Concepts
The essential vocabulary of AI strategy and growth engineering, defined with precision and context
Key Performance Indicators — quantifiable metrics that track progress toward critical business objectives and strategic goals.
A workflow management method using visual boards to optimize work in progress, reduce bottlenecks, and improve delivery speed.
When multiple pages on the same site compete for the same keyword, splitting ranking authority and reducing overall search visibility.
Identifying and analyzing search terms people use to find information, products, or services to inform content and SEO strategy.
Optimizing help documentation and FAQ content to rank for support-related queries, reducing support tickets while driving organic traffic.
Training a compact student model to reproduce the outputs of a larger teacher model, achieving similar performance at a fraction of the computational cost.
A structured representation of entities and their relationships enabling AI systems to reason about real-world concepts and connections.
Strategies for earning and controlling the information displayed in Google's Knowledge Panels for brands and individuals.
Evaluating large language models across dimensions like accuracy, speed, cost, context length, and specialized capabilities for specific use cases.
The ratio of customer lifetime value to customer acquisition cost, with values above 3:1 generally indicating a healthy and scalable business model.
A sales strategy starting with a small initial deal then growing revenue by adding users, features, or departments within the same account.
A framework for building stateful, multi-step AI agent applications as graphs, enabling complex workflows with conditional branching and cycles.
A neural network trained on massive text datasets to understand and generate human language, forming the basis of modern AI assistants.
Assigning numerical values to leads based on behavior and characteristics to prioritize sales outreach toward highest-potential prospects.
A one-page business model adaptation of Business Model Canvas optimized for startups, emphasizing problem, solution, and unfair advantage.
Systematic elimination of waste in business processes to maximize value delivered to customers with minimal resource expenditure.
A methodology combining lean waste reduction with Six Sigma quality improvement to optimize processes and eliminate defects.
An entrepreneurship methodology emphasizing rapid iteration through build-measure-learn cycles, validated learning, and minimum viable products.
Automated email sequences triggered by user actions or milestones that nurture customers through each stage of their journey from trial to advocacy.
The process of acquiring hyperlinks from external websites to improve search engine rankings and referral traffic.
An investor right determining payout order and multiples in an exit event, protecting investors before common shareholders receive proceeds.
Low-Rank Adaptation, a parameter-efficient fine-tuning method that adds small trainable matrices to frozen model weights, reducing memory and compute requirements.
Optimizing a business's online presence to attract customers from local searches, including Google Business Profile management and local citation building.
Deliberately creating dependencies that make it difficult for customers to leave through data formats, integrations, contracts, and workflow embedding.
Analyzing server log files to understand how search engine crawlers interact with your site, revealing crawl patterns, errors, and indexing issues.
The percentage of customers who cancel their subscription in a given period, regardless of their revenue contribution.
AI models capable of processing extremely long inputs, from hundreds of thousands to millions of tokens, enabling analysis of entire codebases or book-length documents.
Targeting specific, lower-volume search phrases that collectively drive significant traffic and typically have higher conversion intent than broad keywords.
Using AI to find new prospects who share characteristics with your best existing customers, expanding reach while maintaining targeting precision.
A component in an AI application that connects to MCP servers to provide the AI model with access to external context, data, and tool capabilities.
A server implementing the Model Context Protocol that exposes data sources and tools for AI models to access through a standardized interface.
Practices combining machine learning, DevOps, and data engineering to deploy and maintain ML models in production reliably and efficiently.
A subset of AI where systems learn from data patterns to improve performance without explicit programming, using statistical models and algorithms.
The specific point in a user's journey where they first experience the core value of a product, strongly predicting long-term retention.
A sales efficiency metric measuring revenue growth per dollar spent on sales and marketing, guiding investment decisions.
Strategies for increasing profit margins over time through scale economies, pricing optimization, cost reduction, and product mix improvement.
The approach a company uses to enter a new market, including direct entry, partnerships, acquisitions, licensing, or franchise models.
The percentage of a target market using your product, indicating growth potential and competitive position within your addressable market.
Systematic gathering and analysis of market data including customer needs, competitive landscape, and industry trends to inform strategy.
Estimating the revenue potential of a market opportunity using top-down analysis from industry data and bottom-up analysis from customer counts and pricing.
The strategic consideration of when to launch a product or enter a market, as being too early or late significantly impacts success odds.
Software that automates repetitive marketing tasks like email sequences, social posting, and lead nurturing based on predefined rules and triggers.
A centralized repository combining marketing data from all channels and platforms for unified analysis, attribution, and reporting.
Statistical analysis determining each marketing channel's impact on sales, helping optimize budget allocation across the marketing mix.
Coordinating personalized customer experiences across email, ads, web, and mobile channels based on real-time behavioral data and lifecycle stage.
A lead deemed more likely to become a customer based on marketing engagement signals like content downloads and webinar attendance.
Calculating the financial return on marketing investments by connecting marketing spend to revenue outcomes across channels and campaigns.
Key metrics for two-sided marketplace businesses including GMV, take rate, liquidity, and buyer-seller ratio.
Building a two-sided platform connecting buyers and sellers, solving the chicken-and-egg problem through strategic supply or demand seeding.