How to build an e-commerce course: a complete guide for lecturers

Central question: Which E-Commerce model creates value, who captures that value, and where does economic power sit across the digital value chain?

Open with the architecture of E-Commerce rather than a tour of websites. Students need to distinguish direct-to-consumer retail, marketplaces, subscription, service, B2B and hybrid models, then identify the actors that enable discovery, transaction, payment, fulfilment and after-sales service. This gives the rest of the course a common economic map.

What this concept covers

• B2C, B2B, C2C, D2C, marketplace, subscription and hybrid models.
• Revenue models including product margin, commission, subscription, advertising, services and data-enabled revenue.
• The digital value chain from acquisition and storefront through payment, fulfilment, service and retention.
• Network effects, disintermediation, reintermediation and platform dependence.
• The difference between digitising a sales channel and designing a coherent E-Commerce business model.

Learning outcomes

• Classify major E-Commerce models using defensible criteria.
• Map value creation and value capture across an online transaction.
• Compare owned-channel and marketplace economics.
• Identify where platform dependence creates strategic risk.

Supports the course learning outcomes most directly linked to this stage of the E-Commerce lifecycle.

How to teach it

• Give teams three familiar online businesses and require a one-page business-model map for each.
• Ask students to trace one customer order from discovery to returns and identify every actor that takes margin or data.
• Compare the same product sold D2C and through a marketplace, keeping product demand constant.

Case-style example

Northstar Home sells a £120 desk chair. On its own site it earns a 62% gross margin before £24 acquisition cost, £11 payment and fulfilment cost, and £8 expected returns cost. A marketplace offers 40% more volume but charges a 19% commission and controls customer data. Students compute contribution per order under both channels, then recommend channel mix. One defensible view prioritises margin and data; another prioritises reach. Students discover that channel choice is a business-model decision, not only a marketing decision.

Where students struggle

Students often label every online retailer an E-Commerce business without separating customer ownership, revenue logic and the infrastructure that creates the transaction. Push them to specify who pays, for what, and which actor can change the economics.

Reading and a quick check

Use Laudon and Traver, Chapter 2, then ask students to sketch the revenue model and dependency risks for one online business in five minutes.

Teaching activity

Use the case, short model or critique above as the applied activity. A simulation is not needed here because the course is stronger when simulations appear only where they add a genuine decision mechanism.

Where it leads

With the value chain visible, students can ask whether there is a sufficiently important customer problem and a proposition that deserves to exist within it.

Central question: What customer problem is important enough to support an online proposition, and what evidence would persuade you that the proposed value is real?

E-Commerce propositions fail when teams begin with features, channels or technology before proving a customer problem. This concept trains students to define the job to be done, the target user, the proposed value and the evidence that would justify further investment.

What this concept covers

• Problem discovery and customer needs.
• Value proposition design and problem-solution fit.
• Customer segments, jobs, pains, gains and switching barriers.
• Minimum viable proposition and the difference between an MVP and a thin version of the final store.
• Assumption mapping and evidence thresholds before launch.

Learning outcomes

• Frame a customer problem precisely.
• Design a value proposition linked to evidence rather than adjectives.
• Identify the riskiest assumptions in an online venture.
• Specify an MVP test that could falsify the proposition.

Supports the course learning outcomes most directly linked to this stage of the E-Commerce lifecycle.

How to teach it

• Use short interview excerpts and make students separate observed evidence from interpretation.
• Require a one-sentence problem statement before allowing teams to design a store or campaign.
• Ask students to rank assumptions by importance and uncertainty, then choose one test.

Case-style example

ParcelPantry proposes a subscription for office snacks to 200-person firms. Interviews suggest office managers lose 3.5 hours a month coordinating ad hoc orders. The start-up expects a £79 monthly service fee and 22% product margin, but only 7 of 30 interviewees say they would pay the fee. Students calculate the annual value of time saved, design a two-week MVP and decide whether seven positive signals justify a pilot. They discover that a plausible pain does not automatically prove willingness to pay.

Where students struggle

Students frequently convert positive interview comments into demand forecasts. Require them to distinguish stated interest, behavioural evidence and paid commitment.

