📚 The B2B Stack Reference Index
The canonical reference library of The B2B Stack.
📘 Table of Contents — The B2B Stack Reference Index
Introduction
How to use this index as your strategic, operational and analytical companion.Key Models & Frameworks
The core mental models that form the backbone of modern B2B strategy, signal architecture, measurement, identity, and activation.Terminology, Concepts & Definitions
A comprehensive glossary of GTM, ABM, adtech, programmatic, identity, signals, and measurement concepts — from foundational to emerging.Diagrams & Visual Systems
Visual representations of account identity, the Signals Spine, buyer journey systems, and modern programmatic architecture.Flagship Posts & External Canon
The B2B Stack Flagship Essays
Direct links to the definitive essays that power the B2B Stack worldview.External Authority Resources
Industry bodies, identity frameworks, intent leaders, attention research, LinkedIn thought leaders, and measurement standards we trust.
Tooling, Templates & Applied Use Cases
Reference templates, trackers, workflows and applications you can use in your GTM, product, analytics or ABM programs.Purpose & How to Apply This Reference
How each section fits into real-world B2B operations, and how to use this index across strategy, reporting, planning and execution.
📚 THE B2B STACK REFERENCE INDEX
The canonical glossary of models, signals, frameworks & operating concepts
(Updated quarterly - updated November 22nd 2025)
This is the official reference library for The B2B Stack — a structured index of the market leading ideas, definitions, frameworks, models, and methodologies used across modern B2B marketing, measurement, and programmatic activation.
If you’re using The B2B Stack to improve your GTM, build a signals-led operating model, or optimise programmatic performance, this is your source of truth.
🧠 SECTION 1 — CORE FRAMEWORKS
1. The Signals Era
A new operating model for B2B where behavioural signals replace vanity metrics.
Signals include:
High Value Actions (HVAs)
Account-level web behaviour
Dark funnel research patterns
Content depth & attention metrics
Identity-grade actions (IP, location, device)
Programmatic log level data
Page signals like context
Locational signals that can link to working patterns, commuting, conferences and events and other B2B signals
The core belief:
Brands should optimise to real buyer actions, not clicks. This is B2B though so the real ‘conversion’ may not be visible so instead we use proxy signals of growing intent, at an account level, which we can reliably capture. We then use these to score and predict future account level behaviour
2. The B2B Stack Model (The Operating System)
A 6-layer operating system for modern B2B:
Signals Layer
HVAs, attention metrics, buyer-group behaviour, marketing signals and CRM signalsIdentity Layer
Company-level resolution, TAL ingestion, data stitchingAnalytics Layer
Matomo, server-side events, time-weighted scoringActivation Layer
Programmatic (Trade Desk / IX), ABM media, retargetingRevenue Layer
CRM enrichment, pipeline tie-back, scoringPrivacy sovereign layer
I believe vendors need to own their privacy proactively with sovereign data approaches, cutting third party pixels and self hosting of martech
This is the canonical “architecture view” of B2B Stack content.
3. High Value Actions (HVAs) Framework
The framework that replaces CTR.
HVA’s = account level buying signals
Every action is defined by:
Funnel Stage
Strategic Value
Implementation Method (GTM tag, Matomo goal, custom JS)
Scoring Logic
Activation Trigger
HVAs include 100+ trackable actions across:
Core web behaviour
Buying committee signals
Omnichannel programmatic (CTV, audio, native, display)
Post-demo / post-proposal behaviour
4. The Attention-as-a-Signal Model
Attention is treated as:
an engagement multiplier
a scoring input
a quality predictor
a media optimisation surface
A signal which works across clickable and non clickable ad formats, normalising clickable ads like social and banners, with clickless formats like CTV and audio
Attention includes:
Advertising attention seconds
dwell time
Ad placement quality
Eye tracking data
Size of placement
Prominence of placement vs other distractions in view.
5. The Account Scoring Model
A two-part scoring system:
A. Fit Score (Firmographic)
Industry, employee count, region, tech stack, ICP alignment.
B. Behaviour Score (Signals)
HVAs + attention + on-site intensity.
