Why suggested tip amounts make you pay more: The psychology and the case studies

aakanksha singh
Sep 2
3 min read

Walk into a café, order a latte, and when the iPad swivels around, the screen flashes three tip options: 18%, 20%, and 25%.

You probably weren’t planning to tip that high, but suddenly 15% feels “cheap.” Pressing “no tip” feels worse.

This is not an accident. It is psychology by design.

The psychology behind the suggested tips:

Anchoring Effect: When customers are presented with percentages, those numbers become the new baseline for comparison. If the lowest option is 18%, the customer recalibrates. What used to feel generous now feels standard.

Social Norms: Suggested ranges act as subtle cues about what polite society expects. Going below them feels like breaking an unwritten rule.

Choice Architecture: The design of the tipping screen itself is a form of nudging. Pre-set buttons make higher tips easy, while typing a custom amount takes effort. Most people take the frictionless path.

Loss Aversion: Tipping below the suggested amount feels like taking something away from the staff, even if it is objectively acceptable. People are wired to avoid losses, so they round upward.

The evidence:

The impact of these small digital prompts is enormous:

New York City Taxis (2012–2013): When cabs introduced touchscreen payments with preset tips of 20%, 25%, and 30%, the average tip leapt from around 10% to 22%. Annual driver income increased by $144 million.
Stanford Graduate School of Business (2018): Suggested tips raised not only the average percentage but also the likelihood of tipping at all. However, defaults above 30% triggered resistance.
Uber and Uber Eats: When the app added prompts of 15%, 20%, and 25%, tipping rates nearly doubled compared to when users entered amounts freely.
Behavioural Insights Team (UK): Suggested donation levels at charity events consistently drove higher average contributions.

The principle is clear: anchors shift behaviour across industries, from taxis to tech to charity drives.

Why it works:

People unconsciously anchor on the suggested numbers and adjust only slightly.
Pre-set ranges signal what “most people” do, creating pressure to conform.
Choosing a lower option can damage self-image; no one wants to feel like the stingy one.
Effort matters. A quick button tap is easier than manual entry, and ease often equals more money.

How businesses use it:

Restaurants & Hospitality: Payment tablets (Square, Toast, Clover) typically use 18–20–25% as the default range, which boosts staff earnings compared to lower anchors.
Ride-Hailing & Delivery Apps: Prompts highlight typical behaviour (“Most people tip 20%”), framing generosity as the norm.
Charities: Suggested donation levels increase contributions far more effectively than blank entry boxes.
Subscription and SaaS Pricing: The same principle applies when a “recommended” or “popular” plan is highlighted; customers often gravitate upward.

The risks and backlash:

Not all nudges are welcome.

Tipflation: As tipping prompts spread to counter service and coffee shops, consumers feel pressured. A 2023 survey showed that 66% of Americans believe tipping culture has gone too far.
Overreach: If suggestions exceed 30% or higher, customers may push back, skip tipping altogether, or resent the business.
Context and Culture: In fine dining, high tips are expected. At a self-service counter, they feel intrusive. In Europe, suggested tips are unusual; in Japan, tipping is taboo.

What to measure:

Businesses should treat tipping prompts like an experiment, not a rule. The key is balancing staff earnings with customer trust.

Metrics to track include:

Average tip percentage.
Tip participation rate (how many people leave tips).
Employee earnings and turnover.
Customer satisfaction or complaint rates.

Case Studies

NYC Yellow Cabs: A simple interface change increased driver pay by $144 million annually.
Starbucks (US, 2022): Introduced card-based tipping prompts of $1, $2, or custom. Consumers were divided; some welcomed the option, others felt pressured.
Square POS: Common in coffee shops, Square helped normalise tipping prompts across casual dining. This boosted staff income but also fuelled “tip fatigue” debates.

The takeaway:

Suggested tip amounts work because they tap into deep-seated biases. Anchors shift our sense of what is fair, norms shape behaviour, and the easiest option usually wins. For businesses, this can be a powerful lever for staff income and loyalty. For consumers, it is a reminder that our spending decisions are rarely as rational as we think.

The line between smart nudging and customer resentment is thin. The best businesses suggest tips that feel like social norms, not like coercion.

If you found reading this article a bit boring, here is the link to my YouTube video on the same topic, where you can listen and watch me as well:https://youtu.be/RH0ts0nXYH0?si=-Wkrl0MBKfGd1iL5

Cheers!

Akanksha

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