ACADEMY/MODULE 01
Foundation55 minBUILD: Buyer demand map

Start with the market, not keywords

Turn customer evidence into a prioritized map of the problems, comparisons, and questions that create pipeline.

THE OUTCOME

You will leave with one demand map that tells SEO, content, product marketing, and AEO what to build first.

Market intelligence workspace

Buyer demand control room

Combine CRM outcomes, sales language, search demand, and AI prompts before deciding what to publish.

EXAMPLE WORKSPACEDemo data: reporting SaaS, mid-market agencies
Closed-won reviewed42Last 12 months
Buyer interviews93 roles covered
Demand families267 high priority
Evidence coverage68%+18 pts after calls
VISUAL ANALYSIS

Demand by decision stage

Weight themes by commercial evidence, not search volume alone.

ProblemCalls + forums
86
ApproachSearch + prompts
72
CategoryGSC + competitors
61
VendorCRM + reviews
48
ValidationSecurity + proof
37
0weighted mentions86
REVENUE-FIRST DECISION ENGINE

Turn demand data into a strategy.

Traffic is an input. The decision is where evidence, commercial intent, product fit, proof, and team capacity justify action.

01 / FIND INTENTLabel the buyer decision

Start with modifiers, then inspect the live SERP, ranking page types, sales calls, and the next question. A human assigns the final intent.

02 / FIND REVENUEPrefer observed evidence

CRM opportunities and closed revenue outrank modeled value. Use modeled pipeline only where attribution is missing, and label it as directional.

03 / CHOOSE ACTIONScore, cap, and say no

Rank every demand family, then limit the active list to actual quarterly capacity. Everything else is validated, supported, or parked.

INTENT VALIDATION RUBRIC

Modifiers suggest intent. The ranking page types and buyer evidence confirm it.

IntentQuery cluesSERP proofBuyer decisionLikely asset
Diagnosewhy, problem, meaningGuides and definitionsUnderstand the problemExpert guide
Solutionhow to, automate, improveProcesses and use casesChoose an approachUse-case page
Categorysoftware, platform, toolsProduct and category pagesChoose a solution typeProduct / category
Comparebest, top, vs, alternativesLists and comparisonsBuild a shortlistComparison / best-of
Vendorbrand, reviews, demoVendor and review pagesEvaluate a named vendorVendor / proof
Pricingprice, cost, plans, ROIPricing and calculatorsValidate commercial fitPricing / ROI
Validateintegration, security, migrationDocs, proof, implementationRemove purchase riskIntegration / proof
REVENUE EVIDENCE HIERARCHY

Use the strongest evidence available and keep weaker estimates visibly separate.

MethodEvidenceHow to use itConfidence
Sourced revenueLanding page or content is the recorded acquisition sourceUse directlyHighest
Influenced revenueAsset was touched before opportunity or closeReport separately with windowHigh
Opportunity evidenceDemand family appears in calls, forms, notes, or campaignsOpps x win rate x ACVMedium-high
Paid-search evidenceCPC, conversion, and opportunity quality existUse as commercial validationMedium
Modeled potentialNo direct CRM history existsVolume x CTR x conversion x ACVDirectional
MODELING ASSUMPTIONS

Use your own GSC, analytics, and CRM rates. These assumptions affect modeled potential, not observed revenue.

SELECTED NOW5Capacity, not wish list
MODELED PIPELINE$204kDirectional annual estimate
SELECTED VOLUME3,670Not the ranking criterion
PARKED / LATER5Deliberately not active
NowDemand familyIntentSVCRM revenueOppsWin %ACVFitEvidenceGapSalesEffortPage stateOpp expected revenueModeled pipelineScoreNext action
YES$39,440$13,26090.5Refresh + prove
YES$45,360$102,60089.0Refresh + prove
YES$43,560$31,68088.0Refresh + prove
YES$61,380$38,88087.0Build revenue page
YES$43,320$17,67085.0Refresh + prove
LATER$49,980$24,57084.5Build revenue page
LATER$20,800$18,72074.0Fix blocker first
LATER$17,600$60,00069.5Consolidate URLs
LATER$4,320$86,40044.0Park
LATER$0$104,40031.5Park
ACTION THRESHOLDS

80-100: build or refresh now. 65-79: validate and queue. 50-64: supporting backlog. Below 50: park. Overlap and technical blockers override the score.

