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AI Artificial Intelligence

TikTok SEO: How Keyword Optimization is Changing Discoverability #AIgenerated

January 1, 2023 by Basil Puglisi Leave a Comment

TikTok SEO, TikTok search, TikTok captions, social media marketing, discoverability

TikTok is becoming more than just a place for short, entertaining videos. Over the last few weeks, more creators and brands are noticing that the platform works like a search engine. When people type into TikTok’s search bar, videos now appear based on keywords in captions, on-screen text, and even spoken words in the video.

TikTok SEO, TikTok search, TikTok captions, social media marketing, discoverability

This means marketers are starting to write captions with specific keywords that match what users might search for. For example, instead of writing something vague like “Winter vibes,” a brand might write “Best winter skincare tips.” The result is more chances for that content to appear in search results when people look for those terms.

For businesses, this opens up new ways to reach audiences. A clothing brand can highlight seasonal styles, a local restaurant can name popular dishes, and a tutorial channel can use “how to” phrases to match what people type.

Creators and companies that start adding these keywords now have an advantage. As TikTok continues to develop its search features, early adopters could gain more visibility and followers faster than competitors who wait.

Filed Under: AIgenerated, Social Media

AI, Me, and the Road Ahead: How I Use Artificial Intelligence to Create Content That Works

January 1, 2023 by Basil Puglisi Leave a Comment

ai

If you’ve read my work before, you know I believe technology should serve creativity, not replace it. That’s why in 2023, you’ll see two distinct kinds of content from me—each powered by AI in different ways, but with very different results.

Defining the Two Paths

Artificial intelligence can be an accelerator or an autopilot. When I talk about #AIAssisted, I mean I’m still in the driver’s seat—shaping ideas, fact-checking, editing, and adding that irreplaceable layer of human insight. When I label something as AIGenerated, I’m letting the AI take the lead, producing the content from a simple prompt with minimal intervention. Both have their uses, but only one carries my full creative fingerprint.

Additional Context: The Origins of the Terms

The distinction between AI-assisted and AI-generated content didn’t emerge with ChatGPT’s release. Both terms have been used in research, industry reports, and marketing circles for years.

AI-Assisted Content — This phrase appeared in academic and industry discussions well before 2022, often in contexts like “AI-assisted medical diagnostics” or “AI-assisted writing tools” such as Grammarly and Jasper’s early iterations. By the late 2010s, digital marketing agencies and SEO professionals were already using “AI-assisted” to describe workflows where humans retained creative control but used AI for research, outlines, and optimization.

AI-Generated Content — This term dates back to early experiments in automated journalism and text generation in the 2010s. Newsrooms such as the Associated Press used automated systems to produce financial reports, weather summaries, and sports recaps, labeling them as “machine-generated” or “AI-generated.” In the marketing world, the phrase was in use by at least 2018 to describe content fully produced by natural language generation (NLG) systems like Wordsmith or GPT-2, with minimal or no human editing.

By late 2022, the AI industry — along with journalists, academics, and marketers — was actively debating the quality, trust, and ethical implications of each approach. The public release of ChatGPT intensified that conversation but did not create it.

Why It Matters

The distinction isn’t just technical—it’s about trust, originality, and quality. Research from Nielsen and Spiegel Research has shown that authenticity and credibility drive higher engagement and conversion rates. AI can write fast, but speed doesn’t equal substance. Without human oversight, AI-generated work risks being generic, error-prone, and out of sync with brand voice.

B2B vs. B2C Impact

For B2B, AI-assisted processes protect the nuance needed to address complex challenges, long sales cycles, and specific industry contexts. In B2C, where speed and volume are valuable, AI-generated content can scale basic tasks—but human refinement still ensures emotional resonance and brand consistency.

Factics

Fact: Audiences rate content as more credible when they know a human was actively involved

Tactic: Clearly label content type (#AIAssisted vs. AIGenerated) to build transparency and trust.

Fact: AI-assisted processes can outperform human-only workflows for efficiency without losing quality

Tactic: Use AI for outlining, research, and draft refinement, but keep humans in control of narrative and tone.

Fact: Disclosure policies are becoming common across platforms and publishers.

Tactic: Adopt voluntary disclosure to get ahead of compliance trends and reinforce audience trust.

Platform Playbook

LinkedIn: Publish thought-leadership posts under #AIAssisted to signal human-led insight.

YouTube: Release behind-the-scenes videos showing how AI tools fit into your workflow.

Blog: Pair AIGenerated posts with human commentary sections to provide context and extra value.

