A table of jam can look like an unlikely place to learn something about buying.

Yet a supermarket tasting experiment became one of the most familiar stories in consumer psychology. Offer shoppers a large selection, the story goes, and they may become interested without buying. Offer fewer options, and choosing becomes easier.

It is a memorable idea because it reverses an ordinary assumption: surely having more to choose from must be better.

But the research story does not end at the tasting table. Later evidence made the conclusion more complicated. The useful lesson is not that every business should shrink its range. It is that attracting attention, helping someone decide and completing a purchase are different things.

For customers, that distinction can explain why browsing sometimes feels enjoyable while choosing feels difficult. For businesses, it suggests a more helpful question than “How do we make people buy?”: “What do people still need to understand before they can make a suitable decision?”

The experiment that made choice famous

In a paper published in 2000, Sheena Iyengar and Mark Lepper reported three studies examining limited and extensive choice. One took place at Draeger’s supermarket in Menlo Park, California. Shoppers encountered a tasting display with either six or twenty-four jam varieties. The researchers examined attraction to the display and subsequent purchasing, rather than treating stopping to browse as equivalent to buying.

The paper reported a contrast between the appeal of the larger display and purchasing under the smaller selection. The experimental choices and setting matter: this was a particular field study, not a measurement of every shop or product category. The original paper, When Choice Is Demotivating, describes the design and results.

That distinction between attraction and action is the most durable part of the story. A display can make people pause without helping them finish their decision.

A visitor looking at a website, a shopper examining a shelf and someone asking an initial question have taken different steps from someone placing an order. Each step can be useful evidence. None should silently become proof of the next one.

Why the neat lesson became too neat

The experiment is often turned into a simple instruction: reduce the number of options and sales will rise.

That instruction goes further than the evidence. It assumes that the same relationship will hold across different products, customers and situations. It also assumes that the main obstacle is the number of alternatives, rather than the way they are explained.

Imagine two shoppers facing the same shelf. One knows exactly which flavour they want. The other has never tried the range and cannot tell how the options differ. The selection may be useful to the first and difficult for the second.

These are illustrative situations, not additional findings from the jam experiment. Their purpose is to show why a shopping decision needs context.

Reducing a range could help someone who has no useful way to compare it. It could also remove the specific option another customer came to find.

That is why “more is better” and “less is better” are both unreliable as universal rules. The real question is whether the available choice helps the person achieve what they came to do.

Later research changed the question

In 2010, Benjamin Scheibehenne, Rainer Greifeneder and Peter Todd published a meta-analysis bringing together 63 conditions from 50 experiments, involving 5,036 participants. They found a mean effect close to zero, with considerable variation between studies. Their review did not establish that extensive choice always helps or always harms. The published meta-analysis explains why the overall evidence did not support a simple universal effect.

A later review by Alexander Chernev, Ulf Böckenholt and Joseph Goodman examined circumstances that could moderate choice overload. Its framework identified choice-set complexity, decision-task difficulty, uncertainty about preferences and the decision goal as important factors. Their conceptual review and meta-analysis shifts attention from counting options alone towards understanding the decision.

The two reviews should not be flattened into another absolute statement. Nor should the later work be described as proving that every large range needs cutting down.

The more interesting development is that the question became conditional. What kind of choice? For whom? With what information? In pursuit of what goal?

Those questions are less catchy than the famous jam story. They are also more useful when planning an actual customer experience.

Sometimes the problem is not quantity but comparison

Consider a hypothetical customer choosing a sign. A long list of materials may look comprehensive. It may also leave them unsure which options suit an indoor display, an outdoor location or a particular fixing arrangement.

Simply deleting half the list would not necessarily answer the question. Grouping the options by intended use could be more helpful.

The same applies to clothing. Someone may need a garment for regular work, a team event or a one-off occasion. Showing fewer garments is not automatically the solution if the remaining choices still lack useful distinctions.

These examples are Time for Designs’ practical interpretation, not evidence of measured conversion improvements.

The principle is to make differences intelligible. Customers should not have to understand a supplier’s catalogue or a producer’s internal process before they can identify the relevant category.

A useful comparison explains the differences that matter to the job. It does not overwhelm the reader with every attribute simply because the information is available.

Knowing what you want changes the value of choice

A customer with a clear requirement may welcome detail. Someone replacing a familiar item may need a particular specification. A buyer working from an approved design may be looking for confirmation, not inspiration.

For that person, hiding choices or forcing a recommendation can create unnecessary work.

A first-time customer may need a different starting point. They may know the outcome they want but not the product name, material or format that would achieve it.