Outputs:
Prioritisation
Nurture sequencing
Programmatic activation
Sales follow-up
TAL expansion
6. The TAL Resolution Framework
The model for resolving Target Account Lists using:
domain → company mapping
Hyperlocal enrichment
IPFlow / DE Pulse / Dealfront waterfall
Data management platform identity stitching
conflict resolution
dedupe logic
Goal: clean, precise account-first identity.
7. The Goals-Based Optimisation Framework
Replacing CTR with:
HVAs
depth metrics
quality visits
account sequences
weighted attention
post-view analytics
This is the foundational philosophy behind my “bottom-of-funnel programmatic.”
🏗️ SECTION 2 — KEY MODELS
Concise definitions, to make you the B2B expert in the room.
1. Buyer Group Sequencing Model
Tracks individual behaviours that indicate the below, using advanced AI/ML page contextualisation models to pull content that talks to these stakeholders out of the vendors content:
additional stakeholders participating in a decision matrix
technical evaluators
procurement influencers
business decision makers
Uses page categories like:
implementation docs
pricing
security pages
technical architecture
2. Multi-Signal Identity Graph
A model that combines these richest B2B signals era inputs to probabilistically match sessions to companies. Many B2B and ABM/X systems use one single signal, which is unreliable
IP signals for example have exceptionally low agreement rates - often as low as 3% even on big enterprises accounts. It’s thus critical to overlap these signals to confidence score them to drive the probabilities in your favour
The current excitement about hyper personalisation will fail badly without this approach to identity and improving the odds of getting it right. Remember - this is never entirely deterministic, even when signals align. Key signals include
IP - work WiFi signals - ideally double validated with vendor form fills
geolocation to 4 decimal places or office rooftop level
MAIDs from hashed email, location inference and IP to MAID, and programmatic logs
device IDs
cookie IDs (where allowed)
CRM identifiers
behavioural fingerprints
Context to signal mapping to further validate
Goal: derive the strongest possible account-level view.
3. Programmatic Bottom-of-Funnel Model
A playbook where media targets:
known accounts
ICP-aligned companies
surging intent segments
accounts showing evaluation behaviour
Optimised via HVAs → Matomo → DSP events. The unlock with this model by Mike Harty is the pipeline from media to measurement and measurement back to activation, looping through an account knowledge graph to validate the signal
4. The Dark Funnel → Signal Funnel Model
Converts “invisible research” into measurable signals using:
first-party analytics
identity resolution
on-site HVAs
programmatic attention
topic sequences
5. The Signal Vector Model
Definition: A multi-dimensional mapping of each behavioural signal into four axes — Intent Depth, Buying-Committee Breadth, Channel Diversity, and Temporal Momentum. Each signal is placed as a vector in this 4D space and then aggregated at the account level to produce a composite “vector magnitude” which reflects how “ready to buy” that account is.
Purpose: Enables teams to compare signals not just by frequency but by direction (which axis it’s moving in) and velocity. It shifts focus from raw counts (e.g., “10 visits”) to progress-motion (e.g., signals are trending up the Intent Depth axis and crossing thresholds on Buying-Committee Breadth).
6. The Engagement Surface Model
Definition: A layered model showing how buyer engagement spreads across touchpoints. Layers include: Awareness Surface, Research Surface, Evaluation Surface, and Decision Surface. Each “surface” is populated by behaviours and channel interactions (e.g., content downloads, peer reviews, pricing pages, proposal page visits).
Purpose: Helps marketing + operations visualise where engagement is physically happening across the buyer journey – so you can spot “thin surfaces” (weak engagement layers) and optimise coverage. It also gives a framework for “surface expansion” (e.g., building more evaluation-surface engagement once awareness and research surfaces are solid).
7. The Data Confidence Hierarchy
Definition: A tiered model for data integrity and decision-making:
Tier 1: First-party explicit (CRM fills, form submissions)
Tier 2: First-party implicit (site behaviour, logged-in usage)
Tier 3: Second-party (partner-shared data, alliance data)
Tier 4: Third-party (attribution vendors, external firms)
Each tier is accompanied by a confidence score, natural decay rate, and weighting logic.
