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Leveraging AI to Decode Social Media Customer Behavior

Social media platforms like Facebook, Twitter, Instagram, and others have become an integral part of most people’s lives. Brands and businesses have also realized the power of social media for marketing, customer engagement, and data collection. AI or artificial intelligence is proving to be very useful for brands to analyze customer behavior on social media. AI can process huge amounts of social data to derive actionable insights for brands.

Leveraging AI to Decode Social Media Customer Behavior

Artificial intelligence and machine learning tools are enabling deeper social media analysis that was not possible manually. Some key applications of AI for understanding social customers include:

  • Identifying relevant online conversations around the brand for listening and monitoring. AI can quickly parse through millions of posts.
  • Understanding social media user demographics and psychographics by analyzing their online behavior and interests. This allows better audience targeting.
  • Determining positive, negative or neutral sentiment around brands, products or campaigns. This provides reputation and perception tracking.

 

Listening to Conversations

Brands can use AI-based social listening tools to listen to conversations around their brand, products or services. These tools can quickly analyze millions of social media posts, comments, reviews etc to find relevant conversations. Brands get to know what people are saying about their brand, whether it is positive, negative or neutral. They can identify pain points customers are facing with products and find opportunities for improvement.

With manual analysis of social data, brands could only scratch the surface. But AI tools dig deeper to uncover insights like:

  • Commonly discussed topics, keywords and hashtags around a brand – helps plan content strategy.
  • Competitor benchmarking by analyzing their social media presence and audience engagement levels.
  • Analyzing influencer conversations around the industry to identify networking opportunities.
  • Share of voice analysis to compare brand mentions vs competitors and gauge brand awareness.

 

Understanding Buying Intent

Customers often discuss their buying intent on social platforms. By tracking such conversations around specific products/services, brands can gauge genuine user intent to purchase. AI tools analyze language cues in social conversations to determine which users are more likely to become potential customers. These leads can then be targeted with customized marketing.

Some key ways AI helps in identifying buying intent from social data:

  • Look for product-related keywords, hashtags, tagging businesses, queries on features etc to find interested users.
  • Analyze if the user is comparing products, asking for recommendations, or seeking discounts. These indicate higher intent.
  • Check for signals in content or conversations that the buyer is close to making a decision.
  • Combine social data with CRM data to determine users already in the sales pipeline.

 

Identifying Influencers

Influencer marketing has become very popular on social media. AI tools can identify relevant influencers for a brand based on their niche, followers, content etc. Software can also analyze the engagement influencers get from their audience. This helps brands find the right influencers to partner with for promotions.

AI takes influencer identification to the next level by:

  • Looking beyond basic metrics to find influencers with the best content quality and creativity.
  • Analyzing audience demographics and interests to find influencers that cater to the brand’s target groups.
  • Identifying nano and micro-influencers in a niche who can be cost-effective partners.
  • Using network analysis to find influencers with strongest connections in the industry.

 

Personalizing Content

AI and ML allow brands to segment their social media audience and personalize content for each segment. Bots can be programmed to interact with customers and deliver customized content, offers etc based on interests and preferences. A human-like bot interaction also improves customer experience.

Additional applications of AI for content personalization:

  • Create dynamic ads that showcase products customers are more likely to be interested in based on their social profile.
  • Program chatbots to have natural conversations and maintain context instead of just responding with keywords.
  • Adapt content formatting, tone and visuals based on region, language, gender, age group etc.
  • Generate automated recommendations of related content or products personalized for each user.

 

Analyzing Sentiments

Brands want to know how customers feel about them. AI-enabled sentiment analysis classifies social media conversations as positive, negative or neutral. This helps brands gauge public opinion around campaigns, new product launches, brand reputation etc. Actions can be taken to address negative sentiments.

Some advanced sentiment analysis possible with AI:

  • Granular multilingual sentiment analysis even for nuanced languages like sarcasm and emoji reactions.
  • Aspect-based sentiment analysis to classify sentiment towards specific product features.
  • Analyze how sentiment varies across demographics like age groups, men vs women etc.
  • Sentiment analysis around competitors to compare how your brand fares.

 

Improving Customer Service

Bots and AI tools can be leveraged on social media platforms to automate customer service. Bots can handle common queries on messaging platforms. For complex issues, conversations can be routed to human agents. Quick query resolution improves customer satisfaction.

Here are some other AI applications for better social media customer service:

  • AI chatbots personalized for each user with memory of past interactions and context.
  • Smart tools to identify urgent or priority customer queries and route them faster.
  • Analyzing support conversations to identify recurring issues and pain points.
  • Automated suggestions to chat agents on best responses based on past chat data.

 

Generating Leads

AI software can identify visitors who interact with a brand’s social media to be potential leads. Such visitors can be targeted with lead generation campaigns. Lookalike modeling uses data of existing leads to find similar prospects. High-quality leads improve conversion rates.

More tactical applications of AI for social media lead generation:

  • Build custom propensity models beyond just lookalikes to identify potential leads from social.
  • Analyze leads generated from different social platforms to double down on best channels.
  • Track leads nurtured via social media and attribute their path to conversion.
  • Promptly engage visitors identified as leads via chatbots or targeted content.

 

Forecasting Trends

Analyzing volumes of social data can help spot emerging trends. AI tools can identify rising topics, new influencers, changing interests etc at an early stage. Brands can capitalize on such trends with relevant products and messaging. Being ahead of trends benefits brands.

Some key ways AI aids trend forecasting from social data:

  • Predict content formats and platforms gaining traction to guide platform-specific content plans.
  • Identify niche communities and topics that are growing in popularity before mainstream.
  • Analyze correlation between external factors like events, seasons etc and changing social trends.
  • Forecast how audience interests and pain points are likely to evolve in future.

Measuring Campaign Impact

The performance of social media campaigns can be gauged accurately using AI tools. Marketers get data like clicks, conversions, sales etc on ad spends. Tools even suggest adjustments in campaigns to get better results. Optimization improves ROI on social media marketing.

AI elevates campaign measurement by:

  • Tracking detailed user journeys across platforms to attribute conversions accurately.
  • Separating out the incremental impact of campaigns over organic social presence.
  • Optimizing targeting over campaign lifespan based on performance.
  • Predicting expected campaign metrics to set benchmarks for success.

 

Summary

AI and ML technology enables brands to extract value from social media data to understand their customers better. Right from listening to conversations around the brand to measuring campaign performance, AI is a powerful tool. It enhances brands’ ability to identify new opportunities and mitigate risks well in time. AI delivers actionable insights from social media to craft targeted marketing strategies.

 

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AI for social media, Customer Behaviour, Predictive social analytics, social media analytics, Social media listening tools
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