Introduction

Sreenath Reddy: Welcome everyone to IntentWise Up Next, our first-of-its-kind event that we plan to host twice a year. The goal is to share our go-forward direction with our Amazon advertising platform and showcase exciting new developments in AI-powered ad optimization.

We have three primary solutions at IntentWise:

• Ad Optimization Platform - Advanced Amazon advertising optimization for Sponsored Products and DSP campaigns
• IntentWise Analytics Cloud - Out-of-the-box data infrastructure for Amazon and retail media analytics
• IntentWise Explore - Co-developed with Amazon to accelerate Amazon Marketing Cloud (AMC) adoption

Beyond our technology solutions, we invest significantly in educating our community about developments in the Amazon advertising space.

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The Future of Amazon Advertising Technology

Sreenath Reddy: Two major trends are driving our product investments in 2025:

1. Data Abundance: Amazon is sharing more advertising data than ever before with advertisers and partners. The challenge is extracting maximum value from this data.
2. Generative AI Impact: AI is enabling software to understand human language significantly better. We're moving toward conversational interfaces rather than traditional menus, forms, buttons, and screens. Software can now listen, understand, and respond like a teammate would.

Our goal at IntentWise is helping brands and agencies unlock value from this data abundance while using generative AI to dramatically improve productivity levels.

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Three Categories of AI Innovation

We're showcasing developments in three key areas:

1. Embedding AI in existing applications - Enhancing current solutions with AI capabilities
2. Building smart applications leveraging AI - Creating new solutions that surface insights faster on problems that traditionally take significant time
3. Transforming dashboards - Moving from static, inactionable dashboards to AI-powered, actionable analytics

Wizi: Your AI-Powered Advertising Assistant

Sreenath Reddy: Let me introduce the enhanced version of Wizi, your AI-powered teammate for Amazon advertising management. We launched an initial version a couple of months ago, but it's undergoing significant changes.

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Enhanced Wizi Capabilities:

Platform-Wide Availability: Wizi is now available across the entire IntentWise platform, not just the campaign screen.

Conversational Interface: Wizi is now fully conversational with expanded capabilities.

Multi-language Support: Wizi works in multiple languages, including Spanish and English.

Natural Language Command Examples:

• "Pivot by campaign type" - Automatically organizes and rolls up campaign data
• "YTD" or "MTD" - Instantly adjusts date ranges to year-to-date or month-to-date
• "Compare June and July" - Switches to comparison mode with appropriate timeframes

Advanced Search and Filtering Example:

• "Find me search terms that I've spent more than $100 in the last 30 days and have zero ad revenue" - Wizi navigates to search terms with appropriate filters applied automatically

Automated Alerting Example:

• "Alert me when products are suppressed" - Sets up monitoring alerts using plain language
• "Find me underperforming campaigns" - Identifies campaigns where ACoS exceeds target ACoS

Bulk Campaign Management Example:

• "Decrease budgets of these campaigns by 10%" - Executes changes across multiple campaigns instantly

Advanced Analytics Task Examples:

• "Tell me what changed between June and July" - Wizi creates analytical tasks, typically completing in under 10 minutes with automatic notifications
• Provides account-level summaries with text narratives
• Offers suggestions for additional analysis

Interactive Results: Users can interact directly with Wizi's analytical results and recommendations.

Kenton Snyder: What you see in Wizi today isn't what was there a month ago, and what you'll see next month will be different again. This rapidly evolving technology will fundamentally change how you interact with Amazon advertising platforms.

Sreenath Reddy: Looking ahead 6-9 months, it's entirely possible that software solutions will start with a search bar rather than traditional interfaces. The goal is helping you reclaim tactical and manual time for strategic and creative work, which are the real drivers of growth for brands and advertisers.

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Product 360: Revolutionary Product Performance Monitoring

Sreenath Reddy: Product 360 addresses a critical e-commerce challenge: understanding why product performance changes. Whether a product performs exceptionally well or underperforms, determining root causes traditionally consumes significant time due to multiple factors: pricing, inventory, buy box status, advertising, and competitor activities.

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Product 360: The E-commerce Observability Solution

In the technology world, "observability" solutions track software performance, identify errors, and determine causes. The e-commerce world lacks this concept, which is why we're introducing Product 360.

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Key Features:

Simple Setup: Connect your advertising and Seller Central or Vendor Central accounts - that's all required.

