Insights on perspective, context and decision-making.
Essays on perspective, context and decision-making: market intelligence, business assessment, data and scenario planning.
Business strategy and intelligence consulting: what it does and when to hire a firm
Understand what a business strategy and intelligence consultancy does, when to hire one, and how it connects market, customers, product, and revenue.
Strategy consultancy and specialized agency: differences in scope, deliverables, and responsibility
Understand the differences between a strategy consultancy and a specialized agency, what each delivers, and how to choose a partner for your company.
Business assessment: how to set priorities before investing in solutions
Understand how a business assessment analyzes the market, customers, and operations to set priorities and guide investment in solutions.
Decision-making in complex environments: how to use perspective, context, and data
Learn how to use perspective, context, and data to compare alternatives, guide investments, and track results in your company.
Scenario planning: how to prepare for decisions in volatile markets
Understand how scenario planning guides investment, offerings, and delivery capacity under different market conditions.
Market intelligence: how to guide positioning, product, and investment
Understand how market intelligence guides positioning, products, segments, and investments using customer, competitor, and operational data.
Data in context: how metrics become meaningful for management
Learn how to analyze metrics in context, compare periods, and connect marketing, sales, product, and revenue data to the management of your business.
Single source of truth: how to organize data across marketing, sales, and finance
Learn how to organize definitions, sources, and responsibilities to reconcile marketing, sales, and finance data in your company.
Data governance for AI: foundations, responsibilities, and information quality
Learn how to organize sources, quality standards, access, and responsibilities to use data in your company's artificial intelligence projects.
Executive metrics: how to measure marketing, revenue, and operations
Organize executive metrics to track marketing, revenue, and operations, with clear definitions and analysis tied to your company's objectives.
Semantic brand identity: how to be understood by people, search engines, and AI
Understand how to organize your category, offering, audiences, and supporting evidence so customers, search engines, and AI assistants can understand your brand.
SEO, GEO, and AEO in 2026: what changes in organic visibility
Understand the differences between SEO, GEO, and AEO and how to organize content, technical access, and measurement for AI searches and answers.
How to get cited by ChatGPT, Gemini, Google AI, and Microsoft Copilot
Learn how to organize content, authorship, sources, and technical access to support your company's presence in AI searches and answers.
B2B content for Search AI: how to answer buyers' questions
Organize B2B content with clear answers, experience, sources, and authorship to support buyers using search engines and AI assistants.
B2B digital authority: trust signals before the first sales conversation
Understand which information, evidence, and references help B2B buyers evaluate your company's experience and credibility.
Revenue architecture: how brand, acquisition, CRM and sales contribute to the business
Understand how to connect brand, acquisition, CRM, sales, product and retention to organize how your company generates and sustains revenue.
Marketing and sales: how to align audiences, information and responsibilities
Learn how to align marketing and sales through definitions of target audiences, qualification, inquiry handling and sales follow-up tied to revenue.
Demand quality: how to assess intent, fit and sales potential
Learn to assess demand quality by fit, intent, purchase timing and sales potential, using marketing and sales information.
B2B marketing attribution: how to analyze influence across long buying journeys
Understand B2B attribution models, their limits and how to combine channel, CRM and customer data to analyze marketing's contribution.
Paid media planning: how to allocate investment across brand, demand and purchase
Learn how to plan paid media around your audience, offer, purchase intent, and sales capacity, with investment and measurement aligned to each objective.
AI in business: how to choose applications with economic value
Learn how to choose AI applications based on tasks, data, investment, and results, using tests and ongoing measurement of their value to your company.
AI projects: how context, data, and adoption contribute to returns
Understand how to evaluate returns on AI projects using data, actual usage, output quality, and total implementation and operating investment.
AI agents in B2B purchasing: information brands and sales teams need to organize
Understand how AI agents support B2B research and what information your company needs to organize about its offering, implementation, and experience.
Technology as a management tool: how to choose tools based on your business context
Learn how to choose tools based on your company's processes, data, integration needs, total investment, and capacity for adoption.
Change management in marketing, data, and AI: how to plan for adoption
Learn how to plan the adoption of processes and technologies in marketing, data, and AI, with clear responsibilities, training, and usage monitoring.
Event intelligence: how audiences, content, and sales generate business value
Learn how to connect market insight, audiences, content, exhibitors, and sponsorship to build business value for trade shows and professional events.
Market research for trade shows: audience, positioning, and commercial proposals
Learn how to research markets, visitors, exhibitors, and sponsors to guide a trade show’s positioning and commercial proposals.
Registration data: how to assess an event’s audience profile
Understand how to analyze registration, attendance, profiles, and interests to assess your audience and guide your event’s sales planning.
Audience intelligence for exhibitors and sponsors: how to structure commercial proposals
Learn how to use audience data to structure proposals for exhibitors and sponsors, with defined deliverables, objectives, and performance tracking.
Trade show results: how to measure audience, relationships, and ongoing engagement
Learn how to measure trade show results using audience, experience, opportunity, and revenue data, distinguishing participation from confirmed business.
Digital complexity: how to connect marketing, sales, data, and technology
Learn how to connect marketing, sales, customer service, product, data, and technology to improve your company's management and performance.
Digital transformation: how to connect technology, processes, and results
Learn how to select and implement technology with objectives, accountable owners, data, and metrics tied to your company's results.
From digital presence to market intelligence: how to use business signals
Learn how to connect searches, content, customer service, CRM, and product usage to guide positioning, offerings, and investments.
The company as an adaptive system: connecting signals, response, and learning
Learn how to connect markets, customers, marketing, sales, product, and data in a regular process of analysis, response, and monitoring.
The B2B sales funnel: what it measures and what happens outside it
Understand what the sales funnel measures, how B2B buyers research, and why management needs to track accounts, buying groups, and signals.
The B2B dark funnel: what happens before the first sales contact
Understand how buyers research suppliers outside the CRM and how to connect content, events, referrals, and sales data to the B2B journey.
From lead to purchase intent: how to evaluate B2B account signals
Learn how to analyze fit, frequency, depth, and buying group participation to guide sales engagement with B2B accounts.
Full pipeline, uncertain revenue: how to evaluate sales opportunities
Understand how to analyze fit, buyer progress, time in stage, and probability to improve sales pipeline quality.