Purpose: Provides an operational way to prioritise which data sources you trust most when building models, scoring, and activation. It also helps communicate to stakeholders where “we might be making decisions on Tier 4 data” and therefore apply appropriate caution or governance.
8. The Account Lifecycle Signal Rhythm
Definition: A model which defines “pulse” patterns for account behaviour across the lifecycle phases: Pre-Targeting, Targeted Awareness, Evaluation Acceleration, Decision Triggering, and Post-Sale Expansion. Each phase has a target “signal rhythm” (e.g., X HVAs/week, Y attention minutes/day, Z channels engaged) and a defined drop-off threshold (when rhythm slows, you’re at risk).
Purpose: Enables operations teams to set cadence benchmarks, monitor when accounts are “falling off rhythm,” and programmatically intervene. It also fosters tighter alignment between marketing, sales and rev ops on where an account should be in terms of activation.
9. The Signal Conflict Resolution Matrix
Definition: A decision-matrix that governs how to handle conflicting signals. Dimensions include: Priority (fit vs behaviour), Recency vs Historical Pattern, Channel Source Reliability, Signal Type (explicit vs implicit). The matrix then triggers one of three actions: Override, Merge, or Flag for Review.
Purpose: In complex signal ecosystems (especially B2B) you will inevitably get conflicts (e.g., high attention but low committee breadth; account visits but no firmographic fit). This model gives a clear rule-set for how to treat those cases, reducing ad-hoc decision-making and improving consistency in prioritisation.
10. The Privacy-Safe Activation Stack
Definition: A layered architecture of activation that avoids third-party cookies/pixels and is fully privacy-sovereign. Components: On-Property First-Party Tracking, Server-Side Tagging, Self-Hosted Analytics, Data Clean Rooms, Identity Graph with hashed/consented IDs only, Programmatic DSP integration via clean feed.
Purpose: Provides a blueprint for B2B organisations to move from legacy pixel-based tracking to future-proof activation. Especially relevant in an era of de-prioritised third-party cookies and rising data-governance requirements.
Purpose of Section 2 – Key Models
This section serves as the model-toolkit of the B2B modern stack — a collection of repeatable frameworks, operating logic blueprints, and model archetypes that serve as building blocks for strategy, measurement, activation and governance. By referencing these models, B2B teams can ensure they are speaking the same language, aligning around best practices, and operating on a mature signal-led infrastructure.
Use this section as:
A strategy anchor – when drafting GTM plans or signal-led frameworks, pick your relevant models from this index.
A training resource – onboard new team members, internal stakeholders, or agency partners faster with a shared mental model.
A decision support tool – when debates arise (e.g., “Should we trust this data source?” or “How do we prioritise this account?”) the models help steer objective decision-making instead of ad hoc judgments.
A reference architecture – as the ecosystem evolves (new channels, new privacy regimes, new measurement tech) you can map them into these models rather than reinventing frameworks each time.
📘 SECTION 3 — TERMINOLOGY & DEFINITIONS
A curated glossary for GPT to reference.
Account Identity
The process of resolving anonymous traffic into company-level intelligence.
Signal
A measurable behavioural action that indicates intent, interest, or evaluation.
High Value Action (HVA)
A behaviour with direct predictive value for pipeline creation. Standing for High Value Action, these equate to account level buying signals. These should be reverse mapped from CRM to account graph to firmographic segmentation to historic HVA to then add predictive weight to these HVAs when the same actions are taken by similar profiles of companies
A core complement of my work
Attention metrics for B2B
Quality and depth of engagement, measured beyond bounce or clicks. A measurement which normalises clickable and clickless ad formats in a manner which maps to pipeline. Key technologies include lumen research, and Adelaide
TAL
Target Account List — priority companies to be targeted and measured. Usually given as a prescriptive list of companies that a vendor wants to engage in an account based marketing program. There is no standard format for these lists which creates a major challenge in their usage, and they’re often unsegmented and out of date
Signal Spine
The flow of first-party signals across analytics → identity → activation → revenue.