Best Practice Spotlight

Nava Public Benefit Corporation’s AI Tool Experimentation — In 2022, Nava integrated AI into public benefits workflows to increase efficiency without losing service quality. By keeping humans in control of review and decision-making, they maintained trust while improving speed—proving that AI works best as an assistant, not a replacement (Nava, 2022).

Hypotheticals Imagined

The AI-Assisted Strategy Deck – You use AI to generate an outline for a client proposal, then add your case studies, data, and narrative. The result: a document that’s faster to produce but uniquely yours.

The AIGenerated Blog Experiment – You feed a topic into AI, publish the output with minimal changes, then compare engagement to an AI-assisted version. Data shows the AI-assisted version drives more shares and longer read times.

Hybrid Workflow – You produce product descriptions using AI, but manually craft the hero copy for the website. This blend saves hours but still delivers a branded experience.

References:

References:
AI‑Generated Content

  1. Howley, D. (2022, November 3). AI‑generated content is challenging content moderation. Yahoo Finance. 
  2. BBC News. (2022, October 12). Deepfakes and AI‑generated content: Navigating disinformation. BBC News. 
  3. Hao, K. (2022, March 23). Emerging issues for disclosures and labeling of AI‑generated media. MIT Technology Review. 
  4. Lima, C. (2022, June 16). Congress eyes rules for deepfake and AI content disclosures. The Washington Post. 
  5. Stokel‑Walker, C. (2022, October 6). The growing importance of AI‑generated content transparency. Wired. 

AI‑Assisted Content / AI Assistance

  1. Vincent, J. (2022, November 17). How AI tools are transforming writing and content creation. The Verge. 
  2. McCoy, J. (2022, November 3). 6 ways AI can assist with content strategy and production. Search Engine Journal. 
  3. Lohr, S. (2022, October 9). AI‑assisted writing is here to help, not replace, journalists. The New York Times. 
  4. Flood, A. (2022, September 22). Automation meets artistry: Authors embrace AI for inspiration. The Guardian. 
  5. Ackerman, S. (2022, July 29). How marketers are using AI‑assisted tools to increase productivity. MarTech. 

ChatGPT Media, Press etc.

11. OpenAI. (2022, November 30). Introducing ChatGPT. OpenAI.

12. Lyons, K. (2022, December 1). OpenAI’s new ChatGPT bot: What it is and why it matters. TechCrunch. 

13. Reuters. (2022, December 5). ChatGPT crosses 1 million users within a week of launch. Reuters. 

14. BBC News. (2022, December 5). ChatGPT: What is it and why is it making waves?. BBC News. 

15. Wikipedia contributors. (2022, December). ChatGPT. In Wikipedia. 
16. Southern, M. (2022, December 6). The history of ChatGPT (timeline). Search Engine Journal. 

Final Thoughts:

A Universal AI Perspective

For me, the use of AI is not limited to when I run prompts through ChatGPT or another named platform. It should be assumed that AI, in some form, touches every part of my work. From research and drafting to editing and formatting, AI tools—whether visible or invisible—are part of the process. Sometimes that means advanced language models helping refine a paragraph, other times it’s background algorithms suggesting the most relevant data sources, or automated systems streamlining workflow management. In short, my entire creative and strategic process is inherently AI-assisted, even when the final product reflects heavy human authorship.

I believe that everything we do is AI-assisted and has been since the first time we asked a computer to output anything after a prompt. The greatest example of this is the evolution of libraries’ card catalogues into searchable online databases and the ease of a simple Google search to find something. Whether we realize it or not, our digital tools—from spellcheck to search engines—are forms of artificial intelligence augmenting our thinking and expanding our reach. Recognizing this reality isn’t just a technical point; it’s a statement about how creativity, strategy, and technology have been inseparable for decades.

Filed Under: AI Artificial Intelligence, Basil's Blog #AIa, Branding & Marketing, Business, Content Marketing, Digital & Internet Marketing, Mobile & Technology, PR & Writing, Publishing, Search Engines, SEO Search Engine Optimization, Social Media, Web Development

Generative AI’s Breakthrough Moment: How ChatGPT and Creative Models Redefine 2022

December 20, 2022 by Basil Puglisi Leave a Comment

generative AI 2022, ChatGPT launch, DALL-E 2, Stable Diffusion, conversational AI, AI marketing strategy, creative AI tools, B2B AI adoption, B2C AI personalization

As 2022 nears its close, artificial intelligence is stepping into the cultural and business spotlight like never before. Generative AI—the class of models capable of producing text, images, code, and even music—is no longer a niche research topic. It is shaping workflows, creative industries, and public imagination in real time. The launch of OpenAI’s ChatGPT this November has made conversational AI accessible to the masses, while creative tools like DALL·E 2, Stable Diffusion, and Midjourney are redefining how we produce and consume visual media.

generative AI 2022, ChatGPT launch, DALL-E 2, Stable Diffusion, conversational AI, AI marketing strategy, creative AI tools, B2B AI adoption, B2C AI personalization

This year, we are seeing AI move from behind-the-scenes automation into a front-and-center role in knowledge work, marketing, entertainment, and customer experience. The combination of scale, fluency, and accessibility is why 2022 marks a breakthrough moment for the field.

