<b>The jam study, revisited: why "fewer options" advice is shakier than you think</b>

<b>The jam study, revisited: why "fewer options" advice is shakier than you think</b>

Deep dive: The jam study — 24 jams drew more samplers but 6 jams drove ~10x more purchases (Iyengar & Lepper, 2000) — is the bedrock citation for "reduce choices on your lander." It's worth knowing the finding doesn't replicate cleanly.

A 2010 meta-analysis (Scheibehenne, Greifeneder, Todd) pooled 50 choice-overload experiments and found a mean effect near zero, with results swinging both ways. Choice overload is real but <i>conditional</i> — it appears mainly when options are hard to evaluate, the person lacks clear preferences, and there's no good default. When choices are easy to compare or the buyer knows what they want, more options can <i>help</i>.

The mechanism is preference construction. Overload bites when a visitor has to <i>build</i> a preference on the spot from confusing options — that's high cognitive load and high decision risk, so they defer (i.e., bounce). It doesn't bite when the page does the comparison work for them.

This sharpens the lander implication. The lever isn't raw option count — it's whether you've made the choice <i>evaluable</i>. Three plans with a highlighted "recommended" default and a clear comparison can outperform a single forced option, because you've removed the construction cost while preserving fit. "One call-to-action" is good advice for a cold-traffic lander, but the real principle is: reduce the work of choosing, which sometimes means a smart default rather than fewer things.

TL;DR:
— The choice-overload effect is conditional and barely replicates in aggregate (~zero mean effect)
— It bites when options are hard to evaluate and there's no default — not just when there are many
— Lower the cost of choosing (defaults, comparisons), don't reflexively minimize options