Reading and a quick check

Use the opportunity and business-model chapters in Laudon and Traver, then run a quick check: what single observation would most weaken your current proposition?

Where a simulation fits

Startup Creation fits directly after students can distinguish a problem, customer segment and value proposition. The simulation asks start-up teams to define the opportunity, build a Business Model Canvas, size the market and prepare a venture pitch, while student VC teams develop investment criteria.

Where it leads

A credible proposition still needs a market. The next concept asks students to estimate demand and examine the external conditions that can help or break the opportunity.

Central question: How large and accessible is the opportunity, and which external conditions could materially change the launch decision?

The objective is not to reward a large market-size slide. Students should learn to triangulate customer evidence, top-down data, bottom-up demand logic and the political, economic, social, technological, legal and environmental conditions around an online market.

What this concept covers

• Primary and secondary customer research.
• TAM, SAM and SOM with explicit assumptions.
• Bottom-up demand estimation using traffic, conversion, frequency and order value.
• PESTLE factors that affect online entry, payments, logistics, trust and regulation.
• Evidence quality, source recency and uncertainty ranges.

Learning outcomes

• Build a transparent demand estimate.
• Distinguish TAM from realistically serviceable demand.
• Prioritise external factors by materiality rather than listing them.
• Explain how new evidence should change a launch recommendation.

Supports the course learning outcomes most directly linked to this stage of the E-Commerce lifecycle.

How to teach it

• Give all teams the same data pack and compare how different assumptions create different SOM estimates.
• Run a source-quality ladder from company blog to regulator or official statistics.
• Ask students to weight external factors to 100% and defend why the top two dominate.

Case-style example

LumaPet wants to launch connected pet feeders in Germany. There are 10.6 million target households, but the team assumes only 18% are addressable, 4% visit its site in year one and 2.8% convert at a €169 price. A proposed EU data rule may add €7 per unit in compliance cost. Students compute first-year unit demand and revenue, then re-run the case at 1.4% conversion. They discover that a huge TAM can coexist with a fragile first-year business case.

Where students struggle

Students tend to present market size as a fact rather than a chain of assumptions. Mark the provenance and logic of each assumption, not the size of the final number.

Reading and a quick check

Use Laudon and Traver, Chapters 1 and 8. Quick check: ask students to identify one external factor that changes revenue, one that changes cost and one that changes permission to operate.

Where a simulation fits

PESTLE Analysis fits after students know the six categories. Its value is the weighting and defended market-entry recommendation, not the framework labels themselves.

Where it leads

Market attractiveness is not enough. Students next need to see how rivals, suppliers, customers, substitutes and platforms distribute profit within the market.

Central question: Is the online market structurally attractive, and what advantage could an entrant defend when customers and competitors can compare options quickly?

E-Commerce can make entry technically easy while leaving profitability difficult. This concept helps lecturers separate digital reach from economic attractiveness, and connect Five Forces, platform strategy, network effects and switching costs to a defendable competitive position.

What this concept covers

• Rivalry, buyer power, supplier power, substitutes and threat of entry.
• Marketplace governance, network effects and multi-homing.
• Switching costs, data advantages, brand trust, assortment, convenience and fulfilment as potential sources of advantage.
• Winner-take-most versus contestable market conditions.
• Strategic responses to platform fees, algorithm changes and channel conflict.

Learning outcomes

• Apply Five Forces to an online market with evidence.
• Assess whether network effects are present and how strong they are.
• Distinguish a useful feature from a defensible advantage.
• Recommend where an entrant should avoid direct competition.

Supports the course learning outcomes most directly linked to this stage of the E-Commerce lifecycle.

How to teach it

• Compare two digital markets with similar growth but different industry economics.
• Have teams score each force, then force them to explain which force matters most to profit.
• Ask students to design one moat that does not rely on “better UX” as a generic answer.

