How to build a customer relationship management course: a complete guide for lecturers

Central question: What makes customer relationship management a business strategy rather than a database or software project?

Start by separating CRM as a management philosophy from CRM technology. The course should frame CRM as the coordinated process of selecting customers, acquiring them, developing relationships, retaining profitable business and learning from interaction data. Technology matters because it makes those processes scalable, but the managerial question comes first: which relationships should the organisation build, for whom, and to create what mutual value?

What this concept covers

• CRM as strategic, operational and analytical practice.
• Relationship marketing, exchange, trust, commitment and value creation.
• The customer lifecycle from prospect to retained, expanded or lost customer.
• Customer equity and the tension between customer value to the firm and value to the customer.
• Cross-functional ownership across marketing, sales, service, operations, product and analytics.

Learning outcomes

By the end of this concept, students should be able to:

• Distinguish CRM strategy from CRM software implementation.
• Explain how customer relationships create and consume economic value.
• Map the main functions that contribute to a customer relationship.
• Diagnose whether an organisation is product-led, transaction-led or relationship-led.

How to teach it

• Open with two companies that own similar CRM technology but deliver very different customer experiences.
• Ask groups to identify which decisions belong to marketing, sales, service, data and senior management.
• Use a relationship-purpose canvas: target customer, desired behaviour, customer value, firm value and evidence.

Case-style example

Oak & Elm Energy serves 40,000 household customers. Annual churn is 24%, average revenue is £52 per month, and the firm is considering a £900,000 CRM platform upgrade. Students must recommend whether the first £900,000 should go to technology, service redesign or retention offers, then specify the evidence needed. One team can defend technology; another can defend process. Students discover that CRM performance depends on strategy and operating choices before software.

Where students struggle

Students often equate CRM with a vendor category or a contact database. Insist that they name the customer decision the system is meant to improve and the organisational process that has to change.

Reading and a quick check

Use Prior, Buttle and Maklan, Chapter 1, then ask students to write a two-sentence CRM definition that contains customer value, firm value and coordinated processes.

Teaching activity

Run a short relationship-strategy workshop: students diagnose a weak customer process and specify the managerial decision, owner, data and customer outcome before discussing technology.

Where it leads

The strategy needs a customer view across time, so the next concept turns the relationship into a lifecycle and a journey.

Central question: How should a firm understand the sequence of interactions through which a customer discovers, buys, uses, seeks help and renews?

Journey mapping is useful only when it moves beyond attractive diagrams. Lecturers can use this concept to connect lifecycle stages, customer goals, moments of truth, channels, backstage processes and measurable outcomes. The important distinction is between the journey the firm has designed and the journey customers actually experience, especially when ownership crosses departments or channels.

What this concept covers

• Lifecycle stages: awareness, consideration, acquisition, onboarding, use, service, renewal, expansion and exit.
• Customer goals, effort, emotion and moments of truth.
• Frontstage touchpoints and backstage processes.
• Channel switching and journey continuity.
• Journey metrics, pain points and prioritisation.

Learning outcomes

By the end of this concept, students should be able to:

• Construct a journey map linked to customer goals and business outcomes.
• Identify moments of truth and failure points.
• Distinguish touchpoint satisfaction from end-to-end journey performance.
• Prioritise journey improvements using impact and feasibility.

How to teach it

• Give groups raw interview snippets and contact-centre records rather than a pre-filled journey map.
• Require each pain point to be linked to an owner, evidence source and business consequence.
• Compare the firm-designed funnel with a customer-led journey.

Case-style example

MetroPass Mobility sells annual commuter subscriptions. Of 8,000 trial users, 62% activate within 48 hours, 18% contact support in the first week and 31% fail to renew after year one. Students map the first 30 days, then choose one intervention from onboarding calls, in-app guidance or simplified billing. Different choices are defensible because cost and friction move differently. Students discover that the highest-volume touchpoint is not always the most important moment.