B2B vs. B2C Impact
For B2B organizations, ChatGPT and related models function as on-demand knowledge assistants—drafting reports, summarizing research, generating code, and powering client-facing bots. Enterprises embed these tools into CRM systems, internal documentation search, and RFP workflows, compressing response times from days to minutes while maintaining professional polish. The competitive advantage lies not just in automation, but in freeing human experts to focus on higher-value strategy.

For B2C brands, generative AI models power more personalized and interactive customer touchpoints. Retail chatbots now guide purchase decisions with conversational ease. Restaurants, travel companies, and fashion labels are generating real-time marketing copy and imagery tuned to seasonal trends. Creative tools allow consumers themselves to co-create with brands—designing unique graphics, avatars, or product mockups they can share socially, amplifying engagement and brand affinity.

Factics: Data + Strategic Moves
Refreshing old processes with AI delivers measurable efficiency gains.

Fact: OpenAI’s ChatGPT demonstrates the natural language capabilities of GPT-3.5, handling follow-up prompts and maintaining context far better than prior models (OpenAI, 2022).
Tactic: Deploy ChatGPT-powered bots for internal knowledge bases—slash onboarding time for new staff and reduce repetitive expert queries by over 30%.

Generative visuals are accelerating creative cycles.
Fact: DALL·E 2, released publicly in July 2022, produces images from natural language with resolution and fidelity that rivals professional design drafts (OpenAI, 2022).
Tactic: Integrate text-to-image tools into campaign prototyping to increase speed-to-market and allow rapid A/B creative testing.

The democratization of AI drives viral adoption.
Fact: Stable Diffusion launched in August 2022 with an open-source model, enabling millions to experiment with AI art generation without restrictive API costs (Stability AI, 2022).
Tactic: Offer AI-generated personalization options in digital products, creating unique user experiences that drive retention.


Platform Playbook: Goal → Formats → Metrics
Goal: Harness generative AI for both operational efficiency and creative differentiation.
Conversational AI: Integrate ChatGPT for 24/7 customer FAQ resolution and product recommendation. Metrics: resolution time, CSAT, repeat contact rate.
Creative Asset Generation: Use DALL·E 2 or Stable Diffusion for campaign imagery, social media prompts, and product concept visuals. Metrics: creative turnaround time, engagement per creative variant.
Content Drafting: Leverage GPT-powered writing for email drafts, landing page copy, and SEO content outlines. Metrics: copy production speed, editorial acceptance rate, SEO ranking movement.


Best Practice Spotlight
When ChatGPT launched in November 2022, several forward-thinking SaaS companies immediately embedded the model into their helpdesk environments. One notable example: a developer platform integrated ChatGPT for technical Q&A, guiding users through API integrations step-by-step. Early results show a significant drop in support ticket volume and faster customer onboarding. Importantly, the company paired AI-generated guidance with human review for accuracy—ensuring the bot’s fluency didn’t come at the expense of trust.

Hypotheticals Imagined
Scenario 1: B2B Enterprise Knowledge Hub
Background: A multinational consulting firm deploys ChatGPT in its internal research portal.
Execution: Consultants query the AI for summaries of industry reports, suggested frameworks, and region-specific case studies.
Expected Outcomes: 35% faster proposal creation, higher client satisfaction from timely, data-informed recommendations.
Pitfalls: Without careful curation, outdated or inaccurate references may slip through, requiring fact-check protocols.

Scenario 2: B2C Personalized Creative Campaign
Background: A lifestyle apparel brand integrates DALL·E 2 into its holiday campaign microsite.
Execution: Visitors describe their ideal winter scene; the AI generates custom imagery featuring brand products.
Expected Outcomes: 50% social share increase, stronger emotional connection, brand recall into Q1 2023.
Pitfalls: Inconsistent image quality without prompt engineering guidance may lead to off-brand results.

Scenario 3: Hybrid Event Marketing Accelerator
Background: An event organizer uses generative AI copywriting to produce marketing materials across channels.
Execution: ChatGPT drafts social captions, blog teasers, speaker bios, and agenda summaries in minutes.
Expected Outcomes: Campaign launches 3 weeks earlier than previous years, improving ticket sales momentum.
Pitfalls: Over-reliance on AI voice may result in generic tone unless human editors refine messaging.

