The bandwagon effect is the tendency to adopt a product, belief or behavior because many other people already have.
In marketing, it is why "Best Seller" labels, "1,200 bought this week" counters and "most popular" plan tags can raise conversions: popularity works as a shortcut for quality.
In our database it often helps, but not always, and badly placed or weak popularity signals have lost tests.
Economist Harvey Leibenstein gave the term its formal meaning in 1950, defining the bandwagon effect as "the extent to which the demand for a commodity is increased due to the fact that others are also consuming the same commodity" (Leibenstein, Quarterly Journal of Economics).
The same paper described the opposite, the snob effect, where demand falls because too many others are buying. Both matter for stores.
This page covers the theory: why people follow the crowd and when that instinct backfires.
For the practical playbook of reviews, testimonials and placements, see our social proof guide.
The bandwagon effect in marketing: what research and A/B tests show
The bandwagon effect is one form of social proof, one of the persuasion levers in Cialdini's principles.
It sits in the wider family of cognitive biases that let people decide quickly with incomplete information.
Why people follow the crowd
Two motives drive it, and they call for different tactics.
The first is social: Leibenstein described buyers who want to get into "the swim of things" and be "one of the boys."
The second is informational: when you can't judge quality yourself, what others chose is evidence.
The second motive is the one most store tests tap, because a shopper on a product page is short on information, not on friends.
That distinction explains a lot of results. A crowd signal adds the most when the shopper knows little, such as a first visit, an unfamiliar brand or a new product.
It adds the least when the shopper already trusts the store or has done their research.
What the research shows
Conformity is real and replicable. In Solomon Asch's line-judgment experiments from the 1950s, real participants gave the wrong answer on 36.8% of the critical trials where the group answered wrongly.
A 2023 replication with 210 participants found a 33% error rate, falling to 25% when people were paid for correct answers (Franzen and Mader, PLOS ONE).
This is one of the few classic social psychology findings that has held up well.
Popularity creates winners, not just reflects them. In the MusicLab experiment, 14,341 people downloaded unknown songs either with or without seeing earlier listeners' download counts.
Showing the counts made success more unequal and less predictable.
The best songs rarely did poorly and the worst rarely did well, but anything in between was possible (Salganik, Dodds and Watts, Science, 2006).
Early ratings snowball. In a randomized experiment on a social news site, a single fake upvote made the next rating 32% more likely to be positive and raised final ratings by 25% on average.
Fake downvotes did not snowball the same way: users corrected them (Muchnik, Aral and Taylor, Science, 2013).
The research mostly measures choices made in labs or on free platforms.
Buying something costs money, and the size of these effects doesn't carry over directly to a checkout.
That gap is why the tests below matter.
What A/B tests show
Stores apply the bandwagon effect through a few repeatable formats.
Here is how they have performed in tests from our database.
| Popularity signal | Test | Result | Ran by |
|---|---|---|---|
| "Best Seller" label above the product title | PDP label test | +11.59% conversion rate, +12.99% revenue per visitor | Dave Diederen |
| Units bought today vs. times viewed | NYX product page | Purchases line: +43% buy-button CTR, transaction rate doubled. Views line: +32% CTR, +33% transaction rate | NYX Professional Makeup |
| "Popular" badge on a subscription frequency | Subscription badge test | +14.81% conversion rate, +42.98% autoship selection | Blend Commerce |
| Recent product views under the reviews | Decathlon UK | +2.4% transactions across 400 product pages | Decathlon UK |
| Popularity messages tuned per market | Hunter Boots | +9% conversion rate (UK), +6% (US) | Conversio |
| Recent-buyer count instead of an empty review widget | Branch Furniture | +4.3% conversion rate | Visually |
Two patterns stand out. First, purchase signals tend to beat attention signals: in the NYX test, "bought today" outperformed "viewed" on the same page.
A purchase is a stronger cue because someone paid.
Second, the effect is stronger when the shopper has less to go on.
Decathlon UK saw the view-count line work better on items under GBP 10 than on expensive ones.
