R Labs
“Where history meets prediction.”
Core Concept:
R Labs is an advanced analytics and intelligence hub that combines historical advertising data with cutting-edge AI insights to power smarter campaigns, stronger brands, and faster decision-making.
It transforms past performance into future foresight—turning hindsight into a competitive edge.
Value Proposition:
“R Labs helps brands see around corners.”
Use AI to forecast ad performance, customer behavior, and creative trends.
Combine legacy performance data with generative AI to test concepts and messaging before launching.
Pinpoint where spend is wasted and where to double down.
AI-powered testing, targeting, and iteration—all based on what’s worked before.
Use Cases:
1.
Pre-Campaign Intelligence
Upload old ads → AI evaluates messaging, creative, and targeting.
Get recommendations on audience, platform, timing, and tone based on past results.
2.
Live Campaign Optimization
3.
Post-Campaign Reports That Think
Ideal Clients:
Growth-stage DTC brands
Agencies managing multiple brands
Internal marketing teams with legacy ad data
Retailers shifting ad budgets post-privacy updates
Tech Stack Suggestions:
Data Ingestion: Funnel.io, Supermetrics, or Stitch
Visualization: Looker Studio, Power BI, or Tableau
AI Layer: GPT-4 + fine-tuned LLMs on ad copy data
Automation: Zapier / Make + Slack / Notion for delivery
Sample Taglines:
“Learn from your past. Lead with AI.”
“Historical data. Future focus.”
“Smarter ads start here.”
“Ad history, reimagined with AI.”
Expansion Ideas:
Offer a proprietary “Ad DNA” Score—a unique metric combining engagement, conversion, and creative signals.
Build an AI plugin that can auto-generate ads based on top historical traits.
Develop industry benchmarks: “How your ads stack up vs. X category in 2022–2025.”
Here’s a structured Product Roadmap for R Labs, divided into 3 key phases: Foundation, Intelligence, and Autonomy — with each building on the previous to scale your AI-powered ad intelligence platform.
R Labs Product Roadmap
PHASE 1: FOUNDATION (Q3–Q4 2025)
Goal: Establish essential data infrastructure, a Minimum Viable Product (MVP), and core AI-assisted analytics capabilities.
1. Data Aggregation & Historical Uploads
Integrate connectors for key advertising platforms (e.g., Meta, Google Ads, TikTok, Klaviyo, Shopify).
Enable the upload of historical ad data (campaigns, spend, ROAS, copy, audience) via CSV/XLS files.
Normalize and tag all legacy ad data for consistency.
2. Insights Dashboard (MVP)
Visualize top-performing ads based on ROI, CTR, platform, and format.
Present time-series performance charts with filtering options for brand, industry, and creative type.
Provide exportable PDF reports and link-sharing functionality.
3. “Ad DNA” Score (Beta)
Launch a prototype scoring system that generates an “Ad DNA Profile” for each ad. This profile will serve as a benchmark and will combine:
CTR, CVR, ROAS, and engagement metrics
Copy structure, including headline length, tone, and call to action (CTA)
Audience and time targeting
PHASE 2: INTELLIGENCE (Q1–Q2 2026)
Goal: Enhance decision-making with predictive AI and generative tools.
4. Predictive Performance Modeling
AI model forecasts Return on Ad Spend (ROAS) based on platform, copy, creative type, and spend.
Includes a "If this, then that" scenario builder for budget or creative adjustments.
5. Copy + Creative Generator (R AI Studio)
Input: Campaign goal, past winning assets, desired tone, and target audience.
Output: Multiple ad copy versions and image/video prompts.
Feedback Loop: Users rate ads, enabling AI to learn brand voice and performance preferences.
6. Competitive & Industry Benchmarks
Upload competitor screenshots or URLs.
Compare your "Ad DNA" score against industry benchmarks.
Receive recommendations for positioning shifts or whitespace opportunities.
PHASE 3: AUTONOMY (Q3–Q4 2026)
Goal: Achieve automated insights delivery and campaign adjustments.
Key Initiatives:
7. Auto-Pilot Alerts + Slack/Email Integration:
Provide real-time alerts for underperforming ads.
Offer AI-powered suggestions to pause, duplicate, or update ad copy/images.
