δiscovery Lab™ for Marketing
Your MQL numbers are up. Your SQL conversion is down. The problem isn't your campaigns.
Four Questions Worth Asking
What Changes
When discovery actually works
Positioning that lands
Built from words customers actually used. Sales stops saying "the messaging doesn't work."
ICP based on evidence
Who has the problem today, not who bought last year. Your targeting reflects current demand.
Content that converts
Anchored in real pain points customers articulated. Not thought leadership about problems you assume they have.
Sales alignment
When positioning is grounded in validated customer language, sales and marketing argue about tactics, not fundamentals.
Insight you own
Customer understanding that stays in-house. Not rented from agencies, not stale after six months.
What Your Marketing Leaders Actually See
δiscovery Lab is a platform. Here's what it produces.
STRUCTURED RESEARCH
For every prospect or market segment, the platform generates structured intelligence: company context, buyer profile, market dynamics, competitive landscape. All sourced and cited, not a generic summary.
TESTABLE ASSUMPTIONS
From the research, the platform generates specific, testable assumptions about what the buyer cares about. After each conversation, these are tracked as validated, invalidated, or untested. With evidence. This is how you know whether your positioning is based on reality.
VALIDATED CUSTOMER LANGUAGE
Specific verbatim quotes from conversations, tagged by theme and mapped to your assumptions. Not a survey response to a question you wrote. Their words, unprompted, about problems they articulated themselves. This is what your next positioning review should have in the room.
ICP EVIDENCE
Which customer segments respond to which pain points. Confirmed or contradicted by real conversations. Which messaging themes have evidence behind them and which are internal consensus wearing a customer hat.
How It Works For Your Team
Five stages. Every segment. Every customer conversation.
Works With Whatever You Already Use
You Might Be Thinking
Common Questions
What is this exactly? Software, service, or consultancy?
δiscovery Lab is a platform. Software you log into. It researches prospects, generates testable assumptions, prepares structured questions, evaluates conversations against rubrics, and produces coaching recommendations. Not a consultancy engagement. Not a one-off workshop. A permanent capability your team owns.
How does this help us fix positioning?
The platform captures validated customer language. Specific words customers used to describe their problems, mapped to specific assumptions your positioning is built on. You see which messaging themes have evidence and which are internal assumptions. Your next positioning review has real customer language in the room, not survey data.
Does this replace our agency?
No. Agencies deliver periodic research projects. δiscovery Lab gives your team continuous customer understanding between agency engagements. The insight stays in-house. The capability compounds. Your agency work gets better because the briefs are grounded in validated evidence, not assumptions.
How does this help with sales alignment?
When sales says "the messaging doesn't land," you can show them exactly which customer conversations the messaging was built from. Validated customer statements, mapped to specific pain points, with evidence strength ratings. The argument shifts from opinion to data.
Does this work with Marketo / HubSpot?
δiscovery Lab works upstream of your marketing automation. It improves the quality of the messaging and targeting that feeds your campaigns. Better positioning in, better conversion out. Direct integration is on the roadmap.
What does a discovery cycle actually look like?
Before the meeting, you define what needs to be learned. Testable assumptions about the customer's situation. The platform generates structured preparation around your hypotheses. After the meeting, you upload the transcript and the platform evaluates what was actually discovered. Evidence accumulates across conversations, so each meeting builds on the last. The whole cycle takes less time than writing a call summary, and produces something you can actually use.
How does the evaluation work?
The platform evaluates every conversation on two axes. Performance measures how well you discovered. Question quality, structure, depth. Assessment measures what you learned and how qualified the prospect actually is. You get scores, breakdowns, and specific coaching recommendations. Based on rigorous AI evaluation against structured rubrics. Not a sentiment score.
What counts as evidence?
Not call notes. Not "the customer seemed interested." Evidence is a validated customer statement mapped to a specific testable assumption, with a source, a strength rating, and a proof weight. The distinction is the difference between positioning you can defend and positioning you hope is right.
Do we need to change our existing tools or workflow?
No. δiscovery Lab works upstream of whatever you already use. Your tools stay. Your workflow stays. The quality of what goes into them gets better.
Can one person use it, or does it need a team deployment?
Both. An individual can start immediately. Team deployment adds comparable quality across everyone who does customer conversations. Most organisations start with one team, prove the impact, then expand.
How long does it take to get started?
An individual can start today. Team onboarding typically takes one focused session. Your first real conversation goes through the platform within the first week. No lengthy implementation, no IT project, no training programme to schedule.
Where does our data go?
Your data stays yours. Hosted on EU infrastructure. Conversation transcripts and evaluation data are not used to train AI models. Access controlled per user and per team.
What does it cost?
Individual access is available immediately. Team and enterprise pricing depends on team size and scope. Talk to us about your situation.
δiscovery Lab™ helps marketing teams understand what customers actually need.
Before you commit budget to assumptions.