Unit Economics and Pricing
We build transparent unit economics: configure P&L views by channel/SKU/tariff, test prices and discounts, calculate elasticity and margin. Growth and scaling decisions are based on numbers, not intuition.
Request audit and launchWhy is it business?
Without the unit economy, it's easy to go negative: expensive traffic, generous discounts, hidden costs. We combine sales, marketing, logistics, returns and support data into a single system, and the result is that you see the true returns on each unit and know where to raise the price and where to optimize costs or disconnect the channel.
Business effects
- Gross margin growth by 3-12 p.p. due to correct pricing and discount rules.
- 10-30% CAC through redistribution of budgets to profitable clusters.
- Predictability: ROI of campaigns and new SKU/tariffs before launch.
Tools and architecture
We implement the stack: cost and sales collection -> P&L views -> calculators and simulators -> pricing engine -> dashboards and alerts.
Data and windows
- Import of expenses: marketing (UTM / creative), logistics, procurement, fulfillment, support.
- Normalization of prices/currencies/VAT, accounting for returns, refusals and cancellations.
- Unit P&L views: by SKU/category/channel/campaign/region.
Calculators and simulators
- Unit calculator: price → margin → ROI / Payback for CAC / LTV / retention.
- Pricing simulator: “what if” scenarios (prices, cost, discounts, commissions).
- LTV cohort models by segment and channel.
Elasticity and segmentation
- Evaluation elasticity* Demand by SKU/categories/audiences.
- Segments by price sensitivity: price-sensitive, quality, B2B / retail.
- Minimum margin rules and price corridors.
price-engine
- Models: fix/tiered, bundles, subscriptions, pay-as-you-go, two-component rates.
- Discount policies: coupons, volume/loyalty, B2B-price lists, MAP/parity.
- Update algorithms: by demand/elasticity/competitors/residues.
Tests and controls
- A/B-tests of prices/discounts/bands (clustering by region/stores/accounts).
- Holdout zones to evaluate the incrementality of promos.
- Guardrails: CR, returns, NPS, delivery/support speed.
Dashboards and alerts
- P&L by units and channels, ROI/ROAS, payback, promo sales share.
- Alerts: falling margin/ROI, rising returns, price wars on SKU.
- Download CSV/JSON and API for ERP/CRM/windows.
Typical stack
Implementation process
(1) Diagnosis and objectives
Cost and price inventory, discount/share audit, KPI alignment: margin, ROI/ROAS, payback, LTV/CAC.
(2) Unit economy model
Data collection and normalization, Unit P&L views, calculators and simulators, metric and formula dictionary.
(3) Price strategy
Price corridors, discount rules, bundles / tariffs, A / B plan and holdout zones.
(4) Launch of tests
Experiments in SKU/categories/segments, guardrails, promo hierarchy and anticannibalization.
(5) Rollout and procedures
Frequency of price revision, discount permissions, margin control, reporting and allerts.
What do you get?
Artifacts
- A unit economics model with formulas and P&L data marts.
- Price policy: corridors, discounts, bundles / tariffs.
- A/B price/discount test plan and method of calculating the effect.
Infrastructure
- DWH and Unit P&L views, calculators/simulators.
- Dashboards of margin and ROI, alerts, unloading.
- Integration with ERP/CRM/marketplace/acquiring.
Growth strategy
- Recommendations for price increases/decreases, "good/better/best" packages.
- Matrix promo: when, for whom and how much can be discounted.
- Roadmap cost optimization and contribution margin.
Examples of KPI
- E-commerce: gross margin, share of promotional sales, returns, AOV, ROI campaigns.
- SaaS: ARPU/ARPPU, churn, LTV/CAC, payback, share of discount deals.
- B2B: project margin, win-rate vs price, payback period.
Cases
E-commerce: “Smart discounts”
Unit P&L data marts by SKU, elasticity segmentation, and a ban on discounts below the minimum margin. Result: +6.5 p.p. gross margin, negative-margin checks down to 0.9%.
SaaS: migration to tiered tariffs
LTV model by segment, good/better/best, limit packages + pay-as-you-go. ARPU +18%, churn -2.7 p.p., LTV/CAC 2.4→3.1.
B2B services: price lists and ROI
Unified calculation of labor costs and overheads, quotas for discounts, ROI-benchmarks. Win-rate +7 p.p., project margin +4.2 p.p.
Checklists and quality control
Data and model
- Cost includes purchase/logistics/commissions/fulfilment/support.
- Marketing costs are tied to orders (UTM/click-ID/attribution model).
- Returns/cancellations are accounted for in the period and segment of the source.
Price-policy
- Minimum margin and floor price by SKU/category/segment.
- Discount rules: who, when, how much, confirmation of super-limits.
- Exceptions: VIP, wholesale, B2B contracts, marketplaces/partners.
Experiments and risks
- A/B/cluster price tests, guardrails: CR, returns, NPS, margin.
- Holdout-control incremental promo, protection against cannibalization.
- Ethics and compliance: transparency of conditions, honest communication of discounts.
Alerts and thresholds
- Margin by SKU/channel below threshold -> stop promo or revise pricing.
- Promo revenue share above target -> revise the discount matrix.
- Campaign ROI below 1.0 for two weeks -> pause or reallocate budget.
| Signal. | Threshold | Action. |
|---|---|---|
| Marge SKU | < minimum | Raise the price / optimize the cost / exclude from the promotional |
| LTV/CAC by segment | < 2.5 | Shift of channels / offers, increase of ARPU, revision of discounts |
| Elasticity | |epsilon| < 1 (inelastic) | Increase the price in the corridor, increase the value instead of discounts |
| Proportion of returns | > benchmark +30% | Check the promotional promises/quality/logistics, change the rules |
FAQ
How long does the base launch last?
Usually 5-10 business days: data collection -> Unit P&L views -> calculators -> pricing policies -> dashboards and alerts -> first A/B tests.
Can we do without DWH?
At the start, yes (CSV/connectors). For scaling, we recommend DWH and data marts.
How to take into account marketplaces and commissions?
We allocate individual data marts with commissions / logistics / fines, separate price corridors and promotional rules.
Will conversions fall as prices rise?
We work on elasticity and tests, use bundles / packages / value-add, save guardrails for CR / NPS / returns.
Decoding of terms
- Unit P&L: profit and loss per unit (SKU/customer/tariff/order).
- Elasticity (ε): demand sensitivity to price.
- CAC: Cost of attracting a customer.
- LTV: lifetime value of the customer.
- Payback: the payback period of the attraction.
- ARPU/ARPPURevenue per user/paying user.
- Contribution margin: Gross margin minus variable costs.
- MAPMinimum advertised price (limit to partners).
- Holdout: Control zone without promotional/price changes.
- GuardrailsSecurity metrics (CR, returns, NPS) limiting risk.
Are you ready to manage profits at the level of each unit?
We will build Unit P&L data marts, configure calculators and pricing policies, and launch tests and alerts. Pricing and promo decisions will become transparent and profitable.
Request an audit and work plan