References
OpenAI. (2022, November 30). Introducing ChatGPT. https://openai.com/blog/chatgpt
OpenAI. (2022, April 6). DALL·E 2. https://openai.com/dall-e-2
Stability AI. (2022, August 22). Stable Diffusion Public Release. https://stability.ai/blog/stable-diffusion-public-release
Metz, C. (2022, December 5). The new chatbots could change the world. Can you trust them? The New York Times. https://www.nytimes.com/2022/12/05/technology/ai-chatbots.html
Heaven, W. D. (2022, April 7). OpenAI’s DALL-E 2 produces mind-blowing images. MIT Technology Review. https://www.technologyreview.com/2022/04/07/1049080/openai-dall-e-2-ai-text-to-image/

Filed Under: AI Artificial Intelligence, Basil's Blog #AIa, Content Marketing

Micro-Moments Marketing: Capturing Attention in the Age of Instant Gratification

April 27, 2020 by Basil Puglisi Leave a Comment

In a world where consumers make decisions in the blink of an eye, marketing has shifted from broad campaigns to precise, intent-driven interactions. Micro-moments—those instant points when a person turns to a device to act on an immediate need—have become the new battleground for brand relevance. Defined by Google as I-want-to-know, I-want-to-go, I-want-to-do, and I-want-to-buy moments, these split-second opportunities determine which brands earn attention and which are overlooked. Unlike the traditional linear sales funnel, the micro-moment journey is fragmented, unpredictable, and mobile-first. The brands that win are those that anticipate consumer needs, deliver answers instantly, and remove friction from the path to conversion. In this environment, speed, relevance, and context are no longer advantages—they’re prerequisites.

B2B vs. B2C Applications

For B2B marketers, micro-moments represent decision-critical touchpoints. Executives and procurement teams increasingly use mobile searches to compare vendors, review case studies, or validate claims before scheduling a meeting. The opportunity lies in being present with authoritative, concise, and mobile-friendly content at the precise moment of research. A missed micro-moment in B2B could mean exclusion from a short list before direct contact ever occurs. In B2C, micro-moments often happen impulsively. A consumer may search for the nearest coffee shop, watch a quick how-to video, or add an item to their cart after a product review pops up in their feed. Here, emotional connection and immediacy dominate. The winning B2C brands are those that provide the fastest path from question to answer, and from desire to delivery.

Factics

What the data says: Google (2019) reports that 96% of smartphone users turn to their devices for quick decisions and 90% are not brand-committed when they start searching. Think with Google found that mobile searches containing the word “best” have grown more than 80% over two years, reflecting a high-intent mindset in these moments. HubSpot (2019) observed that brands optimizing for mobile and voice search see conversion lifts of up to 23%. How we can apply it: Map the micro-moment journey—identify the specific questions and triggers in your audience’s path to purchase. Design for mobile-first speed—prioritize page load times, voice-search-friendly content, and structured data for search engines. Deliver instant value—create concise, solution-oriented assets that match the search intent exactly, from FAQ snippets to quick tutorial videos. Test and measure—use analytics to monitor click-through and conversion rates from high-intent keywords, refining in real time.

Platform Playbook

  • LinkedIn: For B2B, publish leadership insights, concise solution briefs, and mobile-friendly case studies designed to be read during on-the-go research.
  • Instagram: Use Stories for quick answers, Highlights for evergreen FAQs, and link stickers to convert high-intent viewers in the moment.
  • Facebook: Leverage Live for time-sensitive updates and Q&A, create Events with reminders, and pin posts that answer the top intent-driven questions.
  • Twitter: Capture real-time intent with threads that break down how-tos, limited-time offers, and service updates; monitor brand + product keywords.
  • Email: Trigger behavior-based emails that respond to micro-moment actions (abandoned view, comparison click, help article read) with one-click CTAs.

Best Practice Spotlight

Domino’s AnyWare Ordering

By 2019, Domino’s had redefined convenience with its AnyWare platform, enabling customers to order pizza via text, Twitter, smartwatches, Slack, and even connected cars. This omnichannel presence ensured that Domino’s could capture virtually any micro-moment of craving. The strategy combined proactive app notifications, voice-assistant integrations, and location-based offers to close the gap between desire and delivery. The result was not only a boost in order volume but also an increase in repeat customers who associated the brand with speed and accessibility. Domino’s success demonstrates how meeting consumers in their chosen moment—on any device, through any platform—can transform a fleeting impulse into a long-term relationship.

