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Most journey maps are drawn in a workshop from what the team believes. A DTC brand can draw one from what its customers did.
The usual journey map is made in a day: sticky notes, a persona, an emotion curve with a dip at “delivery” and a peak at “unboxing”. The photo goes into a deck. Six months later nobody can say what it changed.
A workshop isn’t wrong in itself. The Nielsen Norman Group, a user-experience research firm, calls a map built from the team’s existing knowledge an assumption map or hypothesis map, and it recommends one as a starting point. Kate Kaplan’s warning is about what happens next: the process “often stops before validation occurs”, and the hypothesis map ends up driving critical decisions Reported. The emotion curve is the clearest case. It’s drawn with confidence, and in most workshop maps nobody measured it.
A DTC brand is unusually well placed to skip that risk. Its systems record the journey as it happens: the order, the carrier’s scans, every email and text, every ticket, return and reorder, each with a timestamp and a customer ID. The map you need is mostly a query.
The case for mapping the whole journey, rather than polishing each step, comes largely from McKinsey. In a 2013 Harvard Business Review article, Alex Rawson, Ewan Duncan and Conor Jones, then McKinsey partners, reported from their firm’s cross-industry surveys that performance on whole journeys was 30% to 40% more strongly correlated with customer satisfaction than performance on single touchpoints, and 20% to 30% more strongly correlated with outcomes such as revenue, repeat purchase and churn Reported. Their example was a pay-TV provider whose onboarding ran about three months, with six or so phone calls and a technician visit. Each interaction was likely to go well, yet in key customer segments average satisfaction “fell almost 40% over the course of the journey” Reported.
This is a consulting firm reporting its own research, without a journal’s scrutiny, so take the direction rather than the percentages: the customer’s verdict forms across the stretch, and the damage often sits between touchpoints, where no team is looking.
| Map | What it shows | Whose view | Use it for |
|---|---|---|---|
| Journey map | The steps a person takes to reach a goal with one business, often with thoughts and emotions | The customer’s | Seeing the experience in order |
| Experience map | The same kind of path, for a goal that isn’t tied to any one business | A generic person’s | Understanding a category before you design for it |
| Service blueprint | The people, systems and processes behind each step, split at the line the customer can see | The organization’s | Finding where the work behind a touch breaks |
| The measured journey | Stages defined by events, with conversion and time in stage by cohort, every touch against the stages, and a blueprint for the worst stretch | Both, from data | Deciding what to fix next and who fixes it |
ReportedFirst three rows: Sarah Gibbons, Nielsen Norman Group, “UX Mapping Methods Compared: A Cheat Sheet”, 2017. The last row is this book’s method.
Katherine Lemon and Peter Verhoef’s 2016 review in the Journal of Marketing splits the journey into prepurchase, purchase and postpurchase stages and calls it “iterative and dynamic” Published. They sort touch points into four kinds: brand-owned, partner-owned (your carrier, your returns app), customer-owned, and social or external, such as reviews and friends. And they’re blunt that firms have “much less control, overall, of the customer experience and the customer journey” Published.
That’s the argument for building from data. The parts you don’t control still leave traces: a carrier delay becomes a ticket, an unopened product becomes a missing reorder. A workshop can only guess at those. A query can count them.
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Written by Andrew Lauchner, a growth and retention operator for consumer brands. The paid work is one ninety-day Sprint.
This is one chapter of The Journey Map, which is free and readable in full on a single page with no form in front of it.