Where students struggle

Students produce descriptive maps without prioritisation. Require every journey claim to answer: what evidence shows this matters, and what customer or financial outcome would improve?

Reading and a quick check

Assign Tueanrat, Papagiannidis and Alamanos (2021) and ask students to distinguish a touchpoint map from an end-to-end journey management problem.

Teaching activity

Use a journey-redesign workshop in which groups submit one prioritised intervention, an owner, a metric and a test design.

Where it leads

Once the journey is visible, students need a reliable data and identity layer to connect interactions across touchpoints.

Central question: What data should a firm capture about customers, and how should it turn fragmented records into an ethical, usable customer view?

CRM data teaching should connect architecture to managerial use. Students need to see the difference between identity, transactions, interactions, preferences, service history and inferred attributes, and why a single customer view is difficult when identifiers conflict. Privacy, consent, access control and data quality should be integrated into the design rather than taught as a compliance appendix.

What this concept covers

• First-party customer data, transaction, behavioural, service and preference data.
• Customer identity resolution, duplicate records and master data.
• CRM, CDP, marketing automation and service-system roles at a conceptual level.
• Consent, purpose limitation, data minimisation, access and governance.
• Data quality dimensions and the business cost of poor data.

Learning outcomes

By the end of this concept, students should be able to:

• Design a minimum viable customer data model for a CRM use case.
• Diagnose identity and data-quality problems.
• Explain why more data is not automatically better CRM.
• Set basic governance rules for consent, access and retention.

How to teach it

• Give students three conflicting records for the same customer and ask them to create a matching rule.
• Ask them to remove fields that have no justified use case.
• Use a data-lineage exercise from source to CRM decision to customer action.

Case-style example

Harbour Fitness has 25,000 members across app, gym and corporate plans. A sample of 5,000 records contains 620 probable duplicates, 14% missing email consent status and 9% inconsistent cancellation dates. Students must choose whether to launch a personalised win-back campaign now or delay it for data remediation, then specify matching and consent rules. Students discover that speed and personalisation can increase risk when identity confidence is weak.

Where students struggle

Students treat a single customer view as a simple database join. Use uncertain identity matches and consent conflicts so they have to trade coverage against confidence.

Reading and a quick check

Use Prior, Buttle and Maklan on customer-related databases and privacy, then run a five-field data minimisation challenge.

Teaching activity

Set a CRM data-governance memo: which data is necessary, who may use it, what quality threshold applies and what action is prohibited when confidence is low.

Where it leads

With a usable customer view, the next decision is which customer groups deserve different propositions, service levels and resources.

Central question: Which customers should the organisation prioritise, and what should it do differently for each segment?

CRM segmentation should go beyond demographics. The useful teaching move is to combine needs, behaviour, current value, future potential, cost-to-serve and strategic fit, then ask what action changes by segment. Customer portfolio management also introduces a difficult point: good CRM is selective. Treating every customer identically can destroy value for both the customer and the firm.

What this concept covers

• Needs, behavioural, value-based and lifecycle segmentation.
• Targeting criteria and segment attractiveness.
• Customer portfolios using current value, future potential and cost-to-serve.
• Service differentiation and resource allocation.
• Segment stability, migration and fairness.

Learning outcomes

By the end of this concept, students should be able to:

• Build actionable customer segments from a defined purpose.
• Evaluate segment attractiveness using multiple criteria.
• Recommend differentiated value propositions or service strategies.
• Defend resource allocation across a customer portfolio.

How to teach it

• Provide a customer table with volume, margin, tenure, channel and churn indicators.
• Force groups to choose no more than three target segments.
• Require an explicit non-target decision and a customer-safe treatment for that group.

Case-style example

Northstar Learning has 12,000 business customers. Segment A is 8% of accounts but 34% of gross profit; Segment B is 42% of accounts with high support cost; Segment C is 25% with low current spend but 18% annual growth. Students allocate a £600,000 growth budget and design a treatment for each segment. Two allocations can be rational because near-term profit and future growth conflict. Students discover that segmentation is a resource-allocation decision, not a labelling exercise.

