Four Questions Worth Asking
What Changes
When discovery actually works
Pipeline truth
Opportunities reflect real customer needs, not wishful thinking. Your pipeline stages mean what they say.
Forecast confidence
When discovery is real, forecasting is arithmetic rather than guesswork. You can defend your number.
Faster, bigger deals
Better discovery upfront means fewer surprises, less rework, and scope that reflects the full customer need.
Fewer wasted cycles
Disqualification happens early when discovery is structured. Your team stops chasing opportunities that were never going to close.
Coaching on quality
Coaching based on what your reps actually discovered. Not just whether they made the call.
What Managers Actually See
After every conversation, the platform scores what was actually discovered.
Discovery Quality
Every conversation scored across five dimensions. One overall score. Your managers see at a glance which reps are discovering and which are presenting. No need to listen to a single call.
Prospect Evaluation
Every conversation gets evaluated on two dimensions — OPEN (the strength of the opportunity signal) and READY (whether the buyer is in a position to act).
Hypothesis Tracking
In preparing a conversation, the platform generates testable assumptions, tagged by type (Pains, Jobs to be Done, Sources of Value, and more). Post-meeting processing evaluates which were tested, validated, or invalidated. With specific evidence, directly from the conversation.
Performance Insights
Per-dimension analysis of what landed and what didn't. Missed opportunities from the conversation. Targeted advice for the next one. A learning pathway for the rep over time.
The Verdict
PROCEED · WITH CONDITIONSThe synthesis. Four analyses feed one recommendation on this conversation — proceed, defer, or exit. Drawn from what the customer actually confirmed, not from what the rep reported. Built from the Discovery Quality score, the OPEN and READY reads, the hypotheses resolved, and the per-dimension Performance Insights.
How It Works For Sales Professionals
Three stages. Every deal. Every conversation.
Prepare
Before the conversation
Not added work — restructured work. Your AEs already prep. This makes that prep produce the conversation instrument the platform then evaluates. First conversation takes the most time. Subsequent conversations reuse and refine hypotheses as evidence accumulates.
Run
In the conversation
Run a structured discovery conversation, with the instrument live on screen. Not improvising. Not pitching. Evidence captured as it surfaces.
Evaluate
After the conversation
Upload the transcript. The platform evaluates the conversation, tracks the hypotheses, surfaces the coaching specific, and delivers the Verdict.
Works With Whatever You Already Use
Teach teams how to sell.
Show what happened on the call.
Track the deal. The system of record for the opportunity.
Builds the understanding those systems depend on.
You Might Be Thinking
Gong shows you what happened on the call. δiscovery Lab ensures your team knows what to discover before they hit record. And proves whether they actually did.
Training teaches the method. δiscovery Lab makes it stick. Every day, in every conversation, with proof it happened.
Talking is not discovering. δiscovery Lab turns conversations into validated understanding. Not just another meeting note.
Common Questions
Where does this sit relative to Salesforce?
δiscovery Lab captures what your CRM can't. What the customer actually confirmed. Which assumptions were validated. How qualified the opportunity really is. Salesforce tracks the deal. δiscovery Lab builds the evidence the deal depends on. Your AEs run δiscovery Lab before and after every customer conversation. The evidence they generate informs the way they use Salesforce, not the other way around. Discovery Quality scores and Verdicts are designed to write directly to Salesforce Opportunity fields. Native field-level integration is on the product roadmap.
What do we see in the first conversation?
Before your AE walks in: a structured conversation instrument built specifically for this prospect. Research, testable hypotheses, three-step question structure. Not added work — your AE already preps. The platform turns that time into structured output, with hypotheses that carry forward to subsequent conversations.
In the meeting: structured discovery interview, not improvising.
After the meeting: upload the transcript. A Discovery Quality score. A Prospect Evaluation with OPEN and READY reads. A Verdict. (Buyer Forces assessment: what's pulling the prospect toward change and what's holding them in place — Push, Pull, Inertia, Friction.)
How is this different from Gong?
Gong records and analyses what happened on the call. δiscovery Lab works before and after: it structures what your rep needs to discover before the conversation, then evaluates whether real discovery actually happened afterwards. Gong tells you what was said. δiscovery Lab tells you what was learned.
What does my sales pro actually have to do differently?
Before each meeting, the platform generates structured preparation in minutes. After the meeting, upload the transcript. The platform does the rest.
What does a Discovery Quality score actually mean?
Every conversation is scored across five dimensions. One overall score. Consistent rubric across every rep and every deal.
What does a discovery cycle actually look like?
Before the meeting, you define what needs to be learned. 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.
How does the evaluation work?
Two independent axes. Performance measures how well you ran the discovery. Prospect Evaluation measures what you learned about the prospect (OPEN for opportunity signal, READY for buyer readiness). The outputs: a Discovery Quality score, a Verdict on the conversation.
What are the five dimensions in Discovery Quality?
Question Quality — the structure, precision, and depth of the questions asked.
Discovery Depth — how far the conversation moved past surface statements into the underlying cause, constraint, or commitment.
Interview Structure — the flow and coverage of the conversation relative to what needed to be learned.
Stakeholder Understanding — the extent to which decision dynamics, roles, and authority were identified.
Business Intelligence — how well the rep built a picture of the prospect's business beyond the immediate opportunity.
What are the OPEN and READY scales?
OPEN (out of 40) measures the strength of the opportunity signal — across four dimensions, each scored out of ten. The prospect's recognition of a problem worth solving, the urgency behind it, the fit with what the platform addresses, and the access to the people who can act on it.
READY (out of 50) measures whether the buyer is in a position to act — across five dimensions, each scored out of ten. Decision authority, budget, timing, organisational alignment, and procurement path. A high OPEN with a low READY is a real opportunity that isn't yet movable. A high READY with a low OPEN is a buyer ready to act on the wrong thing.
What counts as evidence?
Not call notes. Not "the customer seemed interested." Evidence is a customer statement that maps to a specific testable assumption. The platform records the source, weights the strength of the statement, and tracks whether it confirms or breaks the assumption.
How do managers get visibility?
Managers see per-conversation evaluations across all reps and all active deals. Which prospects advanced after the last conversation. Which stalled. Why.
Do we need to change our existing tools or workflow?
No. δiscovery Lab works upstream of whatever you already use. Your methodology stays. 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 scoring across reps, manager visibility, and coaching at scale.
How long does it take to get started?
An individual can start today. Team deployment is a single focused session, then live in the work — every conversation generates evaluation, every evaluation generates coaching specific. The platform reinforces what training started.
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.
What does it cost?
Individual access is available immediately. Team and enterprise pricing depends on team size and scope.
40% of your pipeline is unverified.
One conversation to show you what verified looks like across your team — and what it would take to get there.