Choice Overload: Why Fewer Options Lead to More Sales

24 jams, 6 jams, and the death of "more is better"

In 2000, psychologists Sheena Iyengar of Columbia University and Mark Lepper of Stanford set up a tasting booth at an upscale grocery store in Menlo Park, California. On some days, they displayed 24 varieties of Wilkin & Sons jam. On other days, just 6. Then they watched what happened.

The large display attracted more attention. 60% of shoppers stopped at the 24-jam table, compared to 40% at the 6-jam table. More options drew more eyeballs. So far, so intuitive.

But here's where it gets uncomfortable. Of the shoppers who stopped at the 24-jam display, only 3% purchased a jar. At the 6-jam display, 30% bought one. Ten times more purchases from fewer options. And the customers who bought from the smaller display reported higher satisfaction with their choice.

More variety attracted browsers. Less variety created buyers.

Iyengar and Lepper called it choice overload, and it challenged a core assumption of consumer economics: that more options are always better. They weren't the first to notice it, but they were the first to quantify it this cleanly. Two decades later, the jam study is still one of the most cited experiments in behavioral economics, and it applies well beyond grocery store displays.

The paradox of choice: why more options make us miserable

In 2004, psychologist Barry Schwartz pulled the research together in a book called The Paradox of Choice: Why More Is Less. His central argument: the explosion of options in modern life doesn't liberate us. It paralyzes us.

Schwartz identified two types of decision makers. Maximizers try to find the absolute best option. They compare exhaustively, research endlessly, and often end up less satisfied because they can't stop wondering if something better existed. Satisficers set a threshold for "good enough" and stop searching once they find it. They decide faster and feel better about their decisions.

The problem with abundant choice is that it pushes everyone toward maximizing behavior. When you're choosing between 3 options, satisficing is easy. When you're choosing between 30, the nagging feeling that you missed the best one is hard to suppress. Schwartz argues that this drives analysis paralysis (inability to decide), decision fatigue (deteriorating judgment after too many choices), and anticipated regret (worrying about the wrong choice before you've even made one).

The mechanism underneath all of this is opportunity cost. Every option you don't choose is a potential benefit you're giving up. With 3 options, you're giving up 2. With 30, you're giving up 29. The emotional weight of those phantom alternatives grows with every option added.

For marketers, the takeaway is blunt: every additional option you present to a potential customer doesn't just add value. It adds cognitive cost. Past a certain threshold, the cost wins.

Hick's Law: the math behind decision paralysis

The relationship between options and decision time was formalized decades before the jam study. In 1952, British psychologist William Edmund Hick published research showing that the time it takes to make a decision increases logarithmically with the number of choices. The following year, American psychologist Ray Hyman independently confirmed and extended the finding. Their combined work became what's now called the Hick-Hyman Law.

In practice, going from 2 options to 4 roughly doubles decision time, but going from 10 to 20 doesn't hit as hard. The steepest increase is at the low end. Adding a fourth pricing tier to your page creates more friction than you'd expect.

But Hick's Law describes decision time, not decision quality or likelihood. The jam study added the missing piece: past a certain point, the increased decision time doesn't just slow people down. It makes them leave. The choice becomes so cognitively expensive that not choosing is the easiest option.

This matters for conversion. Every extra second a visitor spends trying to figure out which plan to choose, which testimonial to read, or which feature to care about is a second closer to them hitting the back button. Hick's Law tells you the friction is measurable. The jam study tells you the result is abandonment.

The Scheibehenne challenge: when does choice overload actually happen?

In 2010, Benjamin Scheibehenne, Rainer Greifeneder, and Peter Todd published a meta-analysis in the Journal of Consumer Research that complicated the picture. They analyzed 63 conditions from 50 experiments (N = 5,036) and found a mean effect size of virtually zero. Some studies found strong choice overload effects. Others found the opposite. The average washed out.

I think this is important to acknowledge, because the jam study gets cited as if it's an iron law of human behavior. It's not. Context matters a lot.

The meta-analysis identified several moderating factors. Choice overload is more likely when:

• The options are complex and hard to compare (enterprise software vs. flavors of jam)
• The chooser has no clear preference going in (browsing vs. targeted shopping)
• The stakes feel high (annual subscription vs. impulse buy)
• There's no categorization to help filter options

When options are simple, preferences are clear, and good filtering exists, more options can actually help. But when options are complex, preferences are fuzzy, and the buyer has to sort through everything on their own, choice overload hits hard.

Here's the thing, though: most SaaS pricing pages, testimonial displays, and feature comparisons check all those boxes. The options are complex. The visitor often doesn't have a clear preference. The stakes feel real. And most pages do a terrible job of filtering. That's why the jam study's lesson, while not universal, applies directly to most online buying contexts.

Your pricing page is a jam display

The research on SaaS pricing lines up with the jam study almost perfectly.

68% of high-growth SaaS companies use some form of tiered pricing, with an industry average of about 3.5 tiers. A ConversionXL study found that moving from four tiers to three increased conversion rates by an average of 27% across tested companies.