Deliver weekly executive summaries through a dedicated "R Labs Insight Drop" Slack app.
8. Smart A/B Testing Engine:
Utilize AI to select test variables based on historical performance.
Enable automated test launches and early termination of underperforming variations.
Generate uplift reports with recommendations for future iterations.
9. API & White-Label Solution:
Grant API access for agencies and platform partners.
Provide customizable dashboards for white-label branding.
Offer the option to include an "R Labs Certified" insights stamp.
Ultimate Vision
“Your entire ad history becomes a living, learning asset.”
R Labs becomes the first memory-based, performance-forecasting AI for marketers.
One-Pager for R Labs — ideal for early-stage fundraising conversations, pitch events, or VC outreach.
R LABS – Investor One-Pager
Where advertising history meets predictive AI.
Company Overview
R Labs is an AI-powered platform designed to bridge the gap between creative strategy and data science. We transform historical advertising data into predictive insights and creative intelligence, empowering businesses to build winning campaigns with confidence. By analyzing past successes and failures, our platform helps brands make smarter, faster decisions.
The Problem: Wasted Marketing Spend
A staggering 72% of marketing budgets are squandered due to inefficient targeting, redundant testing, and suboptimal creative choices. Brands are sitting on a treasure trove of historical ad data, yet it remains fragmented, static, and largely unutilized.
Our Solution: R Labs - A Living Intelligence Engine
R Labs transforms dormant ad history into a dynamic, learning intelligence engine by:
Centralizing Performance Data: Consolidating historical performance across all advertising platforms.
Proprietary "Ad DNA" Scoring: Utilizing our unique model to score ads based on their effectiveness.
Predictive Campaign Outcomes: Forecasting campaign results before launch to optimize strategy.
Generative AI for Ad Creation: Producing new ad copy and creative inspired by successful past campaigns.
Automated Alerts & Optimization: Providing real-time performance alerts and actionable optimization recommendations.
Product Highlights:
Insights Dashboard:
A comprehensive visualization of past campaign performance, audience targeting, and Return on Ad Spend (ROAS) trends.
Ad DNA Score:
An AI-driven metric that assesses ad strength across creative, copy, and audience elements.
R AI Studio:
Generative tools for crafting compelling copy, headlines, and ad concepts informed by winning historical data.
Smart Alerts:
Real-time performance recommendations delivered via Slack or email when ads underperform.
Traction:
Successfully completed 3 brand pilot programs.
Processed six-figure media budgets within our Minimum Viable Product (MVP).
Achieved over 80% accuracy in ROAS prediction based on historical variables.
Secured early partnerships with leading performance agencies and Direct-to-Consumer (DTC) brands.
Market Opportunity:
The global digital ad spend is projected to reach $640 billion in 2024.
There's a significant industry shift towards AI-driven creative and privacy-safe performance tools.
Increasing demand for post-cookie attribution solutions and contextual optimization strategies.
Business Model
The business model of R BRANDS focuses on three key areas:
Revenue is generated through monthly Software-as-a-Service (SaaS) subscriptions, with pricing tiered based on ad spend volume.
The company offers white-labeling solutions for enterprise clients and agencies, allowing them to brand the platform as their own.
R BRANDS provides API licensing for in-house analytics teams, enabling them to integrate the platform's data and functionalities into their existing systems.
Roadmap
Phase
Timeline
Focus
Phase 1
Q3–Q4 2025
Data ingestion, Insights Dashboard, Ad DNA Score
Phase 2
Q1–Q2 2026
Predictive modeling, R AI Studio, Benchmarking
Phase 3
Q3–Q4 2026
Autopilot alerts, Smart A/B testing, API access
Product Roadmap
Our product development will unfold in three key phases, each with a distinct focus:
Product Roadmap: A Phased Approach to Innovation
Our product development journey is strategically segmented into three distinct phases, each meticulously designed to build upon the last, culminating in a comprehensive and powerful solution. This phased approach ensures a focused and efficient development process, allowing us to deliver value incrementally and adapt to evolving market needs.
Product Roadmap:
Phase 1 (Q3–Q4 2025): Foundation and Core Insights
The initial phase is dedicated to establishing the fundamental infrastructure and delivering immediate, actionable insights. This period will concentrate on:
Data Ingestion:
Building robust and scalable systems for collecting, processing, and integrating vast amounts of diverse marketing and advertising data. This includes ensuring data quality, consistency, and efficient storage to serve as the bedrock for all subsequent analytical capabilities.