Where students struggle

Students create segments that sound distinctive but do not change decisions. Ask: if two segments receive the same proposition, channel, service and budget, why are they separate?

Reading and a quick check

Use Kumar and Reinartz on customer portfolio and value management, then ask groups to define the action that changes for each segment.

Where a simulation fits

The Go To Market Simulation fits directly after segmentation and targeting. Students analyse customer groups, select a focused target and position an offer through pricing, messaging, proof strategy and brand focus. Use the CRM debrief to ask what relationship strategy follows the initial market-entry choice.

Where it leads

After choosing customers, the course turns to acquisition, onboarding and the proposition that begins the relationship.

Central question: How should a firm acquire the right customers and convert a promise into a relationship that starts well?

Acquisition is not simply a lead-volume problem. CRM teaching should connect target choice, customer acquisition cost, qualification, proposition design, expectation setting and onboarding quality. A cheap acquisition can be expensive if it attracts poor-fit customers who churn, complain or consume high service effort.

What this concept covers

• Acquisition channels and customer acquisition cost.
• Lead qualification and fit.
• Value proposition design and expectation setting.
• Onboarding milestones and time-to-value.
• Acquisition quality, early churn and cohort comparison.

Learning outcomes

By the end of this concept, students should be able to:

• Evaluate acquisition channels using cost and customer quality.
• Construct a value proposition for a chosen target segment.
• Design an onboarding sequence linked to early success milestones.
• Diagnose whether growth is creating valuable relationships or low-quality volume.

How to teach it

• Compare two channels with different CAC, activation and retention.
• Ask teams to rewrite an over-promising proposition using evidence.
• Map the first 30 days and identify one measurable time-to-value event.

Case-style example

CloudCraft CRM can spend £240,000 on partner referrals or paid search. Referrals cost £480 per acquired customer and 78% remain after 12 months; paid search costs £260 and 54% remain. Gross contribution after onboarding is £1,050 for retained customers. Students compute expected first-year contribution and then consider scale. Paid search may still win if capacity and future improvements are credible. Students discover that the cheapest lead source can produce the most expensive customer relationship.

Where students struggle

Students optimise CAC in isolation. Make them include activation, retention, service cost and proposition fit before calling a channel efficient.

Reading and a quick check

Use Kumar and Reinartz on acquisition and Prior, Buttle and Maklan on value propositions. Quick check: identify one promise that marketing can make only if operations can deliver it.

Where a simulation fits

The Startup Creation Simulation is a useful secondary fit here. Students act as founders, research and validate customer needs, develop a value proposition, build a business model and move toward product and pitch decisions. Frame the debrief around acquisition quality, onboarding assumptions and what evidence would justify a repeatable customer strategy.

Where it leads

Acquisition creates the installed customer base. The next concept asks how much those relationships are worth and when retention investment is economically justified.

Central question: How much is a customer relationship worth, and when should the firm spend to acquire, retain or grow it?

Customer lifetime value gives CRM its economic discipline. The objective is not to turn every cohort into a forecasting exercise but to teach the logic of contribution, retention, timing, discounting and uncertainty. Students should also see the ethical and strategic limits of reducing relationships to a single score.

What this concept covers

• Customer profitability, contribution and cost-to-serve.
• Retention rates, churn, survival and cohort logic.
• Simple and multi-period CLV models.
• Acquisition-versus-retention economics.
• Customer equity, sensitivity analysis and model limitations.

Learning outcomes

By the end of this concept, students should be able to:

• Calculate and interpret a simplified CLV.
• Compare customer cohorts using contribution and retention.
• Evaluate whether a retention intervention is economically justified.
• Identify assumptions that make a CLV estimate fragile.

