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Customer Journey Mapping & High-Impact Friction Points: A Learning Guide

What You're About to Understand

After working through this guide, you'll be able to run a friction audit on any customer journey and prioritise which problems to fix first. You'll spot the difference between friction that destroys value and friction that creates it. And when someone in a meeting says "our touchpoint satisfaction scores look great," you'll know exactly why that can be dangerously misleading — and what to measure instead.

The One Idea That Unlocks Everything

Friction compounds like interest on debt.

Imagine a customer journey with 10 steps. Each step works well 90% of the time. Sounds fine, right? But the probability of ALL ten going well is 0.9 raised to the 10th power — just 34.9%. That's a journey that fails two-thirds of the time, built entirely from touchpoints that "pass."

This is the compounding friction principle, and it changes how you think about everything. It explains why a company with 90% touchpoint satisfaction can watch overall satisfaction fall by 40% across a journey (McKinsey observed exactly this). It explains why removing a single friction point improves completion rates by 3-8% — you're not just fixing one step, you're improving the compound probability of the entire chain. And it explains why the biggest leverage in CX isn't building delightful moments — it's eliminating the small, silent failures nobody notices individually.

If you remember only this, you'll have better instincts than most CX teams.

Learning Path

Step 1: The Foundation [Level 1]

Forget the abstractions for a moment. Picture this real scenario:

An e-commerce team in Canada noticed their checkout conversion rate was underperforming. They didn't redesign the page. They didn't run a branding workshop. They fixed a single postal code validator that was rejecting valid Canadian formats. Conversion jumped 34% in one month.

That's what friction point identification looks like in practice — finding the specific, concrete places where customers get stuck, confused, or annoyed, then fixing them in priority order.

What is a customer journey map? It's a visual document that traces what a customer does, thinks, and feels as they move through stages of interacting with your business — from first hearing about you through purchasing, onboarding, using, and (hopefully) recommending you. It typically captures:

What is a friction point? Any moment where the customer's progress toward their goal is slowed, confused, or blocked. Friction comes in three flavours:

  1. Technical breaks — things that literally don't work (bugs, errors, failed page loads)
  2. Usability issues — things that are confusing (unclear labels, hidden options, bad navigation)
  3. Emotional barriers — things that create doubt (no trust signals, unclear pricing, social risk)

How do you detect friction? Two complementary approaches:

Key Insight: There's a critical distinction between a journey map and a friction map. Journey maps document the ideal path you hope customers follow. Friction maps diagnose where customers actually struggle. As one practitioner put it: "We've confused documentation with diagnosis. We're drawing maps of territories we hope exist instead of surveying the terrain customers actually navigate."

Check your understanding:
1. A SaaS company's sign-up form has 10 fields and they see 65% drop-off. They add a chatbot to the form page to help users. Why might this make the problem worse rather than better?
2. You have 90% satisfaction on every individual touchpoint in a 10-step journey. What's the approximate probability that a customer has a satisfactory experience across the whole journey, and why?

Step 2: The Mechanism [Level 2]

Now that you know what friction looks like, let's understand why it behaves the way it does. Three mechanisms from behavioural economics explain almost everything:

Mechanism 1: Loss Aversion (Kahneman & Tversky)
Negative experiences are weighted approximately 2x more heavily than equivalent positive ones. This means one bad moment in a journey does more damage than one good moment does repair. The implication is profound: most CX investment is misallocated toward "wow" moments when the highest ROI comes from removing friction.

A landmark CEB study of 75,000+ customer interactions confirmed this. Over-the-top service efforts made customers only marginally more loyal than simply meeting their needs. But high-effort experiences? 96% of those customers became more disloyal. The asymmetry is staggering.

Mechanism 2: The Peak-End Rule (Kahneman)
People don't judge experiences by averaging all the moments. They judge by two moments: the most intense point (the peak) and the ending. This means:
- A journey with nine great touchpoints and one terrible one will be remembered as terrible (if the terrible one was the peak negative)
- The final interaction matters disproportionately — a smooth ending redeems a lot
- Paradoxically, "there are no peaks without valleys." A uniformly pleasant experience may be less memorable than one with contrast

Mechanism 3: Cognitive Load
Every unnecessary step, choice, or decision depletes finite mental resources. Working memory holds roughly 4 items. When a checkout process asks you to create an account, choose a shipping method, re-enter your address, AND verify your email, you're burning through cognitive budget fast. More than 3-4 simultaneous choices during onboarding drops completion rates by up to 60%.