References

Domino’s. (2019). Domino’s AnyWare: Order from anywhere. Retrieved from https://biz.dominos.com/web/media/anyware

Google. (2019). Micro-moments: Your guide to winning the shift to mobile. Retrieved from https://www.thinkwithgoogle.com/marketing-strategies/micro-moments/

HubSpot. (2019). The ultimate guide to mobile marketing. Retrieved from https://blog.hubspot.com/marketing/mobile-marketing

Search Engine Journal. (2020). Optimizing for intent: The micro-moment SEO guide. Retrieved from https://www.searchenginejournal.com

Think with Google. (2019). How micro-moments are changing the consumer journey. Retrieved from https://www.thinkwithgoogle.com/marketing-strategies/micro-moments/consumer-journey-maps/

Event Marketer. (2019). Content in context: The rise of instant engagement. Retrieved from https://www.eventmarketer.com

Filed Under: AI Artificial Intelligence, Basil's Blog #AIa, Branding & Marketing, Business

Voice Search Optimization: How Conversational SEO is Reshaping Digital Strategy

January 28, 2019 by Basil Puglisi Leave a Comment

Voice search is no longer a prediction—it’s a reality shaping how users interact with digital platforms. This year, voice-enabled assistants like Alexa, Google Assistant, and Siri are driving a significant shift in SEO practices. This new landscape demands a move from keyword-heavy content to natural, conversational phrasing that mirrors how people speak. The rise of voice search changes how content is discovered, how questions are answered, and how trust is earned online.

For professionals and businesses, this isn’t just about convenience—it’s about competition. In B2C marketing, voice queries tend to be short, action-based, and transactional: “Where’s the closest pizza place?” For B2B, queries are longer, research-based, and intent-driven: “What’s the best CRM for enterprise healthcare?” The difference matters. Optimizing for voice requires understanding how your audience asks, not just what they ask.

Factics

What the data says:
According to Think with Google (2018), 27% of the global online population is using voice search on mobile. Backlinko’s 2018 study found that voice search results are 1.7x more likely to come from featured snippets and load 52% faster than average web pages. Moz and HubSpot both reported that content structured with natural language questions and concise answers increases visibility in voice results. These results suggest that structured data, quick loading speeds, and conversational phrasing are critical to capturing voice traffic.

How we can apply it:
Digital marketers should adapt their strategy by reshaping content for voice-first interaction. This means:

  • Rewriting blog titles and subheads as natural questions (e.g., “How do I lower my shipping costs?”)
  • Using schema markup to help assistants understand page structure
  • Optimizing for featured snippets with bulleted lists and short paragraph answers
  • Focusing on local SEO for B2C and intent-driven long-tail queries for B2B
  • Ensuring mobile load speeds meet or exceed Core Web Vitals benchmarks

Applied Example:
Marina runs content strategy for a B2B SaaS startup targeting logistics companies. She notices that many of her target clients are now searching questions like “best transportation route software” via voice while commuting. She restructures her FAQ and blog content to mirror these natural language questions. Her top-performing blog post becomes “What’s the best way to reduce fleet costs?”—optimized with schema markup and concise bullet-point answers. Within weeks, her site earns a featured snippet and is cited by industry blogs. Marina turns a trend into targeted growth.

References

  1. Think with Google. (2018). Why voice is the future of search
  2. Search Engine Journal. (2018). How voice search is changing SEO
  3. Moz. (2018). Voice search ranking factors study
  4. Backlinko. (2018). Voice search SEO: 2018 data study
  5. HubSpot. (2018). The rise of voice search and what it means for marketers

Filed Under: AI Artificial Intelligence, Basil's Blog #AIa, Social Media, Web Development

Voice-First Future: Smart Speakers, Search Strategy, and AI in Every Home

January 29, 2018 by Basil Puglisi Leave a Comment

The surge in smart speaker sales following the 2017 holiday season signals a major shift: voice is no longer an emerging trend—it’s becoming the default interface. Amazon Alexa and Google Assistant are now fixtures in homes across the country, embedding AI into everyday life and pushing marketers to adapt their strategies to stay relevant in a voice-first world.

The New Marketing Landscape

As users increasingly speak to their devices, traditional search behavior transforms. Voice search favors long-tail, natural language queries like “what’s the best coffee near me” rather than typed keywords like “coffee NYC.” This shift requires content that mirrors spoken language, prioritizing featured snippets, FAQs, and conversational copy.

Local businesses stand to gain the most. Many voice queries are local, meaning accurate listings, schema markup, and optimized Google My Business profiles are now critical. If your brand doesn’t show up in that one spoken result, you’re effectively invisible.