Branch Furniture used a recent-buyer count on a new product that had few or no reviews, where the crowd signal filled a gap.
Some of these are vendor case studies (the Visually and AB Tasty-based ones) without published sample sizes.
Treat the direction as useful and the exact percentage as uncertain.
@DaveDiederen
Blend Commerce
VisuallyThe bandwagon effect in SaaS and lead generation
Outside ecommerce, the most common format is the "most popular" tag on a pricing plan.
It points buyers toward one option, often alongside the decoy effect.
ArchiveSocial's pricing page redesign, run by VWO Services, marked the mid-priced plan as most popular and lifted lead submissions 64.76%.
The redesign also simplified plans and the CTA, so the tag can't take sole credit.
Herd mentality marketing: when following the crowd works and when it backfires
Herd mentality marketing goes beyond "this is popular" to "everyone like you is doing this, so you should too."
Economists explain why it works with the idea of an information cascade: once enough people have chosen something, a new person can rationally ignore their own judgment and copy the crowd (Bikhchandani, Hirshleifer and Welch, Journal of Political Economy, 1992).
The same model explains why cascades are fragile and why fads can collapse quickly.
That fragility shows up in testing. The herd only helps when the signal looks big, credible and relevant to the shopper.
Signal too weak or too common
Leibenstein's snob effect has a practical version: if every product says "Best Seller," none of them stand out.
Dave Diederen's team first put a Bestseller badge on 3-4 products on a collection page and conversion rate fell 4.72%.
Badging only the single top product won: +6.03% conversion rate and +8.89% revenue per visitor.
Small numbers can also work against you. Bag Servant replaced a badge showing 4,000+ Twitter followers with a hard-to-win business award and saw +72.05% visits to partner retailer sites.
FietsPunt added a Facebook widget showing over 1,000 likes to product pages and measured no meaningful change.
Decathlon UK only showed its view-count line once a product passed 20 views, which avoided showing tiny crowds.
Wrong placement or wrong priority
The same signal can win in one spot and lose in another.
Clean Commit tested "New" and "Best Seller" badges over the main product image on 20,113 visitors and got -0.5% conversion rate and -9.1% revenue per visitor, with a 46.9% probability of beating control, so no clear winner either way.
Compare that with the label above the title in the table above.
Popularity can also crowd out the reason to buy.
Dave Diederen tested a product page that focused less on social proof and more on benefits: +35.3% conversion rate and +43.1% revenue per visitor.
A crowd tells shoppers a product is safe.
It doesn't tell them why it fits their problem.
Telling people that everyone does the wrong thing
Herd messages can push behavior in the direction you are trying to stop.
At Arizona's Petrified Forest National Park, a sign saying many past visitors had removed petrified wood led to 7.92% of marked pieces being stolen.
A sign asking visitors not to remove the wood led to 1.67% (Cialdini et al., Social Influence, 2006).
For a store, "most shoppers abandon their cart" is a norm you don't want to advertise.
Faking the crowd
Invented purchase counts, "23 people are viewing this" messages driven by random numbers, and seeded reviews are deception, not social proof.
They also carry legal risk under consumer protection rules; our social proof guide covers the FTC's fake review rule.
We cover these tactics on our dark patterns page.
Every counter in the tests above was based on real data.
How to test the bandwagon effect on your site
- Use the strongest true signal you have. Purchases beat views, and a big round number of customers beats a modest follower count.
- Be selective. One best seller per collection page is a signal. Four is decoration.
- Place it where the decision happens. Near the title or the add-to-cart button, not buried in the image.
- Segment the results. New visitors, low-priced items and new products with few reviews are where a crowd signal has the most to add.
- Measure revenue, not just clicks. A badge can lift conversion on cheap items while pulling attention from higher-value ones.
Pair popularity with urgency carefully. Our page on scarcity and urgency covers when "selling fast" helps and when it creates anxiety.
You can browse more popularity tests on the bestseller badges and social proof element pages, or return to the full psychology section.
@DaveDiederen@DaveDiederen
Clean Commit