Signal Score
Weighted scoring based on HVAs and attention. Proprietary scoring for each vendor, enabling the basis of a custom programmatic B2B algorithm.
Bottom-of-Funnel Programmatic
Media activation optimised for pipeline, not CPM or CTR. Programmatic model which drives real business outcomes and not high bounce rate vanity Metrics
Surging Account
A company showing accelerated research and intensity.
An account which needs to be captured fast, and nurtured to pipeline
Signal Sequence
Order and clustering of actions indicating evaluation.
Programmatic & Adtech Foundations
AdCP (Ad Conversion Protocol)
A next-generation post-cookie conversion framework that treats conversions as structured signals, passed via server-side pipes into DSPs and CDPs. Unlike legacy pixel attribution, AdCP uses encrypted payloads, deterministic keys and privacy-safe match networks to optimise to actual business outcomes.
Purpose: Prepares B2B teams for the era where DSPs optimise only to server-verified signals, not front-end events.
Clean-Feed Activation
A buying model where only curated, matched, identity-enriched impressions hit the DSP seat. Eliminates waste, protects privacy, and enforces inventory quality before bidding even begins.
Purpose: Foundation of modern ABM programmatic — reduces spend, increases match rate accuracy, and protects against bad inventory.
REDS Logs (Real-Time Event Delivery Stream)
Trade Desk’s log-level data format for impression, auction, and outcome-based transparency.
Purpose: Enables TAL-level attribution pipelines, attention frameworks, and post-view conversion analytics.
Curated Supply Containers
A private supply layer pre-filtered for brand safety, B2B relevance, attention, fraud-resistance, and contextual alignment. Used heavily across Index Exchange, OpenX, Magnite.
Purpose: Dramatically improves downstream performance without modifying DSP logic.
Bid Shading Intelligence (BSI)
ML models that predict the “true” clearing price and automatically shade bids below the max bid to reduce CPMs without hurting win rate.
Purpose: Key to margin improvement, especially in B2B where CPM efficiency drives incremental TAL reach.
Identity, Resolution & Signals
Federated Account Identity (FAI)
A privacy-safe identity principle where account-level IDs are formed through multiple hashed, decentralised signals (IP ranges, MAIDs, email hashes, corporate network metadata) without centralising raw data.
Purpose: The post-cookie backbone of B2B identity, replacing cookies and fingerprinting.
Company-Based Identity (CBI)
Identity models that start from company objects rather than domains — using postal addresses, IP infrastructures, network signatures, CRM firmographics, and DSP-level identity graphs.
Purpose: Overcomes the long-standing issue of fragmented domains (e.g., sub-brands, subsidiaries). Essential for accurate TAL targeting.
Signal Confidence Scoring (SCS)
A weighted scoring model that evaluates how reliable a signal is based on type, capture method, decay, frequency, and alignment with historical behaviour.
Purpose: Ensures no single noisy signal derails scoring or prioritisation.
Attention Quality Minutes (AQM)
A unified metric that combines scroll depth, dwell time, interaction intensity, and on-page focus signals to measure engagement strength.
Purpose: A better B2B KPI than CTR — correlates with genuine interest and intent.
Multi-Threaded Account Behaviour (MTAB)
A framework describing engagement across multiple buying-committee personas within the same account.
Purpose: Better measurement of deal readiness than single-persona signals.
B2B Performance, Measurement & Attribution
Goal-Based Optimisation (GBO)
Programmatic strategy that optimises to first-party HVAs instead of CTR. Uses server-side events passed via Conversions API or clean-room bridges.
Purpose: Moves B2B away from vanity metrics and towards full-funnel value.
Dark-Traffic Attribution (DTA)
A framework for measuring behaviour from private browsing, shared links, Slack/Teams internal sharing, and direct load events.
Purpose: Captures the 40–60% of B2B buying activity that never shows up with referrers.
HVAs (High-Value Actions)
Defined, technically capturable micro-behaviours that indicate deeper intent: pricing page visits, solution pages, form starts, benchmark downloads, integration docs, partner pages.
Purpose: Core building block of B2B scoring, account prioritisation, and DSP learning loops.
