The best AI-powered tools for social listening

May 21, 2024

AI-powered social listening is revolutionizing how companies gather insights from the vast expanse of social media content. Social listening means analyzing social media posts to understand how customers perceive and discuss brands. 

By leveraging artificial intelligence, businesses can tap into platforms like Twitter, Facebook, and Instagram to uncover valuable trends and sentiments. In this blog post, we will explore the power of AI-driven social listening and how it is reshaping the marketing landscape by providing actionable insights derived from social media data.

6 Ways to uncover customer sentiment and trends with AI

AI can decipher and categorize customer feedback, reviews, and online discussions using natural language processing and machine learning algorithms.

1. Automate sentiment analysis

AI-powered sentiment analysis tools can analyze social media posts, reviews, and customer feedback and summarize the sentiment behind them. Marketers can use this information to gauge customer satisfaction, identify trends, and make data-driven decisions.

You can incorporate sentiment analysis into your daily workflow by setting up dashboards that monitor and report the sentiment of mentions across social platforms in real-time. React promptly to negative sentiments with customer service efforts, and leverage positive sentiments in your marketing campaigns. Check out these tools to help you automate sentiment analysis:

  • Brandwatch: Offers extensive sentiment analysis capabilities, allowing marketers to monitor and analyze conversations about their brand across the internet. It provides insights into whether those conversations are positive, negative, or neutral.
  • Sprout Social: Sprout Social analyzes social media messages and mentions to gauge public sentiment.
  • Hootsuite Insights: Powered by Brandwatch, Hootsuite Insights offers real-time sentiment analysis across multiple social media platforms, enabling marketers to monitor the emotional tone of conversations related to their brand.

2. Create alerts for emerging trends

Tracking emerging trends helps businesses spot opportunities or threats early on. By staying ahead, businesses can adapt strategies swiftly and mitigate potential crises.

Set up alerts for specific keywords, hashtags, or topics related to your industry. Review these alerts daily to quickly pivot your strategy or content creation to align with emerging trends. These are some of the most common tools that marketers use to keep an eye on emerging trends:

  • Google Alerts: Allows marketers to monitor the web for new content about specific topics, providing email alerts whenever new mentions are found. It's useful for tracking industry news and brand mentions.
  • Talkwalker Alerts: A more advanced tool than Google Alerts, offering in-depth insights and alerts for keywords across the internet, including social media platforms. It's powerful for identifying emerging trends relevant to your brand.
  • Mention: A real-time media monitoring tool that notifies marketers about mentions and keywords across websites and social media. It's useful for tracking brand mentions, competitors, and industry trends.

3. Topic modeling

Artificial Intelligence can uncover prevailing themes and subjects within social conversations, feedback, and online content. AI-driven topic modeling tools go beyond simple keyword analysis, employing natural language processing (NLP) to understand context and recognize nuances that simpler tools might miss. 

This facilitates a more granular and accurate understanding of consumer interests, behaviors, and preferences, enabling marketers to tailor their strategies with unprecedented precision. Use topic modeling tools to analyze social media conversations and customer feedback. Segment the data by demographic or channel to  tailor your campaigns to different audiences. Integrate findings into your content calendar or R&D briefings for product improvements. These two tools can help you model topics more effectively:

  • Quid: Visualizes big data by mapping out topics and trends from news articles, blogs, forums, and more. Quid's topic modeling capabilities allow marketers to identify key themes and narratives emerging within their industry.
  • MonkeyLearn: An AI platform enabling text analysis through machine learning models. Marketers can use MonkeyLearn for topic detection and understanding key themes and sentiments within customer feedback or social media conversations.

4. Image and video analysis

With the rise of video content on social media, image and video analysis tools can unlock insights that text-based tools overlook. This is crucial for understanding how your brand is perceived visually and for monitoring branded content usage.

Use image recognition technology to monitor your brand logo, products, or promotional materials across social media platforms. Use these insights to guide your visual content strategy and enforce brand guidelines. Explore these tools to see if they are right for your brand: 

  • Brandwatch (again): Offers image recognition capabilities, allowing marketers to find and analyze images related to their brand across the internet. This is useful for monitoring brand visibility and the context in which a brand is being discussed or depicted.
  • Talkwalker (again): Provides video and image analytics, enabling brands to track visual mentions and sentiment. Its AI-powered image recognition technology identifies logos, scenes, and activities in images and videos.

5. Predictive analytics

Almost a fifth of marketers are already using AI for predictive analytics. AI algorithms can analyze historical data to predict future customer behavior and trends. Marketers can leverage predictive analytics to anticipate customer sentiment, identify potential issues, and proactively address customer needs, allowing for more targeted and effective marketing campaigns.

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Incorporate predictive insights into strategic planning sessions. Use historical trends to inform future campaigns, product developments, or customer engagement strategies. These tools might be helpful: 

  • Zignal Labs: Offers a predictive analytics suite that forecasts trends and potential crises before they happen. This allows marketers to adjust strategies proactively.
  • Sprout Social (again): Its reporting and analytics features, including predictive analysis, help anticipate future social trends and consumer behaviors, informing more strategic decisions in marketing planning.

6. Creating customer personas

Segmenting customers is a common use case for AI-based marketing software and is currently being used as such by 44% of businesses. Social listening helps marketers segment their audience and create detailed customer personas based on social media data. Aggregate social media data to flesh out existing personas or to create new ones. Look for patterns in interests, sentiment, demographic data, and engagement behaviors. Use these insights to refine marketing messages, product features, or targeted advertisements.

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These tools can help marketers create and manage customer personas easily: 

  • HubSpot: Features analytics tools that can be used to track visitor behavior across your website, social media channels, and more. The insights derived can be used to create detailed customer personas.
  • Audiense: Specializes in audience intelligence and segmentation, helping marketers discover new target audiences and refine existing customer personas based on social data.

How Marin can offer you greater insight into your customers’ minds

Marin provides a unified platform for all your data and analysis. Data collected by social listening tools can be fed into Marin and associated to specific keywords or audiences to help you understand the full picture when analyzing the performance of your paid media campaigns. Schedule a demo to learn more about Marin’s AI-powered campaign management and optimization suite.

Lauren Neels

Marin Software
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