Intercom learned this the hard way. After years of adding pricing tiers for different segments, they noticed conversion rates slipping. When they consolidated from six plans to three, they saw a 17% increase in conversions. HubSpot's benchmark data tells a similar story: companies with three pricing tiers have conversion rates roughly 40% higher than those with five or more.

The decision speed data tells the same story. Customers spend 42% less time on pricing decisions when they see three well-differentiated options versus five or more tiers. Less deliberation, faster commitment. And according to Price Intelligently's analysis of 512 SaaS companies, those with three tiers had 30% higher average revenue per user (ARPU) than those with four or more.

The jam study in miniature. Fewer options, more purchases.

If your pricing page has more than three or four options, you're probably losing conversions. Not because your options are bad, but because the act of choosing between them costs too much mental energy. Cut the options. Make the remaining ones clearly different from each other. And highlight a recommended tier to give the undecided a default. (For more on how that first number shapes every comparison that follows, see The Anchoring Effect: How Your First Price Changes Everything.)

50 testimonials can overwhelm. 3 picked ones can convert.

The same thing happens with social proof.

I've seen landing pages with 50 testimonials in a scrolling wall. The thinking is obvious: volume signals credibility. And it does, to a point. But there's a threshold where volume stops building trust and starts creating the same paralysis the jam study measured.

When a visitor sees 50 testimonials, they face a decision: which ones do I read? Do I scroll through all of them? Do I look for someone in my industry? The cognitive cost of parsing that wall is real, and most visitors resolve it the same way shoppers resolved the 24-jam display. They don't engage. They glance, get a vague impression, and move on.

Now compare that to 3-5 carefully picked testimonials, each representing a different buyer persona or use case. The visitor doesn't need to choose which to read. They just read all of them. The cognitive cost is low, the signal-to-noise ratio is high, and because each testimonial does specific work (answering a specific objection, representing a specific industry, showing a specific outcome), the combined impact beats a wall of undifferentiated praise.

This doesn't mean you should only collect 5 testimonials. Collect as many as you can. The Spiegel Research Center at Northwestern found that purchase likelihood for a product with five reviews is 270% greater than for a product with zero reviews. Volume in your collection matters. (If you're starting from zero, see Zero to One: The Hardest Part of Social Proof Is Getting Started.)

But what you display should be curated. Think of your testimonial collection as inventory and your display as merchandising. A store doesn't put every item on the front table. It puts the best sellers at eye level and organizes the rest for customers who want to browse deeper. For guidance on designing that display, see How to Build a Testimonial Wall of Love (That Doesn't Look Fake).

PraiseLane is built around this idea. Collect testimonials continuously from every happy customer, then moderate and curate from your dashboard. Your embed widget displays the approved selection, not the entire archive. You keep the volume in your collection while the display stays focused.

This applies everywhere, not just pricing pages

Choice overload isn't limited to jam, pricing, or testimonials. It shows up at every decision point you ask a customer to navigate.

Feature pages are a common offender. If you list 47 features in a flat grid, you've built a jam display. Group them into 3-4 categories. Lead with the features that matter most to each segment.

Call-to-action buttons, too. One page, one primary action. A page with "Start Free Trial," "Book a Demo," "Download the Guide," and "Watch the Webinar" is four jams too many. Pick the one that matters most for this page's traffic source and make it the obvious next step.

Onboarding flows are another place this bites. Don't present every feature on day one. Reveal options as the user needs them. The IKEA effect research shows users value products more when they invest effort into them, but that effort needs to be sequenced, not dumped in their lap.

And email sequences: one email, one ask. Emails with three different CTAs convert worse than emails with one. The reader shouldn't have to decide what to click.

The thread running through all of this: every decision you eliminate for the customer is one less reason for them to leave. Schwartz, Iyengar, Hick, and two decades of follow-up research all land in the same place. Your job isn't to give customers every possible option. It's to reduce the number of decisions standing between them and the outcome they want.

Iyengar's shoppers didn't want 24 jams. They wanted one good jar. Make it easy to find, and they'll buy it.

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Sources:

• Iyengar, S. S. & Lepper, M. R. (2000). "When Choice Is Demotivating: Can One Desire Too Much of a Good Thing?" Journal of Personality and Social Psychology, 79(6), 995-1006.
• Scheibehenne, B., Greifeneder, R., & Todd, P. M. (2010). "Can There Ever Be Too Many Options? A Meta-Analytic Review of Choice Overload." Journal of Consumer Research, 37(3), 409-425.
• Schwartz, B. (2004). "The Paradox of Choice: Why More Is Less." HarperCollins.
• Hick, W. E. (1952). "On the Rate of Gain of Information." Quarterly Journal of Experimental Psychology, 4(1), 11-26.
• Hyman, R. (1953). "Stimulus Information as a Determinant of Reaction Time." Journal of Experimental Psychology, 45(3), 188-196.
• Spiegel Research Center, Northwestern University (2017). "How Online Reviews Influence Sales."
• SaaStock (2025). "The SaaS Pricing Trap: When Too Many Tiers Kill Conversions."
• Chernev, A., Bockenholt, U., & Goodman, J. (2015). "Choice Overload: A Conceptual Review and Meta-Analysis." Journal of Consumer Psychology, 25(2), 333-358.