tl;dr
Luppa’s benchmark system is built on multi-source sampling across demographic segments and unit-level weighting – methodologies commonly used in organizational research to enable fair, accurate comparisons. It combines data from clients and a broad population of individual users (via Personal Luppa) to help mitigate bias and represent a wider workforce spectrum. Each client’s contribution is capped equally regardless of company size, and only the most recent 24 months of data are used. The result: benchmarks built on transparent, consistent methodology that give you a realistic view of where you stand – without data noise.
Introduction
From day one, Luppa has believed in the importance of benchmarking*. With this in mind, our goal has always been to provide a comprehensive and highly relevant selection of benchmarks, ensuring that our clients have access to the best possible data and context for making informed decisions.
In this blog, we will explore how Luppa's benchmark system works, the methodology behind it and provide answers to frequently asked questions regarding our benchmark offerings, including how relevant they truly are.
*In psychological research and test manuals, what we call a benchmark is typically referred to as a norm - a reference value derived from a representative sample against which individual scores are interpreted. We use benchmark throughout this article as a more accessible, industry-neutral term.
What are Luppa's benchmarks?
Benchmarking is the process of evaluating your company's practices and performance by comparing them with those of competitors, industry leaders and other organizations of similar size, industry and market. This approach allows organizations to identify performance gaps, improve business processes, boost competitiveness and highlight best practices. Benchmarking not only highlights areas for improvement but also identifies strengths, helping companies develop a clear path to success.
Luppa's advanced benchmarking system takes this a step further, enabling you to compare every aspect of your analysis with your peers for deeper insights.
The benefits of benchmarking include: gaining valuable insights, understanding your market and competition, contextualizing your performance and knowing your position in order to set realistic improvement goals.
Which benchmarks are available?
Luppa offers two types of benchmarks:
- Market benchmark: Through these benchmarks, businesses can better understand their market share, consumer base and the competitive environment.
- Industry benchmark: These benchmarks allow companies to evaluate their performance in relation to industry standards and discover areas for growth and improvement.
A full list of available benchmarks is available here.
Which benchmark to choose?
Industry benchmark:
To choose the most relevant industry benchmark, select the benchmarks that best align with your company’s operations.
If your business spans multiple industries, we recommend selecting 2-3 industries that are the most similar.
For companies in even more sectors, the system will calculate an average of the selected benchmarks for a holistic view.
Market benchmark:
For organizations operating in a single country, simply choose your country from the list.
If your company operates in multiple countries, select the relevant markets and the system will calculate an average benchmark.
For companies in more than five markets, we suggest using regional benchmarks such as Europe, EMEA, or the Middle East to get more contextual and precise data.
Choosing the right benchmark helps you see where your organization stands, but knowing how to act on that information is what drives real improvement. Our e-book on employee engagement analytics explores 14 practical strategies to ensure your measurement methods lead to accurate insights.
What data is used to calculate benchmarks?
Luppa’s benchmarks are based on two key types of data:
Luppa Client Data
This includes all data points collected from the usage of Luppa clients. All data is anonymised and analysed at an aggregate level - no individual or company-level data is ever disclosed. Luppa collaborates with a wide variety of clients from different sectors, which allows for a more comprehensive analysis of performance and trends across different industries and markets.
Personal Luppa Data
Personal Luppa is an extension for personal usage that allows individual users to fill out a Deep Dive survey, which provides personal insights on satisfaction and engagement compared to industry and market benchmarks. In exchange for this participation, Luppa collects valuable data on variables such as industry, market, company size, gender, age etc.
Choosing a tool that provides rich data and reliable benchmarks is essential for understanding your organization’s satisfaction and engagement. Our guide on finding the right fit outlines key features to look for when selecting an employee satisfaction and engagement tool, helping you make an informed choice.
Why is Personal Luppa data so important?
Personal Luppa data is significant because it helps improve the accuracy of our benchmarks. In research terms, it improves benchmark representativeness by expanding coverage beyond the client base - ensuring our benchmarks reflect the full population, not just a high-performing subset. Here is why:
1. Upward selection bias in client data - Luppa clients are not a random sample - they are organizations that have already invested in engagement measurement, which means they tend to perform above average. In fact, employee satisfaction among Luppa clients is, on average, 30% higher than the benchmark.
2. Generalizability constraints - Our client base skews toward larger, more mature organizations. In statistical terms, this limits the generalizability of client-only data across company sizes, industries, and markets.
3. Minimum adequate sample size - A statistically meaningful benchmark requires a sufficient number of data points per industry and market segment. Relying solely on client data would make many niche benchmarks statistically unreliable - for example, gathering enough financial-sector clients from Slovakia to reach significance would be impractical.
This is where Personal Luppa data becomes invaluable. It functions as a broad population sample with post-hoc balancing across key demographic and organizational dimensions - capturing responses across company sizes, satisfaction levels, socio-economic backgrounds, educational levels, and age groups. This follows similar goals as (inter)national workforce studies in improving population-level representativeness.
By including such a diverse pool of data, Personal Luppa ensures that our benchmarks reflect a much broader spectrum of the population and industries. This allows us to provide more precise, nuanced and comprehensive insights, rather than relying solely on data from larger, more advanced companies.
How does Personal Luppa collect and structure data?
