---
title: "Packaging design testing"
url: "https://help.getdecode.io/en/article/packaging-design-testing"
language: "en"
last_updated: "2026-08-28T07:53:30.900Z"
---

# Packaging design testing

**Overview**

Packaging design testing helps you understand how a specific packaging design performs with real participants, before it goes to print or production. You can upload a digitally designed package or a photo of a physical one, digital designs tend to give the cleanest results, since the image quality is consistent and every element is clearly visible.

**How to run this in Decode**

Upload your packaging design as an image using a **Media block**, the same setup covered in *Set up a media block*. Enable **Eye Tracking** and **Facial Coding** to capture where attention goes on the pack itself, and how people respond emotionally while looking at it.

**Mark specific elements as AOIs**

Once your packaging image is uploaded, mark the individual elements you want to understand as separate AOIs, rather than only looking at the overall heatmap. For example, on a typical product package you might mark:

-   The **brand name or logo**, to see whether it's actually being noticed
-   The **core product visual**, such as the product itself or its main image
-   Any **key visual callouts**, for example, an image representing a specific ingredient or feature the packaging is built around
-   The **price**, if it's shown on the pack
-   The **tagline or headline text**

Marking these separately tells you not just that people looked at the package, but specifically which elements actually got noticed, and which ones were missed entirely.

**Comparing multiple designs**

If you're comparing multiple packaging directions, use **Group & Randomization** to set up a monadic design, so each participant evaluates one design independently, see *Sequential vs monadic design* for guidance on choosing between monadic and sequential setups for this kind of comparison.

Add follow-up questions after the image, such as Likert Scale or Multiple Choice, to capture stated reactions (appeal, clarity, purchase intent) alongside the behavioural attention and emotion data.

**What you'll learn from the results**

For each AOI you've marked, you'll see Time to Discover and Earned Attention, alongside emotion data (engagement, attention, and specific emotions) tracked while participants viewed the package. This tells you, for example, whether your brand name is being missed entirely, whether a key visual is drawing attention away from the price, or whether a tagline is going unnoticed. See *Pack heatmap interpretation* for how to read this data in full.

**What to do next**

To test how this design performs once it's actually placed on a shelf, see *Shelf visibility analysis*.