It’s no secret that YouTube is a valuable channel for brands to be on as part of their digital marketing strategy. With the ability to publish long and short-form video content and its status as the second-most popular search engine, YouTube is a perfect medium to reach customers in the discovery and consideration stages of the social media marketing funnel.
Paired with a YouTube SEO strategy, social listening and sentiment analysis can help you refine your content strategy for YouTube by tapping into how your audience feels about your brand and content.
In this article, we explore:
- What is YouTube sentiment analysis?
- Why is analyzing sentiment important?
- How to conduct a YouTube sentiment analysis.
- How Dash Hudson provides YouTube audience insights.
What Is YouTube Sentiment Analysis?
Sentiment analysis is a process powered by AI and Natural Language Processing (NLP) that analyzes YouTube users’ comments on your videos and categorizes them into ‘positive’, ‘negative’ or ‘neutral’ sentiments. With these insights at your disposal, brands can quickly glean not only what the audience you reach says but how they say it and, ultimately, if they enjoy the content you produce.
Why Is Analyzing Sentiment on YouTube Important?
As a marketer, it’s critical to perform audience research and analysis to understand your target customer better. After all, if you don’t know what your ideal customer wants, how can you craft a content strategy that will resonate with them?
By only looking at the number of likes or views your videos receive, you’ll fail to understand what your audience is really saying. With readily available comments, brands that practice sentiment analysis can quickly tap into their audience and create a stronger YouTube marketing strategy.
4 Steps To Conduct a YouTube Sentiment Analysis
Collect and Organize Comments
The first step in any analysis is to gather your data. In this case, your comments. It’s important to collect all comments since this helps you easily see trends on your YouTube channel. Understanding how your video content performs on the YouTube Algorithm, rather than viewing comments one-by-one or post-by-post, is key. Connecting your social accounts to a multi-channel inbox is a simple way to do this.
Eliminate Noise From Data
Of course, with any social channel can come spam or bot comments. YouTube does a great job of flagging comments as potential spam by holding them for review, but occasionally some harmful or spam comments can make their way into your inbox. It’s best to hide or delete these comments to protect your brand reputation as well as your viewers. What’s more, these harmful comments can also skew the data around sentiment analysis. Removing the comments gives you a more accurate picture of how real viewers are reacting to your content.
Analyze Data and Sentiment
This is where the lightbulb moments occur. There are two simple ways to gain intelligence on your YouTube strategy using sentiment analysis. First, look at which videos have the highest degree of positive reactions. These are highly engaging and likely something you should produce more of. Conversely, look at which videos have the highest degree of negative reactions. This provides you an opportunity to understand ways to improve. Ask yourself, is it the subject matter, an influencer, or perhaps the way your video was edited that is spurring these negative comments? Secondly, look at the trending keywords popping up in audience comments. These will give you an idea of how your community is speaking and what they’re asking for. Use this valuable data to help guide what content to create and how to speak to your engaged community.
Visualize Findings
Brands that assess which videos contain the most positive and negative audience reactions and performance metrics can put together a holistic, data-backed content report to share with their team. To do this without a sentiment analysis tool likely means manual analysis within a spreadsheet, creating charts and taking screenshots of videos to insert into a slide deck which can be a time-consuming process. However, sentiment analysis tools can significantly automate this process, streamlining the generation of comprehensive and insightful content reports. Not only does this save precious time, but it also ensures higher accuracy in data analysis and interpretation, thereby enhancing the overall strategic decision-making process within the team.
Dive Deeper Into Your YouTube Audience With Dash Hudson
A tool that incorporates end-to-end social listening and sentiment analysis drastically reduces the time it takes to tap into your audience’s valuable insights.
Dash Hudson’s AI-Powered Social Listening solutions can support a brand’s YouTube strategy. In addition to understanding the sentiment of your YouTube audience, brands can monitor their closest competitors' social strategies using Competitive Insights or keep a pulse on how their industry is posting about certain subjects using Topics. Brand Health reports allow brands to create dedicated dashboards to understand how their cross-channel content strategy resonates with their audience via engagement and sentiment metrics in one, easy-to-show-your-boss report.
AI-Powered Social Listening is embedded throughout the platform, bringing powerful insights to the entire social media content lifecycle.
FAQs
What's the most time-consuming part of social listening for YouTube?
Without a proactive tool that can perform social listening searches and social monitoring, the most time-consuming part of social listening for YouTube is performing all the tasks manually. This could include scrolling through every comment on your YouTube posts, refreshing your competitors’ YouTube pages for new content and comments, or performing keyword searches on each native social channel. Dash Hudson’s AI-powered Social Listening solution drastically reduces the time it takes to know exactly what’s happening on social media.
How to perform sentiment analysis on YouTube videos?
With Dash Hudson’s Community Insights tool, you can quickly and easily understand the health of your YouTube channel. Some examples of YouTube sentiment analysis tools are:
- Sentiment applied on all YouTube comments, top (and bottom) performing content by sentiment.
- Most frequently used keywords in comments.
By performing sentiment analysis on YouTube, you’ll be able to tap into the minds of your community to understand them better.
What is the best way to mine YouTube data?
Authenticated third-party analytics software that uses the official YouTube API to provide trustworthy data and, in turn, provide insights on content and community engagement is the best way to mine YouTube data. Data mining via web scraping is not suggested, as this method could violate YouTube’s Terms of Service and legal standards.
