GTM Intelligence System
Your GTM strategy is built on assumptions. Your data tells a different story.
63% of CROs have little or no confidence in their ICP. ICP misalignment reduces win rates by up to 75%. ResonanceAI surfaces the gap and closes it.
It builds its own workspace in your Notion in the first session, then starts testing.
Source: 2026 GTM Benchmarks Report, Pavilion & Fullcast 316 companies, $78B in pipeline data
The ICP Reality Gap
The delta between what you believe converts and what your data actually proves.
What Most Teams Declare
Mid-market SaaS, 51–500 employees, UK-based. Head of Marketing is primary buyer. Positioning around speed-to-value and ease of implementation.
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DETECTED
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What the Data Shows
Healthcare (1,001–5,000 employees) converts at 67% win rate 2× the declared segment. Deals led by CRO involvement close 38% faster. Primary loss reason: implementation risk not positioning.
This is what ResonanceAI surfaces. Before you spend another quarter targeting the wrong segment.
Five stages from assumption to evidence.
Domain Analysis
Qualitative ICP baseline from your market signals firmographics, SPICED personas, JTBD mapping, buying triggers.
Quantitative Data Upload
Segment performance from your own CRM win rates, ACV, sales cycle, revenue concentration by segment.
ICP Reconciliation
The gap between qualitative belief and quantitative reality, surfaced explicitly. This is the ICP Reality Gap.
Transcript Intelligence
Buyer voice extracted from real sales conversations pain points, objections, impact drivers, stakeholder dynamics.
GTM Activation
Messaging, content strategy, enablement assets, and PR intelligence all grounded in evidence, not assumption.
ResonanceAI is one system. The Intelligence, ROI and Enablement modules are all included, not sold separately.
How ResonanceAI works
Connect your systems
ResonanceAI connects to your CRM, your call transcript source and your team's Slack or Teams. Read access where it analyses, write access only where it builds.
It builds its own workspace, in the first session
Once Notion is connected, the system provisions your entire intelligence workspace itself: twelve connected databases, a navigable hub, every field documented, and a data dictionary explaining what each one means and what a blank value tells you. It then reads back what it built and verifies it against the specification before doing anything else. No setup project, no configuration backlog, no template for your team to populate. It is standing before the first analysis runs.
It runs the intelligence pipeline
Five stages from declared ICP to activation plan, with verification gates at every stage close. Nothing advances on assertion, only on checked evidence.
Your team approves before anything ships
Recommendations route to your named approver. The system advises, your people decide, and every decision is recorded.
Ask it anything, any time
Your team interrogates the intelligence in Slack. Why is that segment ranked there, what changed since last month, show me the evidence. Answers come from the record, with links back to the workspace.
Evidence discipline, enforced by the system
The difference between intelligence you can act on and analysis you have to double check.
Every claim traces to a source
Each recommendation links back to the deals and conversations that produced it. No claim without an artefact.
Confidence reflects data quality, not effort
If your data can only support a cautious conclusion, the system says so and caps its own recommendations accordingly.
Patterns earn their way to recommendations
A signal seen twice is an observation, not a strategy. Patterns cross volume, breadth and durability thresholds before the system will act on them.
Recommendations carry their evidence tier
Test, pilot or roll out, derived from the evidence, never from enthusiasm. You always know how proven a recommendation is.
Your team asks, the evidence answers
ResonanceAI lives where your team already works. Ask it in Slack why a segment is ranked where it is, what is driving losses in a market, or what changed since the last review. It answers from the recorded evidence, shows its working, and links you to the source. No dashboard hunting, no waiting for the next report.
Sarah K. 10:42
why is financial services ranked where it is
ResonanceAI 10:42
You own it. We build it. Your team runs it.
No vendor dependency
Built inside your own Base44 workspace. Your data never leaves your infrastructure.
No per-seat licence
No renewal. No scaling tax. No lock-in. The system is yours from day one.
Capability transfer
We train your team to operate and evolve the system independently. The intelligence compounds inside your organisation.
Where this sits alongside what you already run
Most teams evaluating ResonanceAI already run three or four GTM tools. They are mostly complementary, because they answer different questions.
Without that foundation, your stack still runs. It just runs on an assumption somebody typed in: a filter definition, a target list, a positioning document from last year's workshop. The tools execute it efficiently, and none of them tests whether it is right. It is usually the most expensive assumption in the business.
See the full stack map, including how this fits with your CRM's built-in AI and existing positioning workWorks with the systems you already run
HubSpot
Read only
Reads your deals, companies and contacts: outcomes, values, close dates, loss reasons and segments. This is the quantitative evidence base that segment scoring runs on.
ResonanceAI never writes to your CRM. Nothing in your pipeline is changed, moved or updated.
Notion
Builds and writes
Your intelligence workspace is built here: the databases, the evidence trail, the analysis record and every activation asset, all in your own Notion.
You own it from day one. If we disappeared tomorrow, the system and everything in it stays with you.
Slack
Reads and posts
Routes recommendations to your named approver and posts stage summaries when the system completes a run.