HVA Momentum Score
A rolling, time-weighted scoring index showing whether an account’s intent is accelerating or decelerating.
Purpose: Predictive for pipeline creation and deal timing.
Cross-Journey Activation (CJA)
Framework linking anonymous programmatic exposure → on-site behaviour → CRM → email → sales outreach using one signal taxonomy.
Purpose: Ends channel silos and creates a fluid, signal-centred GTM motion.
Next-Gen GTM, RevOps & Pipeline Thinking
Pipeline Attention Model (PAM)
A revenue-ops measurement method that tracks where each Target Account is allocating mindshare across channels (paid, owned, earned, onsite).
Purpose: Allows teams to quantify attention shifts before opportunities surface.
Account Graph
A multi-layer mapping of firmographic fit, behavioural signals, HVA history, attention score, buying-committee breadth, and multi-threading.
Purpose: Single source of truth for account-based pipeline prioritisation.
Buying-Committee Graph (BCG)
A graph that maps the behavioural signatures of different functions (IT, procurement, operations, finance, security) and tracks new participant emergence.
Purpose: Allows detection of new stakeholders entering deals (“committee expansion”), a strong predictor of mid-funnel progression.
Activation-Ready Account (ARA)
An account that has passed all minimum thresholds on fit score + HVA depth + attention minutes + committee breadth.
Purpose: Ensures outbound, ads, and SDR timing are synchronised for maximum effect.
Pipeline Acceleration Events (PAEs)
Model capturing key moments that statistically accelerate deal progression — proposal page visits, pricing calculator use, integration docs, security pages.
Purpose: Converts programmatic from top-of-funnel to bottom-of-funnel stimulus.
Advanced Adtech & Infrastructure
Identity-Safe Post-View Conversion Model (IS-PVC)
A method using log-level impression data and first-party analytics to attribute on-site HVA behaviour without any cookies or user IDs.
Purpose: Unlocks the cleanest measurement for ABM programmatic in the post-cookie world.
DSP-Bypass Buying
Direct activation using SSP pipes (e.g., Index/SMA curation) or server-to-server bidding models, skipping the DSP layer in some workflows.
Purpose: Reduces fees, increases transparency, and is emerging as the future for high-volume identity-enhanced supply.
Postcode-Level Precision
Identity technique for Europe/UK where corporate networks are mapped down to postcode geography, enabling clean account mapping and exclusion.
Purpose: Solves the IP-accuracy problem in GDPR regions.
Signal Decay Curves
Mathematical models defining how quickly a signal loses its predictive value. Different curve shapes exist for research behaviour, competitor comparisons, demos, and pricing pages.
Purpose: Allows proper time-weighting in scoring algorithms.
Signal Conflict Arbitration (SCA)
Rules for determining which signals “win” when data sources disagree — e.g., Bombora says surging, on-site behaviour flat.
Purpose: Prevents false positives and inflated scoring.
B2B Creatives, Personalisation & UX
Persona-Directed Creative (PDC)
Creative variant mapped to specific buying roles (IT security, procurement, ops) served programmatically based on signal inference.
Purpose: Bridges persona work with real-time media activation.
Dynamic Account-Level Messaging (DALM)
Server-side personalisation framework where messaging switches per page based on the visiting company ID.
Purpose: High-impact UX for mid-funnel ABM.
Contextual Precision Layering
Combining first-party signals with page-level semantics, time-of-day, inventory ratings, and publisher-tier scoring.
Purpose: Massive uplift in relevance without relying on cookies.
Purpose of Section 3 — Why This Glossary Matters
Section 3 serves as the linguistic backbone of modern B2B — the shared vocabulary that unifies product, growth, ops, media, analytics, and executive strategy.
This glossary is designed to:
1. Establish a single shared language
In high-complexity B2B orgs, inconsistent terminology causes misalignment. A unified glossary lets teams move faster and make decisions with less friction.
2. Capture the evolving edge of adtech
Many of these concepts (clean-feed, AdCP, privacy-safe activation, federated identity) are not yet mainstream. This glossary future-proofs your org by documenting them early.
3. Create internal clarity & external authority
Founders, GTM leaders, agency partners, and even DSPs will reference this. It becomes the B2B operating dictionary.
