Quality Engineering Proposal - https://rasa.io/

Quality Engineering Excellence

Prepared for Eric

https://rasa.io/ • Comprehensive proposal • Tailored solutions • Measurable outcomes

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Hi Eric,

It's clear that rasa.io is doing significant work in transforming how associations engage their members through AI-powered personalization. We believe our QA expertise can provide valuable support as your team continues to innovate and expand its impact in this critical area.

01 Business Context

Based on what we understand about rasa.io's mission and offerings:

  • Your core focus is on AI-powered personalization to drive engagement, renewals, and revenue for associations and nonprofits.
  • You offer a suite of cutting-edge AI software, including Newsletters, Campaigns, and Market Intelligence.
  • The platform is specifically designed for associations, emphasizing ethical AI and maximizing value.
  • You are an AI-native company, having served hundreds of organizations for years and consistently updating your AI.
  • Your system handles high volume, sending a million unique emails daily, which actively makes your AI smarter.
  • A key value proposition is consistently delivering 3x higher engagement rates, increasing non-dues revenue, and saving staff time.
  • Your work fundamentally changes how associations connect with members, addressing challenges like content discoverability and member churn.
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02 Key Risks & Quality Gaps

Given the sophisticated nature of your AI and personalization capabilities, we've identified potential areas where dedicated quality assurance can strengthen your offerings:

  • AI Personalization Accuracy: Ensuring that the "AI-personalized newsletters" and "multi-step email campaigns" consistently deliver relevant content and achieve desired engagement, rather than misfiring or causing user frustration.
  • Data Integrity & Privacy-Forward Approach: Validating the accuracy and ethical use of the "monetized data collected in rasa.io in a privacy-forward way" to prevent breaches or misrepresentation, which is critical for trust.
  • Campaign Logic & Conversion: Verifying that the complex "AI-personalized multi-step email campaigns" function as intended across various use cases (marketing, membership, events) and consistently lead to increased conversion rates.
  • Scalability & Performance Under Load: With "a million unique emails every day," ensuring the system maintains optimal performance, reliability, and that the AI continues to learn effectively without degradation.
  • AI Model Validation & Regression: As you "continually update your AI to ensure the best results," there's a risk of new updates inadvertently introducing regressions or reducing the effectiveness of personalization.
  • Engagement Consistency & Churn Reduction: Proving that the AI consistently "keeps folks engaged year-round" and effectively "retains members and reduces churn," rather than experiencing periods of disengagement.
  • Content Unlock & Discoverability: Confirming that AI personalization genuinely helps members find content they want, preventing them from "stop trying and go elsewhere."
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03 Value Proposition Summary

Aspect Current State (As addressed by rasa.io) Desired Future State (rasa.io's goals) How Our QA Helps
Member Engagement Inconsistent engagement; members receiving generic content. 3x higher, consistent engagement year-round. Validate AI personalization relevance and effectiveness across all products to ensure sustained engagement.
Revenue & Renewals Challenges with member retention and non-dues revenue generation. Increased renewals, reduced churn, higher non-dues and ad revenue. Verify campaign conversion logic and market intelligence monetization without compromising member trust.
Product Reliability Existing AI solutions are functional and continually updated. AI solutions are robust, highly accurate, and perform flawlessly at scale. Implement targeted testing for AI model accuracy, data privacy, system scalability, and new feature releases.
Operational Efficiency Staff time spent on manual personalization efforts. Significant staff time savings. Ensure automation and AI features perform as expected, freeing up staff time with confidence.
Ethical AI & Data Commitment to privacy-forward, ethically sound AI. Proven, auditable adherence to ethical AI and data privacy standards. Develop and execute privacy and ethical AI testing protocols.

04 90-Day Roadmap

Phase Focus Area Key Activities Expected Outcomes
Weeks 1-4: Discovery & Assessment Understand your AI ecosystem and quality needs. Conduct in-depth sessions with your product, engineering, and data science teams to map current workflows. Review existing data sources, AI models, and current testing practices for Newsletters and Campaigns. Clear understanding of your AI architecture, data flows, and current QA landscape for core products. Identification of initial high-impact areas.
Weeks 5-8: Strategy & Framework Development Tailor a QA strategy for AI personalization. Propose a customized QA strategy focusing on AI accuracy, data integrity, and privacy compliance for Market Intelligence. Define a robust test framework for personalized content generation and campaign execution. A comprehensive, actionable QA strategy and a well-defined test framework for your key products.
Weeks 9-12: Initial Implementation & Baseline Begin testing and establish quality benchmarks. Execute initial test cases based on the developed framework, focusing on a critical personalization flow or campaign. Establish baseline quality metrics for AI output and system performance. Identification of immediate improvements, a quantifiable baseline for quality, and a proven approach to your specific AI testing needs.

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05 KPI & Success Metrics

Metric Category rasa.io's Goal (as per website) Our QA Contribution Long-Term Impact (Joint)
Engagement 3x higher engagement rates; year-round member engagement. Validation of AI personalization accuracy and relevance. Sustained and verifiable increase in member engagement metrics.
Conversion & Revenue Increased conversion rates; higher non-dues revenue. Testing of campaign logic, targeting, and Market Intelligence monetization. Improved ROI from campaigns and increased recurring revenue streams.
Product Quality Best results through continually updated AI; reliable platform. Reduction in critical defects post-release; improved AI model validation scores. Enhanced product stability, faster time-to-market for new features, reduced support burden.
Trust & Compliance Privacy-forward data monetization; ethical AI. Test coverage for data privacy controls and ethical AI guidelines. Strengthened member trust, ensured compliance, and reinforced brand reputation.
Performance & Scalability Sending a million unique emails daily; making AI smarter. Verification of system performance under load; data integrity for AI learning. Seamless operation at scale, continuous AI improvement, and high system reliability.

06 Engagement Approach & Next Steps

Our approach is highly collaborative, integrating with your existing teams to augment your capabilities and embed a culture of quality tailored to AI-driven products. We prioritize clear communication, data-driven insights, and practical recommendations that align with your business objectives.

We would appreciate the opportunity to discuss this proposal further with you and your team. A brief call would allow us to answer any questions you may have and explore how we can best support rasa.io's continued success. Please let us know what time works best for you.

Ready to Transform Your Quality Engineering?

Let's discuss how we can elevate your product quality and accelerate delivery

Limited Q1 2026 Slots Available
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