Foundation & Strategic Alignment // khaki.mov

Before we write a single line of code, or even think about what data we need, we need to know why we’re doing this. This isn’t about building a cool technology; it’s about solving real business problems and delivering measurable value. This is the “User-First” principle in action.

Objective of this step: Precisely articulate the business problems our Knowledge Graph (KG) will solve, identify the primary users, and define the specific questions it must answer. If we can’t answer this clearly, we’re building a solution in search of a problem, and that’s a waste of resources.

Identify Key Stakeholders: List out the departments and specific roles (e.g., “Competitive Intelligence Analyst,” “Sales Strategy Lead,” “Product Manager for X Division”) that would benefit most from a comprehensive understanding of competitors and market data. We need to interview them.

1. Identified Key Stakeholders & Roles:

Verdict: Sufficient for initial identification.
Extracted Roles:
- Competitive Intelligence Analysts
- Sales Strategy Leads / Sales Teams (including “boots on the ground”)
- Product Managers (PMs) / Product Development Teams
- Strategy Teams / Business Analysts
- Data Scientists (as potential users/contributors)
- Buyers (though their feedback is data source, their pain points are typically channeled through the above roles)

2. Summary of Top 3-5 Pain Points:

Verdict: Excellent and clearly articulated.
Synthesized Pain Points:
1. Manual & Time-Consuming Data Aggregation: “Manually tracking competitors across various sources can be time-consuming and resource-intensive, diverting focus from core business activities.” “require aggregating data from multiple sources.”
2. Lack of Actionable Insights from Raw Data: “struggle with turning raw data into actionable insights.”
3. Difficulty in Tracking Fast-Changing Markets & Emerging Threats: “keeping up with fast-changing markets,” “miss emerging players in niche markets.”
4. Inability to Address Detailed, Multi-faceted Questions: “Companies need answers to detailed questions they currently can’t easily address.”

Conduct “Why” Workshops/Interviews:

What are their biggest pain points related to competitive intelligence and company data today? (e.g., “It takes me days to manually compile a list of competitors for a new product launch,” “I can’t quickly find out what technologies our competitors are actually using vs. just marketing,” “We often miss emerging players in niche markets.”)
What specific questions do they need answered by a system that they currently cannot answer, or can only answer with immense effort? Get concrete examples. Don’t let them say “I need to understand the market.” Push for: “List all companies in the ‘FinTech AI for SMBs’ space that have raised over $10M in the last 12 months and were founded after 2020.”
How would answering these questions impact their daily work or business outcomes? (e.g., “Reduce analysis time by 30%,” “Identify 10% more relevant acquisition targets,” “Improve sales targeting accuracy.”)

3. At least 5-7 Concrete, Specific Questions the KG Must Answer:

Verdict: You’ve provided an abundance of specific questions. I’ve selected the most relevant and actionable ones for an initial KG, prioritizing those that leverage graph capabilities and NLP for unstructured data.
Selected Specific Questions:
1. “List all companies in the ‘FinTech AI for SMBs’ space that have raised over $10M in the last 12 months and were founded after 2020.” (Excellent, highly specific, combines multiple data points).
2. “What are the key features of [Competitor X]‘s latest product, and how does its pricing compare to ours?” (Requires structured feature/pricing extraction and comparison).
3. “Identify emerging players (founded in the last 3 years) in Industry Y, and summarize their stated go-to-market channels and core technologies from their websites and recent press releases.” (Refinement of “Who are the new players…” - requires NLP and relation extraction).
4. “What are the top pain points our customers experience with [Competitor Z]‘s product, as identified in public customer reviews (e.g., G2, Trustpilot), and how does our product compare in addressing these points?” (Requires sentiment/aspect-based analysis from review data).
5. “For Company X, summarize their current hiring trends by location and technology focus (e.g., are they hiring a lot of AI/Mobile engineers in California?), inferring strategic investment areas.” (Requires job posting analysis and inference).
6. “Given Company A, Company B, and Company C as direct competitors, what shared technologies and product categories do they mention on their websites, and what unique offerings differentiate each?” (Highlights comparative analysis and differentiation).
7. “Which competitor products are frequently used alongside another competitor’s product by the same customer (based on review analysis), and what is the stated reason for this co-use?” (Crucial for understanding market dynamics and ecosystem plays).

Draft a “KG Mission Statement”: Based on these discussions, formulate a concise, compelling statement that captures the core purpose and value proposition of our KG. Something like: “To empower [Target Users] with real-time, comprehensive, and actionable insights into the competitive landscape, accelerating strategic decision-making and fostering innovation.”

Proposed KG Mission Statement: “To empower strategic decision-makers with timely, integrated, and actionable insights into the competitive landscape, transforming disparate raw data into a cohesive knowledge graph that significantly reduces manual analysis time, increases sales effectiveness, and accelerates product innovation.”

Prioritize Initial, High-Impact Use Cases: From the laundry list of questions, identify 2-3 initial, high-impact use cases that, if solved well by the KG, would demonstrate significant value and gain immediate buy-in. These will form the basis of our MVP.

Prioritized MVP Use Cases:
1. Emerging Competitor Identification & Basic Profile: Focus on automatically identifying new and growing companies in specified industry niches, extracting their foundational details (founding date, reported funding rounds, primary product/service categories, and explicit technology mentions from their ‘About Us’ and ‘Product’ website pages).
  - Directly addresses: Pain point 3 (“missing emerging players”).
  - Answers questions like: “List all companies in the ‘FinTech AI for SMBs’ space that have raised over $10M in the last 12 months and were founded after 2020.”
2. Competitor Product Feature & Value Proposition Overview: For a curated list of top competitors, extract and summarize their core product features, stated value propositions, and publicly available pricing models (if discoverable). This will enable direct comparisons.
  - Directly addresses: Pain point 4 (“detailed questions about features/pricing”).
  - Answers questions like: “What are the key features of [Competitor X]‘s latest product, and how does its pricing compare to ours?”
3. Technology Landscape & Strategic Focus Inference: Analyze competitors’ stated technologies (from websites) and hiring patterns (from job postings) to infer their current and upcoming technological investments and strategic focus areas.
  - Directly addresses: Pain point 4 (“what technologies our competitors are actually using”).
  - Answers questions like: “For Company X, summarize their current hiring trends by location and technology focus, inferring strategic investment areas.”

What I Expect from You (Your Deliverable for this step):

A list of identified stakeholders and their roles.
A summary of the top 3-5 pain points identified across these stakeholders.
A list of at least 5-7 concrete, specific questions that the KG must be able to answer, directly tied to the pain points. - These should be complex enough that simple database queries couldn’t easily answer them.
Your proposed KG Mission Statement.
Your prioritized list of 2-3 high-impact MVP use cases, clearly described.