AI-Led Social: Going from listening to interaction
- Part 1 AI-Led Social: Going from listening to interaction
- Part 22025 social media landscape for brands trying to implement AI
- Part 3How many social media channels can you name in one minute?
- Part 4Customer engagement metrics or brand visibility KPIs?
- Part 5AI-Led Social: Going from listening to interaction (copy) (copy) (copy)
Episode Chapters
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00:00: Social Media Response Importance
Research shows that brands must respond quickly on social media or risk losing customers to competitors.
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01:15: From Passive to Conversational
AI is transforming social media from passive monitoring to active engagement by helping brands find valuable conversations and respond at scale.
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02:00: Engagement Over Publishing
The conversation explores how meaningful interaction with customers is becoming more important than simply broadcasting content.
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03:15: Social Listening Best Practices
Effective social listening requires identifying important conversations and buying signals specific to each brand's needs.
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04:00: Mining Organic Conversations
Finding and engaging with existing conversations about topics related to your brand can be more effective than creating new content.
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06:15: AI-Powered Response Generation
Retrieval augmented generation combines brand guidelines with language models to create factually and tonally correct responses.
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08:00: Managing Brand Reputation
Clear social media policies help brands distinguish between criticism and toxicity while maintaining appropriate engagement.
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10:30: Human Oversight in AI Responses
Legal teams and technology limitations currently require human review of AI-generated responses to ensure appropriate communication.
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12:00: Amplifying Positive Engagement
Removing negative content creates space for positive interactions that can be further amplified through strategic engagement.
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13:30: Platform Algorithm Changes
Social media platforms are increasingly promoting positive content, shifting away from the old belief that controversial content drives engagement.
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Episode Summary
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AI-Led Social: Going from listening to interaction
Introduction
In this episode, Matthew McGrory, CEO and co-founder of Arwen.AI, explores how artificial intelligence is transforming social media management from passive monitoring to active engagement. With his extensive background in tech entrepreneurship and digital transformation, McGrory offers valuable insights into how brands can leverage AI to identify meaningful conversations, respond at scale, and build stronger customer relationships through social media interactions. -
The Shift from Broadcasting to Conversation
Social media has evolved beyond being just a publishing platform. McGrory emphasizes that the real opportunity lies in engagement rather than simply pushing content: "What we are really seeing is brands are finally realizing that social media is about being social, about having conversations." Despite this opportunity, only 7% of top B2C brands are meaningfully engaging with their audiences on social platforms. This disco ect is significant, especially considering that 73% of users report they'll buy from a competitor if a brand doesn't respond immediately on social media. -
Finding the Golden Needles in the Haystack
AI technologies are revolutionizing how brands identify relevant conversations. Using techniques like retrieval augmented generation (RAG), companies can now efficiently scan social platforms for buying signals and engagement opportunities. McGrory explains that brands need to understand which conversations matter most to their business objectives, whether those are product inquiries, positive brand mentions, or specific customer questions. AI helps filter through the noise to find these "golden needles" in the haystack of social media comments, allowing marketers to focus their attention where it matters most. -
Personalized Engagement at Scale
One of AI's most powerful applications in social media is enabling personalized interactions at scale. By combining a brand's existing content (guidelines, FAQs, customer service scripts) with large language models, companies can generate responses that are both factually accurate and tonally consistent with their brand voice. This approach allows social media managers to have 80% of response content created for them, which they can then review and customize before posting. The result is more efficient engagement without sacrificing the human touch that customers expect. -
Managing Brand Reputation
McGrory makes an important distinction between criticism and toxicity when managing negative content. He recommends that brands establish clear community policies about acceptable conversations on their cha els. While toxic content (abuse, unsafe material) can be removed, criticism should be addressed with empathy. "You should accept the criticism, have empathy for the client's experience with your brand or with your product or with your service," McGrory advises. He shares how dating app Hinge improved their App Store rating by 0.9 points simply by responding to reviews with empathy, demonstrating the tangible business impact of engagement. -
Amplifying Positive Engagement
Creating a positive social environment is similar to Patrick Swayze's role in "Roadhouse" – removing troublemakers to create a welcoming atmosphere where positive interactions can flourish. McGrory notes that social platforms like Meta are now algorithmically promoting positive content, contrary to the old belief that controversial content drives engagement. By using AI to identify and amplify positive interactions while filtering out negative ones, brands can create virtuous cycles of engagement that benefit both their community and their visibility on platforms. -
Key Takeaways
AI is transforming social media from a broadcasting cha el to an interactive engagement platform. By implementing AI-powered listening tools, brands can identify relevant conversations, respond with personalized messages at scale, and create positive environments that foster meaningful customer relationships. While human oversight remains essential, particularly for nuanced situations, AI tools can dramatically increase efficiency and effectiveness in social media management. For marketing professionals, the message is clear: social media success increasingly depends not just on what you post, but how well you listen and respond. -
- Part 1 AI-Led Social: Going from listening to interaction
- Part 22025 social media landscape for brands trying to implement AI
- Part 3How many social media channels can you name in one minute?
