How To Use Instagram Sentiment Analysis For Customer Insights

Instagram sentiment analysis is perfect for customer insights because you can identify sentiments in social mentions, hashtags, posts, comments and videos. With sentiment analysis on Instagram you can discover and attract new target audiences, and improve your brand presence. Many companies already know this. Data shows that the projected marketing spend on Instagram influencer-led marketing programs is estimated at US$8.08 Bn. Currently, there are over one billion user accounts on the platform, and all of them can be harnessed for consumer insights.

Sentiment analysis can improve your operational efficiency because it gives you a peek into the reason behind the good or bad sentiments in posts and comments. That’s why, with the use of an Instagram sentiment analysis solution, you can easily gauge aspects like brand awareness, brand image, and predict consumer behavior.

In this article, we explain how you can implement sentiment analysis on Instagram, and how it can benefit you.

Which formats are used for extracting customer insights from Instagram Social Listening?

The main formats for getting sentiment analysis on Instagram involve posts, comments, hashtags, videos, and Instagram TV (IGTV). Let’s get to know them better.

1. Posts and Comments:

You can explore the JSON data from the URL of a specific account to discover insights like account name, followers, people followed, post number, likes, etc. A web scraper is needed for more in-depth data collection. Instagram’s official API will only provide access to Instagram data that belongs to your account. So in order to get customer insights from other accounts, you’ll need to work outside of Instagram’s API and use a web scraper. A web scraper will automatically extract data from the platform by sending HTTP requests to different web pages you are focusing on, to download them. From there, the data is parsed and saved to a database where you can use visualization software to make sense of the information. One method of scraping Instagram posts and comments is by using Python. Python-based tools like Selenium are very popular among marketers, as it is a very powerful, automated insight-gathering tool that can be used in browsers.

2. Hashtags:

Hashtags are great to extract sentiment analysis on Instagram from. With an Instagram Hashtag scraper like Instascrape, you can go through 22 different data points surrounding a single Instagram hashtag in order to compile data related to those hashtags. This includes commonly associated words and accounts. Apify is an excellent Instagram scraper that can be customized to focus on hashtags, in addition to profiles, comments, posts, and places. The platform has a number of different automation tools in addition to the scraper. The data output format is in JSON.

3. Videos and IGTV:

Reel and IGTV scrapers can be equally as useful. These types of scrapers offer a few different data types that it will compile, such as recent comments, full JSON data, and more. Instascrape is probably the most popular video scraper for Instagram. This tool can scrape long-form videos on IGTV, post videos, story videos, reels, and more. The syntax is simple and provides a flexible API for scraping Instagram data in general.

How do you use an Instagram Sentiment Analysis Solution?

Data from Instagram videos and text needs to be gathered, edited, and processed for text analytics to disambiguate entities. They are then processed for sentiment analysis and the resulting data shown on a dashboard.

Below we explain the steps in which Repustate’s Instagram sentiment analysis solution analyses data from the platform:

• Step 1 - Speech to text transcription All video files meant for sentiment analysis on Instagram are converted into text using a speech-to-text model. Data can be gleaned using web scraping tools. There are open-source scrapers that do this, such as:

  • Instagram Scraper
  • Instaloader
  • Instagram PHP Scraper
  • Instalooter
  • Socialmanagertools lgbot

• Step 2. Caption overlay Videos are broken into frame-by-frame image formats. Any text that appears in these frames is recognized and extracted. Once the scraper finds the captions, it can scrape the last ten or so captions from the page in one instance. The Instagram Graph API and Instagram Basic Display API are good for this purpose.

• Step 3. Image recognition Similar to captions, through its video analysis AI, the model also recognizes logos and images present in the background. Brand names and logos are detected and classified as entities.

• Step 4. Text from comments Any comments accompanying the video content are ingested and processed using Repustate’s Text analytics API. The text analytics pipeline recognizes hashtags, emojis, and other common social media colloquialisms.

• Step 5 - Applying sentiment analysis With all the video, audio, and text data thus gathered, sentiment analysis on Instagram is implemented by Repustate’s sentiment analysis solution, which extracts key topics and themes, and their relative sentiment.

• Step 6 - Visualizing sentiment The sentiment visualization dashboard will show all the insights produced by the Instagram sentiment analysis solution in the form of graphs, tables, and easy-to-read charts. You can see data based on your parameters and also do a comparative analysis of current and historical data.

Applications of Instagram Sentiment Analysis

Business applications include brand monitoring, reputation management, voice of the customer (VoC) reviews, product enhancement, and more. For example, when there is an instance where a marketing/ advertising video receives negative attention, Instagram Sentiment Analysis will allow a company to detect this negativity in real-time so they can remove the material immediately.

Thus, areas that use applications of Instagram sentiment analysis include:

• Overall social media listening

• Customer support

• Brand monitoring

• Reputation management

• Voice of the Customer analysis (VoC)

• Voice of the Employee analysis (VoE)

• Product or service analysis

• Market research

• Competitive analysis

What are the Benefits of Using Sentiment Analysis on Instagram?

Sentiment analysis on Instagram helps you keep track of your brand position and gives you customer insights that you wouldn’t have got unless you conducted a detailed market survey. Instagram sentiment analysis can also help avert a PR crisis and strengthen your branding efforts. Major benefits are as follows:

• Stronger brand performance: You might have thousands of Instagram posts that collect engagements but with no way to actually understand them. Instagram sentiment analysis can give you all of the necessary avenues needed to understand how your business account is doing.
• Better audience: It helps you understand your audience better. You can interpret user engagement, brand mentions, demographic behaviour, and also identify the nuances in emotions.
• Competitor analysis: You can monitor competitors better. Watching how your audience is engaging with your competitors will give you perspectives that you wouldn’t have got otherwise.
• Excellent customer service: Instagram sentiment analysis can help you improve your customer service program and fill in gaps if any.
• Improved product: It can give insights for product enhancement including optimal pricing, new features, and other aspects.
• Deeper engagement: You can develop a deeper engagement level with your customers and bridge the gap between brand leaders, ambassadors, and the actual consumers.
• Focussed marketing: Your marketing and advertising campaigns can benefit enormously with sentiment analysis of Insta comments and videos. It can also help identify potential mistakes in marketing strategies.

Learn more about social media sentiment analysis.

Get customer insights no matter what language

The world is a global village that has been brought together by the internet. That’s why Repustate offers Instagram sentiment analysis across verticals and brands. The Repustate’s sentiment analysis engine understands over 23 languages in the native tongue, leading to the highest accuracy rate possible. Don’t take our word for it the data speaks for itself. You can gain consumer insights from customers across regions, no matter what language they speak. Armed with a more thorough view of your audience, you can now develop a more focussed, data-backed, stellar marketing campaign.