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Lucrative Analytics

Ask a revenue question and see the evidence behind the answer.

Explore pipeline, attribution, forecast, campaign, and customer performance in plain language. Build repeatable views and trace each result back to its sources and logic.

Shared revenue definitionsConnected source mappingQuestions in plain languageAnswers with evidence
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Use the same customer and revenue model that powers the work.

See what supports the answer.

Review the sources, definitions, model, and confidence used to produce the result.

Illustrative Lucrative Analytics dashboard
Which campaigns generated enterprise pipeline last month?
Founder Story$0K
Field · NYC$0K

Lucrative Analytics · 4 connected sources

Lucrative Analytics note

Founder Story shows stronger enterprise conversion. Review budget and audience quality before the next planning cycle.

Why revenue answers are hard to trust

Data is spread across systems, and the meaning of the metric is often separated from the result.

The answer needs context.

Business questions turn into a queue for the analytics or operations team.

Definitions and relationships differ across systems and reports.

Simple attribution views miss much of the buying journey.

A dashboard shows the number but often hides the cause and supporting evidence.

Every team creates another version of the metric.

S
Lucrative AnalyticsEdit this execution plan with natural language
Compare my Google Ads spend last month against the actual closed-won revenue in HubSpot for those same campaigns. Which campaign had the highest actual ROI?
Lucrative Analytics example: CRM and advertising data
Connected performance analysis for last month:
• Total Google Ads Spend: $42,500
• HubSpot Closed-Won Revenue: $188,000
• Overall Blended ROI: 4.42x
Top Performing Campaign:
“Q2 Enterprise Search - Competitor Alt” · Google Ads Spend: $8,200 (24,100 Clicks) · HubSpot Deals Created: 18 SQLs · HubSpot Closed-Won: $56,000 (3 Deals) · Campaign ROI: 6.83x
Ask me anything

Understand the number and the evidence behind it

Lucrative Analytics keeps sources, definitions, models, and confidence with the answer.

Measure the marketing to sales handoff

Connect campaign activity, qualification, sales acceptance, opportunity work, and outcomes. Review which sources produce accounts that Sales accepts and progresses.

HubSpotSalesforceSnowflakeAmazon RedshiftMarketoGoogle AdsGoogle Analytics 4Meta AdsLinkedIn AdsMailchimpKlaviyoPardotMarketing CloudGoHighLevel

Plain language with query visibility

Humanized Data Query lets a user ask in plain language and inspect the generated query. Advanced users can review and adjust the logic when the question requires more control.

“Which campaign generated the highest close rate?”
“Show deals stuck over 30 days.”
“What changed this week?”

Build a dashboard from a defined question

Describe the metric, audience, time period, and comparison. Lucrative prepares the view so the team can review the logic and save it for repeat use.

Pipeline by owner
Pipeline
$0.0M
Contacts Analyzed
0.0k

Compare attribution models with the journey context

Compare attribution approaches and inspect the activities that shaped the journey. Event participation, campaigns, sales acceptance, and opportunity progress can be reviewed in one reporting context.

Webinars0%
Paid search0%
Email nurture0%

Review important changes and proposed actions

A weekly brief can explain what changed and prepare possible actions with supporting evidence and confidence. The accountable owner decides what to test or change.

Shift 15% of paid budget towards webinar promotion; projected + $120k pipelineHigh confidence
Enterprise deals stall at legal review; add a mid-stage touchpoint.Review

Prove your strategy

Run holdout experiments without SQL. Compare two groups. Measure lift. Validate marketing investments with statistical confidence.

Holdout
0.0%
Conversions
Exposed
0.0%
Conversions

Useful to business teams and analysts

Ask in plain language and inspect the logic when needed.

SQLData warehouseETL project

Visible source and relationship mapping

Map external records to the approved revenue model and keep those relationships visible. Integration requirements and available connections are confirmed for each account.

Two ways to run a Monday.

Compare a reporting queue with a connected question, evidence, and decision workflow.

The old way

Dashboards & tickets

The Lucrative Analytics way

Ask, understand, prove

Marketer files a Jira ticket to find out why pipeline dipped.
9:00
Ask why pipeline changed and review the answer with its sources and definitions.
Standup. Reads last week’s dashboard aloud. Nobody knows the why.
9:30
Bring the cause and the open questions into the standup.
RevOps exports 4 CSVs from HubSpot and Salesforce to manually stitch in Excel.
11:00
Review the weekly brief and assign the actions that need owners.
The data breaks because of a messy table relationship.
2:00
Define a holdout test from the insight and review the setup.
Decisions are delayed until next week.
5:00
Record the decision and monitor the result in the same context.
Answer: pendingAnswer reviewed and next action assigned

Bring the required sources into one reporting context

Map the systems, definitions, and ownership behind each measure. Connection availability is confirmed for every account and source.

Lucrative Analytics connects HubSpot, Meta, Salesforce, Google Analytics, LinkedIn, and Google Ads

Analytics by role

One revenue context for four different questions

Marketing, leadership, RevOps, and service providers can use the same governed definitions and evidence.

MARKETINGPERSONA 01/04

Connect campaign performance to pipeline evidence

Review which campaigns influenced accepted accounts and pipeline, then inspect the sources and definitions behind the result before changing the plan.

"Which campaigns generated pipeline last week?"
YOUR WEEKLY BRIEF
$0K
Founder Story · attributed pipeline
•Scale Founder Story0.0×
•Q4 nurture stalling0%
•Retest paid search geonext
One brief. Every channel, ranked by dollars.

What changes when revenue context is connected

Business teams can ask, inspect, compare, and save the answer in one place.

Why did MQLs dip last month?
10:00 EST
Two paused campaigns and a form change on July 2. The evidence is shown below.
4 sources · 10:00 EST
Self-service analytics

Ask the question without opening another request.

Plain languageSources attached

WHAT LUCRATIVE ANALYTICS ALREADY KNOWS

Your funnel: MQL → SQL → Proposal → Won
“Enterprise” = deals over $50K
“Pipeline” = open deals, stage-weighted
Revenue definitions

Use the meaning your business has approved.

Semantic layerDefined funnel

CREDITED REVENUE · BY MODEL

Markov$412K
Shapley$374K
Last-touch$96K
Attribution comparison

Compare models before using the result.

Markov + Shapley8 models, one view

NURTURE SEQUENCE · HOLDOUT

+0%

lift · 95% confidence

Treatment · n=1,240Holdout · n=1,240
Experiments built in

Test whether the change made a difference.

Randomized holdouts95% confidence
Q4 PIPELINE● LIVE
Saved revenue view

Turn a defined question into a repeatable view.

Question to dashboardRefreshable

Analytics that keeps
the evidence attached.

Ask in plain language, inspect the definitions and query, and save a useful answer for repeat use.

Start 14 Day TrialSee It With Your Data

Start with Analytics and the shared revenue workspace.

The Starter plan begins at $90 a month and includes the core revenue products and published allowances.

The $90 monthly Starter Engine Includes
  • 5 user seats included
  • 5,000 Marketing Contacts
  • 25,000 Verified Emails
  • 500 AI Execution Credits
  • Conversational Prompter Analytics
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FAQs

Questions? Answered

Lucrative Analytics is the reporting and analysis workspace inside the Lucrative revenue engine. It covers pipeline, attribution, forecast, campaign, customer, and operating performance.