📚 The B2B Stack Reference Index

The canonical reference library of The B2B Stack.

📚 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 signals
Identity Layer
Company-level resolution, TAL ingestion, data stitching
Analytics Layer
Matomo, server-side events, time-weighted scoring
Activation Layer
Programmatic (Trade Desk / IX), ABM media, retargeting
Revenue Layer
CRM enrichment, pipeline tie-back, scoring
Privacy 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

📘 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.

🔍 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

✔ Why Clicks Are a Lie

Modern B2B requires goals-based optimisation, not CTR.

✔ The 7 Signals You Need to Win in B2B

Foundational signal categories that replace cookies.

✔ The 100 High Value Actions

Actionable, technically implementable HVA library.

✔ The Attention Playbook

Why attention is the highest predictive signal in B2B.

✔ Account Identity 2025

How to resolve TALs into actionable insights.

✔ The Dark Funnel Myth

Why the funnel isn’t dark — it’s just unmeasured.

✔ Programmatic for B2B (Bottom-of-Funnel Guide)

How to approach media like a pipeline operator.

🎯 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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