Tags: commerce map

Commerce & Growth MOC

Date: 2026-08-16

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The arithmetic that decides whether a business works: what a customer costs, what they’re worth, how long they stay, and what you charge. Every growth tactic is downstream of these four numbers.

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Four areas, matching the subfolders, ordered by dependency. Unit economics first — acquisition and pricing decisions are unreadable without it, and most bad growth decisions are unit economics errors wearing a marketing costume.

Statistical material anywhere in this domain follows the statistics rule: worked examples with real numbers, plain-terms lines on anything probabilistic.

Unit Economics

• Contribution Margin — revenue minus the costs that vary with the sale. The number that decides whether growth helps or hurts
• Gross Margin — and why it’s the wrong number for acquisition decisions
• Cost of Goods Sold — what belongs in it, what doesn’t, and the effect of getting the line wrong
• Fixed and Variable Costs — the split that determines whether volume is the answer
• Customer Acquisition Cost — blended versus paid-only, and why quoting the wrong one flatters everything
• Customer Lifetime Value — the several definitions in circulation, and which one is comparable to CAC
• LTV to CAC Ratio — the headline ratio, its conventional benchmarks, and why the benchmarks are mostly meaningless
• Payback Period — how long until an acquired customer has repaid their cost. The cash-flow constraint that ratios hide
• Average Order Value — its uses, and the skew that makes the average misleading — see Skewed and Heavy-Tailed Distributions
• Basket Composition — what’s in the order, and why mix moves margin more than price does
• Merchandising — collection ordering, curation and promoted products; the highest-frequency lever nobody measures
• Stockouts and Availability — out-of-stock as a conversion and margin event, not an operations one
• Return Rate and Reverse Logistics — returns as a margin line, not a customer service line
• Break-Even Analysis — the volume at which a change pays for itself
• Discount Impact on Margin — the arithmetic of how much extra volume a discount must generate to break even, worked properly
• Marginal Analysis — deciding on the next unit rather than the average one

Retention & Lifecycle

• Retention and Churn — the same thing counted from opposite ends, and why the framing changes the decision
• Repeat Purchase Rate — the single most diagnostic ecommerce number
• Purchase Frequency — and the category-dependent expectation that makes it readable
• Time Between Orders — the interval that defines what “churned” even means for a non-subscription business
• Cohort Revenue — revenue by acquisition cohort over time; the honest view of whether the business compounds
• RFM Segmentation — recency, frequency, monetary value as an operational segmentation
• Lifecycle Stages — new, active, lapsing, lapsed, reactivated, and the transitions worth intervening on
• Lifecycle Messaging — the flows: welcome, browse abandon, cart abandon, post-purchase, replenishment, winback
• Replenishment Timing — predicting the reorder point for consumables, which is most of health and beauty retail
• Winback Campaigns — the economics of reactivation versus acquisition
• Subscription Metrics — MRR, churn types, and why involuntary churn is usually the bigger number
• Involuntary Churn and Dunning — failed payments as a solvable engineering problem rather than a customer problem
• Cancellation Flows — the cancel journey as a retention surface: pause, skip, downgrade, and the point where saving a customer becomes obstructing one — see Deceptive Design
• Activation and Time to Value — the first moment a new customer gets what they came for, and why it predicts retention better than the signup does
• Loyalty Programmes — the mechanics, and the margin cost of rewarding behaviour that would have happened anyway
• Net Promoter Score — what it measures, what it doesn’t, and how to use it without believing the number

Acquisition

• Channel Mix — the portfolio view, and concentration risk in a single channel
• Marketing Funnels — top, middle and bottom of funnel as a planning model, and where it misdescribes how people actually buy
• Demand Creation vs Demand Capture — making people want the category versus being there when they already do; the split behind the paid search and paid social entries below
• Growth Loops — acquisition where each customer produces the next (referral, content, user-generated), and why loops compound where funnels don’t
• Paid Search — intent capture; the structural reason it looks efficient in every attribution model
• Paid Social — demand creation; the structural reason it looks inefficient in every attribution model
• Search Engine Optimisation — keyword research, content strategy and intent matching. The technical half is Technical SEO, filed in Architecture
• Answer Engines — retrieval and synthesis answering the query without a click: citation rather than ranking, and the traffic you can no longer see
• Affiliate and Partnerships — the incrementality question that affiliate programmes are built to avoid asking
• Marketplaces — selling on someone else’s platform, and what you give up
• Referral Programmes — the mechanics, and the fraud surface
• Creative Testing — testing the ad, which usually matters more than testing the targeting
• Landing Page Strategy — matching the page to the promise that got the click
• Bid Strategies and Budget Allocation — the automated-bidding tradeoff: efficiency for opacity
• New vs Returning Customer Acquisition — paying to acquire people you already had
• Incrementality Testing — measuring what a channel actually caused, rather than what it was near
• Geo Holdout Tests — the practical incrementality design: withhold spend by region and compare
• Marketing Efficiency Ratio — spend against revenue at the portfolio level, and its blind spots

Where the conversion is a lead, not an order:

• Lead Funnel Stages — lead, marketing-qualified, sales-qualified, opportunity; and turning cost per lead into a true acquisition cost
• Lead Quality vs Volume — form fills rising while pipeline doesn’t, and optimising to the stage that pays
• Speed to Lead — response time as a conversion variable, and the sales handoff that decides it
• Product-Qualified Leads — in-product behaviour, rather than a form fill, as the signal someone is ready to buy

Pricing

• The Offer — product, price, terms, guarantee and bonuses as one package; the thing the visitor actually decides on, upstream of the copy describing it
• Value Ladder — offers sequenced by price and commitment, from entry offer to core to premium or recurring, and what each rung is for
• Risk Reversal — guarantees, free returns and trials moving purchase risk from buyer to seller, and the margin cost of each
• Price Elasticity — how demand responds to price, and how to estimate it without a formal test
• Willingness to Pay — measuring it, and why stated willingness overstates real willingness
• Psychological Pricing — charm pricing, price endings, and what the evidence actually supports
• Price Anchoring — reference prices, was/now framing, and UK pricing-claim rules [CHECK: current CMA guidance on reference pricing]
• Discounting Strategy — depth, frequency, and the trained-buyer problem
• Promotional Cadence — the calendar, and how predictable promotions destroy full-price sales
• Bundling — pure, mixed and the margin logic of each
• Shipping Thresholds — the free-shipping minimum as the most-used pricing lever in ecommerce, and how to set it from basket data
• Tiered Pricing — good-better-best, and the decoy dynamics it relies on
• Subscription Pricing — commitment discounts, and the LTV arithmetic that justifies them
• Value Metric — the unit a subscription is priced on (seats, usage, volume), and why it should rise with the value the customer gets
• Free Trial vs Freemium — time-limited full access versus a permanent free tier, and the activation problem each creates
• Dynamic Pricing — changing price by demand, segment or time, and the trust cost
• Price Testing — why price experiments are harder than they look, legally and statistically
• Margin versus Volume — the central pricing tradeoff, worked as arithmetic rather than argued as strategy

Borders

Filed elsewhere, needed constantly here.

• Analytics — Attribution Models · Cohort Analysis · Retention Curves · Revenue Metrics · Marketing Mix Modelling · Walled Garden Reporting · Offline Conversion Imports · Self-Reported Attribution
• Statistics — Confidence Intervals · Skewed and Heavy-Tailed Distributions · Regression to the Mean · Difference-in-Differences
• Experimentation — Holdout Groups · A-B Tests · Overall Evaluation Criterion
• User Experience — Anchoring · Loss Aversion · Scarcity and Urgency · Checkout Design