Automated Weekly Analysis:

• Platform surfaces performance anomalies on a weekly basis
• Identifies products that outperformed or underperformed
• Accounts for week-over-week changes, mix changes, and seasonality
• Delivers insights via Slack, email, or platform notifications

AI-Generated Performance Summaries:

• Automatic correlation analysis linking performance changes to factors like price changes, inventory issues, and buy box status
• AI detects inflections in key metrics
• Provides both high-level summaries for busy executives and detailed analysis for day-to-day managers

Comprehensive Performance Tracking:

• Last 8 weeks of performance data with labeled periods of underperformance or outperformance
• Detailed weekly performance breakdowns
• Inflection point identification (e.g., "sales started taking off from August 4th")

Example Analysis Cases:

• Outperforming Product: "Price decreased from $15 to $10, correlated with sales increase and glance view improvements"
• Underperforming Product: "Performance declined due to price increase and buy box issues"

Collaborative Features:

• Team messaging and annotations directly on product performance data
• Agency-client communication capabilities
• Real-time collaboration on performance insights

Comprehensive Metrics Coverage:

• Current: Pricing data, buy box status, inventory levels, advertising performance metrics
• Coming Soon: BSR tracking, organic ranking data, competitive intelligence metrics

All-Products View:

• Performance overview for entire catalog over multiple weeks
• Week-over-week and mix change metrics
• Performance tags (outperformed, underperformed, neutral)
• Category roll-ups, product labeling, sub-brand analysis
• Drill-down capabilities for detailed product analysis

Kenton Snyder: Product 360 is just our starting point. We're thinking about unifying all account data and advertising data, then layering Wizi capabilities to dramatically speed up performance analysis on daily, weekly, and monthly levels.

Sreenath Reddy: Our investment in underlying data infrastructure over the last several years enables us to bring together metrics that are otherwise difficult to combine. Product 360 is built on this foundation, with many more similar products coming to our portfolio.

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AI-Enhanced Dashboards: The Future of Analytics

Sreenath Reddy: Traditional dashboards have been static and inactionable. For example, AMC dashboards couldn't let you click to create an audience from a specific cohort. AI is enabling us to dramatically accelerate development speed through prompting and eliminate the separation between dashboards and action-taking applications.

We're converging great-looking dashboards with action-taking capabilities. The old form of dashboards is already obsolete, and we're moving fast to make this transition.

Kenton Snyder: We've had discussions about whether these are even "dashboards" anymore. The future may be more like context-aware applications where you can take direct action, and that mindset guides our dashboard development.

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Enhanced Dashboard Features:

Refreshed Visualizations:

• Completely updated visuals from current platform
• AI in development process speeds up our ability to build insights faster
• Generate additional data modules that weren't previously possible

Context-Aware Capabilities:

• AI recommendations and summaries built directly into dashboards
• Direct callouts about account activity and recommended actions
• Executive-level summaries for high-level overviews
• Detailed recommendations for media managers

Direct Action Integration:

• "Add Audience" - Create audiences directly from dashboard data
• Example: Create audiences from specific path-to-conversion data (DSP to Sponsored Products path)
• Seamless transition from insight to action

Path to Conversion Analysis:

• Enhanced visualization of multi-touch attribution across Amazon advertising channels
• Journey mapping from DSP to Sponsored Products
• Actionable audience creation based on conversion paths

Kenton Snyder: Over the next couple of weeks, current IntentWise customers will see all Amazon Marketing Cloud and Analytics Cloud dashboards updating to this new visual format, adding enhanced visuals, AI summaries, and actionable capabilities.

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Technology Architecture Behind the Innovation

Sreenath Reddy: Our technical foundation supports the future of conversational commerce:

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Multi-Channel Interaction Design:

• Web application interface
• Slack integration
• Email-based interactions
• Any text-based communication format

Agent-Based Architecture:

• Rapidly building library of specialized AI agents
• "What changed" analysis agent demonstrated earlier
• Existing recommendations agent
• Expandable agent ecosystem responding to user requests

Model Control Protocol (MCP) Integration:

• MCP is the AI world's equivalent of traditional APIs
• Enables plug-and-play functionality with any large language model (Claude, OpenAI, etc.)
• Provides flexibility and accelerates agent development

IntentWise Data Layer Foundation:

• Core component we call our "crown jewel"
• Result of 2-3 years of investment in strong data infrastructure
• Enables capabilities only possible through robust data foundation
• Enhanced by Amazon's comprehensive API offerings

Amazon's AI Evolution: Expert Insights from Jeffrey Cohen

Jeffrey Cohen: Amazon Ads has been using AI as part of feature functionality since we developed advertising solutions. Current AI implementations driving ads today include tools like Performance Plus and Brand Plus, along with recommendation systems pushed into partner applications and Ad Console.

Amazon's Comprehensive AI Strategy

Performance Optimization Tools:

• Performance Plus and Brand Plus for campaign automation
• Advanced recommendation systems running scenarios based on historical performance
• Opportunity identification for advertising improvement

Creative and Asset Generation:

• Video, graphics, and audio generation capabilities
• Background image modification and enhancement
• Product detail page improvements
• Motion graphics and animation features
• Simple ASIN input generates comprehensive creative assets

Important Context Considerations:
The key caveat is that generative AI doesn't always understand advertising context. Whether your product is a new launch requiring heavier investment or end-of-life requiring different strategies - these require personal inspection and strategic oversight of AI recommendations.