Worked Example: The McKinsey Onboarding Case

A telecom company's onboarding journey took ~3 months, involving 9 phone calls on average, a technician visit, plus web and mail interactions. At each individual touchpoint, there was a 90% chance the interaction went well. But average customer satisfaction fell nearly 40% across the whole journey.

Here's the mechanism in action:
- Compounding friction: 0.9^10+ touchpoints meant the journey was almost guaranteed to have at least one failure
- Loss aversion: That one failure was weighted 2x more than the successful interactions
- Peak-end rule: The single worst moment and the final interaction defined the memory
- Cognitive load: Managing 9 calls across 3 months consumed enormous mental effort

The fix wasn't making each call better. It was reducing the number of touchpoints and designing the sequence so the journey ended well.

Key Insight: McKinsey found that the gap between top- and bottom-quartile companies on journey performance was 50% wider than the gap on touchpoint performance. Journey-level satisfaction is 73% more predictive of overall customer satisfaction than touchpoint-level. This is why measuring touchpoints individually is so dangerous — you can have green dashboards everywhere while the actual experience crumbles.

Check your understanding:
1. A luxury hotel chain has NPS of 72 but Customer Effort Score is poor. Using the mechanisms above, explain why CES is 40% more accurate than CSAT at predicting loyalty.
2. An onboarding flow has 6 steps. Steps 1-5 are smooth but Step 6 (the final step) has a known bug that causes a 30-second delay. Using the peak-end rule, explain why this specific bug is more damaging than an equivalent bug at Step 3 would be.

Step 3: The Hard Parts [Level 3]

Here's where the neat mental models start to crack at the edges.

Hard Part 1: Good friction exists, and nobody has a framework for how much.

The IKEA effect is real — people value things they've worked to build. Luxury brands deliberately add friction through customization processes, waiting lists, and exclusive access. Security confirmations are friction that builds trust. Researchers have identified four types of friction: frustrating, constructive, preference-based, and rewarding. Only the first should be eliminated.

But here's the unsolved problem: the same friction can be "good" or "bad" depending on the customer's mindset. A verification step feels like security to a cautious buyer and like an obstacle to an impatient one. Friction optimization may need to be personalised — and nobody has cracked that at scale.

Hard Part 2: The journey metaphor might be fundamentally flawed.

Gartner research shows 76% of B2C customers use multiple channels to complete a single transaction. Customer behaviour is "messy, looping, and chaotic" — not a clean left-to-right path. A systematic academic review of customer journey research from 2001-2023 found the field has "adopted different conceptualizations, theoretical perspectives, and methods, fostering fragmentation." There isn't even consensus on what "journey" means.

The counter-argument is pragmatic: "All models are wrong, some are useful." The journey map doesn't need to be real — it needs to be a useful simplification that drives better decisions than departmental tunnel vision. But this tension between accuracy and utility is real and unresolved.

Hard Part 3: 67% of journey maps fail to drive any change.

This is the darkest number in the field. And the root cause isn't methodology — it's organisational. Journey maps reveal that the customer experience is owned by nobody. It falls across departments, each optimising their own silo. The teams that create maps don't control the touchpoints that need changing. ~75% of cross-functional teams report dysfunction due to unclear objectives and poor communication.

The 5-Why analysis is revealing: organisations are structured around functions, not customer journeys → restructuring would require dismantling power structures and reallocating budgets → the people who would lose power are the same people who must approve the change. It's a principal-agent problem dressed up as a CX challenge.

Hard Part 4: The Invisible 70%

70% of customers are invisible on most journey maps. They experience friction, get annoyed, and leave — without ever triggering a support ticket, leaving a review, or showing up in feedback. The customers who do speak up are systematically different from the silent majority. Most maps are built from vocal minorities or ideal-path assumptions, which means they systematically miss the largest untapped revenue opportunity.

Check your understanding:
1. A B2B SaaS company creates a detailed journey map. 70% of their customers are enterprise accounts with 6-10 decision makers. Why might a single journey map be worse than no map at all for this company?
2. Your journey map shows that Step 4 in a checkout flow has the highest drop-off. A colleague says "Step 4 is the problem — fix it." What's the alternative explanation they're missing?