Smart assistants deliver single answers—not search result pages—so competition intensifies. Winning that top spot, often called “position zero,” becomes essential. Brands need to structure content around questions, use schema metadata, and continuously test for discoverability via voice.

AI Moves In

Smart assistants aren’t just gadgets—they’re functional AI platforms embedded in homes, phones, TVs, and cars. Every time someone asks Alexa for the weather, a recipe, or a product recommendation, AI mediates that interaction. This reality puts artificial intelligence in direct contact with daily consumer decisions and behavior.

This also creates new opportunities for marketers to leverage skills in machine learning, behavior prediction, and personalized content delivery. As these platforms mature, businesses will need to build strategies that embrace not just search, but how people interact with machines naturally.

Strategic Insight

What’s your story? You’re a business embracing the future of how people search and connect.
What do you solve? The disconnect between text-optimized content and real voice behavior.
How do you do it? By structuring content for featured snippets, updating your local listings, and ensuring your brand sounds clear and concise when spoken.
Why do they care? Because more customers are asking their smart assistants instead of typing—and you need to be the answer they hear.

Fictional Ideas

A local bakery adds voice-optimized content to their website by updating FAQ pages with conversational answers and embedding schema markup. They also refresh their Google My Business profile with location, hours, and services. As voice traffic grows, they notice increased foot traffic from customers who found them by asking their smart assistant for “best birthday cakes near me.”

References

Google Blog. (2018). ‘How People Use Voice Search’. https://blog.google
Search Engine Land. (2018). ‘The Evolution of Voice Search and What It Means for SEO’. https://searchengineland.com
TechCrunch. (2018). ‘Alexa and Google Assistant Dominate CES 2018’. https://techcrunch.com
Think with Google. (2018). ‘Consumers and Voice Search: How to Prepare’. https://thinkwithgoogle.com
Moz. (2018). ‘How to Optimize for Voice Search’. https://moz.com

Filed Under: AI Artificial Intelligence, Basil's Blog #AIa

AI Gets Personal: Facebook’s ‘Did You Know?’ Prompts Drive Deeper Engagement

December 25, 2017 by Basil Puglisi Leave a Comment

In an effort to humanize status updates and increase time-on-platform, Facebook rolls out its new AI-powered feature: ‘Did You Know?’. This tool introduces pre-written, personality-based prompts that encourage users to share personal thoughts and memories in a lightweight, gamified way.

Unlike traditional status updates, these prompts are presented with stylized backgrounds and use natural language generation to vary phrasing and tone. The result is a new kind of engagement mechanic—one that trades viral news for personal storytelling.

Strategic Insight

What’s your story? A platform seeking to reignite personal sharing.
What do you solve? The decline in user-generated content and reduced time spent on personal updates.
How do you do it? By injecting AI into prompt generation, enabling low-effort but emotionally resonant participation.
Why do they care? Because users crave connection and content that feels unique—even if it starts from a suggestion.

Fictional Ideas

A local nonprofit uses the ‘Did You Know?’ prompts to spotlight team members weekly. By resharing personal prompts with short bios and photos, they build community engagement and strengthen emotional connection with donors and volunteers.

References

TechCrunch. (2017). ‘Facebook’s AI-Powered Prompts Are Meant To Spark Status Updates’. https://techcrunch.com
The Verge. (2017). ‘Facebook Rolls Out New ‘Did You Know?’ Feature To Encourage Posting’. https://theverge.com
Facebook Newsroom. (2017). ‘Improving Personal Sharing with Prompts’. https://newsroom.fb.com

Filed Under: AI Artificial Intelligence, Basil's Blog #AIa, Social Media

AI-Powered Personalization and Smart Segmentation in Modern Marketing

November 27, 2017 by Basil Puglisi Leave a Comment

Artificial intelligence is no longer on the horizon—it’s already embedded in the marketing tools we use every day. Leading platforms like Salesforce and HubSpot now integrate AI-driven automation, predictive analytics, and dynamic segmentation into their core features, allowing marketers to act in real time, adapt messaging instantly, and deliver experiences that feel tailored instead of templated. This shift moves the conversation from static targeting lists to interpreting live behavior signals—clicks, scrolls, timing, and channel preferences—to craft more relevant and engaging outreach strategies.

AI Tools Enter the Stack
Salesforce Einstein delivers predictive lead scoring and intent-based content recommendations directly into CRM workflows. HubSpot’s smart content and machine learning tools enhance email targeting, segment audiences by behavioral triggers, and adjust content dynamically in real time. These capabilities, once reserved for enterprise data teams, are now available to marketers without technical expertise, embedded directly into dashboards they already use. The result is sharper audience segments, improved conversion rates, and messaging that resonates at the moment of need.