How to teach it

• Start with a one-period contribution example, then add retention and discounting.
• Use sensitivity analysis before adding model complexity.
• Ask groups when a high-CLV score should not automatically trigger preferential treatment.

Case-style example

Vista Broadband has 60,000 subscribers. Monthly contribution is £22, monthly churn is 2.4% and a proposed loyalty intervention costs £18 per targeted customer. The pilot is expected to reduce monthly churn to 2.0% for six months. Students estimate incremental contribution under a simple retention model and decide whether to target all customers or a risk segment. Students discover that small churn changes can be valuable, but only if the effect persists and targeting is credible.

Where students struggle

Students mistake model precision for certainty. Require a base, upside and downside assumption and ask which input management can actually influence.

Reading and a quick check

Assign Kumar and Reinartz (2016), then ask students to state the difference between customer value to the firm and value created for the customer.

Teaching activity

Use a spreadsheet workshop comparing acquisition, retention and service interventions under common contribution and churn assumptions.

Where it leads

The economics explain why retention matters. The next question is what customers actually experience and how service quality affects relationship outcomes.

Central question: Which experiences create durable customer value, and how can a firm distinguish satisfaction from meaningful relationship performance?

Customer experience links CRM strategy to the lived relationship. Teach students to separate touchpoint performance, journey quality, expectations, effort, service quality and overall relationship outcomes. Satisfaction scores are useful signals but not sufficient objectives: high satisfaction can coexist with low profitability, weak differentiation or easy switching.

What this concept covers

• Customer experience as cognitive, emotional, social and sensory response.
• Expectations, perceived quality, effort and moments of truth.
• Service quality and service operations.
• Satisfaction, NPS, CES and behavioural outcomes.
• Experience measurement design and attribution limits.

Learning outcomes

By the end of this concept, students should be able to:

• Diagnose an experience problem using more than one metric.
• Design a measurement plan that links experience to behaviour.
• Prioritise service improvements based on customer and firm value.
• Critique over-reliance on a single satisfaction score.

How to teach it

• Give the class a dashboard in which satisfaction rises while renewal falls.
• Ask students to identify three rival explanations.
• Use complaint verbatims to connect quantitative and qualitative evidence.

Case-style example

Aurelia Bank reports NPS of 48, up from 41, yet new-customer 90-day attrition has risen from 7% to 11%. Digital task completion is 93%, but telephone wait time averages 14 minutes after failed identity checks. Students must diagnose the contradiction and recommend one investment. Digital optimisation and service recovery are both defensible. Students discover that an aggregate experience score can hide a small, high-consequence failure journey.

Where students struggle

Students treat satisfaction as a causal proof. Ask what behaviour changed, for whom, compared with what baseline, and what else could explain it.

Reading and a quick check

Assign Becker and Jaakkola (2020), then ask students to identify what a customer experience measure captures and what it cannot establish.

Teaching activity

Run an experience-diagnostics workshop using a mixed dashboard of survey, behavioural, complaint and operational measures.

Where it leads

Experience can support retention, but loyalty and engagement require a separate discussion of repeated behaviour, attitude and relationship development.

Central question: When is repeated purchasing genuine loyalty, and how should a firm deepen relationships without buying behaviour that would have happened anyway?

CRM courses often oversimplify loyalty into points programmes. This concept distinguishes behavioural loyalty, attitudinal loyalty, inertia, contractual lock-in and engagement. It also introduces relationship development through cross-sell, upsell, community, recognition and relevance, while asking whether incentives are incremental or simply expensive discounts.

What this concept covers

• Behavioural and attitudinal loyalty.
• Share of wallet, cross-sell, upsell and relationship depth.
• Loyalty programme economics and incremental behaviour.
• Customer engagement and advocacy.
• Relationship stages, fatigue and over-contact.

Learning outcomes

By the end of this concept, students should be able to:

• Differentiate loyalty from repeat purchasing caused by inertia or switching costs.
• Evaluate a loyalty intervention for incrementality.
• Design relationship-development actions for different lifecycle stages.
• Identify when engagement tactics reduce rather than create customer value.

