The "Next-Gen Marketing: AI, Data Science & Memetic Engineering" conference explores the transformative convergence of Artificial Intelligence (AI), Data Science, and Memetic Engineering in modern marketing. This synergy enables marketers to transcend traditional approaches, gaining deeper insights into consumer behavior, achieving precise targeting, and creating highly impactful, viral content. By integrating these three disciplines, organizations can develop comprehensive strategies that not only optimize immediate campaign performance but also cultivate lasting brand resonance and cultural relevance in an increasingly complex digital ecosystem. AI, in particular, plays a pivotal role in dissecting and predicting consumer behavior by processing vast amounts of data at speeds and scales impossible for human analysis, leading to more informed decision-making and tailored experiences.

Why Attend?

• Gain Cutting-Edge Knowledge: Learn about the latest advancements and practical applications of AI, Data Science, and Memetic Engineering in marketing from leading experts in the field.
• Enhance Your Marketing Strategy: Discover how to integrate these powerful disciplines to develop more effective, data-driven campaigns that resonate with your target audience and drive measurable results.
• Network with Industry Leaders: Connect with a diverse community of AI, Data Science, and marketing professionals, fostering collaborations and expanding your professional network.

Themes:

• The Convergence of AI, Data Science, and Memetic Engineering in Marketing
• AI's Role in Consumer Behavior Analysis and Prediction
• Developing Data-Driven Marketing Strategies
• Creating Viral Content through Memetic Engineering
• Optimizing Campaign Performance with AI and Data Science
• Cultivating Brand Resonance and Cultural Relevance in the Digital Ecosystem

Primary Audience for Conference Attendees

AI and Data Science Professionals:

• Data Scientists:
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  • Specialized Data Scientists: Professionals focusing on specific areas like NLP (Natural Language Processing), computer vision, or time-series analysis for marketing data.
  • Marketing Analytics Engineers: Professionals who build and maintain the infrastructure for data analysis and reporting for marketing teams.
  • Business Intelligence (BI) Analysts: Experts who turn data into actionable insights for business strategy.
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• AI/Machine Learning Engineers:
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  • MLOps Engineers: Specialists who deploy and maintain machine learning models in production environments.
  • Generative AI Specialists: Engineers focused on building and implementing models for content creation, from copywriting to image generation.
  • AI Ethicists: Professionals concerned with the responsible and fair use of AI in marketing, including issues of bias and privacy.
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• AI Researchers:
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  • Academic Researchers: Professors and graduate students exploring new theories and applications of AI and data science.
  • Corporate R&D Scientists: Professionals working in a company's research and development department to innovate new AI solutions.
  • Postdoctoral Fellows: Early-career researchers with deep expertise in specialized AI fields.
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• Software Engineers:
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  • Full-Stack Developers: Engineers who build the entire application stack, from front-end user interfaces to back-end services that integrate with AI models.
  • Data Engineers: Professionals who build the systems for collecting, storing, and processing data for data scientists and AI teams.
  • AI Integration Specialists: Engineers focused on integrating third-party AI APIs and services into a company's existing tech stack.
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• Product Managers:
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  • AI Product Managers: Professionals who oversee the development and launch of AI-powered products and features.
  • Growth Product Managers: Product managers focused on using data and AI to drive user acquisition, activation, and retention.
  • Technical Product Managers: Product managers with a strong technical background who can communicate effectively with both engineers and business stakeholders.
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• UX Designers:
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  • User Research Specialists: Designers who use data and AI to understand user behavior and inform design decisions.
  • Conversational AI Designers: Professionals who design user interfaces and experiences for chatbots and virtual assistants.
  • Data Visualization Designers: Designers who create compelling and easy-to-understand visualizations for complex data.

• Marketing Professionals:

