A business can leverage sentiment analysis for growth, even amid market disruptions like those caused by the COVID-19 pandemic, to stay attuned to customer and employee sentiment. Sentiment analysis is, after all, about generating insights from the emotions that people express, in this case, online via social media, reviews, blogs, user-generated videos, et all, to remain relevant in a competitive marketplace.
So let’s look at some very interesting ways in which a business can leverage AI-enabled sentiment analysis to gain intelligent market insights.
1. Social Media Sentiment Analysis
Regular social media analytics give you all the numerical data you need - the number of likes, the number of shares, total number of impressions, mentions, and other statistics. However, these metrics do not actually reveal the reason behind the numbers. They give you no understanding as to why someone shared your post, or why a particular hashtag is trending, unless you manually go through hundreds of posts and read them.
AI-based social media sentiment analysis provides in-depth social intelligence, including both quantitative and qualitative insights. You can keep a tab on what’s trending, predict upcoming market trends based on online chatter, and fashion a more engaging online presence.
By analyzing sentiment in social listening data, you can also identify common characteristics among users who share your posts, based on their publicly available profiles. You can use this data to build and compare buyer personas and develop more targeted campaigns or advertisements.
Companies invest heavily to boost sales through effective social media ads. If there is no direct proportion between your popularity on social media and your sales conversion figures, sentiment analysis helps you find out why, so you can bridge that gap. Thus, you get clever insights for product innovation, new customer acquisition, market gaps, and consumer behavior.
Summary:
You can leverage sentiment analysis for social media marketing to get qualitative and quantitative insights. It tells you the “why” behind the numbers, which in turn helps you develop more effective strategies for better products, higher customer engagement, and improved sales.
2. Customer Sentiment Analysis
Most companies ask customers for reviews and ratings, either in the form of net promoter scores (NPS), star ratings, or remarks on websites like Google Reviews or Trustpilot. Star ratings are infamous for being unreliable, while NPS scores only tell you how likely a person is to promote you.
Open-ended questions in surveys help with this. But the challenge with this data is that, more often than not, the emotion mining tool doesn't have the capability to capture the essence of the feelings expressed. This is because open-ended questions do not come with predetermined answers.
The smart thing to do here, in order to leverage sentiment analysis, is to make sure that you choose a machine learning (ML) platform that is capable of survey emotion mining. This way, you can also analyze sentiment from data such as customer care emails and chatbot histories to see what is irking your customers and what they seem to appreciate.
An ML platform learns from every single time it processes data, thanks to its neural networks. It analyzes every comment and data point by using semantics and in a contextual setting so that no nuance is missed. Therefore, by automating sentiment mining, you not only remove human bias and errors but also employ an AI solution that becomes smarter with each iteration.
Summary:
You can gain key, action-oriented insights from all types of customer experience data through sentiment analysis. This will help you align your business aspects with customer requirements and develop data-backed marketing strategies aligned with trending market sentiments.
3. Video Content Analysis
YouTube holds the distinction of being the go-to channel for most people for anything—from learning music to recipes to repair and maintenance directions. It's not surprising, then, that companies are investing in YouTube ads and learning how to ensure high click-through rates.
Social media platforms like TikTok, Douyin, Facebook, and Instagram Live have also seen a surge in user-generated and marketing videos. Additionally, in a bid to capitalize on untapped global markets, companies are increasingly turning to video for their e-commerce marketing campaigns. These videos contain invaluable data that can be harnessed to gain customer insights.
Video content analysis (VCA) extracts insights from this large volume of video data. It not only gives you key information for customer experience but also competitor intelligence. It does so by processing videos, GIFs, memes, emojis, hashtags, online abbreviations, colloquialisms, etc., and analyzing them for sentiment, just as it would with text data. VCA-enabled logo identification helps you leverage sentiment analysis by showing you where your logo is used, what subject matter it appears in, and in what context.
Apart from this, video AI also helps you manage knowledge by intelligently organizing your video repository. This helps you with semantic search, so you can find the information you are looking for without relying on keywords.
Summary
Video content analysis lends key findings about a brand, the efficacy of its video marketing, and brand associations. It also enables semantic video search. A business can analyze hundreds of videos on channels like YouTube, TikTok, and Facebook and gain granular customer and brand insights.
4. Monitoring and Nurturing Employee Experience
Unlike some companies that inflate Glassdoor reviews to sway market opinion in their favor, you can use sentiment analysis to genuinely build a nurturing, uplifting work environment. This is ultimately the most reliable way to increase productivity and profitability and ensure business longevity.
The way to move forward is to ensure that employees don’t feel neglected, have a support structure for feedback and grievances, and receive adequate opportunities to upskill. With more companies offering remote work as an option, not only due to the pandemic but also as they come to realize the financial perks of virtual offices, there is so much that can be done to encourage virtual employee engagement.
An AI-powered sentiment analysis solution can give you well-rounded insights into various facets of your business setup and your employees’ feelings about them. You can use employee experience insights to analyze sentiment from not only external websites like Indeed and Glassdoor, but also from employee voice data such as internal surveys, exit interviews, performance review notes, and social media data.
Through emotion-aspect co-occurrence analysis, you can know which employee sentiments pertain to which aspects of your company. For example, you can know how often the emotion “trust”, which the machine learning platform would have recognized and captured as a recurring sentiment, occurs with an aspect like “office policies” or “senior management”. Or the aspect “happy” occurs with “vacation” or “team members”.
Summary:
A business can leverage sentiment analysis to enhance employee engagement programs and nurture its human capital. A stellar employee experience can not only retain your star employee but also attract the best talent in a competitive market.
5. AI-powered Brand Reputation Management
Last but not least, a smart way to leverage sentiment analysis is to proactively and effectively monitor and manage your brand reputation with AI. A sentiment analysis platform can help you gather data from a variety of sources and use intelligent machine learning techniques such as natural language processing, optical character recognition (OCR), semantic clustering, and more to provide brand intelligence.
In an era where businesses are plagued by fake products, illegal use of brand logos, and copyright infringement, sentiment analysis of publicly available data such as online news, reviews, and social media chatter can provide insight into people’s perceptions of your brand. An intelligent platform will alert you of spikes in your mentions based on your settings — whether they are for a particular keyword, type of sentiment, or about competing brands.
You can also leverage sentiment analysis to ensure that your brand ambassadors and social influencers are adhering to brand guidelines and to determine the extent to which their engagement with your brand is beneficial to you. In these times of cancel culture, it is paramount that a business is meticulous about the content in its advertising campaigns, as well as anything posted on corporate social media accounts. This is especially important for startups.
Summary:
An AI-powered sentiment analysis platform can give you insights so you can act in a timely manner before a small PR issue becomes a major one. You can ensure that community standards are not violated in online forums, that your brand name is not misused, and that your online reputation management strategy is developed based on concrete data and insights from current and historical data.
Conclusion
Customer experience depends a great deal not only on the product or service but also on the employees customers deal with directly. It also indirectly depends on how an organization functions as a whole — right from quality assurance to supply chain management to teams. Any company that wants to stay ahead of the game needs the vision to adopt AI-enabled capabilities for emotion mining to gain a holistic view of all aspects of its business.
Now is the time to invest in machine learning technologies, whether you are a start-up or a veteran enterprise. Use it in smart ways to leverage sentiment analysis for market intelligence, and see your business flourish.