How to teach it

• Compare a points programme with a service-based recognition strategy.
• Give teams a control group so they can discuss incrementality.
• Ask students to design a contact rule that protects against over-communication.

Case-style example

GreenFork Grocery proposes a loyalty offer worth £6 per month to 20,000 members. Baseline monthly spend is £118; pilot spend is £126, but a matched non-offer cohort rises from £117 to £122 during the same period. Students compute the incremental lift, compare it with reward cost and decide whether to scale. Students discover that observed uplift is not the same as caused uplift and that loyalty economics need a counterfactual.

Where students struggle

Students celebrate participation rates without asking what behaviour changed because of the programme. Keep bringing the discussion back to incrementality and customer value.

Reading and a quick check

Use Prior, Buttle and Maklan on customer retention and relationship development. Quick check: give one example each of behavioural loyalty, attitudinal loyalty and inertia.

Teaching activity

Use an experiment-design workshop in which students specify target group, control, incremental outcome, cost and stop rule for a loyalty intervention.

Where it leads

Relationship development often involves human selling and account management, which introduces pipeline discipline and customer-level coordination.

Central question: How should CRM connect marketing, sales and service so the organisation manages opportunities and important accounts as one customer relationship?

This concept prevents CRM from becoming a marketing-only course. Students should understand lead stages, opportunity pipelines, account plans, handoffs, forecast hygiene and key account management. The teaching emphasis is not on a particular software workflow but on how definitions, incentives and ownership affect customer treatment and managerial information.

What this concept covers

• Lead, opportunity and account lifecycle.
• Pipeline stages, conversion, velocity and forecast quality.
• Sales-service-marketing handoffs.
• Key account planning, relationship mapping and value co-creation.
• Incentives, data discipline and gaming risk.

Learning outcomes

By the end of this concept, students should be able to:

• Design a pipeline with clear stage-exit criteria.
• Analyse conversion and velocity to identify bottlenecks.
• Construct a key-account plan linking customer objectives to firm objectives.
• Diagnose incentive or data-quality problems in CRM usage.

How to teach it

• Give groups a pipeline with stale opportunities and inconsistent stage definitions.
• Ask sales, marketing and service roles to agree one common handoff rule.
• Use an account map showing economic buyer, user, blocker and champion.

Case-style example

DeltaWorks sells enterprise software. Its £9.2 million pipeline appears healthy, but 38% of opportunities have not changed stage in 60 days and sales teams use different definitions of “qualified.” Students must forecast next-quarter bookings using stated probabilities or rebuild the pipeline using evidence-based exit criteria. Both methods create a defensible debate about comparability and judgement. Students discover that CRM data quality is often an incentive and process problem, not a user-interface problem.

Where students struggle

Students assume accurate data can be mandated. Ask what behaviour the measurement system rewards and why a salesperson might rationally keep an opportunity open.

Reading and a quick check

Use Prior, Buttle and Maklan on sales-force automation and key account management. Quick check: write a stage-exit criterion that another salesperson could audit.

Teaching activity

Run a pipeline-cleaning and account-prioritisation workshop with a short manager memo explaining every rule change.

Where it leads

Once customer and opportunity data is coordinated, firms can orchestrate campaigns and channels with greater relevance.

Central question: How should a firm coordinate messages and offers across channels without creating inconsistent, intrusive or unprofitable customer experiences?

Campaign management is where CRM data becomes action. Teach students the process from objective and audience to treatment, channel, timing, suppression, experiment and measurement. Personalisation should be treated as a decision problem with costs and risks, not an automatic goal. Omnichannel CRM adds continuity: the customer should not have to restart the relationship every time the channel changes.

What this concept covers

• Campaign objectives, eligibility, treatment and suppression logic.
• Personalisation depth and relevance.
• Channel roles, orchestration and continuity.
• Experimentation, attribution and incremental response.
• Contact policy, frequency, fatigue and privacy.

