Customer journey with brain data

A visitor explores your offer, compares options and drops out somewhere. Analytics show where this happens. Conversations help explain the questions involved. Brain data can add a further research layer, provided you know which moment you are measuring and what the measurement supports. The challenge is to combine these sources into a useful decision about the customer journey.

A customer journey with brain data is a research approach linking selected touchpoints to brain measurements and other evidence about behaviour and experience. This is a practical description, not a standardised instrument. The findings help investigate hypotheses about an experience. A brain signal alone does not explain abandonment or prescribe a design change.

The customer journey describes experiences across touchpoints and channels. Lemon and Verhoef’s review connects customer experience with this development over time. It is an influential synthesis, not a claim to have invented the term. Lemon and Verhoef, 2016

Choose a specific route for your research: from exploration to a first order, for example, or from delivery to actual use. Record alternative routes too. Someone returning to a pricing page need not face the same problem as a first-time visitor.

Consumer neuroscience investigates how neuroscientific knowledge and methods can contribute to consumer research. Plassmann and colleagues discuss applications alongside methodological challenges. This supports the relevance of the approach, not every commercial score sold under that label. Plassmann et al., 2015

First state which uncertainty remains after behavioural data and interviews. Are you comparing two presentations, investigating a change around a specific event or assessing whether a measured pattern adds to existing predictors? These are different research objectives.

Ask explicitly what you will do with the additional finding. If the same design decision can be justified without the brain measurement, that measurement needs a clear rationale for inclusion.

Eye tracking, skin conductance and heart rate are not brain measurements. Name the methods separately in the report. Putting them under one label does not make their findings interchangeable.

Mobile EEG requires control of movement artefacts and synchronisation with other recordings. Reis and colleagues discuss these methodological challenges during movement. Reis et al., 2014

In journey research, mark relevant events and verify that the recordings are accurate. Record when information appears, not just the preceding click. Also consider waiting, loading, speaking and movement.

Do not align participants solely by elapsed time. If one sees the price after ten seconds while another is still reading, that second represents different events. Compare corresponding events first and report route and duration differences.

Keep an auditable record of exclusions. A phase with extensive discarded data should not receive the same evidential weight as one with usable measurements from almost everyone.

Inferring a mental process from brain activity requires additional evidence. Poldrack discusses this limitation as the problem of reverse inference. Poldrack, 2006

Show three separate statements: the observation, your proposed explanation and how that explanation will be tested. A change around a price display may motivate research into price understanding or expectations. Without further design, it does not establish “price pain”.

Do not draw a continuous emotional curve through moments that were not measured. A twenty-minute study also does not automatically represent a six-month customer relationship. State which touchpoints were investigated and which remain unexamined.

A fictional provider wants to understand why visitors struggle with three subscription options. The study compares the existing table with a version explaining usage situations more clearly. Prices and contract terms stay constant. This example contains no actual findings.

If participants understand the revised table better, that finding has value in itself. Assess separately what the brain measurement adds. Then test whether actual customers make more suitable choices and require fewer corrections or cancellations.

1. Define the decision. Select a route, touchpoint and specific improvement question.
2. Collect existing evidence. Combine analytics, questions, complaints and observations.
3. Select participants. Document relevant decision contexts and experience; do not use age alone to define groups.
4. Define the comparison. Specify tasks, variants, sequence and outcomes in advance.
5. Pilot the recording. Check markers, synchronisation and usability.
6. Analyse corresponding events. Retain individual differences and missing-data information.
7. Test the proposed improvement. An explanatory study and a conversion experiment answer different questions.

This is an editorial workflow. Sample size and analysis must fit the particular objective; there is no universal participant count here.

For each touchpoint, present the task, available data, measurement quality, finding and proposed next step. Identify findings from behaviour, self-report and brain measurement separately. Also explain when those sources disagree.

Discuss differences using a predefined segmentation. Here, an associative target group means a bounded group making decisions through shared associations. Such a grouping needs its own justification; an EEG peak does not create it automatically.

• Assigning an exact emotion to a physiological response without validation.
• Presenting a striking event selected afterwards as a predicted finding.
• Averaging different customer tasks on one time axis.
• Hiding poor recording quality behind a colour score.
• Calling every touchpoint important without priorities or next steps.
• Equating an improved laboratory outcome with lasting loyalty.

For each improvement, provide a short decision note: the moment investigated, usable data, observation, possible explanations and proposed test. Identify missing information as well. This lets a design team act without treating a colour on a chart as evidence by itself.

Agree when to revise or abandon a proposal. If customers understand a price better but leave more often because it is genuinely unattractive, that calls for a different decision from correcting confusing wording. Research can clarify this distinction; it does not automatically make the commercial decision.

A customer journey with brain data is most useful when the additional measurement helps answer a concrete question. Start with the decision, record events accurately and separate observation from interpretation. Its value ultimately lies in a better-supported improvement that can be tested again.