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Amazon Marketing Cloud AI Advancements

Jeffrey Cohen: AMC represents a excellent example of AI democratization. The skill set required for AMC two years ago was significantly higher than today. While you still need to understand how the product works, AI has made daily usage much more accessible.

Sreenath Reddy: One asset we leverage extensively is AI-driven SQL generation in AMC. Launched 6-7 months ago with 40-60% accuracy, it's now reaching 80-90% accuracy. This represents a huge productivity improvement - you still need AMC expertise to validate outputs, but the efficiency gains are substantial.

Jeffrey Cohen: Andy Jassy has stated we're developing AI across every facet of every team at Amazon, whether for internal operational efficiencies or external product accessibility and democratization.

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The Data Revolution in Amazon Advertising

Sreenath Reddy: The amount of data Amazon shares has transformed dramatically. Three years ago, there were ads APIs and seller APIs - nothing else. That picture looks very different today.

Jeffrey Cohen: Focusing on the advertising side, most advertisers initially viewed Amazon DSP as sophisticated retargeting for people who visited pages but didn't purchase, or hadn't bought in extended periods.

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Expanded Amazon Advertising Ecosystem

Amazon's Growing Canvas:

• Owned and Operated Properties: Prime Video, Wondery Audio, Alexa, and all areas within Amazon's ecosystem
• Third-Party Supply Partnerships: Roku deal announced at Cannes, enabling presence on other streaming services
• Publisher Network: Partnerships with Disney, ESPN, Hulu, and hundreds of other publishers

Enhanced Signal Sharing:
This expansion necessitates more sophisticated advertising targeting, requiring increased signal sharing. Amazon is sharing signals at levels unmatched in the industry, giving advertisers ability to reach broader audiences while measuring success effectively.

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Advanced Targeting and Measurement

AMC Audiences Evolution:

• Understanding what currently works for your brand and audience characteristics
• Using insights to boost bids within Sponsored Products
• First-party data integration capabilities
• Cross-referencing your D2C website or other first-party signals with Amazon data

Expanding Beyond Search-Find-Buy:
Traditional Amazon advertising focused on customers doing "search, find, buy" - a relatively small pool of potential shoppers. Wider signal ranges help understand:

• Shoppers who may be in-market or in-category
• Customers buying similar products
• Users interested in related products that could lead to purchases

Upper Funnel Impact Measurement:
Brands measuring upper funnel advertising impact discover that brand performance investments actually improve conversion performance advertising.

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Real-World Brand Impact Example

Jeffrey Cohen: I recently read about New Balance shoes' remarkable turnaround. After 15 years of declining sales, they brought in a new CMO who spent 2 years investing in brand marketing, transforming them into one of the hottest shoes for teens and young adults. They took what was perceived as "an old man shoe" and made it hip and trendy. My 18-year-old son now wants to borrow my New Balance shoes - two years ago, I was borrowing his shoes from different brands. This demonstrates how brand investment drives overall growth and reach to find new shoppers.

Sreenath Reddy: Brand search volume improvement serves as a proxy for brand performance even on Amazon. The primary driver is brand marketing investment levels.

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Partner Ecosystem and AI Innovation

Jeffrey Cohen: I started this year calling it my "year of discovery" for AI learning. I knew AI would significantly impact our business and partners in 2025, but wasn't certain what that impact would look like.

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Personal AI Journey and Industry Adoption

Personal Experimentation Approach:
I downloaded several AI applications to my phone and computer, making it a personal journey of daily usage. I wanted to understand capabilities, usage methods, prompting importance, and what happens with poor prompting - all designed to understand how consumers are currently and potentially using AI.

Industry Adoption Patterns:
Many people on presentations like this represent the more advanced side of AI adoption. A year ago, maybe 20% would have used ChatGPT. Today, I'd estimate nearly 100% of attendees have used ChatGPT or similar applications.

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Partner Innovation Acceleration

Jeffrey Cohen: The first half of 2024 was relatively slow for partner AI implementations. We saw some major announcements from partners releasing generative AI technology, but innovation speed has dramatically increased over the summer.

Why Implementation Is Challenging:
This is genuinely difficult technology to implement correctly. I consistently hear from partners: "We want to do it, but we want to do it right." When someone asks "what is my ACoS?" or "what is my ROAS?", that answer must be correct. You cannot have AI "hallucination" - where AI provides answers without knowing correctness. Our work context requires accurate answers.

Current Industry Status:
We're reaching a point where technology providers like IntentWise (recent finalists in our hackathon for applications demonstrated today) are showing where the industry is headed. Now users, agencies, tech providers, and brands need to determine daily advertising life implementation.