Learning outcomes

By the end of this concept, students should be able to:

• Design a campaign with explicit objective, audience, treatment and control.
• Evaluate when personalisation creates enough incremental value to justify complexity.
• Map an omnichannel handoff and remove avoidable repetition.
• Interpret campaign results using incremental rather than gross response.

How to teach it

• Give groups a campaign brief with email, app, call centre and branch channels.
• Require a suppression rule before they design the offer.
• Ask how the customer history should follow them across a channel switch.

Case-style example

Orchid Travel can send a generic renewal reminder to 100,000 customers for £8,000 or a personalised, channel-optimised programme to 30,000 high-value customers for £42,000. Expected incremental renewal lift is 0.7 percentage points for generic and 3.0 points for personalised; retained contribution is £95. Students compute expected contribution and then challenge the targeting assumptions. Students discover that more personalisation can be economically superior at lower reach, but only when uplift is genuinely incremental.

Where students struggle

Students compare response rates without a control and assume cross-channel presence equals omnichannel integration. Ask what information persists when the customer changes channel.

Reading and a quick check

Assign Neslin (2022), then ask students to identify one customer benefit and one organisational challenge created by channel integration.

Teaching activity

Use a campaign-design workshop with target, treatment, channel sequence, suppression rules, control group and success metric.

Where it leads

Even good orchestration cannot prevent every failure. The next concept focuses on churn signals, complaints and service recovery.

Central question: How should a firm identify relationship breakdown, respond to complaints and decide which lost customers are worth winning back?

Churn teaching is strongest when prediction is separated from action. A model can identify risk, but the management problem is whether an intervention is appropriate, affordable and likely to work. Complaints add a justice and recovery dimension: customers judge outcomes, process and treatment, while the firm needs to learn from root causes rather than merely close tickets.

What this concept covers

• Churn definitions, leading indicators and risk segmentation.
• Complaint handling, procedural and interactional fairness.
• Service recovery, compensation and root-cause learning.
• Save offers and treatment-effect logic.
• Win-back economics and when to let a relationship end.

Learning outcomes

By the end of this concept, students should be able to:

• Define churn appropriately for a business model.
• Prioritise at-risk customers using value, risk and treatability.
• Design a service-recovery response that addresses outcome and process.
• Evaluate whether a win-back offer is incremental and profitable.

How to teach it

• Give a churn-risk ranking but withhold treatment-effect information until students make an initial choice.
• Role-play a complaint in which policy and customer fairness conflict.
• Ask groups to distinguish a symptom metric from a root-cause metric.

Case-style example

Mosaic Mobile flags 10,000 customers as high churn risk. A £25 save offer retains 18% of treated customers, but a randomised holdout shows 11% would have stayed anyway. Each retained customer contributes £110 over the next year. Students calculate incremental value and decide whether to target all high-risk customers or only high-value, treatable subgroups. Students discover that predicting churn and preventing churn are different analytical tasks.

Where students struggle

Students target the highest-risk customers first even when they are impossible or uneconomic to save. Introduce the idea of uplift or treatability without requiring an advanced causal model.

Reading and a quick check

Use Homburg and Tischer (2023) for journey-management capability and a service-recovery case. Quick check: ask what evidence would show the intervention caused retention.

Teaching activity

Run a complaint and churn triage exercise: students choose an action, budget and escalation path for ten customer profiles, then justify who should not receive an offer.

Where it leads

The final concept integrates customer analytics, AI, governance and the organisational work required to turn CRM decisions into a repeatable capability.

Central question: How should an organisation use analytics and AI to improve customer decisions while governing risk, accountability and implementation?

Close the course by integrating analytics with change management. Students should see descriptive, predictive and prescriptive CRM analytics as inputs to decisions, then examine AI use in next-best-action, service, personalisation, forecasting and summarisation. The implementation discussion should cover operating model, ownership, adoption, measurement, ethics and the danger of automating a poor process faster.

