in content analytics, offering a deep level of content intelligence. At its core, AI breaks down individual assets into their most granular attributes like colors and background, foreground, and overall color palette. Emotions, like the mood conveyed in visuals. Scenes and context. Is it a winter setting, a beach, or a holiday theme? And objects. AI detects elements like people, animals, trees, and specific products. It also evaluates entire experiences, a combination of assets, messaging, and CTAs, providing a holistic view of how content resonates with audiences. When combined with user behavioral data, these insights create a clear picture of content impact. You can measure how it influences, conversions, and orders. Add to cart and wish list actions and downloads and lead generation. It could also identify hidden opportunities, pinpoint underutilized assets, including content with low impressions but high conversions, detect overused assets that may be losing effectiveness, and ensure every piece of content is strategically placed for maximum impact. By making these connections, you can act with confidence, adjusting strategies, reallocating budgets, and optimizing content placement. Understanding which assets are performing against your goals is essential. Are certain assets underutilized or overexposed? Should specific content be retired, repurposed, or strategically repositioned? Are the right assets placed in high visibility areas for maximum impact? Engagement becomes the next key focus. Which assets are driving the most views and clicks? What specific attributes are making the desired impact? Then there’s connecting content to real business outcomes. What conversion metrics are directly impacted by specific content? How can you better measure ROI on your content budget? Last, there’s leveraging AI for content personalization. By identifying what content resonates with different audiences, you can create hyper-targeted experiences by identifying high-value audiences, publishing insights for activation, and executing personalized campaigns with precision. With Content Analytics, you close the loop between content performance and business impact, turning insights into action. Once you understand how content performance changes over time, you can make smarter decisions about where to prioritize your assets. Your content strategy is no longer based on assumptions. It’s backed by data. The result? A smarter, more effective content strategy that maximizes engagement and conversions while reducing wasteful spend. Thank you for watching this introduction to Content Analytics.