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  • Marketing Directors and Managers:
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    • Chief Marketing Officers (CMOs): C-suite executives who set the overall marketing strategy and budget.
    • Vice Presidents of Marketing: Senior leaders responsible for overseeing multiple marketing functions.
    • Head of Performance Marketing: Leaders focused on data-driven campaigns and ROI.
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  • Brand Strategists:
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    • Brand Managers: Professionals responsible for the overall brand identity and value proposition.
    • Brand Analytics Specialists: Professionals who measure the effectiveness of branding efforts using data.
    • Brand Identity Designers: Creatives who use data insights to inform brand messaging and visual identity.
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  • Digital Marketing Specialists:
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    • SEO/SEM Specialists: Professionals who use AI tools to optimize search engine rankings and manage paid search campaigns.
    • Email Marketing Specialists: Experts who use AI to personalize and automate email campaigns.
    • Programmatic Advertising Specialists: Professionals who manage automated ad buying using data and AI.
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  • Content Strategists:
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    • Content Marketing Managers: Professionals who oversee the creation and distribution of content, increasingly using AI for ideation and generation.
    • Copywriters: Writers who use generative AI tools to assist in creating marketing copy.
    • Multimedia Producers: Professionals who use AI tools for tasks like video editing, image generation, and audio production.
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  • Social Media Managers:
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    • Social Media Analysts: Specialists who use data science to track and analyze social media performance and trends.
    • Community Managers: Professionals who use AI-powered tools to manage and engage with online communities.
    • Influencer Marketing Specialists: Professionals who use data to identify and manage partnerships with social media influencers.
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  • Advertising Executives:
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    • Media Planners: Professionals who use data to determine the most effective media channels for ad campaigns.
    • Account Managers: Professionals who manage client relationships and use data to report on campaign performance.
    • Creative Directors: Leaders who use AI-powered tools to generate creative ideas and assets for ad campaigns.
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  • Market Researchers:
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    • Qualitative & Quantitative Researchers: Professionals who use AI for tasks like sentiment analysis and survey data analysis.
    • Consumer Insights Analysts: Professionals who use data and AI to uncover deep insights into consumer behavior.
    • Competitive Intelligence Analysts: Professionals who use data and AI to monitor competitors' strategies and performance.
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  • Customer Experience (CX) Professionals:
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    • CX Managers: Professionals who use data to analyze and improve the overall customer journey.
    • Customer Service Managers: Leaders who use AI-powered chatbots and call routing systems to improve service.
    • Voice of the Customer (VoC) Analysts: Professionals who use AI and data to analyze customer feedback from various channels.
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• Executive Leadership:
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  • Chief Executive Officers (CEOs): Leaders interested in the strategic business impact and ROI of AI and data science in marketing.
  • Chief Technology Officers (CTOs): Executives responsible for the technical infrastructure and implementation of AI.
  • Chief Data Officers (CDOs): Leaders who oversee the company's data strategy, governance, and data-driven initiatives.
  • Chief Financial Officers (CFOs): Executives focused on the financial implications and cost-effectiveness of AI and data science investments.
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• Business Operations and Strategy:
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  • Business Analysts: Professionals who analyze business processes and use data to recommend improvements.
  • Corporate Strategists: Professionals who use market data and AI to inform long-term business strategy.
  • Venture Capitalists and Investors: Individuals and firms looking for new AI and data science startups and investment opportunities.
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• Legal and Compliance:
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  • Legal Counsel: Lawyers specializing in data privacy, intellectual property, and regulatory compliance (e.g., GDPR, CCPA) related to AI.
  • Data Governance Officers: Professionals responsible for ensuring data quality, security, and compliance.
  • Risk Management Professionals: Specialists who assess and mitigate the risks associated with AI implementation.
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• Educators and Students:
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  • University Professors and Instructors: Educators who teach AI, data science, and marketing and are looking for industry case studies and networking.
  • Students: Graduate and undergraduate students studying relevant fields who want to learn about industry trends and career opportunities.
  • Career Counselors: Professionals who guide students toward careers in the intersection of marketing, data science, and AI.

Main Conference Subject Areas

The Convergence: Laying the Foundation

• The Grand Convergence: Marketing's New Era
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  • An introduction to the synergistic integration of AI, data science, and memetic engineering and their profound impact on modern marketing.
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• AI's Role in Consumer Behavior: Decoding the Consumer
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  • Predictive Analytics for Customer Journeys: Forecasting customer actions and mapping journeys to identify purchase likelihood or churn.
  • Natural Language Processing for Sentiment Analysis: Utilizing NLP to extract and interpret consumer emotions from text and speech.
  • Machine Learning for Personalization at Scale: Empowering hyper-personalization by learning from individual interactions to deliver relevant content.
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• Data Science as the Foundation for Memetic Strategy
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  • Big Data Collection and Curation for Market Insights: Collecting and managing data to reveal consumer trends for meme creation.
  • Statistical Modeling for Campaign Optimization: Building predictive models to test hypotheses and forecast campaign performance.
  • Data Visualization for Actionable Marketing Intelligence: Converting complex data into clear visualizations for quick insights.
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• Memetic Engineering: Crafting Virality with Precision
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  • Identifying and Designing High-Propagating Memes: Analyzing successful viral content to understand emotional hooks and cultural relevance.
  • Strategic Dissemination Across Digital Ecosystems: Understanding platform algorithms and audience demographics for effective meme amplification.
  • Measuring Memetic Spread and Cultural Impact: Tracking engagement metrics to assess campaign effectiveness and meme evolution.
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• Expert Panel Discussion: "The Future is Now: Integrating AI, Data, and Memes"
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  • Leading experts discuss best practices, early successes, and the evolving challenges of integrating these three powerful forces.