What this concept covers

• Descriptive, predictive and prescriptive CRM analytics.
• Propensity, churn, CLV, next-best-action and experimentation at a conceptual level.
• Generative and predictive AI in sales, service and marketing workflows.
• Human oversight, bias, explainability, privacy and auditability.
• CRM operating model, adoption, governance, benefits realisation and implementation roadmap.

Learning outcomes

By the end of this concept, students should be able to:

• Match an analytics method to a customer decision.
• Critique an AI-enabled CRM use case for evidence, risk and governance.
• Design a phased CRM implementation roadmap.
• Define success measures that connect adoption to customer and financial outcomes.

How to teach it

• Give students an AI-generated “next best action” recommendation with missing evidence and ask what must be checked.
• Use a benefits map from capability to behaviour to customer outcome to financial outcome.
• End with an executive steering committee in which teams defend a 90-day CRM roadmap.

Case-style example

BrightHome Insurance can deploy an AI next-best-action model across 300,000 customers. Offline validation suggests a 9% response uplift, but consent coverage is 83%, explanation quality is weak for 12% of recommendations and contact-centre adoption is only 46%. Students choose full launch, restricted pilot or delay and allocate a £750,000 implementation budget. Different choices are defensible. Students discover that model performance is only one condition for successful CRM implementation.

Where students struggle

Students assume the best model creates the best customer decision. Ask who is accountable, what data is permitted, how the action is tested and what happens when the model is wrong.

Reading and a quick check

Assign Ledro et al. (2025) and Reinartz (2026). Quick check: ask students to write one permitted AI use, one prohibited use and one human-oversight rule for a CRM team.

Teaching activity

Use a capstone steering-committee exercise: teams propose a 90-day CRM roadmap with decision rights, data controls, customer metrics, financial metrics and one AI pilot.

Where it leads

This integrates the course: students move from relationship strategy through data, customer choice, value, experience and action to implementation and governance.

10-week course structure

A 10-week course should compress adjacent topics rather than removing the customer-value logic. Combine foundations with journey mapping, and combine experience with loyalty, while retaining separate time for data, segmentation, CLV, execution, churn and implementation.

14-week course structure

A 14-week course creates space for simulation debriefs, a separate CLV/customer-equity session and deeper channel, sales and implementation work. Use the extra time to improve evidence and reflection rather than simply adding more CRM software content.

The Go To Market Simulation places students into a focused market-entry decision after they have learned segmentation, targeting and positioning. Students analyse customer groups, choose a target, then position the offer through choices such as pricing, messaging, proof strategy and brand focus. Scenario conditions can change, forcing teams to test whether their customer strategy still holds when demand, competition or the wider environment shifts.

Why it fits here

CRM starts with customer choice. If a team targets the wrong segment or makes a proposition that does not fit customer needs, later service and retention tactics cannot fully repair the economics. Placing the simulation after segmentation lets the lecturer use the outcome as the starting point for a CRM debrief: who did you choose, why should they stay, what data would you collect and what relationship treatment follows?

What students do

• Analyse customer groups and decide which segment deserves priority.
• Select a focused targeting strategy rather than trying to serve every group.
• Position the offer through pricing, messaging, proof strategy and brand focus.
• Respond to changing market conditions and compare the robustness of the original choice.
• Review comparative outcomes and explain which assumptions or choices drove the result.

Recommended course placement

• At the end of Session 4 after segmentation and targeting teaching.
• Inside a two-hour class with pre-reading and a focused debrief, or as a longer 2-4 hour applied block.
• Before the acquisition and onboarding session, so students carry a specific target segment into the next decision.

Knowledge students should have before the simulation

• Segmentation variables and actionable segment criteria.
• Targeting and segment attractiveness.
• Basic positioning and value-proposition logic.
• The difference between customer fit and simple market size.

