buyer intelligence: account targetingThe Six Layer
Account Targeting and Prioritization Framework
For High Converting Revenue Opportunities
Know which accounts to pursue, in what order, and when they are ready.
ONE-TIME$297
THE FOUNDATIONWhere most account targeting breaks.
You have a target account list, and you have been working it for months. You also have a sense that not all the accounts on it belong there. You have a slide or document somewhere that calls itself an ICP, or an IAP, or something close. The team references it, but everyone makes their own judgment calls in practice. You have closed some. You have lost others. You cannot precisely articulate why.
You have started to wonder whether the problem is further upstream than that.
THE FRAMEWORKSix layers of account targeting
and prioritization.
Account targeting that holds up is built in six layers. Together, they tell you which accounts to pursue, in what order, and when they are ready. The output of each layer feeds directly into the next, so by the time an account reaches your engagement list, it has been qualified at every level above it.
01
Layer 1: Industry Pain Prioritization Toolkit
Produces → Ranked Industry Priorities
Score and rank industry-level pains so your GTM focus starts where problems are most revenue-critical. The output is a clear, auto-calculated recommendation per industry: Primary Focus, Secondary, Validate First, or Not Ready.
- Pain Benchmark library of pre-researched, validated industry pains with VOC evidence and source links across SaaS, Healthcare, FinTech, EdTech, Retail, and others
- Industry Identification framework for narrowing focus to 3 to 7 candidate industries before deep analysis
- Industry Pains List for capturing, scoring, and ranking pains across four criteria (urgency, revenue impact, prevalence, strategic fit)
- Selection and Validation tab with auto-calculated pain summary plus a 5-question evidence checklist to confirm readiness
- Quadrant definitions and action guide explaining what each priority quadrant means for resource allocation
- Step-by-step User Guide covering research, scoring, validation, and quarterly review
- AI Prompt Companion with prompts for candidate industry identification, pain research and documentation, pain scoring, score validation, and quarterly pain map review
02
Layer 2: Firmographic Qualification Checklist
Produces → Ideal Account Profile (IAP)
Document qualification criteria across industry, financials, company size, and market position, classified by impact level.
- Firmographics Checklist covering four dimensions (Account Overview, Revenue and Financials, Company Size and Structure, Market Position and Competitiveness)
- Priority Framework for classifying each criterion as High Impact (must-have), Moderate Impact (important), or Supporting (nice-to-have)
- High-Impact Criteria Summary that becomes your rapid qualification reference for screening accounts in seconds
- Threshold guidance for each firmographic dimension with logic for how to determine appropriate criteria for your business
- Step-by-step User Guide covering completion, threshold setting, and quarterly review
03
Layer 3: Technographic Criteria and Prioritization Worksheet
Produces → Technographic Fit Profile
Specify which technologies, maturity levels, and competitive situations signal an account worth pursuing. The output is a documented technographic profile that distinguishes good-fit from poor-fit accounts based on stack, culture, and competitive position.
- Tech Criteria Worksheet covering 12 technology categories spanning core business systems, infrastructure, and industry-specific tools
- Tech Culture and Maturity section covering maturity level, openness to innovation, and infrastructure preferences
- Competitor and Complementary Tools section with switching signal logic that goes beyond binary disqualification
- Priority Framework for classifying tech requirements as Must-Have, Nice-to-Have, or Disqualifier
- Tech Must-Haves Summary as a rapid screening reference
- Step-by-step User Guide covering completion, maturity assessment, competitor handling, and quarterly review
04
Layer 4: Customer Fit Analysis Worksheet
Produces → Validated IAP + Anti-IAP
Compare account attributes across your best and poor-fit customers, then analyze deal-level factors behind wins and losses. The output is IAP criteria and Anti-IAP disqualifiers backed by evidence from your own customer history.
- Account Inventory for documenting accounts across three categories (best fit, poor fit, recent wins) with firmographic, technographic, and deal data
- Pattern Analysis with auto-calculated percentages and the 50% threshold rule built in for elevating attributes to IAP criteria status
- Win-Loss Factors framework that separates external factors (was the account a fit) from internal factors (did we execute well)
- IAP Implications summary translating validated patterns into recommended IAP criteria and Anti-IAP disqualifiers
- Sample size guidance and methodology for distinguishing real patterns from coincidence
- Step-by-step User Guide covering account selection, completion, pattern identification, and ongoing review
- AI Prompt Companion with prompts for account selection, pattern identification, win-loss interpretation, and IAP drafting
05
Layer 5: Account Fit and Tiering Scorecard
Produces → Tiered Account List
Combine your firmographic, technographic, and strategic value criteria into a weighted scoring model that assigns every account to a tier. The output is a prioritized account list with clear coverage rules.