To maintain the diversity and quality of data, Luppa conducts annual media campaigns designed to reach all demographic groups. These campaigns aim to maximize both the quantity and diversity of data, ensuring that the benchmarks are as representative as possible.
To prevent bot activity and ensure the accuracy of our data, we have implemented a series of data quality assurance protocols. The first is the integration of a reCAPTCHA on all of our forms, which effectively blocks bots from spamming and flooding our system. The second measure involves a set of control questions, a response validity screening approach commonly used in psychometric research to filter inattentive or low-effort responses. This approach helps us obtain a higher quality dataset, ensuring the integrity of our benchmarks.
How does Luppa combine client and personal data?
Luppa serves a wide range of clients, from small businesses to large enterprises. To create the most relevant benchmarks, we apply a unit-level weighting system - a methodology that normalizes each client's contribution regardless of company size. Each client is assigned a uniform weight of 50, a conservative estimate anchored to Luppa's average client size of 1,000+ employees.This means that in the benchmark calculation, 1 Personal Luppa data point represents one individual respondent, while 1 Luppa Client is represented as 50 data points - regardless of the company's actual size.
For example, if a company with 20,000 employees in Poland provides data, it is treated as just 50 weighted data points in the calculation, preventing it from introducing size-driven distortion into the benchmark. Without weighting, a single large company - say with 50,000 employees - could dominate the benchmark and skew insights to reflect its unique internal culture rather than the broader market.
By capping each company's influence at a fixed value, we ensure equitable representation across the sample and more accurate, comparable insights across our entire client base.
Here’s an example of how the benchmark is calculated:
For a market with 10 clients (A, B, C, etc.) and 1000 Personal Luppa data points, the formula for calculating the benchmark would be:
Benchmark result = (50A + 50B + 50C + ... + 1000 entry results) / (10x50 + 1000)
This method ensures that the benchmarks are not skewed by any single source of data, providing a more reliable and less size-skewed result.
What age of data is used for benchmark calculation?
To ensure the highest relevance, the most recent 24-month rolling window of data is utilized for benchmark calculations.
Why is there an age limitation on the data?
Organizational sentiment and engagement norms shift over time - macroeconomic conditions, labor market changes, and cultural trends all influence how employees respond. Using a rolling 24-month window ensures the benchmark reflects current conditions rather than outdated baselines.
Why a two-year period instead of a shorter timeframe?
A shorter window - such as 12 months - risks insufficient sample sizes in smaller segments, increasing statistical variance and reducing benchmark reliability. The 24-month window balances recency with sample stability, ensuring minimum sample thresholds are met even for niche industry-market combinations.
What is the minimum relevancy for any given benchmark?
With hundreds of different benchmarks in Luppa, every benchmark has its own data relevancy score - defined as the number of eligible data points for a given benchmark segment ranging from few dozen to thousands.
To ensure statistical reliability, Luppa applies the following minimum adequate sample thresholds before a benchmark is made available:
- Limited: 101+ data points
- Sufficient: 201+ data points
- Robust: 501+ data points
- Comprehensive: 1001+data points
Most of the benchmarks have much more data points, but if any falls below the minimum threshold, it is withheld from the platform to prevent misleading comparisons.
Reminder: take into account that if there is a company of 10,000 employees eligible for the benchmark, it will be counted only as 50 data points as described above.
How does Luppa calculate the market benchmark?
For each market, Luppa's algorithm aggregates all eligible weighted data points and computes a mean engagement score. This serves as the market-level benchmark index - the baseline against which client results are compared.
How does Luppa calculate industry benchmarks?
Industry benchmarks are computed globally - capturing sector-wide norms across all markets - and then adjusted for local context using a market-normalization formula. This two-stage approach separates universal industry patterns from market-specific variation, following this formula:
Industry for Market X = (industry benchmark + market benchmark)/2 *
*This is a pragmatic approximation designed for consistency across segments rather than a variance-weighted model.
In plain terms: your industry benchmark is always adjusted for where you operate. A tech company in Croatia is compared differently than a tech company in Germany, because local workforce norms differ.
How does Luppa calculate regional benchmarks?
For broader regions such as South America or Eastern Europe, Luppa's algorithms follow a two-step process.
In Step 1, benchmarks are calculated for each individual market within the region.
In Step 2, the average of all these market benchmarks is calculated to determine the regional benchmark.
Conclusion
In conclusion, Luppa's benchmark system combines data from a diverse range of clients and personal insights to provide accurate, relevant and comprehensive benchmarks.
By using both client and personal data, Luppa ensures a balanced representation across industries, sectors and market segments. By applying established research methodologies - including purposive sampling with post-hoc weighting, unit-level weighting, rolling temporal windows, and minimum sample thresholds - Luppa delivers benchmarks built on transparent, consistent methodology designed for practical business use.
Even though benchmarks offer a broad view of performance, context matters. Comparing your results to trends in the Workforce Insights Reports can reveal how engagement and satisfaction are evolving in your market, helping you identify realistic improvement targets and prioritize initiatives.
Now you can get an personalized estimate on how much you could save by investing in digital tools for employee engagement and satisfaction. Curious? Try out our ROI calculator.
Want to create a feedback culture where employees feel heard and engaged? Continue reading our blogs to learn more—or contact us to see how Luppa can help you drive participation, track sentiment, and turn insights into action.