Schedule a Meeting
Schedule a Meeting

Corporate Training · Co-Designed Program

Custom Revenue Growth Analytics Program: Train Your Team to Run a Pricing Operating System

Your team trains on your data, your stack, and the pricing decisions on their desk right now — so the work started in the room ships after we leave.”

Get Started
See How It Comes Together

What Your Team Leaves With

A curriculum built from your gaps

Anchored in the RGA Maturity Scorecard diagnostic, not a stock syllabus

Working builds on your data

Labs produce models and workbooks your team keeps extending

A trained bench with named owners

Each capability leaves with an owner, a cadence, and a next step

A 90-day embedding roadmap

What to build next, in what order, against which decision
3–5
Days, shaped to your agenda
6–12
Weeks of co-design lead time
225+
Companies benchmarked via our scorecard
 
90
Day embedding roadmap included
 
 

Why This Program Exists

The fastest way to waste a training budget is to teach elasticity theory to a team whose real constraint is a broken data spine, or dashboard skills to a team that needs causal models. Sequence matters, and it is different for every organization.

 

This program starts before day one. Your team takes the Revenue Growth Analytics Maturity Scorecard (the diagnostic more than 225 companies have used), we audit the data foundation and the stack (Power BI, Tableau, Microsoft Fabric, Snowflake, Databricks, R, Python), and we interview the leads who own pricing, promotion, and customer decisions. The agenda is then co-created with your team from the full Revology module catalog, and every lab is specified on your data under mutual NDA.

Who This Is For

Built for the whole decision chain

cohorts work best when they mix the analysts who build, the managers who own decisions, and the sponsor who clears the path. We design tracks within the cohort so each group leaves with what they need.

Pricing, RGM, Marketing & Finance Teams

Analysts to directors who will run the models and own the decisions the program is built around.

Business Analysts & Data Scientists

The builders aligned to sales, marketing, pricing, finance, or supply chain who turn the labs into standing capability.

Executive Sponsors

The commercial leader who owns the outcome, sets the decision cadence, and clears the adoption path after the cohort.

Learning Outcomes

What your team will take away

Capability matched to maturity

A curriculum sequenced against your scorecard results: foundation work where the spine is weak, causal methods where the data supports them, adoption mechanics where models already exist but sit unused.

Advanced methods, applied to your business

Elasticity and promo models, customer and marketing analytics, or portfolio pricing, taught on your categories, your channels, and your competitive set instead of textbook examples.

Working builds, not workbook exercises

Hands-on sessions produce models, workbooks, and scenario tools on your data that your team keeps extending after the cohort.

A collaboration channel with Revology experts

Strategy discussions and mock action plans built with the practitioners who run these systems in production, tuned to your industry.

A 90-day embedding roadmap

Each capability leaves with a named owner, a refresh cadence, and a next build, so the program compounds instead of fading.

How It Comes Together

Diagnose, co-design, deliver

Six to twelve weeks from first conversation to cohort, with your leads involved at every gate.
Phase 1 · Diagnose
Maturity scorecard and stack audit

Your team takes the RGA Maturity Scorecard; we audit the data foundation and interview the leads who own pricing, promo, and customer decisions.

Phase 2 · Co-Design
Agenda built against your gaps

Modules are selected from the full Revology catalog and sequenced against maturity; labs are specified on your data under NDA; pre-reads and datasets are prepared.

Phase 3 · Deliver & Embed
Cohort, capstones, and the 90-day roadmap

Three to five days in person or online, capstones on live business questions, and a roadmap with named owners so the capability compounds after the cohort.

Program Modules

A sample 4-day agenda

One recent shape of the program. Yours will differ: the diagnostic decides which modules make the cut and how deep each one goes.