Case-style example

TrailKit is considering a UK marketplace for specialist outdoor equipment. Sellers can multi-home across three established platforms; the largest incumbent charges 14% commission and owns 61% of category traffic. Buyer switching cost is near zero, but specialist sellers complain about poor technical search. Students score the five forces, quantify how a 4-point commission reduction affects a £90 average order, and choose between entering as a marketplace or curated retailer. They discover that an unmet feature need can exist inside an unattractive industry structure.

Where students struggle

Students often count competitors rather than analyse bargaining power and economic mechanisms. Require a sentence beginning “This force reduces industry profit because...”.

Reading and a quick check

Use Laudon and Traver, Chapter 2. Quick check: if the leading marketplace reduced its commission by three percentage points tomorrow, which part of your advantage survives?

Where a simulation fits

Porter's Five Forces fits once students know the framework and need to convert it into an entry recommendation. Growth and Risk teams evaluate the same industry from different briefs before defending Go, Conditional Go or Reject.

Where it leads

Once students know where to compete, they can decide whom to serve and how the offer should be positioned and launched.

Central question: Which customer should the business prioritise, what position should it own, and how should the launch choices reinforce one another?

This is the bridge from strategy into commercial action. Students should treat segmentation, targeting and positioning as linked choices that shape region, channel, price, pack, message and acquisition, rather than three isolated lecture topics.

What this concept covers

• Behavioural, needs-based, demographic and value-based segmentation.
• Target selection using attractiveness and ability-to-win criteria.
• Positioning, value proposition and reasons to believe.
• Channel, region, price, pack and promotion choices.
• Launch sequencing and the difference between reach and fit.

Learning outcomes

• Construct useful segments from evidence.
• Select a target using explicit criteria.
• Write a positioning statement that makes a real trade-off.
• Design a coherent first-market go-to-market plan.

Supports the course learning outcomes most directly linked to this stage of the E-Commerce lifecycle.

How to teach it

• Give teams the same customer dataset and compare alternative segmentations.
• Require them to reject at least one attractive segment and explain why.
• Use a consistency check: target, message, price, channel and region must all tell the same strategic story.

Case-style example

PulseFuel sells protein bars online. Students can target Performance Athletes, Busy Professionals or Budget Wellness buyers. Expected annual contribution per acquired customer is £88, £64 and £39 respectively, while estimated acquisition cost is £46, £27 and £18. Performance Athletes are concentrated in two expensive regions; Busy Professionals are broader but less loyal. Students compute contribution after acquisition, choose two launch regions and build positioning. They discover that the highest-value segment is not automatically the best first target.

Where students struggle

Students often choose the biggest segment, then write a positioning statement broad enough for everyone. Penalise target ambiguity and reward explicit exclusion.

Reading and a quick check

Use Laudon and Traver, Chapters 6 and 7. Quick check: ask each team to name the customer they are deliberately not designing for.

Where a simulation fits

Go To Market is the strongest direct fit. In the current single-player simulation, each student segments the US protein-bar market, selects a target, chooses launch regions and builds a position through value proposition, price, pack and promotion decisions.

Where it leads

A strong position must survive contact with the storefront. The next concept translates the promise into journeys, merchandising and conversion design.

Central question: How should an online experience reduce friction, build confidence and help the right customer complete the intended action?

Students do not need to become interface designers, but they do need to understand how information architecture, merchandising, trust signals, mobile usability and service design influence conversion. Teach the experience as an economic system with measurable trade-offs.

What this concept covers

• Customer journey and touchpoint design.
• Information architecture, search, navigation and product detail.
• Merchandising, assortment, recommendations and social proof.
• Mobile-first usability, accessibility and page performance.
• Conversion rate, basket size, abandonment and post-purchase experience.

Learning outcomes

• Map a digital customer journey and identify high-friction points.
• Link interface choices to measurable commercial outcomes.
• Critique merchandising against the selected target and position.
• Design an experiment without confusing correlation and causation.

Supports the course learning outcomes most directly linked to this stage of the E-Commerce lifecycle.

How to teach it

• Use screenshots from several stores and ask students to predict where uncertainty appears.
• Give teams a funnel and make them prioritise one intervention rather than redesign everything.
• Run a conversion experiment design workshop with hypothesis, metric, sample logic and guardrail.