REVENUE HIERARCHY

Best: sourced or influenced CRM revenue. Next: opportunity and win evidence. Last: modeled pipeline using explicit assumptions. Never present modeled value as revenue.

WHY THIS MODULE MATTERS

Keyword tools show what people type. They do not tell you which pains create urgency, which objections stall deals, or how buyers ask AI for a shortlist. Start with evidence from the market, then translate it into search queries and prompts.

01.1

Choose one revenue segment

A broad ICP produces a broad content plan. Pick one segment where the problem, buying process, and product fit are similar enough to write a precise answer.

KEY DECISIONS AND FIELD CHECKS / 5 ITEMS
  • 01

    Export the last 20 closed-won deals and group them by company type, size, use case, and buyer role.

  • 02

    Score each group from 1-5 for win rate, ACV, sales-cycle speed, retention, and access to customer evidence.

  • 03

    Select one segment for this 90-day cycle. Write it as: [role] at [company type] who need [job] before [trigger].

  • 04

    Collect: Export 12 months of closed-won, closed-lost, and stalled opportunities with segment, role, ACV, and loss reason.

  • 05

    Score: Score revenue evidence, frequency, strategic fit, current visibility, and production effort separately.

HUMAN OWNSJudgment and approval

Choose the business priority, interpret exceptions, protect confidential data, challenge weak evidence, and approve the final decision.

AI ASSISTSAnalysis and structure

Clean, classify, compare, calculate, and draft rows from supplied evidence. AI may surface patterns; it does not own strategy.

SOURCE FILESOpportunity export

HubSpot / Salesforce, plus tagged call evidence from Gong / call notes.

OUTPUT PREVIEW / segment-scorecard.CSVOne example row from the finished deliverable
EXAMPLE DATA - REPLACE IT
SegmentWinsWin rateMedian ACVSales cycleRetentionEvidenceWeighted score
Mid-market agencies1434%$18k41 days93%8 calls23.4 / 30
CLAUDE / CHATGPT PROMPTAnalyze the evidence without outsourcing the decision
BEFORE RUNNING

Remove personal or confidential data. Attach the named exports, explain every column, and tell the model when the dataset was collected.

You are assisting a human B2B SaaS SEO and AEO operator with Module 01: Start with the market, not keywords.

Current lesson: Choose one revenue segment
Objective: A broad ICP produces a broad content plan. Pick one segment where the problem, buying process, and product fit are similar enough to write a precise answer.
Required artifact: Buyer demand map

BUSINESS CONTEXT I WILL PROVIDE
- Product, category, target market, pricing model, sales motion, and geography
- The priority customer segment and the commercial outcome for this 90-day cycle
- Opportunity export exported from HubSpot / Salesforce
- Tagged call evidence exported from Gong / call notes
- Definitions for any internal fields, stages, scores, and abbreviations

TASK
1. Export the last 20 closed-won deals and group them by company type, size, use case, and buyer role.
2. Score each group from 1-5 for win rate, ACV, sales-cycle speed, retention, and access to customer evidence.
3. Select one segment for this 90-day cycle. Write it as: [role] at [company type] who need [job] before [trigger].
4. Collect: Export 12 months of closed-won, closed-lost, and stalled opportunities with segment, role, ACV, and loss reason.
5. Score: Score revenue evidence, frequency, strategic fit, current visibility, and production effort separately.

REQUIRED OUTPUT
Return a table using these exact columns: Segment | Wins | Win rate | Median ACV | Sales cycle | Retention | Evidence | Weighted score.
For every recommendation, cite the source row, URL, call note, or data point that supports it.
Add a confidence column in your analysis: High, Medium, or Low.
List missing evidence separately instead of guessing.
Finish with a section named HUMAN DECISIONS REQUIRED.