DAY 1

Price Elasticity: Foundations to Causal ML

  • The state of revenue growth analytics, and where your scorecard places you
  • Volume hurdles and the strategic implications of getting elasticity wrong
  • Regression foundations, then Double ML elasticity modeling
  • Group exercise: elasticity modeling in R and Python on your categories

DAY 2

Promotion Effectiveness & Optimization

  • Promotion Market Effects and the Prisoner’s Dilemma of promotional escalation
  • Baseline vs incremental: lift decomposition and true promo ROI after funding
  • A blueprint for in-house promotion effectiveness capabilities
  • Group exercise: building optimal promo calendars with mixed-integer optimization

DAY 3

Sales & Customer Growth Analytics

  • Marketing mix modeling with open-source stacks (frequentist and Bayesian)
  • Churn and upsell propensity with uplift framing
  • Lookalike and audience-expansion modeling
  • Group exercises: MMM in R, Bayesian MMM in Python, churn models on CRM data

DAY 4

Value, Portfolio & Profit Pools

  • Price-value maps from survey and ML approaches
  • Price-pack architecture and portfolio pricing ladders
  • Industry margin pools: where profit migrates and why it matters
  • Wrap-up: capstone readouts and the 90-day embedding roadmap

The Module Catalog

Choose from the full catalog

Every module below can anchor a half-day or full day, with labs on your data. The diagnostic determines which ones make your agenda.

Pricing and promotion
  • Price waterfall and margin diagnostics
  • Trade promotion effectiveness and optimization
  • Dynamic pricing and markdown optimization
  • Willingness-to-pay research and price-value mapping
  • Causal elasticity with Double ML
  • Price-pack architecture
  • Competitive intelligence and lead-follow strategy
  • Pricing governance, corridors, and guardrails
  • Segmentation and RFM analytics
  • Customer lifetime value modeling
  • Attribution and incrementality testing
  • Next-best-action design
  • Churn and upsell propensity with uplift
  • Marketing mix modeling on open-source stacks
  • Sales and marketing knowledge graphs
  • Commercial data spine design
  • KPI definition and metric governance
  • Quality gates and validation discipline
  • Source-of-record rules and reconciliation gates
  • AI-assisted analytics workflows
  • Adoption cadences and executive reporting

Taught the Way We Work

Co-designed, then partner-taught

Co-created and co-taught by Armin Kakas and the Revology partner bench: former pricing and commercial executives, PhD-level AI practitioners, and data engineering leads, matched to the agenda your diagnostic produces. The same people who build these capabilities inside client organizations teach your team to run them.

Partner-led instruction
Instructors matched to your agenda from the partners who run Revology’s engagements
Built on your stack
Power BI, Tableau, Microsoft Fabric, Snowflake, Databricks, R, and Python, as you actually run them
Working assets, not notes
Every module ships a build on your data plus an owner and a next step

Frequently Asked Questions

Program details, answered

How custom is custom?

The agenda, labs, datasets, and case studies are built for your organization; nothing is stock except the underlying method library. Two clients running this program rarely share more than a third of their agenda.

How much lead time does it take?

Six to twelve weeks from kickoff to cohort, depending on data access and agenda complexity. The diagnostic and stack audit run in the first two weeks.

Who should attend?

Mixed cohorts work best: the analysts who will build, the managers who own the decisions, and a sponsor who clears the adoption path. We design tracks within the cohort so each group leaves with what they need.

How is company data handled?

Every hands-on session can run on your own data under mutual NDA — your team leaves with work in progress, not worked examples. Where data access is not feasible in time, we prepare realistic synthetic datasets matched to your categories.

How does this relate to Revology's advisory work?

It is the Adoption & Execution layer of our end-to-end practice, available standalone. Custom programs frequently follow a Revology build (to train the team that runs it) or precede one (to establish shared foundations before a platform engagement).

Ready to build in-house?

Tell us about your team and stack; we’ll shape the cohort around both.

Get Started
Revology Footer — RevologyAnalyticsLogoonblack3 (fig. 1 of 3) | Revology Analytics

Revology Analytics® is the end-to-end Pricing & Revenue Growth Management advisory firm for mid-market companies: strategy and governance, AI-enabled analytics, and the adoption that turns both into profit.

Who We Are
Advisory Services
Insights
Tools
Data visualization chart showing overall score of 39% for Revology Analytics.

CHECK YOUR SCORE NOW

Over 225 companies took our scorecard to improve their Revenue Growth Analytics & Management capabilities.

GET YOUR SCORE NOW
Revology Footer — bestbuy (fig. 2 of 3) | Revology Analytics
Revology Analytics logo for footer section on website.
Revology Footer — 3Mlogo (fig. 3 of 3) | Revology Analytics
L'Oréal logo representing beauty and cosmetics brand for Revology Analytics.

Copyright © 2026 Revology Analytics LLC