4. Support training, onboarding, and enablement
New team members will ramp 4× faster with a glossary like this.
🔍 SECTION 4 — DIAGRAMS & MODELS (TEXT-VERSION)
1. The B2B Signal Stack
[Signals Layer]
[Identity Layer]
[Analytics Layer]
[Activation Layer]
[Revenue Layer]
2. HVA Funnel Model
Top Funnel → Awareness HVAs
Mid Funnel → Research HVAs
Bottom Funnel → Evaluation HVAs
3. Identity Waterfall
TAL → Domain → Postcode → IP → Device → CRM → Unified Account
Attention model
Scroll Depth × Time on Page × Recency × Topic Depth
🧭 SECTION 5 — SUMMARY OF FLAGSHIP POSTS
Modern B2B requires goals-based optimisation, not CTR. See also this standout piece ‘from clicks to signals’
✔ AI Didn’t Kill The Dark Funnel But It Did Re-Wire It
Foundational signal categories that reveal the dark funnel and make it leveragable buy B2B marketers
Actionable, technically implementable HVA library.
Why attention is the highest predictive signal in B2B, and anchors all paid media to a common signal class
✔ Account Identity Is Being Re-Wired In Signals - Here’s How To Build A B2B Signals Spine
How to resolve TALs into actionable insights.
✔ The Account Scoring System Which Will Win 2026
Why Fit and Intent are not enough anymore
✔ B2B + ABM State Of The Nation In 2025, The Year The Buying Journey Changed Again
How to approach media like a pipeline operator.
External Canon — World-Class References
These are the external sources I’d personally lean on for grounding on the topics we cover on the B2B Stack: B2B signals, identity, attention, ABM, programmatic, and measurement.
5.A — Industry Bodies, Standards & Macro Reports
IAB — B2B Account-Based Marketing Playbook
Authoritative primer on digital ABM, audience definition, activation and measurement – still a solid baseline for ABM vocabulary and workflows.
Foundational overview of how audience data is collected, processed and activated across the adtech stack – good context for your Signals / Identity / Activation layers.
IAB — State of Data & Measuring the Digital Economy (2022–2025)
Macro view of how privacy, signal loss and measurement disruption are reshaping digital advertising and revenue. Great backdrop for your “Signals Era” narrative.
IAB Measurement & Attribution Workshop (Prohaska, 2023)
Slides walking through modern outcome-based measurement, moving from proxy KPIs to validated sales outcomes. Strong reinforcement of your HVAs → revenue argument.
IAB — New Rules for Digital Media: Privacy & Trust
Frames the identity revolution and the move away from third-party cookies as a trust and language problem, not just a tech problem.
5.B — Identity & Programmatic Infrastructure (DSP / IDs)
The Trade Desk — Unified ID 2.0 & EUID Resource Hub
Canonical resources explaining UID2/EUID, first-party identity, and open-internet identity strategy. Essential for readers who want to understand where account-level identity and clean rooms are going.
The Trade Desk — Identity Case Studies (e.g. HP CTV with UID2)
Real-world examples of using first-party data + UID2 to increase reach, cost-efficiency, and closed-loop measurement. Great for anchoring your identity theory in actual campaigns.
The Trade Desk — Programmatic & Platform Guides
Up-to-date overviews of TTD capabilities, omnichannel formats (CTV, audio, native) and best practices. Good “how this actually gets bought” resource for your bottom-of-funnel programmatic readers.
5.C — Attention & Media Quality
Lumen Research — Attention Technology & Attention Economy
Lumen’s work is the backbone of attention as a metric: cross-channel attention measurement, eye-tracking, and the argument that attention is a human-first metric rather than a platform metric.
Adelaide — AU Attention Metric & Fundamentals of Attention
Adelaide’s AU is the reference omnichannel attention score, with strong evidence linking AU to full-funnel outcomes. Their fundamentals and Outcomes Guide give a rigorous view on “attention as media quality.”
Nielsen x Adelaide — Unified View of Reach & Attention
Demonstrates how legacy reach/GRPs are being fused with attention metrics in mainstream measurement stacks – perfect proof that your “attention as a signal” stance is where the market is going.