The Mental Models Worth Keeping

1. Compounding Friction
Small per-step failure rates multiply across a journey. A 10% failure rate at each of 10 steps means a 65% journey failure rate. Use it when: Someone shows you touchpoint-level metrics and declares victory. Multiply the success rates together to see the real picture.

2. Effort > Delight (with exceptions)
Reducing friction delivers more loyalty than creating delight. Low-effort customers: 94% repurchase. High-effort customers: 81% spread negative word-of-mouth. Use it when: Allocating CX budget. Default to friction removal unless you're explicitly investing in brand differentiation moments.

3. Peak-End Framing
Experiences are judged by their most intense moment and their ending, not their average. Use it when: Designing a journey sequence. Put your best moment near the end. If you can't fix everything, fix the worst moment and the last moment.

4. The Friction Map > Journey Map Distinction
Journey maps show the ideal path; friction maps diagnose reality. Documentation is not diagnosis. Use it when: Someone proposes a journey mapping workshop. Ask: "Are we drawing what we hope happens, or measuring what actually happens?"

5. The 70/70 Rule
70% of journey maps lack customer input, and 70% of customers are invisible on the maps that exist. Use it when: Evaluating any journey map. Ask: "Where's the customer data?" and "What about the people who left silently?"

What Most People Get Wrong

1. "The goal is to eliminate all friction."
Why people believe it: The effort-reduction research is compelling, and "frictionless" is a buzzy aspiration.
What's actually true: Four types of friction exist — frustrating, constructive, preference-based, and rewarding. The IKEA effect, luxury customisation, and security confirmations all show that some friction creates value. Remove bad friction. Preserve or design good friction.
How to tell the difference: Does the customer perceive the effort as part of the value (good) or as an obstacle to their goal (bad)?

2. "If every touchpoint scores well, the journey is fine."
Why people believe it: Departments measure their own touchpoints and report green. It looks like everything is working.
What's actually true: McKinsey documented 90% touchpoint satisfaction coexisting with a 40% drop in journey satisfaction. Friction compounds; it doesn't average.
How to tell: Measure the end-to-end journey separately. Track journey-level metrics (total time, total effort, end-state satisfaction) alongside touchpoint metrics.

3. "Customer feedback tells you where friction is."
Why people believe it: Feedback feels like direct evidence. Surveys and support tickets are accessible data.
What's actually true: What people say they do ≠ what they actually do. The ~70% of customers who silently leave never appear in feedback channels. Selection bias means you hear from extremes — very happy or very unhappy — and miss the middle.
How to tell: Compare self-reported data against behavioural data (session recordings, funnel analytics). Expect contradictions.

4. "Smooth experiences are the most memorable."
Why people believe it: Smooth feels good in the moment. "Seamless" is an industry obsession.
What's actually true: Per the peak-end rule, uniformly pleasant experiences are actually less memorable than ones with strategic valleys followed by strong peaks and endings. Contrast creates memory.
How to tell: Ask whether customers remember your experience, not just whether they completed it.

5. "Big redesigns create the biggest impact."
Why people believe it: Major projects feel proportionate to major problems. They're exciting and visible.
What's actually true: Micro-fixes often deliver outsized returns. A single postal code validator fix drove 34% conversion lift. Reducing form fields from 10 to 6 improved conversion 12-28%. Moving payment to after value delivery doubled free-to-paid conversion.
How to tell: Score every friction point by Impact x Business Value x (1/Implementation Effort). The quick wins dominate.

The 5 Whys — Root Causes Worth Knowing

Chain 1: "67% of journey maps fail to drive change"
Maps are treated as deliverables → Map creators don't control the touchpoints → Touchpoints are owned by separate departments → Organisations are structured by function, not journey → Functional specialisation optimises for operational efficiency, not customer experience → Root insight: Journey-centric change requires restructuring power, not just creating documents. The principal-agent problem means those who must approve change benefit from the status quo.
Level 2: Why hasn't the structure adapted? Because restructuring dismantles power, budgets, and careers.
Level 3: Why does resistance persist when ROI is clear? The people who lose power are the ones who must approve the change.