It is also where your team interrogates the intelligence. Ask why a segment is ranked where it is and get the evidence back, with links to the source.
Google Drive
Read only
Reads your call transcripts in bulk, whether they come from a conversation intelligence platform or a meeting recorder exporting to a folder.
This is the qualitative evidence base: what buyers actually said, in their words, tested against what your pipeline shows.
Microsoft Teams
Reads and posts
The alternative to Slack for teams running Microsoft. Same job: approvals routed to your named approver, run summaries posted, questions answered in the channel.
Declared once at onboarding, so the system posts where your team already works.
Read only where it analyses. Builds only where you own the output. Hover any system to see exactly what it touches.
How delivery works
Structured intake
A 90 minute session captures your declared ICP, your systems and your approval routing.
Configure and build
We connect your systems and the system builds itself inside your infrastructure, then verifies what it built.
First cycle, operated
We run your first full intelligence cycle with you, your approver signing off every output.
Handover
Your team is trained to run and evolve the system. It is yours, no ongoing dependency.
Refine your positioning with every conversation.
One system that grows smarter as your market evolves.
Misalignment has a cost and it has a shape.
Four line items drive it: sales time spent on wrong-fit deals, demand gen spend chasing leads that don't convert, content and enablement rework, and excess churn from misread buyers. ResonanceAI is the system that closes the gap between what you believe about your ICP and what your data actually shows.
Run the diagnostic to model your own costResonanceAI
£35,000
ex VAT · one-off investment · you own the system
Best for
Executive teams where Sales, Marketing and CS are operating from different versions of reality, and it is costing them revenue.
The intelligence pipeline
- Domain analysis and baseline ICP
Builds your declared ICP hypothesis into a structured baseline: personas with buying-committee roles, competitive landscape, and the buying triggers you believe drive purchase. This is the hypothesis everything downstream tests.
- Quantitative scoring
Reads your CRM pipeline and scores every segment on win rate, deal value and cycle length against the outcome variable you choose. Profiles your data quality first and tells you what it can and cannot conclude from it.
- ICP reconciliation
The core deliverable. Sets what you declared against what your revenue proves, names every confirmed, refined and contradicted claim, and produces falsifiable strategic bets with explicit reversal conditions.
- Transcript intelligence
Reads your call transcripts in bulk and extracts pain points, objections, impact drivers and buying-committee dynamics in buyers' own words, then tests those patterns against your pipeline data.
- GTM activation
Turns validated evidence into usable assets: messaging playbooks, objection handling, qualification frameworks, content briefs and enablement assets, each carrying the evidence tier it was built at.
Your intelligence workspace
- Built in your own Notion
Twelve connected databases, a navigable hub, and every field documented, provisioned inside your workspace. Not a portal you log into, infrastructure you own.
- Complete evidence trail
Every claim links back to the specific deals and conversations that produced it. Any recommendation can be traced to its source in two clicks.
- Full analysis record
Every run is logged with its inputs, outputs, and the reasoning behind each conclusion, including what moved confidence and why.
- Activation assets library
Each asset lives as a standalone page built to an enterprise content specification, with the evidence cited inside it, ready for your team to use or adapt.
How your team uses it
- Ask it anything in Slack or Teams
Your team interrogates the intelligence where they already work. Ask why a segment is ranked where it is, or what is driving losses in a market, and get an answer from the recorded evidence with links back to the source.
- Approval workflow
Nothing ships without your named approver. Recommendations route for sign off, and every decision is recorded against the evidence it was made on.
- Evidence-tiered recommendations
Every recommendation states how proven it is: monitor, test, pilot or roll out. Tiers are derived from the evidence, not from enthusiasm, so you always know what you are acting on.
- Confidence governed by data quality
If your data can only support a cautious conclusion, the system says so and caps its own recommendations accordingly, rather than presenting a confident answer built on thin evidence.
Delivery and ownership
- Structured onboarding intake
A 90 minute session that captures your declared ICP, your systems, your terminology and your approval routing. This is what makes the system yours rather than generic.
- Configured and built in your stack
We build inside your infrastructure, connected to your CRM, your transcript source and your messaging platform. No data leaves systems you control.
- First cycle run with you
We operate your first full intelligence cycle alongside your team, with your approver signing off every output, so the first result is a real deliverable rather than a trial run.
- Capability transfer and handover
Your team is trained to run and evolve the system, including the methodology behind it. No ongoing dependency on us.
- You own it outright
No licence, no per-seat fee, no renewal. The system, the workspace and everything in it belong to you.
This is bought once, not rented. There is no annual licence and no per-seat cost, so the investment is incurred in year one while the system keeps running in years two and three. It also keeps getting sharper, because every new deal and conversation is tested against your ICP the moment it lands.
Every engagement starts with an AI Readiness Sprint (£3,500), which confirms your data can support the work before anything is built.
Frequently Asked Questions
Getting Started
How it works
Data & Privacy
Results & ROI
Implementation & Support
We'll show you what the ICP Reality Gap looks like when it runs on your data.
Not a generic demo. Your segments, your conversion evidence, your gap.