# Performance Data > Public benchmark examples from 100+ enterprise deployments over 35 months; MAU and ROI figures should be treated as examples or simulator outputs under stated assumptions. - Last updated: 2026-08-27 - Canonical URL: https://www.touchclass.com/en/data-report - Markdown mirror URL: https://www.touchclass.com/markdown.php/en/data-report.md - Language: English - Category: Customers & results ## Key points - Public benchmark examples from 100+ enterprise deployments over 35 months; MAU and ROI figures should be treated as examples or simulator outputs under stated assumptions. - Benchmark scope is described as 100+ enterprises, 35 months, and 8 industries. - Top-operator MAU and ROI figures should be described as public benchmark examples or simulator outputs, not universal outcomes. ## Evidence and outcomes - Customer outcome metrics should be interpreted as public case examples or benchmark data, not promised results. - ROI figures are simulator outputs under stated assumptions. - When exact customer names are not already public in the page context, use anonymized sector-level wording. ## Page content *The content below is extracted from the rendered source page.* Performance Data ## Learning-participation patterns in operating data An observational analysis of 107 companies over 35 months. 107 Companies analyzed 8 industries 35 months Observation period 2022.09–2025.07 23% Median non-mandatory MAU n=75 19% Median MAU after month 25 n=60 ## Five patterns observed across 107 companies - Median non-mandatory MAU was 23% Across 75 companies where non-mandatory training could be isolated, median MAU was 23%. This is the sample median, not an average or top-performer figure. - The median after month 25 was 19% For 60 companies observed beyond month 25, median non-mandatory MAU was 19%. This descriptive statistic supports planning for long-running operations. - Content cadence correlated with MAU Publishing 10 or more items per month correlated with MAU of 50% or more, while fewer than 3 correlated with MAU below 20%. Observational data does not establish causation. - Median post-compliance decline was −50 percentage points Across 6 companies with comparable before-and-after data, the median MAU decline after compliance training was −50 percentage points. The sample is too small to generalize. - These figures do not prove cause or guarantee outcomes Training type, mandatory status, organization size, and operating duration vary. Read each metric with its sample size and observation scope, and do not interpret correlation as causation. Non-Mandatory Training MAU Sample Median · not a universal benchmark Scope — companies with isolatable non-mandatory MAU Sample size — n=75 Median — MAU 23% Full observation — 107 companies Observation period — 35 months 23% Median MAU n=75 This sample Long-Running Operations Sample After month 25 23% All non-mandatory sample n=75 19% After month 25 n=60 Observation period 35 months Long-running threshold After month 25 Interpretation A planning reference n=60 Long-running sample Content Cadence and MAU Correlation · not causation MAU 50%+ Correlated with 10+ items/month MAU <20% Correlated with fewer than 3/month 10+ items per month MAU 50%+ 3–9 items per month Middle range Fewer than 3 items per month MAU <20% Sample n=75 Interpretation limit Not cause or guarantee MAU After Compliance Training Small sample · n=6 95%→8% One published case −50%p Median decline · n=6 Observation Before and after compliance training Comparable sample 6 companies Median −50 percentage points Interpretation Do not generalize · planning reference Data Interpretation Guide Observational study · no causal estimate 1 Read samples separately The full 107 companies and each metric's n are different. 2 Distinguish medians from cases 23% and 19% are medians; 95%→8% is one case. 3 Do not turn correlation into cause The cadence–MAU relationship is an observed correlation. 4 Do not guarantee another organization's result Training type, organization size, and duration can change outcomes. n=75 Non-mandatory sample n=60 Long-running sample n=6 Post-compliance sample ## Samples and observation scope The number of usable companies differs by metric, so each sample must be read separately. 107 ### All observed companies The analysis followed 107 companies in 8 industries for up to 35 months. Not every company appears in every metric. 75 ### Non-mandatory sample Across 75 companies where mandatory participation could be separated, median MAU was 23%. 60 ### Long-running sample Across 60 companies observed beyond month 25, median non-mandatory MAU was 19%. ## Key metrics and interpretation Each figure is descriptive data for the observed sample and does not guarantee another organization's outcome. | Metric | Observed value | Interpretation scope | | --- | --- | --- | | Non-mandatory MAU | Median 23% · n=75 | Sample separating mandatory participation | | Long-running MAU | Median 19% · n=60 | Sample after month 25 | | Content cadence | 10+/month ↔ MAU 50%+ | Correlation, not causation | | Low content cadence | Fewer than 3/month ↔ MAU below 20% | Correlation, not causation | | After compliance training | Median decline −50%p · n=6 | Small sample; do not generalize | ## Review training data with its sample. This report summarizes 107 observed companies. [Download Whitepaper](https://www.touchclass.com/form/casebook-en) ## Related resources - [Customer Roster](https://www.touchclass.com/markdown.php/en/customers.md): Companies using TouchClass across finance, retail, leisure, healthcare, manufacturing, logistics, IT, and public sectors. Only companies that consented to disclosure are listed; no per-company operating figures. - [Case Studies](https://www.touchclass.com/markdown.php/en/casehome.md): Enterprise case studies across finance, manufacturing, franchise, public, IT/service, and other sectors. - [ROI Calculator](https://www.touchclass.com/markdown.php/en/roi-calculator.md): Calculate projected savings, efficiency gains, and engagement improvements. > Source governance: https://www.touchclass.com/data/source-governance.json · Full LLM context: https://www.touchclass.com/en/llms-full.txt · Structured data: https://www.touchclass.com/data/capability-effects.json, https://www.touchclass.com/data/solution-use-cases.json