RULES
- Do not invent search volume, revenue, customer statements, product capabilities, or competitor facts.
- Do not treat correlation as causation.
- Preserve contradictory evidence and explain why it conflicts.
- Do not make the final priority or publishing decision. Prepare the evidence for a human owner.
- Use this example only as a format reference, not as evidence: Head of Marketing at a 20-100 person B2B SaaS company who needs reliable attribution before the next board meeting.
HUMAN APPROVAL GATE

One segment is named precisely. A named human owner must verify this before the lesson is complete.

B2B SAAS EXAMPLE

Head of Marketing at a 20-100 person B2B SaaS company who needs reliable attribution before the next board meeting.

01.2

Mine buyer language

Your best query research is already hiding in sales calls, onboarding notes, support tickets, and reviews.

KEY DECISIONS AND FIELD CHECKS / 4 ITEMS
  • 01

    Collect 10 sales transcripts, 10 support conversations, five reviews, and the notes from five lost deals.

  • 02

    Highlight exact phrases for pain, desired outcome, failed approach, evaluation criteria, objection, and trigger.

  • 03

    Keep the buyer wording. Add a tally each time the same idea appears; frequency reveals the category vocabulary.

  • 04

    Listen: Review at least 10 calls and tag exact problem, trigger, objection, comparison, and proof language.

HUMAN OWNSJudgment and approval

Choose the business priority, interpret exceptions, protect confidential data, challenge weak evidence, and approve the final decision.

AI ASSISTSAnalysis and structure

Clean, classify, compare, calculate, and draft rows from supplied evidence. AI may surface patterns; it does not own strategy.

SOURCE FILESTagged call evidence

Gong / call notes, plus query export from GSC + Semrush / Ahrefs.

OUTPUT PREVIEW / buyer-language-library.CSVOne example row from the finished deliverable
EXAMPLE DATA - REPLACE IT
Exact phraseRoleStageSourceFrequencyMeaningHuman approved
Reports take all MondayOps leadProblemCall 1847Manual consolidationYes
CLAUDE / CHATGPT PROMPTAnalyze the evidence without outsourcing the decision
BEFORE RUNNING

Remove personal or confidential data. Attach the named exports, explain every column, and tell the model when the dataset was collected.

You are assisting a human B2B SaaS SEO and AEO operator with Module 01: Start with the market, not keywords.

Current lesson: Mine buyer language
Objective: Your best query research is already hiding in sales calls, onboarding notes, support tickets, and reviews.
Required artifact: Buyer demand map

BUSINESS CONTEXT I WILL PROVIDE
- Product, category, target market, pricing model, sales motion, and geography
- The priority customer segment and the commercial outcome for this 90-day cycle
- Tagged call evidence exported from Gong / call notes
- Query export exported from GSC + Semrush / Ahrefs
- Definitions for any internal fields, stages, scores, and abbreviations

TASK
1. Collect 10 sales transcripts, 10 support conversations, five reviews, and the notes from five lost deals.
2. Highlight exact phrases for pain, desired outcome, failed approach, evaluation criteria, objection, and trigger.
3. Keep the buyer wording. Add a tally each time the same idea appears; frequency reveals the category vocabulary.
4. Listen: Review at least 10 calls and tag exact problem, trigger, objection, comparison, and proof language.

REQUIRED OUTPUT
Return a table using these exact columns: Exact phrase | Role | Stage | Source | Frequency | Meaning | Human approved.
For every recommendation, cite the source row, URL, call note, or data point that supports it.
Add a confidence column in your analysis: High, Medium, or Low.
List missing evidence separately instead of guessing.
Finish with a section named HUMAN DECISIONS REQUIRED.

RULES
- Do not invent search volume, revenue, customer statements, product capabilities, or competitor facts.
- Do not treat correlation as causation.
- Preserve contradictory evidence and explain why it conflicts.
- Do not make the final priority or publishing decision. Prepare the evidence for a human owner.
- Use this example only as a format reference, not as evidence: “We cannot explain which campaigns influence pipeline” is stronger source material than “marketing analytics software.”
HUMAN APPROVAL GATE

At least 25 buyer questions are mapped. A named human owner must verify this before the lesson is complete.

