How do you leverage AI and machine learning for video content analytics and metrics?

1 Why video analytics matter

Video analytics are the process of collecting, measuring, and interpreting data from your video content. They help you understand how your audience engages with your videos, what they like and dislike, and how they respond to your calls to action. Video analytics can also help you identify trends, patterns, and insights that can inform your content creation and distribution decisions. By using video analytics, you can optimize your video marketing goals, such as increasing brand awareness, generating leads, or driving conversions.

2 How AI and machine learning enhance video analytics

AI and machine learning are technologies that enable computers to learn from data and perform tasks that normally require human intelligence. They can enhance video analytics in several ways, such as automating the extraction of metadata from your video content, providing advanced analytics, and generating insights and recommendations. This can help you categorize, tag, and index your videos more efficiently and accurately, understand the context, content, and quality of your videos more deeply and comprehensively, and improve your video strategy and performance more effectively and dynamically.

3 What video metrics to track

When tracking video metrics, there are several important ones to consider, such as views, watch time, completion rate, click-through rate, and conversion rate. Views can indicate the reach and popularity of your video content, while watch time can indicate the retention and engagement. Completion rate can show the satisfaction and relevance of your video content, and click-through rate can indicate the effectiveness and persuasiveness. Lastly, conversion rate can show the impact and value of your video content.

4 How to collect video data

Various tools and platforms can help you collect video data, such as video hosting platforms like YouTube, Vimeo, or Wistia, which provide built-in analytics and dashboards. These can track basic metrics, such as views, watch time, and completion rate, as well as more advanced metrics, such as demographics, sources, and devices. Video marketing platforms, such as Vidyard, Brightcove, or HubSpot, integrate with video hosting platforms and provide more comprehensive and customized analytics and reports. These can track more specific metrics, such as click-through rate, conversion rate, and attribution, as well as features, such as interactive elements, lead capture, and personalization. AI and machine learning platforms, such as Cloudinary, Valossa, or Vidrovr, enhance video analytics with metadata extraction, advanced analytics, and insights and recommendations. This helps to understand video content and data more deeply and intelligently, as well as optimize video strategy and performance more dynamically and effectively.

5 How to analyze video data

Once you have collected your video data, you need to analyze them to derive meaningful and actionable insights. To guide your analysis, you should first define your video marketing goals and key performance indicators (KPIs). Then, segment your video data by relevant criteria, such as video type, topic, channel, audience, or campaign. Visualizing your video data using charts, graphs, or tables can help you identify trends, correlations, and distributions. Additionally, you can use AI and machine learning tools, such as sentiment analysis, topic modeling, or anomaly detection, to interpret your video data. Finally, you can test and experiment with your video content and data using AI and machine learning tools, such as A/B testing, multivariate testing, or reinforcement learning, to optimize your video content and data.

6 How to use video data

The final step is to use your video data to improve your video strategy and performance. You can use this data to inform your content creation and distribution decisions, such as identifying topics, formats, styles, and channels that resonate with your audience. Additionally, you can use your video data to personalize your video content and experience, segmenting your audience, tailoring your message, and customizing your call to action. Finally, you can use your video data to measure and optimize your video marketing goals and KPIs, tracking and evaluating your video performance, identifying and addressing your gaps and challenges, and testing and implementing your changes and improvements.