- Scoring formulas and tier assignment logic across firmographic, technographic, and strategic value attribute categories
- Model Inputs for configuring category weights, attribute weights, and tier thresholds
- Definitions and Scoring Keys with rubrics for consistent scoring across team members
- Account List for organizing target accounts with enrichment data
- Scorecard where accounts are scored, qualified, and tiered (A, B, C, or D)
- GTM Motion Reference with Tier-by-Segment matrix for mapping tiers to coverage motions
- Dashboard with qualification summary, tier distribution, Tier-by-Segment distribution and pipeline alignment
- Weight derivation guidance for both standalone use and integration with Customer Fit Analysis output
- Step-by-step User Guide covering setup, scoring, dashboard interpretation, and quarterly recalibration
- AI Prompt Companion with prompts for data audit, weight derivation, account list building, scoring, dashboard interpretation, and recalibration
06
Layer 6: Account Signals and Intent Tracker
Produces → Prioritized Engagement List
Convert observed buying signals into a prioritized engagement list, with each signal classified by strength and tracked against its decay window. The output is a defensible engagement list grounded in observed buying behaviour.
- Signal Library with more than 60 pre-loaded buying signals across 10 categories spanning direct engagement, competitive evaluation, behavioral, organizational, and contextual signal types
- Each signal carries a strength rating, time-bound classification, decay window, decay rationale, and detection source examples
- Signal Log with auto-calculating formulas for signal strength, time-bound status, decay window, and days remaining across hundreds of pre-filled formula rows
- Account Monitor with four decision indicators per account covering current intent level, recency of activity, time-sensitivity status, and momentum trend
- Dashboard surfacing Priority Accounts, Closing Windows, Cooling Accounts, a Fit-by-Intent Matrix, and an Interpretation Guide
- Step-by-step User Guide covering setup, daily logging, weekly review cadence, and quarterly maintenance
- AI Prompt Companion with prompts spanning Signal Library configuration, public source scanning, connected tool signal pulling, signal extraction from unstructured notes, account brief preparation, and quarterly recalibration
SIX WORKBOOKS · FOUR AI PROMPT COMPANIONS · USER GUIDES EMBEDDEDONE-TIME$297
THE RESULTAfter the six layers are built.
You walk into your weekly pipeline review with a list that holds up. Every account has been screened, qualified, scored, validated, tiered, and signal monitored. The team is no longer debating which accounts to focus on this week. They are working from a list with tier assignments and timing logic that survive scrutiny. Sales runs the Tier A and B coverage. Marketing runs the campaigns against the right segments. The executive team trusts the targeting because every account earned its place.
The targeting decisions stop being a debate. The prioritization stops being a guess. The timing stops being a gut call.
Your account list becomes infrastructure the entire revenue operation trusts.
WHO THIS IS FORBuilt for decisive targeting.
Your Questions, Answered
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The framework is built for teams operating with one or more of the following: a target account list that is producing inconsistent results, a planned campaign, GTM launch or ABM program where account selection will be a key success factor, a sales and marketing handoff that needs an aligned, consistent list of accounts to focus, or a forecast that has missed for reasons that point upstream of execution. If any of those describe your realities, the timing is right. If none of them do, the framework will still work when they do.
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No. You work through the framework in focused pieces that fit around what you already have running, rather than clearing your calendar for one uninterrupted stretch. Each piece produces something you can use on its own, so the effort pays off as you go rather than only at the end. However, settling your targeting before you commit to your next campaign, SDR ramp, or ABM push means that effort starts aimed at the right accounts instead of being redirected once it is already underway.
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You could. The question is what you would be replicating: extensive research into how demand generation leaders and practitioners build account targeting and prioritization systems, and the methodological judgment to translate that research into structures a team can apply. Building that from scratch is months of work before you have anything to deploy. For a founder, that time is rarely best spent designing internal demand generation methodology. For a lean marketing team, it competes directly with the pipeline you are already accountable for. The framework lets you deploy the work without building it first.
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Good. A documented ICP is the strongest input you can bring to this work. The framework extends it into what an ICP document on its own does not produce: validation of your criteria against your actual customer outcomes, an account-level scoring model that assigns each account to a tier with a defined coverage motion, signal tracking that surfaces which qualified accounts are showing buying behaviour right now, and the architecture that connects all of it into one operating system. Bring your existing ICP in as the starting input. The framework picks up from there.
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The framework still applies. The early work builds your targeting criteria from market research, industry pain analysis, and firmographic and technographic qualification, then scores and tiers accounts against that criteria and monitors them for buying signals. The one part that depends on existing data is the customer-fit validation, which checks your criteria against real outcomes and lost deals. If you have lost deals, that piece can work immediately. If you have neither customers nor lost deals yet, it comes online once you do. The rest proceeds in the meantime.
The decision.
The framework is ready for you and your team the moment you download it.
Six layers, fully built: the scoring logic, the signal taxonomy, the architecture connecting all of it, the AI Prompt Companions, and the User Guides that walk your team through the framework.
ONE-TIME