B2B SAAS EXAMPLE

“We cannot explain which campaigns influence pipeline” is stronger source material than “marketing analytics software.”

01.3

Build the demand ladder

Map the questions a buyer asks from first pain to final vendor validation. This prevents a content plan made entirely of awareness posts.

KEY DECISIONS AND FIELD CHECKS / 6 ITEMS
  • 01

    Create five stages: problem, approach, category, comparison, and validation.

  • 02

    Write five real buyer questions at every stage, using evidence gathered in the previous lesson.

  • 03

    For each question, add the best page type, proof needed, business value, and whether buyers ask it in Google, AI, or both.

  • 04

    Expand: Add GSC queries, paid-search terms, competitor pages, review sites, communities, and AI prompt variants.

  • 05

    Map: Assign one primary asset and one owner to every priority demand family.

  • 06

    Validate: Have sales and customer success challenge the map before content production begins.

HUMAN OWNSJudgment and approval

Choose the business priority, interpret exceptions, protect confidential data, challenge weak evidence, and approve the final decision.

AI ASSISTSAnalysis and structure

Clean, classify, compare, calculate, and draft rows from supplied evidence. AI may surface patterns; it does not own strategy.

SOURCE FILESQuery export

GSC + Semrush / Ahrefs, plus prompt families from ChatGPT / Perplexity.

OUTPUT PREVIEW / demand-ladder.CSVOne example row from the finished deliverable
EXAMPLE DATA - REPLACE IT
ProblemApproachCategoryVendorValidationTarget asset
Manual client reportingAutomate reportsAgency reporting softwareSwydo alternativesWhite-label proof/agency-reporting/
CLAUDE / CHATGPT PROMPTAnalyze the evidence without outsourcing the decision
BEFORE RUNNING

Remove personal or confidential data. Attach the named exports, explain every column, and tell the model when the dataset was collected.

You are assisting a human B2B SaaS SEO and AEO operator with Module 01: Start with the market, not keywords.

Current lesson: Build the demand ladder
Objective: Map the questions a buyer asks from first pain to final vendor validation. This prevents a content plan made entirely of awareness posts.
Required artifact: Buyer demand map

BUSINESS CONTEXT I WILL PROVIDE
- Product, category, target market, pricing model, sales motion, and geography
- The priority customer segment and the commercial outcome for this 90-day cycle
- Query export exported from GSC + Semrush / Ahrefs
- Prompt families exported from ChatGPT / Perplexity
- Definitions for any internal fields, stages, scores, and abbreviations

TASK
1. Create five stages: problem, approach, category, comparison, and validation.
2. Write five real buyer questions at every stage, using evidence gathered in the previous lesson.
3. For each question, add the best page type, proof needed, business value, and whether buyers ask it in Google, AI, or both.
4. Expand: Add GSC queries, paid-search terms, competitor pages, review sites, communities, and AI prompt variants.
5. Map: Assign one primary asset and one owner to every priority demand family.
6. Validate: Have sales and customer success challenge the map before content production begins.

REQUIRED OUTPUT
Return a table using these exact columns: Problem | Approach | Category | Vendor | Validation | Target asset.
For every recommendation, cite the source row, URL, call note, or data point that supports it.
Add a confidence column in your analysis: High, Medium, or Low.
List missing evidence separately instead of guessing.
Finish with a section named HUMAN DECISIONS REQUIRED.

RULES
- Do not invent search volume, revenue, customer statements, product capabilities, or competitor facts.
- Do not treat correlation as causation.
- Preserve contradictory evidence and explain why it conflicts.
- Do not make the final priority or publishing decision. Prepare the evidence for a human owner.
- Use this example only as a format reference, not as evidence: Problem: “Why is our attribution different in every tool?” Comparison: “Dreamdata vs HockeyStack for B2B SaaS.”
HUMAN APPROVAL GATE

Every question has evidence and a stage. A named human owner must verify this before the lesson is complete.