Case-style example

MiraSkincare receives 100,000 monthly sessions. Product-page-to-basket conversion is 11%, checkout start is 62% of baskets and purchase completion is 54% of checkouts, giving roughly 3,683 orders. A new guided selector is expected to raise basket entry to 13% but adds £8,000 monthly software cost. At £24 contribution per order, students calculate the break-even uplift and decide whether to test. They discover that attractive UX ideas still need an economic threshold.

Where students struggle

Students often suggest more features without identifying the behavioural bottleneck. Make them choose one metric and one causal mechanism.

Reading and a quick check

Assign Zheng and Li (2024) on omnichannel customer journey design. Quick check: which single uncertainty in the journey would you remove first, and which metric should move if you are right?

Teaching activity

Use the case, short model or critique above as the applied activity. A simulation is not needed here because the course is stronger when simulations appear only where they add a genuine decision mechanism.

Where it leads

Conversion depends on trust. The next concept covers the payment, privacy, security and consumer-protection architecture that makes an online transaction credible.

Central question: What must the business do to make digital transactions safe, lawful and trustworthy without creating so much friction that customers leave?

This concept prevents E-Commerce teaching becoming purely commercial. Students should be able to reason about payment choices, fraud, privacy, cyber risk, returns rights, dark patterns and consumer vulnerability as design and governance decisions with revenue and reputational consequences.

What this concept covers

• Payment journeys, authorisation, settlement, chargebacks and alternative payment methods.
• Fraud prevention, account security and basic cyber-risk controls.
• Privacy, consent, data minimisation and responsible personalisation.
• Consumer protection, returns, cancellation and transparent pricing.
• Dark patterns, vulnerable consumers and trust as a strategic asset.

Learning outcomes

• Map the risk points in an online payment journey.
• Evaluate a privacy or fraud control against conversion impact.
• Identify manipulative interface practices.
• Recommend a proportionate trust and consumer-protection policy.

Supports the course learning outcomes most directly linked to this stage of the E-Commerce lifecycle.

How to teach it

• Use a checkout flow and ask students where fraud, privacy and abandonment risks arise.
• Run a policy trade-off: stronger authentication reduces fraud but may reduce conversion.
• Give teams ambiguous design patterns and ask them to classify acceptable persuasion versus manipulation.

Case-style example

BrightBasket processes 18,000 orders a month at £72 average order value. Fraud losses are 1.6% of sales. A new authentication rule is expected to halve fraud but reduce checkout completion from 71% to 68%. Gross contribution before fraud is 31% of sales. Students calculate expected fraud savings and lost contribution, then recommend full rollout or targeted authentication. They discover that the stricter control is not automatically the economically or ethically superior design.

Where students struggle

Students tend to treat regulation as a checklist or security as an IT department issue. Require them to connect each control to customer harm, economic cost and decision ownership.

Reading and a quick check

Assign OECD (2023), Consumer vulnerability in the digital age. Quick check: identify one practice that is legal-looking but would still weaken customer trust.

Teaching activity

Use the case, short model or critique above as the applied activity. A simulation is not needed here because the course is stronger when simulations appear only where they add a genuine decision mechanism.

Where it leads

Once the order is secure, the company has to fulfil it. The next concept moves behind the storefront into inventory, delivery, returns and service.

Central question: How should the business promise availability and delivery while controlling inventory, fulfilment cost, service quality and returns?

E-Commerce strategy becomes operational at the moment a customer clicks buy. Students should see fulfilment, inventory placement, delivery promise and returns as part of the proposition, not back-office detail.

What this concept covers

• Inventory availability, safety stock and stockout trade-offs.
• Own fulfilment, third-party logistics and marketplace fulfilment.
• Last-mile economics and delivery-speed promises.
• Returns, reverse logistics and refund timing.
• Service levels, supplier lead times and operational resilience.

Learning outcomes

• Explain how fulfilment choices affect proposition and margin.
• Diagnose inventory and service-level trade-offs.
• Estimate the cost of delivery and returns policies.
• Recommend an operating model for a defined proposition.

