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Decisions Lab

Supported by

Simulate customer
responses before launch.

Test who cares, what they care about, and what to say.

Methodology

Built from 25M+ real-world behavioral data points across 50+ sources, validated at 92.5% prediction accuracy.

We combine public signals, CRMs, and private data to build customer profiles grounded in real observed behavior, modeling how they think, decide, and respond.

Persona

Louis Cheung

Louis Cheung

Founder in Tech

Values

proof over hypepeer recommendationshands-on trialsflexible stackfounder to founder trust

Beliefs

  • Whether it is a stack or vendor to buy, starts with an honest try, not a polished deck.
  • Trust other builders' receipts and word of mouth more than branded claims at work when shopping for themselves.

Signal sources

Public

LinkedInRedditHacker NewsXSubstackarXiv+44 more

Custom connectors

SalesforcePostHog+ yours

Data engine

Maps signals into behavioral personas grounded in real decisions.

IngestsMapsPersonalizes
Real observed behavior

Message Comparison

Which positioning lands stronger 'AI revenue platform' or 'sales intelligence layer'?

Sales intelligence layer

0.0%

AI revenue platform

0.0%

A/B testSegments 3Agents 00m:00sActive

Go To Market

Test which messages, offers, and campaigns are most likely to resonate.

Focus budget on the ideas most likely to convert.

Message fit

See which segment responds to what.

Test your pain triggers, aha moments, jobs-to-be-done, objections, and beliefs and find what actually moves each segment.

Pain trigger test · RevOps

Best pain trigger · RevOps

  • Manual CRM hygiene is quietly wrecking forecast accuracy

    44%
  • Forecasts miss every quarter with no clear owner

    31%
  • Reps won't update pipeline before the QBR

    18%
  • Leadership can't trust the number they're signing

    7%
Message fitSegments 4Agents 4,200

Target priority

RevOps shows the strongest early-entry signal

RevOps88% interest24% effort

Prioritize
RevOps
VP Sales
Sales Enbl.
CFO / Finance
Founder / CEO
High effortEffort to convertLow effort
Segment prioritySegments 5Agents 4,800

Strategy

Know which segment to focus on first.

We map buying interest against effort to convert, so you can put scarce GTM resources where they'll pay off.

Results

Case Studies

Examples of how teams used Decisions Lab to test decisions before launch and measure real-world outcomes.

Restaurant team and partners at Pick Coffee by Pokka Cafe, the pilot location.

95% match to a Hong Kong government pilot

Simulated a restaurant food waste intervention.

  • Modeled a 40% weekday reduction.
  • Live pilot recorded a 41.9% reduction.
  • Closely matched the real-world results.

Simulate customer
responses before launch.

Test who cares, what they care about, and what to say.