- Part 4Customer engagement metrics or brand visibility KPIs?
- Part 5AI-Led Social: Going from listening to interaction (copy) (copy) (copy)
Up Next:
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Part 1AI-Led Social: Going from listening to interaction
Social media requires interaction, not just monitoring. Matthew McGrory, CEO of Arwen.AI, explains how AI transforms social channels into conversation hubs by identifying buying signals and automating personalized responses. He demonstrates how retrieval augmented generation can craft brand-appropriate replies while maintaining human oversight, and reveals why positive engagement is now being algorithmically prioritized across major platforms.
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Part 22025 social media landscape for brands trying to implement AI
In this lightning round episode of the MarTech Podcast, host Benjamin Shapiro is joined by Matthew McGrory, Co-founder and CEO of Arwen AI, to break down the rapidly evolving role of artificial intelligence in social media marketing. Matthew describes the 2025 social media landscape as “fractured,” pointing to the overwhelming array of AI tools and niche use cases emerging across the industry. They discuss the challenges brands face in choosing the right solutions amidst a crowded market, the slow adaptation of large enterprises, and the opportunities startups have to deliver agile, targeted technologies. Listeners will gain insights into how fragmentation in AI and social media platforms can lead to both innovation and decision fatigue—and why flexibility and niche specialization are key for modern marketers.
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Part 3How many social media channels can you name in one minute?
Host Benjamin Shapiro challenges Matthew McGrory, Co-founder and CEO of Arwen AI, to a playful rapid-fire round: name as many social media platforms as possible in 30 seconds. The result is a lighthearted exchange that underscores the generational and professional lenses through which people experience digital media. While Matthew humorously leans on his teenage children’s usage patterns, Benjamin rattles off a diverse list of platforms including TikTok, YouTube Shorts, Discord, Reddit, and more. This brief but lively segment highlights the expanding and fragmented nature of the social media ecosystem—an environment where staying current is both a personal and professional challenge.
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Part 4Customer engagement metrics or brand visibility KPIs?
Host Benjamin Shapiro and guest Matthew McGrory, Co-founder and CEO of Arwen AI, debate a fundamental marketing dilemma: should brands prioritize customer engagement metrics or brand visibility KPIs on social media? Matthew champions engagement as the core purpose of social platforms, especially for B2B startups operating on tight budgets. Benjamin offers a nuanced take, noting that brand visibility is essential for early-stage companies seeking awareness before engagement can follow. Their conversation explores how factors like company size, growth stage, and B2B vs. B2C models influence strategy, while also touching on creative, low-cost visibility tactics—like branded sun hats at Cannes Lions—that can boost presence without breaking the bank.
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Part 5AI-Led Social: Going from listening to interaction (copy) (copy) (copy)
Benjamin Shapiro and Matthew McGrory, Co-founder and CEO of Arwen AI, tackle a strategic question facing modern marketers: when launching an AI-powered social media strategy, should brands prioritize algorithmic optimization or influencer partnerships? Matthew leans toward influencer relationships, arguing that human endorsements carry more weight than trying to game ever-evolving platform algorithms. Benjamin offers a balanced view, framing influencers as a short-term growth lever and algorithmic strategies as a long-term brand asset—comparing it to the difference between paid media and SEO. They also explore the broader definition of influence, highlighting how founders, customers, and even case studies can serve as powerful credibility boosters.
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