Supports the course learning outcomes most directly linked to this stage of the E-Commerce lifecycle.

How to teach it

• Give teams the same demand profile but different delivery promises.
• Use a simple fulfilment P&L so every service choice has a visible cost.
• Ask students to distinguish inventory problems caused by demand uncertainty from those caused by poor process.

Case-style example

UrbanThread offers free next-day delivery and 60-day returns. It sells 25,000 units a month at £48, with 42% gross margin. Fulfilment costs £5.80 per order and 28% of units are returned, costing £4.20 each to process; 15% of returned units need a £9 markdown. Students estimate contribution erosion, then compare a free-return policy with a £2.50 return fee and slower delivery. They discover that a customer-friendly promise can destroy economics if operations are not designed around it.

Where students struggle

Students often optimise delivery speed in isolation. Make them show the linked effect on inventory, fulfilment capacity, conversion, returns and margin.

Reading and a quick check

Use Laudon and Traver, Chapters 9 and 12. Quick check: if demand uncertainty doubles, which operating metric becomes the first warning signal?

Where a simulation fits

Working Capital Management provides an applied finance-and-operations bridge after students know inventory and supplier trade-offs. In the single-player CFO scenario, students calculate and manage DSO, DIO, DPO and the cash conversion cycle across a 12-month business case.

Where it leads

Operational choices become financially meaningful through contribution, cash conversion and working capital. That is the focus of the next concept.

Central question: Does each order create economic value, and can the business finance growth without running out of cash?

Revenue growth is not enough. Students need a compact economic model that connects price, gross margin, acquisition, fulfilment, returns, payment timing, inventory and supplier terms to contribution and cash.

What this concept covers

• Price architecture, discounting and willingness to pay.
• Gross margin, contribution margin and order economics.
• Customer acquisition cost and payback.
• Inventory days, receivable days, payable days and cash conversion cycle.
• Growth funding, negative working capital and cash traps.

Learning outcomes

• Build a per-order contribution model.
• Diagnose when discount-led growth destroys value.
• Calculate basic working-capital metrics.
• Explain why profitable growth can still create a cash crisis.

Supports the course learning outcomes most directly linked to this stage of the E-Commerce lifecycle.

How to teach it

• Give students a clean order-level P&L and add one cost at a time.
• Make them calculate both accounting profit and cash timing.
• Run a growth scenario in which sales double while inventory and supplier terms worsen.

Case-style example

GlowGear sells at £80 with £34 product cost, £9 fulfilment, £6 expected returns cost and £14 acquisition cost, leaving £17 contribution. Monthly orders can grow from 8,000 to 14,000 if price falls to £72 and acquisition rises to £16. Suppliers require payment in 30 days while inventory sits 74 days. Students compare monthly contribution and incremental cash tied in inventory, then decide whether to chase growth. They discover that higher total contribution can still create an uncomfortable financing requirement.

Where students struggle

Students mix gross margin, contribution and cash. Require three separate lines: accounting margin, customer-level economics and timing of cash.

Reading and a quick check

Use Laudon and Traver, Chapters 2 and 12. Quick check: ask students to explain how a business can report positive EBITDA while experiencing severe cash pressure.

Where a simulation fits

Working Capital Management fits strongly here. Students act as CFO of Northwood Furnishings, work through a 12-month scenario and connect operational choices to DSO, DIO, DPO, cash conversion and an expansion recommendation.

Where it leads

Once the economics are visible, students need a measurement system that tells them whether the proposition and growth engine are improving.

Central question: Which metrics should management trust, and how can experiments distinguish genuine improvement from noisy movement?

E-Commerce produces abundant data, which creates a teaching risk: students may report dashboards rather than make decisions. Focus on a small metric tree that connects traffic, conversion, order value, retention and margin to a business objective, then teach experimentation and attribution limits.

What this concept covers

• Funnel metrics and metric trees.
• CAC, LTV, repeat purchase, retention and cohort analysis.
• A/B testing, hypothesis design and guardrail metrics.
• Attribution limits across paid, owned and marketplace channels.
• Leading versus lagging indicators and dashboard governance.

