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Turn customer revenue files into source-mapped, reviewable Wysdome evidence.

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Customer-revenue analytics and diligence outputs for financial institutions.

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ServicesCustomer CubeData PackConsultingMonarch AI

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Contact

Sales: sales@wysdome.comLegal: legal@wysdome.comSupport: support@wysdome.comPhone: +1 302 610 3055

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Services

Pick the output or access model the buyer needs.

Customer Cube, Data Pack, Consulting, and Monarch AI are separate choices so the workflow starts with the deliverable instead of a vague product pitch.

Available services

Make the buying choice simple before any scope call.

Buyers should be able to choose the Excel model, the PPTX chart book, strategic consulting, automated access, or a combination without decoding product language.
01Customer CubeA segmented Excel output for M&A diligence and client-base analysis. It maps customers, products, periods, cohorts, segments, source exceptions, and definitions into one reviewable workbook.Open
02Data PackAn 80+ page PPTX with every major graphical breakdown by slice: charts, bar charts, trend lines, correlations, matrices, and written explanations of the trends.Open
03ConsultingStrategic decks, commercial analytics guidance, and custom analysis when the buyer needs interpretation or a tailored narrative beyond standard data deliverables.Open
04Monarch AIAutomated access to the Wysdome analytics workflow for teams that want repeatable customer-revenue outputs without starting every request as bespoke consulting.Open

Builder

An end-to-end workflow for financial-institution revenue evidence.

The platform route is not a generic dashboard. It is a controlled path from files to reviewable transaction outputs.
source_pipeline.tsconst sourceFiles = intake.crm + intake.billing;const customerMap = reconcile(sourceFiles);return generateCube(customerMap, definitions);

Monarch AI

Evidence BuilderDescribe the output, source systems, required definitions, and review constraints.
Generate cube, Data Pack, and exception log...
task previewCustomer CubeData PackException Log

Source-mapped

Inputs stay tied to customer records and source exceptions.

Reusable outputs

Cube and Data Pack patterns repeat across transactions.

Governed review

Definitions, caveats, and boundaries stay visible.

Scoped consulting

Commercial interpretation is separated from standard analytics.

Workflow detail

The operating choices stay explicit after the visual overview.

The reference page design can be quiet without making the Wysdome service model vague: output type, source requirements, timing, and whether consulting is needed remain visible.

Service menu

4Cube, Pack, Consulting, Monarch AI

Customer Cube

XLSXSegmented Excel deliverable

Data Pack

80+PPTX pages with charts

Target timing

5 business daysAfter complete source data, signed engagement letter, agreed NDA coverage, and usable source-file access without material remediation

Service routes

Choose the output first, then scope the work around it.

Customer Cube

A segmented Excel output for M&A diligence and client-base analysis. It maps customers, products, periods, cohorts, segments, source exceptions, and definitions into one reviewable workbook.

View Customer Cube

Data Pack

An 80+ page PPTX with every major graphical breakdown by slice: charts, bar charts, trend lines, correlations, matrices, and written explanations of the trends.

View Data Pack

Consulting

Strategic decks, commercial analytics guidance, and custom analysis when the buyer needs interpretation or a tailored narrative beyond standard data deliverables.

View Consulting

Monarch AI

Automated access to the Wysdome analytics workflow for teams that want repeatable customer-revenue outputs without starting every request as bespoke consulting.

View Monarch AI

What the workflow answers

The repeated finance questions are handled from source-mapped evidence.

01Which customers drove growth, expansion, contraction, and churn?02Is revenue broad-based or dependent on a few accounts?03Which products create cross-sell, renewal, or concentration risk?04Do projections reconcile to customer-level history?05Where are one-time revenue, credits, refunds, or services revenue affecting the story?06Which source-data exceptions need follow-up before buyer or committee review?

Fit and intake

Confirm readiness before sharing confidential files.

First-pass outputs are targeted within 5 business days after Wysdome receives complete source data, a signed engagement letter, agreed NDA coverage, and source-file access that is usable without material remediation.

Deal fit checklist

Can you provide customer-level revenue history for at least 12 months?

Can customers be mapped with stable IDs, account names, or parent-child hierarchy fields?

Do source files include product, service line, or revenue category fields?

Is the transaction team prepared to sign an NDA before confidential file transfer?

Do you need customer cube, retention, concentration, churn, revenue bridge, or buyer Q&A outputs?

Can one client-side owner confirm definitions, source exceptions, and final delivery scope?

CRM exports

Salesforce, HubSpot, opportunity/account exports, customer owner files, pipeline snapshots, and segment fields.

Billing and subscription

Stripe, Zuora, Chargebee, invoice exports, ARR/MRR schedules, renewal tables, and usage billing files.

ERP / GL

NetSuite, SAP, GL exports, revenue reports, customer revenue by period, product revenue, and management reporting files.

Flat files

Excel, CSV, TSV, and structured spreadsheet exports with stable customer IDs, dates, product fields, and amounts.

Contracts and forecasts

Contract metadata tables, renewal schedules, commercial-term tables, budget files, and forecast workbooks.

Not supported as primary input

Scanned PDFs, screenshots, unstructured email threads, images of tables, payment card data, tax IDs, SSNs, and files without customer-level grain.

Next step

Request the workflow without sending live customer files.

Start with firm type, transaction side, source systems, timing, and whether the team needs Customer Cube, Data Pack, Consulting, Monarch AI, or a combination.
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