Explicit and incidental anchoring: what replication studies found

An anchoring effect occurs when a number influences a later numerical judgment. But the way the number enters the situation matters. Asking someone whether a quantity is above or below a suggested value is a different intervention from putting an unrelated number in the background.

Explicit numerical anchoring has strong replication evidence in studied estimation tasks. Claims that incidental numbers reliably change consumers' price estimates have a less secure record. Treating both as one psychological trick hides the distinction that matters when you try to use the research. Many Labs, 2014; Shanks and colleagues, 2020.

The number in the question

Consider a hypothetical estimate: how long is a river you know little about? Before asking for your best answer, one version of the question asks whether the river is longer or shorter than 500 kilometers. Another asks whether it is longer or shorter than 5,000 kilometers. The suggested number is an explicit reference point. The research question is whether the two groups then give different estimates.

The example shows how an anchoring task is built; the numbers are not results from a study. What matters is that the person has to consider the anchor while making the judgment. It is not just a number that happened to be visible somewhere else.

The Many Labs project tested four explicit numerical anchoring questions based on earlier work by Karen Jacowitz and Daniel Kahneman. The effects appeared consistently across the participating samples. The project also noted design and effect-size differences between original and replication studies, so the result does not show that every original magnitude was reproduced exactly. Klein and colleagues, 2014.

That is evidence for a recognizable procedure and outcome: a numerical comparison followed by an estimate. It does not yet show what happens to sales, negotiation outcomes or long-term behavior.

The number in the background

A more surprising claim is that an incidental number can influence what a consumer thinks something is worth. For example, a number in a restaurant's name might supposedly shift people's estimates of what a meal costs, even though the number says nothing useful about the food.

David Shanks and colleagues tested incidental environmental anchors in three studies and did not find consistent effects on price estimates. In the second and third studies they also included standard numerical anchoring questions, for which they observed clear effects. Those standard questions asked about general-knowledge quantities, such as the population of Chicago, not prices, and the authors note that this rules out a direct comparison of the two effects' sizes. This was not a perfectly matched test showing that relevance alone explains the difference. Shanks, Barbieri-Hermitte and Vadillo, 2020.

The useful conclusion is narrower: under conditions that produced standard anchoring, these incidental-number procedures did not reliably produce the claimed consumer effect. The paper leaves open whether other circumstances could produce incidental anchoring. A null result in these studies is not proof that every unrelated number is powerless.

Why the distinction matters in practice

Imagine you are redesigning a pricing page. One proposal gives visitors a clear comparison with a relevant alternative. Another adds a large unrelated number because “anchoring works.” These proposals share a word, but they do not share an evidential foundation.

Even a relevant comparison introduces questions beyond the classic estimation tasks. Is the comparison accurate? Do visitors interpret it as useful information or as a sales tactic? Does it change the choice they make, or only an answer on a rating scale? Does it improve the decision from the customer's point of view?

The anchoring studies discussed here cannot answer all of those questions. To evaluate a pricing change, measure what it actually changes against an appropriate alternative. Do not use a well-replicated estimate shift as a substitute for evidence about purchases or customer benefit.

A field experiment on willingness to pay shows why. Tongzhe Li and colleagues asked adults to bid on gardening products using a slider whose starting price was set at random. In the original study, raising the starting price from the lowest anchor to the highest increased valuations by 31 percent. An overlapping team then ran a replication with 621 adults and far more statistical power. The estimated effect fell to 3.4 percent, with a 95 percent confidence interval from −3.4 to 10 percent, which rules out an effect as large as the original. Li, Weigel, Ferraro and Messer, 2025.

That replication does not show that numbers never move prices. It shows how a striking price result from an underpowered study can shrink sharply when tested again with enough participants, even in a similar setting run partly by the same researchers.

This is a general lesson for applied behavioral science: keep the procedure attached to the finding. “A number influenced an estimate in this task” is a testable claim. “Numbers can control decisions” has discarded the conditions that made the result meaningful.

What holds up

Explicit numerical anchors deserve a place in an account of how people make estimates. A meta-analysis by Dan Schley and Evan Weingarten, covering 2,601 effect sizes from five decades of anchoring research, supports the split this review describes. It found a large average effect when people compared a number before making a judgment, and that effect remained large after adjustment for publication bias. It found reduced or null effects for incidental anchors, for anchors that were random numbers and when incentives were present. Schley and Weingarten, 2026.

The replication record gives more support to the studied explicit-estimation procedures than to the particular incidental consumer-price claims tested here, or to large effects on what people will pay. It does not support one universal effectiveness rating for everything called anchoring.

Read the anchoring definition for the basic concept. The evidence review of nudges at scale follows the next practical question: how much should a research finding lead you to expect from a real intervention?

The number in the question

The number in the background

Why the distinction matters in practice

What holds up

Key sources