Learning outcomes

• Build a KPI tree from business objective to operating driver.
• Interpret CAC and LTV with cohort discipline.
• Design a basic controlled experiment.
• Identify when a metric improvement creates a harmful trade-off elsewhere.

Supports the course learning outcomes most directly linked to this stage of the E-Commerce lifecycle.

How to teach it

• Give teams a dashboard with 20 metrics and require them to keep five.
• Show a conversion uplift accompanied by higher returns and ask whether the experiment won.
• Use cohort data to expose why blended averages can hide deterioration.

Case-style example

NookBooks reports CAC falling from £31 to £24 and conversion rising from 3.2% to 3.8%. However, the new channel brings customers with six-month repeat purchase of 18% versus 34% for the existing base, and return-related service cost is £5 higher per customer. Students estimate a simple six-month contribution for both cohorts and decide whether to scale the channel. They discover that a cheaper acquisition can be a worse customer investment.

Where students struggle

Students love surface metrics because they are easy to compare. Force them to state the business question before showing the metric.

Reading and a quick check

Use Laudon and Traver, Chapters 6 and 7. Quick check: what metric would you pair with conversion rate to prevent the team from optimising the wrong behaviour?

Teaching activity

Use the case, short model or critique above as the applied activity. A simulation is not needed here because the course is stronger when simulations appear only where they add a genuine decision mechanism.

Where it leads

Metrics become more complex as businesses span owned stores, marketplaces, physical touchpoints and countries. The next concept addresses channel and ecosystem integration.

Central question: How should an E-Commerce business combine owned and partner channels, and what changes when it crosses physical-channel or national boundaries?

The teaching goal is strategic coherence. Students should compare direct and marketplace channels, channel conflict, customer-journey integration and the additional frictions created by cross-border regulation, payments, logistics and localisation.

What this concept covers

• Owned store, marketplace, social commerce and physical-channel roles.
• Omnichannel customer journeys and inventory visibility.
• Marketplace ecosystem governance and partner dependence.
• Cross-border localisation, duties, payments, returns and data rules.
• Country selection and sequencing.

Learning outcomes

• Design a coherent channel architecture.
• Assess channel conflict and platform dependence.
• Compare country-entry choices using commercial and institutional criteria.
• Recommend where to standardise and where to localise.

Supports the course learning outcomes most directly linked to this stage of the E-Commerce lifecycle.

How to teach it

• Ask teams to map one customer journey that starts on a marketplace and ends in an owned channel.
• Give two countries with opposite demand and regulatory profiles and force a single entry choice.
• Use a channel P&L to reveal that omnichannel convenience can shift cost rather than remove it.

Case-style example

NordNest sells homeware online in the UK and is choosing between France and Poland. France offers estimated year-one demand of 42,000 orders at €76 average value but return rates are forecast at 24%; Poland offers 31,000 orders at €68, 15% returns and stronger marketplace concentration. Students score market, logistics, regulation and platform dependence, then choose entry mode. Two conclusions can be defended: larger direct potential in France or lower operating risk through a marketplace-led Poland entry.

Where students struggle

Students often treat internationalisation as translation plus advertising. Require a full transaction map from traffic source to duty, payment, delivery, return and customer service.

Reading and a quick check

Assign Ahi, Sinkovics and Sinkovics (2023) on E-Commerce policy and inclusive development. Quick check: which cross-border friction changes the model most if it doubles?

Where a simulation fits

PESTLE Analysis can support country-entry risk; Porter's Five Forces can support industry attractiveness. Use them selectively, after students already know the frameworks, rather than stacking two simulations into the same session by default.

Where it leads

The final concept asks how the business scales responsibly while AI and sustainability change both operating choices and competitive expectations.

Central question: What should management scale, automate or redesign, and how can it grow without losing economic discipline, trust or strategic control?

Close by integrating the course. Students should bring proposition, market, channel, operations, economics and governance into one decision and examine how AI, automation and sustainability alter the assumptions rather than being bolted on as separate trends.