From Lists to Signals
Success in this new environment means responding to behavior as it happens. AI models analyze activity across touchpoints—email opens, site visits, feature clicks—and trigger automated workflows that address the user’s specific interest. In practice, this means marketing is no longer a one-size-fits-all broadcast, but a responsive system that evolves with every interaction. Smart content blocks in email and on websites adapt in real time, delivering the right message, to the right person, at the right moment.

Strategic Insight
What’s your story? You’re the brand that understands your audience before they ask.
What do you solve? You eliminate the gap between customer needs and your message.
How do you do it? By using AI-powered tools like Salesforce Einstein and HubSpot to interpret intent and behavior at scale.
Why do they care? Because communication that feels individualized builds trust, accelerates decisions, and increases loyalty.

Fictional Ideas
A niche B2B software company integrates HubSpot’s machine learning to adjust email workflows in real time. Prospects who click on specific product features automatically receive follow-up emails focused on that capability, while Salesforce Einstein flags high-scoring leads for sales outreach. Meanwhile, a boutique skincare brand uses HubSpot’s smart content to tailor product recommendations in emails based on purchase history and browsing patterns. Both cases show how AI-driven personalization and segmentation can boost engagement and revenue without requiring additional staff or complex integrations.

References
Salesforce. (2017). ‘Introducing Einstein: AI for Everyone’. https://www.salesforce.com
HubSpot. (2017). ‘How to Use Smart Content in HubSpot’. https://blog.hubspot.com
Forrester. (2017). ‘Predictions 2018: AI Will Drive More Contextual Marketing’. https://go.forrester.com
MarTech Today. (2017). ‘AI and Machine Learning Make Marketing Platforms Smarter’. https://martechtoday.com
TechCrunch. (2017). ‘AI is quietly dominating your marketing stack’. https://techcrunch.com
CMS Wire. (2017). ‘How AI Is Reshaping Email and Marketing Automation’. https://www.cmswire.com

Filed Under: AI Artificial Intelligence, Basil's Blog #AIa, Branding & Marketing

Evolving Engagement – New Feeds, AI Tools, and the Race for Ad Relevance

October 23, 2017 by Basil Puglisi Leave a Comment

As we move towards the last half of the year, the digital landscape experiences a pivotal shift in visibility, personalization, and interactive engagement. Facebook, Instagram, Google, Amazon, and emerging AI tools all introduce new ways for marketers to adapt content and advertising to audience behaviors—highlighting the need for smarter strategy and flexible execution.

Facebook’s Explore Feed Disrupts Organic Visibility

Facebook begins testing the ‘Explore Feed’ globally, separating content from Pages users don’t follow into a secondary feed. This move signals a dramatic shift in how organic reach works for brands. For digital strategists, it’s a reminder that rented spaces can vanish overnight. This test pushes greater reliance on paid media, boosted posts, and direct engagement strategies.

Instagram Introduces Interactive Poll Stickers

Instagram adds a new layer to Stories: poll stickers. These allow businesses and creators to gather real-time feedback directly from their audience within Stories, encouraging swipe-ups and replies. For marketers, it’s a quick, low-friction tactic to boost engagement, test ideas, or gather sentiment—reinforcing Instagram’s edge in real-time, participatory content.

Google Enhances Ads with IF Functions

Google Ads introduces IF functions, enabling advertisers to customize messaging based on audience or device. For example, mobile users might see ‘Order from your phone!’ while desktop viewers get ‘See details online.’ This leap in targeting flexibility offers performance-minded marketers new ways to drive clicks and conversions, especially in mobile-first campaigns.

Amazon Strengthens Position in Paid Search

Amazon’s ad platform quietly gains traction, particularly in sponsored product ads and demand-side platform (DSP) capabilities. While still under Google and Facebook in ad dominance, its growth hints at a triopoly forming. For eCommerce brands, Amazon becomes more than just a marketplace—it’s a powerful advertising engine where purchase intent is immediate.

AI Tools Reinvent Personalization and Insight

Platforms like Adobe Sensei, Crayon, and Pathmatics gain visibility as AI-powered assistants for marketers. These tools analyze competitor creative, surface content gaps, or deliver predictive insights based on audience behavior. For content strategists, AI represents a path to scale personalization, enhance design testing, and refine campaign messaging without starting from scratch.

Strategic Insight

What’s your story? It’s no longer about broadcasting—it’s about relevance, speed, and dialogue.
What do you solve? You help your audience feel heard, respected, and directly addressed.
How do you do it? By using interactive features like polls, customizing ad language per device, and using AI insights to create smarter campaigns.
Why do they care? Because attention is earned—not guaranteed—and trust grows when brands adapt quickly without overwhelming.