Chain 2: "70% of maps lack customer input"
Customer research takes time → Teams think they "know the customer" → Curse of knowledge blinds experts → Expertise filters out disconfirming data → Confirmation bias is the default cognitive mode → Root insight: The output LOOKS complete. There's no visible gap that signals missing customer voice. And teams never test their map against reality — the exact step they skip — creating a self-reinforcing ignorance loop.

Chain 3: "Cart abandonment is 70%"
Unexpected friction in checkout → Sites optimise for getting people TO checkout, not THROUGH it → Marketing and product measure different things (traffic vs. revenue) → Incentives reward filling the funnel, not fixing it → Acquisition metrics are visible to executives; checkout friction requires deeper analysis → Root insight: When everyone has 70% abandonment, nobody perceives it as abnormal. The industry benchmark itself is wildly suboptimal — Baymard Institute counts 39 potential usability improvements in the average checkout.

Chain 4: "CES beats NPS and CSAT at predicting loyalty"
Effort captures friction directly → Loyalty is driven by avoiding negatives more than creating positives → Loss aversion: losses weighted 2x → Evolutionary wiring prioritises threat avoidance → Root insight: When outcomes are commoditised (the product works), differentiation shifts to the process experience. CES captures exactly the dimension where competitive differentiation exists.

Chain 5: "Behavioural data contradicts 2-3 team assumptions in every serious mapping exercise"
Teams form assumptions from their own experience → Availability bias overweights memorable stories → Vocal customers are systematically different from silent majority → Selection bias in feedback captures extremes, misses the middle → Root insight: The real value of journey mapping isn't the map. It's systematically confronting your wrong assumptions. The process is the product.

The Numbers That Matter

70.19% — Average cart abandonment rate (Baymard, 48+ studies). Seven out of ten shoppers who put something in their cart don't buy it. On mobile, it's 85.65%. Collectively, this represents $18 billion in annual lost revenue. The top cause? Unexpected costs at checkout (48%). That's not a UX problem — it's a transparency problem.

96% vs. 9% — The loyalty asymmetry. 96% of customers who have a high-effort experience become more disloyal. Only 9% of low-effort customers do. This 10:1 ratio is why effort reduction beats delight as a strategy. To put it in perspective: making your experience easy retains 91 out of 100 customers. Making it hard loses 96 out of 100.

0.9^10 = 34.9% — The compounding math. Ten touchpoints, each 90% successful, yield only a 35% chance of a clean journey. This single calculation explains the McKinsey finding (90% touchpoint satisfaction, 40% journey satisfaction drop) better than any other framework.

3-8% per friction point removed — The consistent yield. Each unnecessary step, form field, or decision point you eliminate improves completion rates by this range. Reducing form fields from 10 to 6 delivered 12-28% improvement. This compounds: removing 5 friction points could improve completion by 15-40%.

67% of journey maps fail to drive change. Two-thirds. Despite the ROI data being compelling (56% more cross/up-sell revenue, 15.3% vs 9.8% YoY growth, 10x improvement in service costs), most maps become "expensive decorations." The bottleneck is organisational, not methodological.

70% of journey maps are created without direct customer input (Gartner 2023). Teams map what they think the customer experiences. In virtually every serious mapping exercise, behavioural data contradicts at least 2-3 confident team assumptions.

40% more accurate — CES vs. CSAT at predicting loyalty (Gartner). Customer Effort Score isolates the exact dimension — process friction — where competitive differentiation actually lives when products are commoditised.

3 percentage points of revenue growth — The value of a 1-point improvement on a 10-point journey satisfaction scale (McKinsey). Journey-level improvements have measurable P&L impact.

38% drop off after the first screen in SaaS onboarding. 40-60% who sign up never return after the first session. 75% abandon within the first week. The onboarding journey is where most SaaS companies haemorrhage users — and it's usually the least optimised stage.

Where Smart People Disagree

1. Static Maps vs. Dynamic Orchestration
The disagreement: Are journey maps still useful, or are they obsolete artifacts replaced by real-time AI orchestration?
Best argument for maps: They create shared empathy and cross-functional alignment that no dashboard can replicate. Understanding the customer is a human act, not a data act.
Best argument for orchestration: Static maps can't keep pace with real customer behaviour. 70% of customers are invisible on them. The future is systems that detect and resolve friction in real time.
Why it's unresolved: Partly because they serve different purposes (strategy vs. execution), and partly because vendors selling orchestration platforms have a financial interest in declaring maps "dead."

