BehaviorLens Workbook: Product Emotions

BehaviorLens Workbook: Product Emotions

Overview

The Product Emotions test is an image-led test. Panelists react to samples across a set of emotion attributes, and separately choose a metaphor image that captures how each sample makes them feel. It combines the sample × attribute engine of the Product Experience report with an image-selection module, so an emotion-metaphor image library sits alongside the implicit emotion scores. Each timed Positive/Negative answer is scored on the Implicit/Explicit Score.


Why would I use it?

Use the Emotion Projection test when you want to understand the emotional territory a product owns, how it makes people feel, not just whether they like it. Panelists react to a set of emotion words for each sample and pick an image that captures the feeling, so the report pairs implicit emotion scores with a projective image library.

Every answer is timed, so the report separates a fast, instinctive Positive from a slow, considered one and places each response on the 0 to 100 Implicit/Explicit Score. That lets you:

  • see which emotions each sample owns, and how strongly;
  • read the images and verbatim people associate with each sample;
  • compare how different audiences react using the descriptive splits.

How is the Implicit / Explicit Score calculated?

BehaviorLens® separates an instinctive (implicit / fast) reaction from a deliberate (explicit / slow) one by timing every Positive/Negative answer. The response time is compared against a per-panelist threshold, and the Positive/Negative answer combined with implicit/explicit maps onto the 0 to 100 Implicit/Explicit Score:

Response typeScoreMeaning
Fast Positive100Positive selected in the implicit (fast) time: at or below the threshold
Slow Positive75Positive selected in the explicit (slow) time: above the threshold
Slow Negative25Negative selected in the explicit (slow) time: above the threshold
Fast Negative0Negative selected in the implicit (fast) time: at or below the threshold


The calibration threshold

Each panelist completes 18 calibration trials (10 numbers + 8 colours). To set their threshold, the second slowest trial becomes the implicit/explicit (IE) threshold between an implicit (fast) and explicit (slow) response. The threshold is capped at the max time (default 6,000 ms). A response at or below the threshold is Fast; above it, Slow.


Character-length adjustment

From the Raw Data sheet onward, the threshold is adjusted for stimulus length using the Character-length adjustment set on the Calibration block (default 0.015 s/char, 0 disables): the per-response threshold = calibration threshold + (0.015 s × character count). Longer statements get proportionally more time before a response counts as explicit/Slow. This adjustment applies across all analysis sheets and to every test type.


What’s included in the workbook?

The workbook flows from calibration and raw data into per-panelist scores, then into mean, composition, statistical and descriptive views (each organized by sample and by attribute), alongside the image-selection module.

SheetWhat it does
Calibration18 calibration trials per panelist (10 numbers + 8 colours). The threshold is found by taking the second slowest trials, capped at the max time (default 6,000 ms). Includes a Status Summary (OK / Max time reached) and a Distribution of Calibration Thresholds plotted in 500 ms bins.
Raw DataOne row per panelist × sample × emotion: Sample Set Number, Sample, panelist UI fields, Emotion, Response, Response time (ms), Threshold (ms), Fast/Slow, Implicit score, and demographics. The single source of truth.
Comment QuestionsOpen-end verbatims per panelist × sample: the image chosen plus Q1 (why this image?) and Q2 (describe the image).
Image LibraryPer-sample metaphor library. For each sample it surfaces the top emotion (INDEX/MATCH against the mean scores) and its score, then ranks the chosen images by Times Selected with a representative verbatim.
Implicit ScoresOne column per emotion with samples grouped together; panelists in rows.
Mean Scores - SampleHeat-map of mean implicit scores by sample, colour-coded by zone, showing all data combined then one table per sample. Rows: Category, n, Implicit Score, Min, Max, %Fast Positive, %Slow Positive, %Slow Negative, %Fast Negative.
Mean Scores - AttributeThe same means re-pivoted so emotions lead: all data combined then one table per emotion.
Fast/Slow - SampleThe n and four-type composition (% Fast Positive / Slow Positive / Slow Negative / Fast Negative) grouped by sample, with stacked bars; all data then one block per sample.
Fast/Slow - AttributeThe same composition grouped by emotion.
Stats - Within SamplePer sample: Table 1 (emotions in columns) n, Mean, SD, SE, CI lower, CI upper and post-hoc letters; Table 2 the pairwise comparison matrix (* marks significance); Table 3 the fast/slow Positive/Negative responses with post-hoc lettering. Repeats for each sample.
Stats - Within AttributeThe mirror analysis, repeating the three tables for each emotion (samples in columns).
Nudge vs DisruptClassifies each stimulus (or sample × attribute cell) as Nudge / Nudge & Disrupt / Disrupt / Weak from its Fast and Slow shares. Thresholds are adjustable; this sheet is deselected by default in the report options.
Descriptive Splits - By SampleTable 1 shows the base n; a further table gives the fast/slow breakdown, mean and post-hoc letters per sample across the demographic subgroups, with a score-means graph.
Descriptive Splits - By AttributeThe same split organised by emotion.


How do I read the results?

Calibration summary

The Calibration sheet reports a Status Summary counting panelists as OK (below the max time) or Max time reached (≥ 6,000 ms by default), and a Distribution of Calibration Thresholds plotted in 500 ms intervals so you can see the spread of thresholds across the panel.


Zone colours on the heat-maps

Mean-score views are colour-banded so the whole matrix can be read at a glance:

ZoneMean implicit score
Strong Positivemean ≥ 75
Positive50 to 74
Negative25 to 49
Strong Negativemean < 25


Response composition (Fast / Slow breakdown)

The breakdown sheets split each stimulus into its four response types. Reading the composition, not just the mean, tells you whether a middling score comes from broad indifference or from a genuine split between fast acceptance and slow rejection.


Image selections

The Comment Questions sheet holds the open-end verbatims and the image each panelist chose. The Image Library ranks those images by Times Selected (with a % share and a tie-broken RANK order) and surfaces a representative verbatim of more than ten words for each, plus the top emotion per sample via INDEX/MATCH.


Nudge vs. Disrupt

Each stimulus (or sample × attribute cell) is classified by how its Positive or Negative (depending on selection made) responses split between the fast and slow routes. The thresholds are adjustable and the sheet is off by default in the report options:

MechanismRuleRead
NudgeFast ≥ 45% and Slow < 25%Instinctive appeal: reinforce it.
Nudge & DisruptFast ≥ 30% and Slow ≥ 25%Both instinctive and reflective pull.
DisruptFast < 30% and Slow ≥ 25%Works on reflection: needs a reason to believe.
Weakotherwise (low fast + low slow)Low pull on either route.


Statistical analysis

The statistical sheets carry a sample breakdown and an attribute breakdown. Within each, Table 1 gives n, Mean, SD, SE and the 95% CI lower/upper with post-hoc letters; Table 2 is the pairwise comparison matrix where * marks significance; and Table 3 covers the fast/slow Positive/Negative responses with post-hoc lettering. The three tables repeat for every sample (or attribute). Overlapping confidence intervals, or a shared post-hoc letter, are the first check before calling any pair different.


Descriptive Splits

The Descriptive Splits sheets (by sample and by attribute) show the panelist demographics: one table gives the base n, another the fast/slow breakdown and mean implicit score by subgroup with post-hoc letters, plus a score-means graph.