Boost Recommendations by 40% with NPS Tools

For chain restaurant brands, "customer satisfaction" does not equal "customer willingness to recommend." Bean There, a U.S.-based coffee chain, once faced this bottleneck: its store ratings remained stable at 4.3/5, but the proportion of new customers referred by existing ones stayed below 15%. It wasn’t until the brand used an NPS calculator to quantify recommendation willingness and paired it with targeted question examples to uncover customers’ true thoughts that it increased the recommendation rate to 55% in just 4 months, with average monthly revenue per store growing by 22%.

The key logic behind this success is: an NPS calculator turns vague "favorability" into analyzable numbers, while question examples help customers explain the underlying reasons for their "willingness to recommend"—only when combined can customer satisfaction be transformed into tangible word-of-mouth growth.

1. Bean There’s Dilemma: Many Satisfied Customers, Few Recommenders

Bean There operates 32 stores across the U.S., focusing on "handcrafted freshly ground coffee + healthy light meals." Initially, the brand collected feedback through "in-store service satisfaction questionnaires," with questions like "Are you satisfied with the taste of your coffee today?" and "Was the service friendly?" Most customers gave ratings of 4 or above (out of 5), and the operation team once thought "customer experience is problem-free."

However, the actual data was striking: only 12% of new customers were referred by existing ones, far below the industry average of 25%. Some customers even commented, "The coffee is good, but not good enough to recommend to friends." Mark, the brand’s director, realized: "We only know customers are ‘satisfied,’ but not ‘why they are unwilling to recommend’—without a clear direction, optimizing service is just aimless effort."

At this point, the marketing team proposed trying an NPS survey: "NPS directly asks about ‘willingness to recommend,’ and we can calculate a specific score with an NPS calculator—it’s more informative than just satisfaction ratings."

2. Calculating Scores with NPS Calculator, Finding Reasons with Question Examples

Instead of launching the survey blindly, Mark’s team first designed a "scoring + follow-up" NPS survey plan, focusing on two core steps:

Step 1: Use the core NPS question to collect recommendation willingness: "How likely are you to recommend Bean There to friends or colleagues in the next 3 months?" (Scored 0-10, with 10 being "extremely likely"). Then, the NPS calculator automatically categorized customers—scores 9-10 as "Promoters," 7-8 as "Passives," and 0-6 as "Detractors." Using the formula (Promoter percentage - Detractor percentage), the initial NPS score was calculated at 28, far below the coffee industry’s NPS benchmark of 45.

Step 2: Design question examples to follow up on reasons for different customer groups:

For "Promoters": "What’s the main reason for your willingness to recommend?" (Options: coffee taste/value for money/store environment/employee service; multiple choices + additional comments allowed);

For "Passives": "What makes you hesitant to recommend?" (Open-ended question, e.g., "It’s slightly more expensive than Starbucks, but the taste is not much better");

For "Detractors": "What issues make you unwilling to recommend?" (Options: long waiting time/unfresh ingredients/crowded seating; multiple choices + additional comments allowed).

After the survey was launched for 1 month, over 8,000 valid responses were collected. Data from the NPS calculator showed that "Passives" accounted for 52%—the key factor dragging down the overall score. The follow-up results from question examples were even more specific: 73% of "Passives" mentioned "waiting over 15 minutes to order on weekends," and 68% felt "the vegetables in light meal sets are not fresh enough."

"It turns out customers are not dissatisfied—it’s just two small issues, ‘long waits’ and ‘average ingredients,’ that make them feel ‘no need to go out of their way to recommend,’" Mark finally found the direction for optimization.

3. Optimizing Based on Feedback, Tracking Results with NPS Tool

Targeting the issues identified in the survey, Bean There quickly implemented improvement measures:

Solving "long waits": Adding one more order-taker during weekend peak hours and launching a "mini-program pre-order" feature—customers can place orders in advance and pick them up in-store;

Improving "ingredient freshness": Partnering with local farms to switch to "same-day delivery" for vegetables in light meal sets, with harvest dates marked on packaging.

To track results in real time, the team used an NPS tool to build a "monthly retest" mechanism: launching a survey with the same NPS question every month, comparing score changes via the NPS calculator, and adding an Online question to follow up on "satisfaction with new features."

Three months later, the retested NPS score rose from 28 to 62, the proportion of "Passives" dropped to 23%, and the proportion of "Promoters" increased from 22% to 48%. More surprisingly, the rate of new customers referred by existing ones jumped from 12% to 55%—a store in Seattle even saw weekend revenue double by 1.5x due to the large number of new customers brought in by "Promoters."