5.D — Intent, ABM & Signal Platforms (Vendor Canon)
Bombora — Company Surge® & Intent Fundamentals
Bombora’s resources on what intent data is, how their Co-op works, and how to select topics / deploy intent across your stack. This is the canonical intent data reference in B2B.
6sense — Revenue AI, Orchestrations & Signalverse
6sense’s docs and blogs on orchestrations, intelligent workflows, and ABM tactics are effectively the “playbook” for AI-driven, signal-led ABM orchestration.
Demandbase — ABM Intent Data & Use Cases
Good complementary view to Bombora/6sense on how to use intent signals across sales, marketing and product – shows the broader ecosystem around your HVA/Signal Spine approach.
5.E — B2B Marketing Science & Brand / Demand Thinking
LinkedIn B2B Institute — Research Hub
The B2B Institute is the marketing-science north star for B2B: brand vs demand balance, mental availability, category entry points, and long/short effects.
“How B2B Brands Grow” — B2B Institute
Evidence-based view of distinctiveness, reach, and mental availability in B2B – the “How Brands Grow” lens adapted for B2B. Great for readers wrestling with brand vs demand trade-offs.
Tom Roach — The Wrong & the Short of It + Performance Plateau
Tom Roach’s writing on short-termism, the long vs short debate, and the performance plateau (with Grace Kite) is the best articulation of why pure lower-funnel performance eventually stalls.
WARC — Effectiveness 2.0 / Attention & Outcomes
WARC’s Effectiveness 2.0 work and related pieces link attention, creative effectiveness and long-term brand outcomes – ideal companion reading to my Attention Playbook.
5.F — Practitioner Voices & People to Follow
I recommend following these people on socials.
Chris Walker (Encoded) — Demand & Pipeline-First B2B
One of the most influential operators on demand, pipeline marketing and dark social. His feed is a live lab for demand-led GTM and pipeline-as-north-star.
April Dunford — B2B Positioning & Narrative
The canonical voice on B2B tech positioning. Her site, newsletter and talks give readers a structured way to think about positioning, differentiation and sales narrative.
Kate Newstead & the LinkedIn B2B Institute Team
Kate + the B2B Institute crew are doing the heavy lifting on evidence-based B2B brand building, creative effectiveness and media mix. Great “north star” for brand-side readers.
Others to watch: Grace Kite, Jon Lombardo, Ty Heath, Tom Roach
5.G — Modern Measurement & Signals Frameworks
Eliya — Marketing Measurement Framework (2025 Guide)
A clean, modern breakdown of MMM, MTA, KPIs and first-party data in a post-cookie world — good “generic” measurement context for your more opinionated HVAs model.
Seer Interactive — ABCs of Marketing Measurement
Human-first framework that emphasises measuring behaviours that matter, not vanity metrics. Strong philosophical alignment with your “Signals over CTR” stance.
Funnel.io — B2B Marketing Measurement Done Right
Interviews and guidance from LinkedIn, BrainLabs, Magic Numbers & co on aligning B2B measurement with finance and business outcomes. Nice external validation that serious players are moving beyond last-click.
Onebite — Effective B2B Measurement in a Changing Media Landscape
Explains why traditional attribution models fail in complex B2B journeys and advocates for more holistic, multi-signal approaches to proving impact.
Why these links?
These are the external sources we’d trust if we were re-building The B2B Stack from scratch tomorrow. They’re the research bodies, vendors, practitioners and measurement frameworks that actually shape how modern B2B works in the wild. If The B2B Stack is the operating manual, this canon is the supporting library.
🎯 SECTION 6 — HOW TO USE THIS INDEX
This reference is designed for:
GPT prompting
strategy docs
dashboards
training teams
building measurement frameworks
onboarding agencies
internal B2B education
client-facing decks
Bookmark it. Link to it.
This is the single source of truth for the B2B Stack ecosystem.
📌 these models are advanced and we only discuss ideas in our free posts - if you want to go deeper or implement these ideas, upgrade to our paid tiers
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