Social Listening For Instagram Insights
Instagram social listening allows you to mine data from both videos and their comments for customer insights that go beyond standard dashboard analytics of likes and shares. This allows you a deeper understanding of not only what content resonates with your audience but also gives you granular product insights that help you improve your products, services, customer experience, and prepare for emerging market trends.
Which Sources Of Data Help In Instagram Social Listening?
There are three major sources on the Instagram platform that we can extract customer insights from. We can do it through Instagram dashboard analytics, from the comments and hashtags accompanying the videos, and from the content in the video itself, which we can analyze for Instagram sentiment analysis.
Let us get into the details of these sources.
1 - Instagram Dashboard
You can track your performance in the Instagram Professional Dashboard and get insights into your outreach traffic. The dashboard can tell you how many people interacted with your content and whether this percentage was less or more than previous times. This gives you an idea if your content was relevant enough to resonate with your audience. The point to note, however, is that it does not tell you whether these interactions were because of positive or negative feelings about your content.
You can get other detailed information for a dive deeper into content interaction and accounts reached stats. An interesting thing about the Instagram Dashboard for professional accounts is that it also tells you a breakdown of audience profiles in terms of gender, locations, and activity times. This helps you figure out how to create more relevant content and what times are optimal for posting content on your feed for maximum engagement.
You can discover various aspects of Instagram social listening that can help you improve your interactions on the dashboard by exploring Instagram’s educational content that is available in the form of user guides, tips, and tricks.
2 - Instagram Comments & Hashtags
Comments and hashtag-based content can give you in-depth customer insights when they are processed by a sentiment analysis and text analytics platform. You can parse comments with the help of a web scraper or you can download the comments and upload them as a .csv file.
Instagram’s web scraper will only allow you to download your data but if you want to compare and analyze comments on videos and hashtags from other profiles you will need to use third-party web scraping tools. These tools will collect and download the relevant data on your social video analysis platform where you can analyze sentiment and see the results on a visualization dashboard. Hashtags can give you multiple videos, and you can analyze all comments accompanied by those videos seamlessly if you’re using a robust sentiment analysis API.
The other important aspect of a hashtag is that each hashtag itself can be a treasure trove of information when parsed by a web scraping tool. For example, Instascrape can give you more than 20 data points around which you can extract relevant customer experience insights data.
3 - Content in Videos
Instagram social listening also, more importantly, enables you to analyze content in videos, which you can use for customer insights and to measure Influencer effectiveness. Social video content analysis classifies the data in Instagram videos into themes, topics, and aspects so that it can process it for semantics and sentiment analysis. Further to this, Repustate’s Instagram sentiment analysis platform can process this video content in 23 languages, without the need for translation. This means, however diverse your audience demographic, you can still get all the customer and market insights you need.
The video sentiment analysis API first turns all video content into text format. It scans the entire video by breaking it into frames and captures any captions to extract any text present. Once this is done, it processes them through text analytics, whereby machine learning algorithms extract topics and entities from the text, while named entity recognition (NER) identifies important places, people, brands, currencies, etc that are mentioned in the video.
All this accumulated information is analyzed for sentiment to give an overall score of the video in relation to the subject, as well as sentiment for entities and topics the platform has identified. You can view all the insights on a customer experience dashboard to discover sentiment trends, market gaps, customer intent, competitor overview, and other key findings.
Further in the article, we will see examples of the detailed analysis a video content tool can provide to analyze Instagram for social listening.
Learn more about social media sentiment analysis.
How Can You Do Instagram Social Listening?
You can benefit from Instagram social listening by getting customer insights from both video data as well as the comments that follow it. As mentioned earlier, the machine learning platform does this through a coordinated process that comprises certain stages.
It extracts all the video data by turning all the audio into text. It also captures all the captions in the video and extracts any text present.
The platform now extracts all the text in comments including special characters like emojis. Repustate’s social media listening tool analyzes emojis for sentiment too, unlike other platforms that ignore special characters when extracting text. Emojis can help detect the real intent of the comment and help the algorithm find out if it is a positive or sarcastic comment, which it will then classify as negative.
All the collected Instagram social listening data is now analyzed for customer sentiment this includes overall sentiment as well as sentiment per aspect, entity, and topic.
All the insights from this voice of the customer analysis are presented on a visualization dashboard.
Some of these insights are as below.
1. Total volume of sources
If you are only analyzing Instagram for social listening as we have done for this example, you will get a source volume as below. The sentiment per source will tell you how much of that data was positive, negative, or neutral. Positive sentiment is coded green, negative is red, and neutral is identified by blue.
2. Language detection and sentiment analysis
In this example of Instagram for social listening, Repustate’s platform discovered 10 languages in the comments and video combined. The graph below shows you the percentage of the languages, the majority of which is English.
The second graph shows the percentage of positive, negative, and neutral sentiment in comments in particular languages. In the second bar, you can see question marks and the corresponding sentiment as 100% blue, which means neutral. The question marks are in relation to certain text in the combined data that do not reflect any emotion.
3. Total sentiment score
We can see that the total sentiment score for the data source is 68%, and it all appears to have originated during the time period between mid-Dec 2021 and Jan 2022. This can give an indication to marketers that there must have been some activity during that time that resulted in the particular sentiment from consumers.
Repustate’s Instagram social listening platform gives you all the advantages of artificial intelligence-powered social media sentiment analysis to foster more efficient social marketing campaigns and a deep dive into understanding your product through the eyes of the consumer. The solution is available on-prem as well as a cloud-based platform.
It can be highly customized to your business requirements, and once trained, gives you the most accurate, high-precision customer insights available. With capabilities like search inside video, semantic clustering, native natural language processing, and others, it gives you results quickly and efficiently, at your fingertips.