2. Effort Reduction vs. Delight
The disagreement: Should CX investment prioritise removing friction or creating memorable positive moments?
Best argument for effort reduction: The CEB data from 75,000+ interactions is clear — effort predicts loyalty; delight doesn't move the needle much.
Best argument for delight: Effort reduction is table stakes, not a strategy. You can't differentiate by being merely "not annoying." Brand love requires positive emotional peaks.
Why it's unresolved: It's likely context-dependent (reduce effort in service; create delight in brand experiences), but nobody has defined precisely where the boundary sits.

3. Qualitative vs. Quantitative Approaches
The disagreement: Should journey mapping be driven by analytics or human research?
Best argument for quantitative: Self-reported data is unreliable. What people say ≠ what they do. Behavioural data doesn't lie.
Best argument for qualitative: Analytics show WHAT happened but not WHY. "A journey map based only on analytics reflects what a system recorded. A journey map built with qualitative research reflects what a customer actually experienced. These two are often dramatically different."
Why it's unresolved: Everyone agrees "use both," but resource-constrained teams must prioritise, and there's no formula for the right mix.

4. Is "the customer journey" even real?
The disagreement: Does the journey metaphor impose false linearity on fundamentally chaotic behaviour?
Best argument it's flawed: 76% of customers use multiple channels per transaction. Behaviour is looping, backtracking, and messy. The metaphor may constrain thinking.
Best argument it's useful: "All models are wrong, some are useful." Journey maps drive better decisions than the alternative, which is usually departmental tunnel vision.
Why it's unresolved: This is a philosophical question about the value of simplification, and it probably has no universal answer.

What You Don't Know Yet (And That's OK)

After this guide, you have solid intuition about friction identification, prioritisation, and the behavioural science behind it. Here's where your knowledge runs out:

Open problems nobody has solved:
- Measuring emotional friction at scale in real time. Behavioural proxies (rage clicks) are imprecise. Self-reports are unreliable. Facial expression analysis raises ethical concerns. This is arguably the biggest open measurement problem in CX.
- Determining the optimal amount of friction for a given context. We know good friction exists, but there's no framework for calibrating how much.
- Attributing journey-level outcomes to specific touchpoint changes. Correlation is everywhere; causation is elusive. A drop-off at Step 4 might be caused by a false expectation set at Step 1.
- Understanding cross-journey interaction effects. A smooth purchase journey may set expectations that make a subsequent support journey feel worse by comparison. Journeys don't exist in isolation, but their interactions are unstudied.
- Cultural variation. Most frameworks are WEIRD-centric (Western, Educated, Industrialised, Rich, Democratic). Friction tolerance, privacy expectations, and channel preferences vary dramatically across cultures.
- The ethics of predictive intervention. When does "anticipating needs" become "manufacturing consent"? As AI-driven orchestration matures, this question becomes urgent.
- The organisational design problem. Journey optimisation requires cross-functional authority that doesn't exist on most org charts. This is an unsolved structural problem, not a knowledge gap.

Subtopics to Explore Next

1. Customer Effort Score (CES) — Implementation and Benchmarking
Why it's worth it: CES is 40% more accurate than CSAT at predicting loyalty; understanding how to implement and benchmark it gives you the single best friction metric.
Start with: The original HBR article "Stop Trying to Delight Your Customers" (Dixon, Freeman, Toman, 2010), then Gartner's CES benchmarking resources.
Estimated depth: Medium (half day)

2. Behavioural Economics for CX Design
Why it's worth it: Loss aversion, peak-end rule, cognitive load, and the IKEA effect are the "physics" underneath all friction — learning them deeply makes you dangerous.
Start with: Kahneman's "Thinking, Fast and Slow" (chapters on prospect theory and peak-end rule), then apply to CX by reading Laws of UX (lawsofux.com).
Estimated depth: Deep (multi-day)

3. Friction Mapping Methodology (The 4-Week Sprint)
Why it's worth it: Turns theory into a repeatable operational process — the bridge between knowing about friction and actually fixing it.
Start with: The CMD Agency framework (business goal → persona journeys → quantitative + qualitative data → prioritised fixes → measure), then the 383 Group friction mapping masterclass.
Estimated depth: Medium (half day to learn, weeks to execute)

