All initiatives
Validation Operating Room
BuildingPrototypeLead Intelligence

ProspectIQ

Know before you reach out.

How this opportunity moved from research into execution — and what still has to be proven before it becomes a venture.

Sourced from Lead Databases · AI Productivity
Validation progress48%

Currently in Prototype

Opportunity score

2/5

Experiments passed

1/3

Gates cleared

Section 1 · Validation Mission

The hypothesis we are here to test

Every initiative exists to prove one bet. This is the bet, why it exists, and the gates that decide its fate.

Hypothesis under test

Layering intent and enrichment scoring lets teams spend time only on accounts ready to buy.

Why this initiative exists

Buyers already budget for AI and lead-intelligence line-items — no category education needed.

Success criteria
  • Intent scoring predicts conversions better than list order
  • Reps work scored accounts first, unprompted
  • Enrichment depth justifies the per-seat price
Section 2 · Validation Progress

Where the evidence stands today

A live read on the current stage, the proof gathered so far, and the unknowns still blocking a build decision.

Evidence collected · 1/3 gates
  • Signal sourced from Lead Databases · AI Productivity and queued for structured validation.
  • Confirmed — intent scoring predicts conversions better than list order.
Remaining unknowns
  • Still proving — reps work scored accounts first, unprompted.
  • Still proving — enrichment depth justifies the per-seat price.
Section 3 · Experiments Run

The validation tests and what they taught us

Each experiment is a gate on the path to a venture — with its outcome, learning, and pass / fail status.

Demand signal test

Pass

Validated live search and radar demand against the sourcing hypothesis.

Outcome

Demand confirmed at 70/100 with durable, recurring query volume.

Learning

Pull is real and recurring — the problem is worth pursuing, not invented.

Buyer interview round

Pass

Ran structured problem interviews with target operators.

Outcome

Interviews confirmed the pain is urgent and currently unsolved.

Learning

Buyers articulate the problem unprompted — strong pull, weak incumbents.

Willingness-to-pay test

Running

Put pricing in front of design partners before building.

Outcome

Pricing offers in market; first commitments landing.

Learning

Anchor pricing holds so far; testing tier and packaging sensitivity.

Prototype workflow test

Queued

Shipped a working prototype of firmographic and technographic enrichment to partners.

Outcome

Prototype build queued behind willingness-to-pay validation.

Learning

Beta retention test

Queued

Onboarded an early cohort and instrumented retention.

Outcome

Beta cohort not yet onboarded.

Learning

Section 4 · Market Feedback

What the market is telling us

Direct signal from interviews, pilot usage, and the objections that surfaced during validation.

23Customer interviews

Structured problem and pricing conversations with target operators.

67Pilot users

Early hands-on participants across design-partner cohorts.

InstrumentingDemand signals

Tracked monthly search and intent volume behind the thesis.

Strongest positive signal

Buyers already budget for AI and lead-intelligence line-items — no category education needed.

Objections discovered
  • “We already have an AI tool” — buyers are saturated with generic copilots.
  • “Can we trust the output?” — reliability and guardrails decide adoption.
  • “Is this a feature, not a product?” — incumbents could bolt it on.
Section 5 · Key Insights

What changed from the original research thesis

Validation rarely confirms the first thesis verbatim. These are the shifts and surprises that reshaped the bet.

Surprise

Validation sharpened the wedge: the original sourcing thesis — "Layering intent and enrichment scoring lets teams spend time only on accounts ready to buy." — now points at one concrete buyer workflow rather than a broad category.

Section 6 · Decision Framework

Build, continue, or archive

The studio gate: every initiative resolves to one of three calls. The recommended path is derived from current evidence.

Build Venture

Graduation gates are clearing — form the operating company and move from validation to commercialization.

Recommended

Continue Validation

Signal is strong but unproven — keep running experiments before committing build capital.

Archive Opportunity

Demand is cooling or the edge is thin — park the thesis and reallocate to a stronger signal.

Section 7 · Connected Ecosystem

Research → Initiative → Venture → Solution

Where this initiative sits in the operating model — the lineage it emerged from and the ventures and solutions it feeds.

Section 8 · Validation Timeline

From idea to decision

The chronological path this opportunity has travelled — and the milestones still ahead.

  1. Signal detected on the Radar

    Completed

    Sourced from Lead Databases · AI Productivity — buyers already budget for AI and lead-intelligence line-items — no category education needed.

  2. Sourced into an initiative

    Completed

    Written thesis locked: layering intent and enrichment scoring lets teams spend time only on accounts ready to buy.

  3. Buyer interviews & willingness-to-pay

    Completed

    Structured interviews and pricing tests against the success criteria.

  4. Prototype the core workflow

    In progress

    Ship a working build that solves the wedge job end to end.

  5. Beta cohort & retention

    Q1 2027

    Onboard early teams, instrument usage, and prove stickiness.

  6. Graduation decision

    Q2 2027

    Clear the gates and form the operating venture.