B2B SAAS EXAMPLE

Problem: “Why is our attribution different in every tool?” Comparison: “Dreamdata vs HockeyStack for B2B SaaS.”

01.4

Prioritize by revenue, not volume

A low-volume comparison can be worth more than a high-volume definition. Use a score that reflects commercial value.

KEY DECISIONS AND FIELD CHECKS / 4 ITEMS
  • 01

    Score business fit, buying intent, evidence advantage, and sales usefulness from 1-5.

  • 02

    Subtract execution difficulty from 1-5. Use: fit + intent + evidence + sales value - difficulty.

  • 03

    Move the ten highest-scoring questions into the next modules. Park everything else in a later backlog.

  • 04

    Cluster: Group language by buyer job and decision, not by matching words.

HUMAN OWNSJudgment and approval

Choose the business priority, interpret exceptions, protect confidential data, challenge weak evidence, and approve the final decision.

AI ASSISTSAnalysis and structure

Clean, classify, compare, calculate, and draft rows from supplied evidence. AI may surface patterns; it does not own strategy.

SOURCE FILESPrompt families

ChatGPT / Perplexity, plus opportunity export from HubSpot / Salesforce.

OUTPUT PREVIEW / demand-priority-queue.CSVOne example row from the finished deliverable
EXAMPLE DATA - REPLACE IT
Demand familyRevenue evidenceSearch / prompt evidenceCurrent gapEffortPriorityOwner
Automate client reports11 wins1,120 queriesNo use-case pageMediumP1Growth
CLAUDE / CHATGPT PROMPTAnalyze the evidence without outsourcing the decision
BEFORE RUNNING

Remove personal or confidential data. Attach the named exports, explain every column, and tell the model when the dataset was collected.

You are assisting a human B2B SaaS SEO and AEO operator with Module 01: Start with the market, not keywords.

Current lesson: Prioritize by revenue, not volume
Objective: A low-volume comparison can be worth more than a high-volume definition. Use a score that reflects commercial value.
Required artifact: Buyer demand map

BUSINESS CONTEXT I WILL PROVIDE
- Product, category, target market, pricing model, sales motion, and geography
- The priority customer segment and the commercial outcome for this 90-day cycle
- Prompt families exported from ChatGPT / Perplexity
- Opportunity export exported from HubSpot / Salesforce
- Definitions for any internal fields, stages, scores, and abbreviations

TASK
1. Score business fit, buying intent, evidence advantage, and sales usefulness from 1-5.
2. Subtract execution difficulty from 1-5. Use: fit + intent + evidence + sales value - difficulty.
3. Move the ten highest-scoring questions into the next modules. Park everything else in a later backlog.
4. Cluster: Group language by buyer job and decision, not by matching words.

REQUIRED OUTPUT
Return a table using these exact columns: Demand family | Revenue evidence | Search / prompt evidence | Current gap | Effort | Priority | Owner.
For every recommendation, cite the source row, URL, call note, or data point that supports it.
Add a confidence column in your analysis: High, Medium, or Low.
List missing evidence separately instead of guessing.
Finish with a section named HUMAN DECISIONS REQUIRED.

RULES
- Do not invent search volume, revenue, customer statements, product capabilities, or competitor facts.
- Do not treat correlation as causation.
- Preserve contradictory evidence and explain why it conflicts.
- Do not make the final priority or publishing decision. Prepare the evidence for a human owner.
- Use this example only as a format reference, not as evidence: A query with 40 monthly searches and a score of 16 outranks a 2,000-volume glossary term with a score of 7.
HUMAN APPROVAL GATE

The top 10 opportunities are scored and selected. A named human owner must verify this before the lesson is complete.

B2B SAAS EXAMPLE

A query with 40 monthly searches and a score of 16 outranks a 2,000-volume glossary term with a score of 7.

DEFINITION OF DONE0% complete
0/4

Check each item only after the artifact meets the standard.