Insights Dashboard:
Developing an intuitive and dynamic dashboard that provides users with a clear, real-time overview of key performance indicators (KPIs) and trends. This dashboard will be designed for easy navigation and customization, allowing users to quickly identify strengths, weaknesses, and opportunities within their campaigns.
Ad DNA Score:
Implementing a proprietary scoring mechanism that analyzes the core components and characteristics of advertisements to predict their potential effectiveness. This score will leverage machine learning to identify patterns and attributes that contribute to successful ad performance, offering a quantifiable measure of an ad's intrinsic quality and potential impact.
Phase 2 (Q1–Q2 2026): Predictive Power and Benchmarking
Building on the data and insights established in Phase 1, the second phase will elevate our capabilities to include predictive analytics and comparative analysis. Our focus will shift to:
Developing advanced machine learning models that can forecast future campaign performance, identify emerging trends, and predict consumer behavior. These models will empower users to make proactive, data-driven decisions, optimizing their strategies before campaigns even launch.
Launching a dedicated AI studio within the platform, providing users with tools and functionalities to experiment with and apply AI-driven insights to their campaigns. This studio will offer features such as audience segmentation suggestions, content optimization recommendations, and predictive budget allocation guidance.
Integrating robust benchmarking tools that allow users to compare their performance against industry averages, competitor data, and best-in-class campaigns. This feature will provide valuable context for performance metrics, highlighting areas for improvement and identifying opportunities to gain a competitive edge.
Phase 3 (Q3–Q4 2026): Automation, Optimization, and Integration
The final phase will introduce advanced automation, intelligent optimization, and seamless integration capabilities, empowering users with ultimate control and efficiency. Key developments in this phase include:
Implementing an intelligent alert system that proactively notifies users of critical changes, anomalies, or opportunities within their campaigns. These alerts will be customizable, allowing users to set specific thresholds and receive real-time notifications via their preferred channels.
Introducing an advanced A/B testing framework that goes beyond simple comparisons. This smart A/B testing will leverage AI to dynamically optimize test parameters, identify optimal variations faster, and provide deeper insights into what drives superior performance.
Providing comprehensive API (Application Programming Interface) access, enabling seamless integration of our platform's capabilities with existing marketing tech stacks, CRM systems, and other third-party applications. This will allow for greater flexibility and automation, empowering businesses to build custom workflows and leverage our insights across their entire ecosystem.
Team
Founder: Rachel Stuppy
A global digital strategist with a proven track record at organizations like Spartan Race, NBC Sports, and Be Well Nation. Rachel successfully scaled Spartan's social media presence from 60k to over 3 million followers in under 3 years. Her expertise spans ad performance, creative trends, and marketing automation.
Advisors:
Our team is supported by a strong network of advisors, including leading experts in AI, data science, media buying, and startup growth.
Funding Goals
Contact
Rachel Stuppy
1-757-561-9839
www.rbrands.co
New York, NY
Here’s the Investor Traction Chart for R Labs — highlighting brand pilots, ad spend processed, predictive accuracy, and partnerships.
Next, I can create product mockups for the:
Insights Dashboard
The Insights Dashboard provides a high-level overview of advertising campaign performance, blending real-time data with predictive analytics. The layout is clean and modular, allowing users to customize which widgets they see.
The top of the page features a date range selector, a dropdown for filtering by campaign or brand, and a "Share" button to export the dashboard as a PDF.
A prominent row of cards at the top displays essential metrics like Total Spend, Return on Ad Spend (ROAS), Click-Through Rate (CTR), and Conversion Rate. Each card includes a small sparkline chart showing performance trends over the selected time period.
A large, interactive line graph shows key metrics (ROAS, Spend, Conversions) over time. Users can toggle which metrics are displayed and hover over the graph to see specific data points.
A set of pie charts and bar graphs breaks down performance by audience demographics (age, gender), geography, and device type. This section highlights which audience segments are performing best and worst.
A gallery-like section displays top-performing ad creatives. Each thumbnail shows the ad image or video, along with key metrics like CTR and ROAS. Users can click on a creative to see a detailed performance breakdown.