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Critical Questions for AI Implementation

Data Usage and Privacy:
What happens to information you provide? Are you helping train algorithms? How is your personal brand data being used? These aren't different from pre-AI data questions - they're just more prominent now.

Quality Control Requirements:
Always maintain high inspection levels for AI results. This builds trust. AI isn't initially a time saver - it becomes one over time. Whether rewriting emails, creating LinkedIn posts, editing papers, or other tasks, I had to inspect everything thoroughly until comfortable with AI understanding my needs and providing required results.

Market Evolution Context:
It's interesting that five years ago, tools existed where you entered your ASIN and it handled all advertising automatically. The market rejected this, wanting control over all levers. Now you can control all levers, but with so many data signals and information to process, you need AI tools to help discover anomalies deserving time and energy focus.

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Balancing AI Implementation Challenges

Sreenath Reddy: I completely agree about implementation difficulty. At IntentWise, we see challenges in three key areas:

1. Quality of Output: Precision requirements, especially where precision is necessary. "What is my ACoS?" cannot be a plausible answer - it needs precision.
2. Latency: If using the IntentWise app and asking a question that takes 35 seconds to respond, why wait? This dictates model selection and architecture decisions.
3. Cost Management: Every LLM call costs money. Balancing output quality, delivery speed, and cost while maintaining economic viability for our business is where we spend significant time.

Practical AI Usage Recommendations

Jeffrey Cohen: The best advice I give people: experiment with AI outside your business first. Whether asking AI to fix emails or solve problems, you'll improve at everything while learning to provide proper inspection.

Simple Example: I needed to find a car mechanic named Mr. Lee. Traditional search for "mechanic in my area named Mr. Lee" provides unclear results. Using AI: "I live in Northbrook, Illinois, looking for a mechanic named Mr. Lee, can you help?" AI responded: "Based on reviews, people reference mechanic Mr. Lee at this facility, here's the information." Learning to use AI in personal life translates to professional usage.

Organizational Considerations:
Executives tend to be more engaged with AI, using it for difficult questions, running scenarios - areas where AI excels. However, frontline workers are hesitant because they're not receiving management support, direction, or education about what and how to use AI tools.

Management Guidance:

• Consider how you're supporting AI throughout your organization
• Discuss AI with teams and make it accessible and comfortable for experimentation
• Understand company policies (at Amazon, certain AI is allowed internally, others aren't)
• Update SOPs and processes to understand how AI provides efficiency

Strategic Business Focus

Core Business Questions:

• What do I need to accomplish today?
• How should I prioritize activities?
• How do I achieve the best return on investment?

These are excellent questions for AI because it can perform deep analysis focusing on business anomalies - not just any anomalies, but those impacting or potentially impacting your business.

Anomaly Prioritization:
If an anomaly affects a tail ASIN you don't care about, it creates noise. If it affects a high-performing head ASIN, you need to stop everything and address it immediately. We must train systems to understand these distinctions.

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Looking Ahead: The Future of Amazon Advertising

Sreenath Reddy: Three major trends will define the next 12-24 months:

1. Agent-Led Advertising Execution: AI agents will become mainstream for campaign management
2. Actionable Dashboards: All IntentWise Analytics Cloud dashboards and AMC dashboards will adopt this enhanced format
3. Smart Applications: Product 360 represents the beginning, with numerous additional applications launching soon

Immediate Product Roadmap

Wizi Rollout: Enhanced Wizi will roll out to all IntentWise users in the near future. We encourage user engagement and feedback - more feedback improves the platform.

Dashboard Updates: Enhanced AI-powered dashboards will be available to current IntentWise customers over the next few weeks.

Product 360 Beta: We're actively seeking beta participants. Whether you're currently an IntentWise client or not, we'd love your participation and feedback.

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Conclusion and Next Steps

Sreenath Reddy: The brands that embrace Amazon Marketing Cloud and rethink their measurement approaches will build serious competitive advantages over the next 12-24 months. Our vision is a future where AI handles operational and tactical tasks, freeing time for strategic and creative work that truly drives brand and advertiser growth.

Jeffrey Cohen: Thank you for having me. I encourage everyone to connect on LinkedIn - I'm always available for questions. Looking forward to seeing everyone at Accelerate.

Upcoming Events: The IntentWise team will be present at both Amazon Accelerate and Unboxed conferences.

About IntentWise:
IntentWise is an advanced Amazon advertising partner providing AI-powered optimization, analytics, and Amazon Marketing Cloud solutions. Our platform helps brands and agencies maximize their Amazon advertising performance through data-driven insights and automated optimization.

Contact Information:

• Website: intentwise.com
• Community: Join our Amazon advertising community for ongoing education
• LinkedIn: Follow Sreenath Reddy, Kenton Snyder, and Jeffrey Cohen
• Events: Visit us at Amazon Accelerate and Unboxed conferences

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