A helpful service can accommodate both. It can offer a direct route for a known requirement and a simpler explanation for someone who needs guidance.

That does not require elaborate interaction. Clear headings, meaningful categories and an obvious route to a real person can be sufficient.

The aim is not to make everyone follow the same path. It is to avoid making people do unnecessary work before they can reach the information or help they need.

Browsing, intention and buying are not the same measure

One reason buying psychology becomes misleading is that different outcomes are discussed as though they were interchangeable.

Looking at a product is not the same as wanting it. Saying it looks appealing is not the same as choosing it. Asking for information is not the same as approving a quotation.

Likewise, research that measures stated purchase intention does not automatically establish actual purchasing behaviour. The outcome recorded in a study should remain attached to its conclusion.

The jam study is useful partly because its field experiment distinguished attraction to the display from purchasing. That does not make it universally applicable; it does make the distinction worth preserving.

Businesses should apply the same discipline to their own evidence. More page views can mean that an article reached more people. Longer visits can mean interest, but they can also mean difficulty finding an answer. An enquiry may progress—or reveal that the offer was not suitable.

None of those observations should be dismissed. They should be described accurately rather than upgraded into sales success.

Uncertainty is not something to exploit

A discussion of consumer psychology can easily become a list of tricks for pushing people towards a decision.

That is not the lesson we take from this research. If someone is uncertain, the useful response is to identify what remains unclear—not to add artificial pressure.

A genuine deadline can be relevant information. An invented countdown is something else. Limited availability should be communicated only when it is real and relevant, not used as a generic decoration intended to rush the reader.

Similarly, a recommendation should explain why an option suits the requirement. It should not merely steer everyone towards the same choice while pretending to provide personal advice.

Helping a customer decide includes recognising when they need more information or when an option does not fit.

For a service business, a suitable decision is more valuable than a hurried one that creates misunderstanding, rework or disappointment.

A useful brief begins before the product choice

When someone contacts a print, signage or clothing business, the most helpful information may concern the job rather than the item.

What is it for? Where will it be used? How many are needed? Is there a fixed event date? Is the artwork ready, or does it need work?

These questions can reveal which choices are relevant and which do not need to occupy the customer’s attention.

They also leave room for the customer’s preferences. A person may have a visual idea, a practical constraint or a previous item they want to match. Advice should take that information seriously.

The process is not about removing choice from the customer. It is about making the remaining choices easier to discuss.

A clear brief can therefore be a form of reassurance. It shows what information is needed, what has already been understood and what still requires confirmation.

For a practical starting point, see how to turn a rough idea into a useful design brief.

How to review a page without guessing at people’s minds

A business does not need to claim access to hidden motives to improve an unclear page.

Start with observable tasks. Can someone identify what is offered? Can they find the differences between relevant options? Can they understand what information to send? Can they reach help without searching the entire page?

Then observe where people hesitate or ask repeated questions. Those moments may suggest missing information, unfamiliar terminology or a choice that needs a clearer explanation.

A revision can address one such problem without changing everything at once. That makes later evidence easier to interpret.

For example, a page might explain options by use before presenting technical details. Another might make the quotation requirements clearer. Neither change guarantees an increase in orders. Each has an identifiable customer problem to solve.

That is more defensible than assuming that six choices must work better than twenty-four because an experiment once used those numbers.

The customer’s side of the decision

For shoppers, the practical lesson is equally straightforward: a large range does not mean you must compare everything.

Begin with the requirement. Decide what matters for this particular purchase, and ask for help identifying the differences that affect it.

If several options look similar, ask what would make one more suitable than another. If a recommendation is offered, ask what it is based on. If important information remains missing, taking more time can be reasonable.

These are practical suggestions, not a promise that a decision method will eliminate every uncertainty.

The purpose is to turn an undifferentiated collection into a manageable question: which option fits this need?

The lesson is not “sell less choice”

The tasting-table story survives because it is surprising. Its familiar retelling also shows how easily a bounded finding can become a marketing rule.

The later research asks us to keep the context. Different decisions create different difficulties. A large selection can be useful, while a small selection can still be confusing.

Our Time for Designs interpretation is to preserve meaningful choice and improve the guidance around it.

Explain what suits whom. Make important differences visible. Be honest about what still needs checking. Give customers a straightforward way to ask for help.

We do not need a story about dopamine, mind-reading software or automatic fear of missing out to justify those decisions.

The useful objective is simpler: help someone understand the offer well enough to make a suitable choice.

Sources and research limits

These studies do not establish a universal optimum number of products, guarantee sales improvements or measure Time for Designs’ customers. The practical examples and recommendations above are our interpretation, not additional experimental results.