Strategic Applications: Unlocking New Marketing Frontiers

• Evening Keynote: "From Insights to Impact"
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  • A deep dive into how the synergistic integration of AI, data science, and memetic engineering transforms how organizations connect with consumers.
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• Hyper-Personalization and Customer Engagement
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  • Dynamic Content Generation for Individual Preferences: Using AI to create and adapt marketing materials in real-time based on consumer preferences.
  • AI-Driven Chatbots for Real-time Interaction: Providing personalized customer service and gathering valuable data through conversational agents.
  • Personalized Product Recommendations and Offers: Leveraging machine learning to suggest relevant items and deals based on behavior.
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• Predictive Marketing and Trend Forecasting
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  • Anticipating Market Shifts with AI: Using AI to analyze datasets to forecast changes in consumer demand.
  • Identifying Emerging Consumer Needs Through Data: Analyzing online conversations and reviews to uncover unspoken desires.
  • Proactive Campaign Adjustment Based on Predictive Models: Fine-tuning targeting and messaging by simulating scenarios and forecasting outcomes.
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• Building Brand Narratives and Cultural Resonance
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  • Crafting Authentic Brand Stories Through Memes: Transforming core brand values into shareable, emotionally compelling "memes."
  • Fostering Community and User-Generated Content: Designing memes that encourage participation and active consumer contribution.
  • Measuring Brand Sentiment and Cultural Alignment: Tracking how brand memes are received and interpreted within cultural conversations.
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• Interactive Workshop: "Build Your Own Viral Campaign Strategy"
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  • Participants work in groups to develop a hypothetical next-gen marketing campaign.

Challenges & Ethical Considerations: Navigating the Future Responsibly

• Evening Keynote: "The Ethical Imperative: Trust and Transparency"
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  • A critical examination of the ethical implications of AI, data science, and memetic engineering in marketing.
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• Data Privacy and Security Concerns
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  • Navigating Regulations (e.g., GDPR, CCPA): Understanding and complying with strict data privacy rules.
  • Protecting Consumer Data from Breaches: Implementing robust cybersecurity measures to safeguard personal details.
  • Ensuring Transparency in Data Collection and Use: Communicating clearly with consumers about data gathering and providing opt-out options.
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• Algorithmic Bias and Ethical AI Development
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  • Mitigating Bias in AI Models: Using diverse datasets and fairness-aware algorithms to correct discriminatory patterns.
  • Ensuring Fairness in Marketing Personalization: Preventing AI-driven recommendations from disadvantaging certain groups.
  • Developing Responsible AI Guidelines for Marketing: Establishing clear guidelines for data governance and algorithmic transparency.
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• The Future of Consumer Trust and Manipulation
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  • Addressing Misinformation and Disinformation in Marketing: Brands promoting factual accuracy and distancing themselves from deceptive practices.
  • Balancing Persuasion with Ethical Influence: Respecting consumer autonomy and avoiding manipulative practices.
  • Fostering Long-Term Consumer Relationships Based on Trust: Prioritizing consumer well-being and providing genuine value.
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• Closing Keynote & Future Outlook: "Ethical Innovation in Next-Gen Marketing"
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  • A forward-looking discussion on the ongoing responsibility of marketers to innovate ethically.

Experiencing the Heart of Steamboat Springs, Colorado

Nestled in the Yampa Valley, Steamboat Springs offers a unique blend of authentic Western heritage and world-class outdoor recreation. Famous for its "Champagne Powder" snow, Steamboat Ski Resort provides diverse terrain for all skill levels. Beyond the slopes, Steamboat Square buzzes with après-ski activities, dining, and family amenities. The town's genuine, unpretentious atmosphere and rich history have made it home to more winter Olympians than any other place in the U.S.

Here are 3 cool things to do or adventures in Steamboat Springs, Colorado:

• Soak in the Hot Springs: Choose between the developed Old Town Hot Springs or the rustic, secluded Strawberry Park Hot Springs for a truly unique and relaxing experience.
• Mountain Biking on Emerald Mountain or Steamboat Bike Park: Explore a vast network of cross-country trails on Emerald Mountain or experience gravity-fed thrills on downhill trails at Steamboat Bike Park.
• Tubing the Yampa River (Summer) or Howelsen Hill (Winter): Enjoy a quintessential summer experience by tubing the gentle currents of the Yampa River, or in winter, head to Howelsen Hill for exhilarating snow tubing.

Call for Presentations & Papers

This conference is a vital forum for marketers, data scientists, AI developers, and ethicists to explore the synergistic integration of AI, data science, and memetic engineering. This event will provide a platform for sharing groundbreaking research, innovative strategies, and critical insights on how these powerful forces are redefining how organizations connect with consumers.

We invite you to contribute your expertise and join a community dedicated to shaping the future of marketing. We are seeking compelling presentations, insightful papers, interactive workshops, and concise lightning talks that showcase original research, practical implementations, and forward-looking analyses.