What this concept covers

• Scaling constraints across acquisition, technology, inventory, fulfilment and service.
• AI in search, recommendations, customer service, content, forecasting and decision support.
• Automation risk, bias, transparency and human accountability.
• Packaging, returns, last-mile emissions and sustainability trade-offs.
• Capstone integration: what to scale, stop, test or fund next.

Learning outcomes

• Diagnose the binding constraint in an E-Commerce growth plan.
• Evaluate an AI use case using commercial, operational and governance criteria.
• Connect sustainability choices to customer promise and economics.
• Defend an integrated scale recommendation under uncertainty.

Supports the course learning outcomes most directly linked to this stage of the E-Commerce lifecycle.

How to teach it

• Use a board memo with conflicting KPIs and ask teams to identify the binding constraint.
• Require each AI proposal to name the decision owner, training/data risk and fallback process.
• Finish with a capstone recommendation that specifies what the company will not scale yet.

Case-style example

AsterMarket has grown revenue from £18m to £31m, but CAC rose 29%, return rates moved from 17% to 23% and support cost per order increased from £2.10 to £3.40. Management proposes an AI shopping assistant costing £420,000 a year, expected to lift conversion by 0.4 percentage points and cut support contacts 18%. Students set the break-even logic, identify governance risks and choose scale, pilot or defer. They discover that AI only matters when tied to a real operating constraint.

Where students struggle

Students may treat AI or sustainability as inherently positive. Ask what decision improves, what new risk appears and what evidence would justify rollout.

Reading and a quick check

Assign Wulfert et al. (2024) on E-Commerce ecosystems and sustainability. Quick check: name one scale decision you would defer until a specific metric improves.

Where a simulation fits

Startup Creation can be revisited as a capstone evidence source: teams can compare the assumptions in their original proposition and pitch with what the full course now tells them about launch, economics, operations and scale. No extra simulation is required.

Where it leads

This integration completes the course lifecycle: students can move from an online opportunity to a defensible launch, operating model, economic case and scale decision.

10-week course structure

Compress foundations and proposition work, combine trust with experience, and integrate working capital into the unit-economics session. Keep launch, operations, analytics and scale decisions intact.

14-week course structure

Use the extra sessions to separate market analysis, give the Go To Market simulation its own debrief, deepen trust and operations, and create more space for capstone challenge and individual defence.

The Go To Market Simulation is the most direct application for the commercial-launch part of this course. The current product is a 1.5-2 hour, single-player competitive simulation in which each student acts as a founder entering the US protein-bar market. Students work through segmentation, targeting and positioning, choose two launch regions and make linked positioning choices including value proposition, price, pack and promotion.

Why it fits here

Place it after students have learned segmentation, target selection, positioning and basic contribution logic. The value is not that the platform teaches STP from scratch, but that it makes students commit to a coherent set of launch choices and gives the lecturer a cohort of different strategies to compare.

What students do

• Review a common market briefing and customer information.
• Segment the market and choose the customer group they want to prioritise.
• Select a target and commit to two launch regions.
• Build a position through value proposition, price, pack and promotion decisions.
• Complete the competitive run, then use score, rank and final strategy for structured reflection and cohort comparison.

Recommended course placement

• At the end of Session 5 after STP and launch design.
• Inside a two-hour class with a short pre-brief and a separate debrief.
• Before a go-to-market memo so the simulation choices become evidence, not the final assessment by themselves.

Knowledge students should have before the simulation

• Basic segmentation, targeting and positioning.
• A working distinction between customer attractiveness and ability to win.
• Basic price and contribution logic.

Delivery format

Suggested debrief questions

• Which segment did you choose, and which attractive segment did you reject?
• Did your region, price, pack and promotion reinforce the same position?
• Which decision most affected the difference between your strategy and a higher-performing peer?
• Would you keep the same target if acquisition cost rose by 25%?
• What evidence was missing that you would want before spending real launch capital?

The Startup Creation Simulation fits the earlier venture-design part of an E-Commerce course. It is a 6-10 hour team-based simulation that takes students from opportunity and value proposition through market sizing, Business Model Canvas work and a live pitch to student VC teams. Around 70% of participants typically work in start-up teams and around 30% in VC teams, creating two different perspectives on what makes a venture investable.

