A familiar shopping session begins with one practical need and ends with twenty open tabs.
One product has better reviews. Another is cheaper. A third looks better but has vague dimensions. Two appear identical under different brand names. After enough comparison, the shopper is no longer deciding what fits—they are managing a small research project.
It is tempting to call this “too much choice.” The research suggests a more useful interpretation.
Choice overload is real, but not automatic
The classic paper “When Choice Is Demotivating” reported experiments in which a larger assortment could attract attention while a smaller assortment could make action easier.
Later research added important nuance. A meta-analysis of choice overload found no single effect that applies in every situation. The outcome depends on conditions: how difficult the comparison is, how much someone knows about the category, whether preferences are clear, and how the options are organized.
That distinction matters for product design.
The answer is not always fewer products. It is often better guidance through the products that exist.
Why online comparison becomes work
A long catalog creates several separate tasks:
- Define the category. What kind of product solves the actual problem?
- Choose the criteria. Which dimensions, materials, features, or tradeoffs matter?
- Remove weak matches. Which options are irrelevant, unavailable, repetitive, or poorly explained?
- Compare the survivors. Is a higher price buying something meaningful?
- Remember the reasoning. Why was one option saved and another rejected?
Most shopping interfaces are optimized for steps four and five. They assume the shopper already knows the category and criteria.
Amatok starts earlier
Amatok is being built as a place to start before you know exactly what to search for. You can begin with a feed, then respond naturally as you browse.
A useful discovery experience should recognize that these actions are not equivalent:
| Action | What it may tell us |
|---|---|
| Longer view | Curiosity or careful inspection |
| Like | Clear interest |
| Save | Something worth revisiting |
| Skip | A small hint that it was not right |
| “Not interested” (planned) | A clear preference not to see similar |
These actions may help make future recommendations more useful. They do not all affect what appears first today.
A shortlist should still contain surprise
Personalization can fail in two opposite directions:
- show too much, leaving the shopper to filter everything;
- show only familiar patterns, turning relevance into repetition.
Amatok’s intended feed keeps controlled exploration alongside personalization as a future design goal. That means a useful result may be adjacent to your established taste rather than an exact copy of something you already liked.
The aim is a working shortlist, not a closed bubble.
What this could change for shoppers
A calmer discovery process could help someone:
- identify a useful category before learning its vocabulary;
- spend less time repeating the same filters across stores;
- notice why a product feels relevant;
- preserve interesting options without deciding immediately;
- communicate “not this” as clearly as “more like this” (when the control is introduced).
Amatok will not remove the need to check price, seller reliability, specifications, delivery, and returns before buying. The aim is to make the path to a worthwhile candidate shorter and more personal.
If online shopping often feels like tab management, join early access and tell us where the work becomes frustrating.
Sources and further reading
- Iyengar and Lepper, “When Choice Is Demotivating: Can One Desire Too Much of a Good Thing?”, Journal of Personality and Social Psychology.
- Scheibehenne, Greifeneder, and Todd, “Can There Ever Be Too Many Options? A Meta-Analytic Review of Choice Overload”, Journal of Consumer Research.