I. The Convergence: Laying the Foundation

This track will introduce the core concepts of this new marketing era and how they work together. We encourage submissions on:

• The Grand Convergence: An introduction to the synergistic integration of AI, data science, and memetic engineering and their profound impact on modern marketing.
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• AI's Role in Consumer Behavior: How predictive analytics forecasts customer journeys, Natural Language Processing (NLP) interprets consumer sentiment, and machine learning powers hyper-personalization at scale.
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• Data Science as the Foundation for Memetic Strategy: The importance of big data collection and curation, statistical modeling for campaign optimization, and data visualization for actionable marketing intelligence.
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• Memetic Engineering: Crafting Virality with Precision: How to identify and design high-propagating memes, strategically disseminate them across digital ecosystems, and measure their cultural impact.
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• Expert Panel Discussion: Proposals for a panel of leading experts to discuss the best practices, early successes, and evolving challenges of integrating these three powerful forces.

II. Strategic Applications: Unlocking New Marketing Frontiers

This track will focus on the practical applications and strategic implementations of this converged approach. We are particularly interested in submissions on:

• Hyper-Personalization and Customer Engagement: How AI is used for dynamic content generation, powering chatbots for real-time interaction, and driving personalized product recommendations and offers.
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• Predictive Marketing and Trend Forecasting: Submissions on using AI to anticipate market shifts, identifying emerging consumer needs through data analysis, and fine-tuning campaigns based on predictive models.
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• Building Brand Narratives and Cultural Resonance: How to craft authentic brand stories through memes, foster community with user-generated content, and measure brand sentiment and cultural alignment.
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• Interactive Workshop: Proposals for an interactive workshop where participants can develop a hypothetical next-gen marketing campaign that integrates these concepts.

III. Challenges & Ethical Considerations: Navigating the Future Responsibly

This track will provide a critical examination of the ethical implications of this new era of marketing, emphasizing the need for trust and transparency. We welcome submissions on:

• Data Privacy and Security Concerns: Discussions on navigating regulations like GDPR and CCPA, protecting consumer data from breaches, and ensuring transparency in data collection and use.
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• Algorithmic Bias and Ethical AI Development: Mitigating bias in AI models, ensuring fairness in personalization, and developing responsible AI guidelines for marketing.
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• The Future of Consumer Trust and Manipulation: Addressing misinformation in marketing, balancing persuasion with ethical influence, and fostering long-term consumer relationships based on trust.
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• Closing Keynote & Future Outlook: We are also seeking proposals for a closing keynote that provides a forward-looking discussion on the ongoing responsibility of marketers to innovate ethically.

Submission Types

We invite diverse contributions to enrich our program:

• Oral Presentations (20 minutes): Share your research findings, innovative applications, or case studies in a focused presentation.
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• Technical Papers (Full Length, 8-12 pages, IEEE format): Submit original, unpublished research that will undergo a rigorous peer-review process. Accepted papers will be published in the conference proceedings.
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• Experience & Insight Papers (4-6 pages, formatted for readability): This category is for practitioners, industry leaders, and ethicists to share valuable lessons learned, practical implementations, and insightful perspectives on the challenges and successes of navigating this new marketing landscape. Submissions will be peer-reviewed for clarity, relevance, and practical value.
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• Poster Presentations: Visually showcase preliminary results, ongoing research, or innovative concepts. There will be a dedicated poster session for interactive discussions.
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• Panel Proposals (60 minutes): Suggest and moderate a discussion among 3-5 experts on a controversial, emerging, or complex topic within the themes of this conference.
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• Workshop Proposals (60 minutes): Propose an interactive, hands-on session focused on practical skills, tools, or methodologies related to AI, data science, or memetic engineering in marketing.

Submission Guidelines

• Abstract: All submissions (except workshop proposals) must include a concise abstract (maximum 300 words) summarizing the problem, approach, key findings/insights, and conclusions.
• Author Information: Include full names, affiliations, and a brief professional biography (max 100 words per author).
• Keywords: Provide 3-5 relevant keywords that best describe your submission.
• Originality: Submissions must represent original work that has not been previously published or is not currently under review elsewhere.
• Audience Consideration: Presenters should be prepared to convey complex technical or theoretical concepts clearly to a diverse audience, including both technical and non-technical attendees.
• Formatting: Specific formatting guidelines for full papers will be provided upon the submission portal opening.

Review Process

All submissions will undergo a rigorous peer-review process by the Program Committee, comprising leading experts in marketing, AI, data science, and ethics. Submissions will be evaluated based on:

• Relevance to conference themes
• Originality and novelty of contributions
• Technical merit and soundness (for technical papers)
• Clarity, organization, and presentation quality
• Potential impact and practical applicability

We look forward to your valuable contributions and to a stimulating and collaborative conference!