Why it fits here

Use it after students can define a customer problem and before the course becomes dominated by channels and optimisation. The simulation makes teams translate an idea into a coherent proposition, revenue and cost logic, customer segments, channels and funding request, while VC teams develop criteria and question the evidence.

What students do

• Start-up teams define the opportunity, problem, solution, customer segment and value proposition.
• Teams estimate TAM, SAM and SOM and build Business Model Canvas elements including channels, revenue streams, cost structure, unit economics and use of funds.
• VC teams create an investment thesis, screening criteria and an investment process document.
• Start-up teams prepare and deliver a live pitch; VC teams question assumptions and decide which opportunities fit their criteria.
• Teams negotiate investment amount and equity, producing a post-money valuation and a concrete basis for debrief.

Recommended course placement

• Start in Session 2 after customer problem and value proposition teaching.
• Continue selected preparation between Sessions 2 and 3 where market sizing is taught.
• Use the pitch after students have enough evidence to defend the business model, not on the first day of the course.
• Return to the original assumptions in Session 12 as a capstone reflection.

Knowledge students should have before the simulation

• No advanced finance prerequisite is required.
• Students benefit from a short introduction to customer problems, value propositions and simple market sizing.
• For an E-Commerce course, explain that the venture can be digital commerce, marketplace or digitally enabled rather than requiring a physical start-up.

Delivery format

The platform records what each team decided, the terms they agreed and comparative outcomes across groups. That evidence supports your academic judgement; it does not replace it, and it does not establish which individual student made which argument.

Suggested debrief questions

• Which claim in the pitch had the weakest evidence?
• Where did the VC team value a different risk from the founders?
• Did the negotiated equity reflect market opportunity, evidence quality or bargaining power?
• Which Business Model Canvas block changed most after questioning?
• What would you now test before investing in paid acquisition or fulfilment capacity?

Grading with the Go To Market Simulation

The simulation is individual and competitive, so each student produces an attributable strategy across segmentation, targeting, regions and positioning choices. Do not grade rank alone.

• Target selection supported by evidence.
• Consistency across target, region, value proposition, price, pack and promotion.
• Quality of post-simulation diagnosis and willingness to revise.
• Ability to distinguish simulation outcome from a universal market truth.

Grading with the Startup Creation Simulation

Start-up and VC teams create venture, screening, pitch and negotiated-investment evidence. Because much of the work is team-based, combine the team artefact with an individual assumptions note or oral defence.

• Problem-solution and value-proposition evidence.
• Market-sizing logic and Business Model Canvas coherence.
• VC criteria and quality of questioning.
• Pitch and negotiation rationale rather than headline valuation alone.
• Individual explanation of contribution, disagreement and learning.

Grading with the PESTLE Analysis Simulation

Students should be graded on materiality and recommendation quality, not whether they can reproduce the six labels.

• Quality of evidence attached to each material factor.
• Weights that sum to 100% and are defensible.
• Written rationale linking factors to the market-entry decision.
• Response to the opposing team and quality of final recommendation.

Grading with the Porter's Five Forces Simulation

Use the role-based industry decision to test whether students can turn framework evidence into profitability and entry judgement.

• Mechanism-based reasoning for each force.
• Recognition of the strongest constraint on industry profit.
• Use of evidence under Growth or Risk role pressure.
• Quality of Go, Conditional Go or Reject recommendation and conditions.

Grading with the Working Capital Management Simulation

The single-player CFO scenario is strongest when students must connect calculations to an operating and expansion recommendation.

• Accuracy and interpretation of DSO, DIO, DPO and cash conversion.
• Quality of policy choices around receivables, inventory and payables.
• Recognition of trade-offs between liquidity, service and growth.
• Final expansion recommendation and supporting rationale.

Moderation and free-riding: keep team and individual evidence separate. Use a common rubric, retain key submitted artefacts, sample oral defences where needed, and moderate borderline work using the same criteria. Platform evidence can support academic judgement, but it does not replace lecturer marking or automatically prove an individual student's contribution to a team argument.