Delivery format

Suggested debrief questions

• Which customer segment did you prioritise, and what evidence justified that choice?
• What did your pricing and messaging imply about the relationship you were trying to build?
• Which change in market conditions most challenged your original target strategy?
• What customer data would you collect next to test whether the segment is attractive?
• What onboarding, service and retention design should follow from the go-to-market choice?

The Startup Creation Simulation is a secondary CRM fit that broadens the customer decision from targeting into need validation and proposition development. Students work as entrepreneurs from ideation toward a viable business, using customer research and validation to refine the idea, value proposition, business model, product direction, branding and marketing before moving toward an investor pitch.

Why it fits here

The activity makes acquisition assumptions visible. Students cannot design a durable customer relationship without deciding whose problem they are solving and why the offer deserves adoption. For CRM teaching, the lecturer should focus the debrief on customer-needs evidence, proposition fit, onboarding assumptions and the early signals that would distinguish a valuable customer base from growth that will churn.

What students do

• Act as founders and develop a start-up idea into a more structured business concept.
• Conduct market research and customer-needs analysis to test and refine the opportunity.
• Develop a Business Model Canvas and value proposition around the selected customer problem.
• Make product or MVP, branding and marketing choices that affect customer adoption.
• Connect the customer logic to a broader business plan and investor pitch.

Recommended course placement

• After Session 5 when students have covered acquisition, onboarding and value propositions.
• Across two teaching blocks or a longer workshop because the activity is broader than a single CRM decision.
• As an optional applied project for programmes that combine CRM with entrepreneurship or new-venture marketing.

Knowledge students should have before the simulation

• Basic segmentation and target-customer logic.
• Customer-needs research and value propositions.
• Acquisition and onboarding concepts.
• A simple understanding of business models.

Delivery format

Suggested debrief questions

• What customer evidence caused you to change the original idea?
• Which assumption about the customer remains least validated?
• How would you define successful onboarding or time-to-value for the customer you selected?
• Which early customer metrics would distinguish genuine fit from short-term interest?
• How would the relationship strategy change if your target customer or value proposition changed?

Simulation evidence can support marking when the criteria reward reasoning, not leaderboard position. Set criteria before students play, moderate team outputs against the written rubric and require an individual evidence point where marks are awarded to individuals.

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.

Grading with the Go To Market Simulation

The Go To Market Simulation asks teams to apply segmentation, targeting and positioning in a changing market-entry context. For CRM assessment, the useful evidence is not simply which team performs best. It is whether students chose a coherent target customer, aligned the positioning choices to that segment and can explain what customer relationship strategy follows.

• Quality and evidence behind the segment and target choice.
• Consistency between target customer, pricing, messaging, proof strategy and brand focus.
• Ability to explain how market changes should alter or preserve the customer strategy.
• CRM implications identified in the debrief: onboarding, service level, data collection, retention and relationship goals.
• Individual assumptions note or oral defence showing attributable reasoning.

Grading with the Startup Creation Simulation

The Startup Creation Simulation is broader than CRM, so the assessment brief should narrow the lens. Ask students to show how customer research and validation changed the value proposition, business model or acquisition assumptions, then explain what evidence would be required before the start-up could claim a repeatable customer relationship model.

• Quality of customer-needs evidence and how it changed the concept.
• Coherence of target customer, value proposition and business model.
• Identification of onboarding or early time-to-value milestones.
• Choice of customer metrics that would test fit, retention and relationship quality.
• Individual reflection on an assumption the team changed, rejected or still cannot validate.

Practical grading safeguards

• Do not award marks for winning the simulation alone.
• Publish the rubric and explain which simulation decisions or post-simulation outputs are evidence.
• Add an individual assumptions note, viva or reflection to control free-riding.
• Moderate borderline work using the same written criteria used for non-simulation work.
• Allow students to explain technical or access issues and separate those from academic judgement.