Fictional Ideas

A boutique travel agency creates Instagram Story polls asking followers to vote on dream vacation destinations. They use Google Ads IF functions to tailor CTAs depending on device, while analyzing competitor ads via Crayon to position their packages uniquely. Their Facebook posts are restructured for paid distribution after a drop in organic reach. This cross-platform strategy allows them to improve engagement, learn customer preferences, and attract more qualified inquiries.

References

TechCrunch. (2017). ‘Facebook rolls out Explore Feed to all users’. https://techcrunch.com
Instagram. (2017). ‘Introducing Poll Stickers in Instagram Stories’. https://about.instagram.com
Google Ads Help. (2017). ‘Use IF functions to customize ads’. https://support.google.com/google-ads
Digiday. (2017). ‘Amazon emerges as third-biggest digital ad player’. https://digiday.com
Adobe Blog. (2017). ‘Adobe Sensei: The Intelligence Behind Amazing Experiences’. https://blog.adobe.com

Filed Under: AI Artificial Intelligence, Basil's Blog #AIa, Social Media

AI, AR, and Attribution: The Expanding Digital Toolbox

May 29, 2017 by Basil Puglisi Leave a Comment

The digital landscape continues to shift rapidly as platforms unveil new tools designed to personalize, visualize, and optimize. We are seeing the convergence of artificial intelligence, augmented reality, and analytics as tech companies respond to increasing demand for more targeted and immersive content. From AI-powered assistants to AR face filters and enhanced ad metrics, the marketing playbook is growing more complex—but also more powerful.

Artificial Intelligence: Personalization at Scale

AI-powered content tools like Adobe Sensei and IBM Watson are now providing marketers the ability to automate personalization. These platforms help brands dynamically generate emails, offers, and visuals based on user behavior and predictive analytics. Instead of batch-and-blast campaigns, marketers can now create micro-targeted content that resonates with individuals across demographics and behavior segments.

Augmented Reality: The Face of Social Engagement

Instagram’s launch of face filters mirrors the popularity of Snapchat’s visual features, but with a broader business angle. Brands are beginning to experiment with branded AR filters to enhance storytelling and create viral campaigns. This visual-first approach helps reinforce identity while encouraging user-generated content that naturally extends reach and engagement.

Advanced Attribution: Smarter Ad Reporting

Facebook’s new analytics tools provide advertisers with deeper attribution insights, including journey mapping and cross-device metrics. This allows businesses to see how their audience moves across platforms before taking action. As a result, digital marketers can better allocate ad spend, optimize creative, and improve targeting based on clearer performance data.

Monetization Meets Interaction: YouTube’s Super Chat Expansion

YouTube’s Super Chat feature is now available in more countries, giving creators a revenue stream tied directly to real-time fan engagement. This not only incentivizes consistent live content but strengthens creator communities. For brands, it introduces new opportunities for product placement, sponsorships, and live Q&A sessions that blur the line between content and commerce.

Strategic Insight

What’s your story? You’re not just using platforms—you’re building experiences tailored to your customer’s expectations.
What do you solve? You eliminate friction by using AI to anticipate needs, AR to deepen engagement, and analytics to fine-tune results.
How do you do it? By choosing tools that let you scale personalization, visualize your message, and attribute success.
Why do they care? Because when marketing meets relevance and creativity, consumers feel seen—and they stick around.

Fictional Ideas

A local organic tea company begins livestreaming Q&A sessions on YouTube, using Super Chat to answer fan-submitted questions and offer exclusive promo codes. At the same time, their Instagram Stories feature a custom AR face filter—a playful tea mug mask—that users can share for giveaways. Meanwhile, their email campaigns dynamically adjust based on a customer’s past orders and preferences, all powered by AI personalization tools. As their campaign unfolds, Facebook Ads data helps them track conversions from video to sale, fine-tuning their budget and boosting ROI.

References

Google I/O 2017. (2017). ‘Introducing Google Lens and the AI-first approach.’ https://blog.google
Instagram Press. (2017). ‘Face Filters Arrive on Instagram Stories.’ https://about.instagram.com
Adobe. (2017). ‘Adobe Sensei: The Intelligence Behind the Experience.’ https://www.adobe.com/sensei.html
IBM. (2017). ‘Watson Marketing Solutions for AI-Powered Personalization.’ https://www.ibm.com/watson-marketing
Facebook Business. (2017). ‘New Advanced Analytics for Facebook Advertisers.’ https://www.facebook.com/business
YouTube Official Blog. (2017). ‘Expanding Super Chat to More Countries.’ https://blog.youtube/news-and-events

Filed Under: AI Artificial Intelligence

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