A dedicated widget powered by R AI Studio provides natural language summaries of the data. For example, it might say, "Campaign X saw a 15% increase in ROAS this week, primarily driven by strong performance among 25-34 year-olds in the Northeast region. Consider increasing budget allocation to this demographic."
Ad DNA Score Interface
The Ad DNA Score interface is designed to help users understand and improve the quality and predicted performance of their ad creative before it goes live.
The top bar includes a file upload button for new creatives, a "History" tab to view previously scored ads, and a "Learn More" link explaining the scoring methodology.
The main part of the screen is a large preview of the ad creative (image or video).
To the right of the creative is a prominent, circular score dial displaying the overall Ad DNA Score from 1 to 100. This score represents the creative's potential effectiveness based on R BRANDS' proprietary algorithm.
Below the main score, a series of gauges or bar charts shows the breakdown of the score into its core components. These could include:
Emotional Resonance: The ad's ability to evoke a strong emotional response.
Clarity & Simplicity: How easy it is for the audience to understand the message.
Brand Integration: How well the brand's identity is incorporated.
Call-to-Action (CTA) Strength: The clarity and power of the call-to-action.
A text box below the score breakdown offers concrete, actionable recommendations for improving the creative. For example, it might suggest, "Increase the contrast of the CTA button to improve visibility," or "Try adding a human element to the image to boost emotional resonance."
R AI Studio (Generative Ad Copy Tool)
The R AI Studio is an intuitive, user-friendly interface for generating and refining ad copy with the help of artificial intelligence.
The header includes a "New Project" button, a list of recent projects, and a "Templates" library for different ad types (e.g., social media post, search ad, email subject line).
On the left side of the screen is an input form where users provide key information. This includes:
Brand Name: A simple text field.
Product/Service: A brief description of what they're promoting.
Key Features/Benefits: A bulleted list or a text box for the most important selling points.
Target Audience: A dropdown or text field to describe the intended audience.
Tone of Voice: A slider or dropdown to select the desired tone (e.g., professional, playful, urgent, luxury).
The right side of the screen displays the generated ad copy. The tool presents several variations of the copy, each optimized for a different platform or goal. For example:
A short, punchy headline with a clear CTA and relevant emojis.
Multiple variations of headlines and descriptions to test in a Google Ads campaign.
A few compelling subject lines with a high predicted open rate.
Users can click on a generated option to edit it directly or use built-in tools to refine it further. These tools could include a "Simplify" button, a "Make More Persuasive" button, or an "A/B Test" option to generate two similar but distinct versions.
I've updated the R BRANDS product mockups to include a powerful new feature in the R AI Studio: generative ad copy powered by the Gemini API! Now, when you fill in the details and click "Generate Ad Copy," the application will use a large language model to create tailored ad content for you.
Here's the updated interactive mockup:
What's New
I've integrated the Gemini API into the R AI Studio tab. Now, when you provide details about your ad campaign (Brand Name, Product/Service, Key Features, Target Audience, and Tone of Voice) and click the "Generate Ad Copy ✨" button, the app will:
Construct a detailed prompt based on your inputs.
Call the Gemini API (gemini-2.5-flash-preview-05-20 model) to generate creative ad copy.
Display three distinct ad copy options: a social media ad, search ad headlines/description, and an email subject line.
Show a loading spinner while the AI is working, and handle potential API errors.
This feature leverages the power of large language models to help you quickly brainstorm and create effective ad content.
http://www.rbrands.co
Fan-Centered Campaign Ecosystems: Leverage crowd-sourced matrices. Scale user-generated content and cross-channel creative efficiently through templated and strict branded automation.
Data-as-Design: Integrate real-time performance metrics with emotional triggers for high-performing, ROI-optimized ad content.
Global Health Initiative: Integrate wellness in its entirety, positively influencing human behaviors and populations.
Global Voices Initiative: Collaborate with worldwide creators, leaders, and influencers to expand market penetration by celebrating diverse language, culture, religion, and identity, unlocking new user segments and unique pathways.
Press-to-Fan Syndication: Strategically integrate PR, paid media, and influencer amplification to generate earned media pre-launch, increasing brand visibility and trust with lower CAC.