4. Service Blueprinting
Why it's worth it: Unlocks the backstage — shows how internal processes create the friction customers experience. The "sequel" to journey mapping that reveals root causes.
Start with: The distinction between frontstage and backstage actions, then read Miro's service blueprint guide for practical templates.
Estimated depth: Medium (half day)

5. Jobs-to-be-Done (JTBD) Integration
Why it's worth it: Traditional journey maps show WHAT customers do but miss WHY. JTBD reveals friction that seems minor operationally but blocks a critical "job."
Start with: "What job was the customer hiring your product to do?" as a framing question, then Phase 5's guide on combining JTBD with journey mapping.
Estimated depth: Medium (half day)

6. Journey Analytics and Orchestration Platforms
Why it's worth it: The field is shifting from static maps to dynamic systems. Understanding the technology landscape (CDPs, CJA, CJO) prepares you for where the industry is heading.
Start with: The 2025 Gartner Market Guide for Customer Journey Analytics & Orchestration; Forrester's key trends report.
Estimated depth: Surface (1-2 hours) for landscape view; Deep (multi-day) for implementation

7. B2B Journey Mapping Specifics
Why it's worth it: B2B journeys involve 6-10 decision makers per account, sales cycles of months/years, and parallel stakeholder journeys — requiring fundamentally different approaches.
Start with: Gartner's B2B buying journey research, then Mouseflow's B2B vs. B2C comparison guide.
Estimated depth: Medium (half day)

8. Cross-Channel Data Stitching and Identity Resolution
Why it's worth it: You can't map real journeys without connecting a customer's behaviour across web, mobile, email, phone, and in-store — this is the technical foundation underneath everything.
Start with: Customer Data Platforms (CDPs) as a concept, then explore how identity resolution works across channels.
Estimated depth: Deep (multi-day, technical)

Key Takeaways

Sources Used in This Research

Primary Research:
- Dixon, Freeman, Toman — "Stop Trying to Delight Your Customers" (HBR, 2010) — the foundational CEB effort study of 75,000+ interactions
- McKinsey & Company — "From Touchpoints to Journeys" (2016) — journey vs. touchpoint satisfaction data
- Baymard Institute — Cart Abandonment Rate Statistics (2026, 48+ studies aggregated)
- Padigar et al. — "Good and Bad Frictions in CX: Conceptual Foundations" (Psychology & Marketing, 2025)
- ScienceDirect — "Unravelling the Customer Journey: A Conceptual Framework" (Technological Forecasting, 2024)
- Forrester — Key Trends in Customer Journey Mapping (2024); Global CX Index Rankings (2025)
- Gartner/CSG — 2025 Market Guide for Customer Journey Analytics & Orchestration

Expert Commentary:
- Nielsen Norman Group — 7-Way Journey Map Analysis Framework (2023); Peak-End Rule (2023)
- CMD Agency — From Customer Friction to Measurable Business Impact (2025)
- Synergist Digital Media — Why Your Friction Map Matters More Than Your Journey Map (2025)
- Beyond Philosophy — How Friction Can Be Good for Customer Experience (2024)
- MIT Sloan Executive Education — Good Friction in Customer Journeys (2024)
- Heart of the Customer — Journey Mapping Tools Don't Address the Most Critical Challenges (2024)
- McorpCX — The ROI Benefits of Customer Journey Mapping (2023)
- Userpilot — Frictionless Customer Onboarding: SaaS Guide (2025)
- 383 Group — Friction Mapping Masterclass (2024)
- FullStory — Customer Journey Analytics with Behavioral Data (2025)

Good Journalism:
- CMSWire — Complete Guide to Customer Journey Mapping (2025); Peak-End Rule for Better Journeys (2024)

Reference:
- Renascence — Origins and Evolution of Customer Journey Mapping (2024)
- Laws of UX — Peak-End Rule (ongoing)
- SurveyMonkey — Customer Effort Score (2025)
- Mouseflow — B2B vs. B2C Customer Journeys (2024)
- Miro — Service Blueprint vs. Journey Map (2024)
- Genroe — Benefits and Disadvantages of CJM (2024)
- Opiniator — The Static Map Trap: 7 Mistakes That Kill ROI (2025)
- Customer Journey Marketer — 7 Common Misconceptions (2024)
- Phase 5 — Combining JTBD & Customer Journey Mapping (2022)