4. How SurveyMars Helps Small & Medium-Sized Brands Replicate This Method

SurveyMars fully meets the NPS tool needs used by Bean There, and is even more suitable for small & medium-sized restaurant brands:

Zero-threshold NPS calculator: No manual score calculation—after customers submit the questionnaire, the system automatically calculates the NPS score and the proportion of each customer group, and generates visual charts (e.g., "NPS score comparison across stores," "feedback proportion for each issue"). Store owners don’t need Excel skills to understand the data;

Ready-to-use NPS survey templates: Built-in "restaurant industry NPS survey" templates with pre-set core NPS questions and question examples (e.g., follow-up options for "waiting time" and "ingredient freshness"). Just change the brand name to use them, saving 80% of design time;

Support for NPS benchmark comparison: SurveyMars provides NPS benchmark data for the same industry (e.g., coffee, burgers, milk tea), so you can clearly see the gap between your brand and competitors without manually searching industry reports.

For example, a small burger joint in California used SurveyMars to conduct an NPS survey. Through question examples, it found "too salty fries" was the main issue. After adjusting the recipe, its NPS score rose from 31 to 58, and the recommendation rate increased by 35%.

5. 3 Practical Tips for Conducting Surveys with NPS Tool

1.Don’t just focus on NPS score—prioritize "Passives": As Bean There showed, "Passives" are the key to improving scores. Using question examples to uncover their hesitations is more effective than fixating on the extreme feedback from "Detractors";

2.Make question examples "specific, not vague": Instead of asking "Do you have any suggestions for our service?" ask "How long do you think the order waiting time should be?" The more specific an Online question is, the easier it is to get actionable feedback;

3.Don’t make retest cycles too long: It’s recommended to use the NPS calculator to measure scores monthly. If major adjustments are made (e.g., new menu launches, process changes), retest every 2 weeks to verify results in a timely manner—SurveyMars’ "survey reminder" feature sends automatic notifications, so you don’t have to remember manually.

Conclusion: NPS Calculator Is Not Just a "Scoring Tool," But a "Growth Compass"

Bean There’s case proves that an NPS calculator and question examples can help brands break out of the dilemma of "knowing satisfaction but not reasons." When you use NPS surveys to find "why customers are unwilling to recommend" and NPS tools to track optimization results, customer satisfaction can truly be transformed into higher recommendation rates and revenue growth.

SurveyMars makes this process more accessible for small & medium-sized brands: no need to spend heavily on research firms or master complex data analysis. With ready-to-use NPS survey templates and an auto-scoring NPS calculator, you can turn customer feedback into tangible business growth—just like Bean There. After all, for any brand, "customer willingness to recommend" is the best word-of-mouth—and it all starts with a targeted NPS survey.

Q1: If I edit my NPS survey (e.g., add a new question), will the SurveyMars NPS Calculator still work correctly?

A: Yes. The NPS Calculator only focuses on the core NPS question (the "0-10 likelihood to recommend" prompt) — adding, editing, or removing other questions (e.g., demographic prompts, open-ended feedback) won’t affect its functionality. It will still automatically tally promoters, detractors, and passives from the NPS question, then compute the correct score. Just ensure you don’t delete or modify the original NPS rating question itself; if you do, re-add it via the "NPS Question" tool to keep the calculator working.

Q2: Does the SurveyMars NPS Calculator support multiple languages for the NPS question (e.g., Spanish, French)?

A: Yes. If you create a multilingual NPS survey (available for paid users), the NPS Calculator will still work seamlessly. When you translate the NPS question (e.g., "¿Qué tan probable es que recomiendes nuestro producto?" for Spanish), the calculator recognizes it as the core NPS prompt regardless of language. It will tally responses from all language versions together to compute a single overall NPS score — perfect for global teams or international customers.

Q3: What happens to my NPS Calculator data if I downgrade from a paid plan to a free plan in SurveyMars?

A: When downgrading, you won’t lose your existing NPS data — but you’ll lose paid-only NPS Calculator features. Your overall NPS score, basic promoter/detractor percentages, and simple bar charts will still be accessible. However, features like time filters, demographic breakdowns, NPS alerts, and advanced export options will be disabled until you upgrade again. SurveyMars will notify you of which features are affected before you confirm the downgrade, so you can back up any critical filtered data first.

Q4: Is it possible to hide the NPS score from certain team members when sharing results via SurveyMars?

A: Yes. When sharing NPS results (via the "Share" button), paid users can set "View Permissions." Choose to let some members see the full breakdown (score + promoter/detractor details) and others only see high-level insights (e.g., "NPS is 'Good' — 45% promoters") by toggling off "Show Detailed Score" for specific users. This is useful if you want to share progress with non-analyst teams (e.g., marketing) without overwhelming them with raw data. Free users can only share full results or no results — no partial permission settings.

Q5: Does the SurveyMars NPS Calculator count "neutral" responses (scores 7-8) when calculating the overall NPS?

A: No. The NPS formula (industry standard, followed by SurveyMars) only uses promoters (scores 9-10) and detractors (scores 0-6) — neutrals (7-8) are excluded from the calculation. The calculator will show neutrals as a separate percentage in the breakdown (e.g., "30% neutrals") to help you understand response distribution, but they don’t affect the final NPS number (promoters% - detractors%). This aligns with global NPS best practices, as neutrals don’t actively promote or criticize your brand.