Key Takeaways
- 90% of customer support leaders say delivering customer service faster than competitors is important to their company’s growth strategy (CX/Customer service priorities survey figure).
- 37% of organizations reported using AI for customer service in 2023 (share of firms using AI for customer service activities).
- 33% of adults used digital government services for at least one purpose in 2023 in the EU (percentage using eGovernment).
- US household expenditure on repair and maintenance services was $339.8 billion in 2023 (consumer spending on repair and maintenance).
- $1.4 billion global spend in 2023 on help desk and customer service software solutions (market spend).
- $7.2 billion global market size in 2023 for customer experience (CX) software (market size estimate).
- 67% of UK consumers reported they used online self-service before contacting a call center in 2023 (share using self-service).
- 72% of organizations use ticketing systems to manage customer support requests (ticketing adoption share).
- 5.2 million US adults used online learning platforms for job training in 2021 (number of users).
- 25% average reduction in operating costs after implementing omnichannel customer service automation (cost reduction).
- 10% of total IT spend is allocated to customer service and support technologies (IT budget allocation).
- 6.5% of companies said compliance and security costs increased in 2023 (share experiencing cost increase).
- 63% of consumers are willing to pay more for a better customer experience (willingness-to-pay share).
- 20% of employees spend time searching for information rather than doing work (time-waste for information search).
- 15% of companies said their self-service deflection rate exceeded 30% in 2023 (share by deflection threshold).
Automating and improving customer support is key, with strong cost and service gains alongside rising AI and omnichannel adoption.
Industry Trends
Industry Trends Interpretation
Market Size
Market Size Interpretation
User Adoption
User Adoption Interpretation
Cost Analysis
Cost Analysis Interpretation
Performance Metrics
Performance Metrics Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Julian Richter. (2026, February 13). Help With Statistics. Gitnux. https://gitnux.org/help-with-statistics
Julian Richter. "Help With Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/help-with-statistics.
Julian Richter. 2026. "Help With Statistics." Gitnux. https://gitnux.org/help-with-statistics.
References
- 1gartner.com/en/newsroom/press-releases/2023-10-12-gartner-customer-service-innovation-still-divides-organization-priorities-and-technology-investment
- 11gartner.com/en/newsroom/press-releases/2024-04-08-gartner-says-worldwide-customer-experience-software-market
- 21gartner.com/en/documents/3988866
- 27gartner.com/en/newsroom/press-releases/2023-10-06-gartner-customer-experience-survey-willingness-to-pay
- 28gartner.com/en/documents/3989471
- 29gartner.com/en/newsroom/press-releases/2023-11-16-gartner-customer-service-research-deflection
- 2salesforce.com/news/studies/research/2023-state-of-service/
- 7salesforce.com/news/studies/research/2024-state-of-service/
- 8salesforce.com/news/stories/now-more-than-ever-customer-expectations-2024/
- 3digital-strategy.ec.europa.eu/en/policies/european-public-sector-innovation-scoreboard
- 4cloudflare.com/en-gb/learning/security/threats/bots/
- 5incapsula.com/blog/bot-traffic-statistics.html
- 6ibm.com/reports/data-breach
- 20ibm.com/thought-leadership/institute-business-value/omnichannel-customer-service
- 9fred.stlouisfed.org/series/CPILFESL
- 10idc.com/getdoc.jsp?containerId=prUS51604824
- 12fortunebusinessinsights.com/customer-engagement-software-market-102921
- 13precedenceresearch.com/customer-service-automation-market
- 14freshworks.com/company/media-room/reports/
- 17freshworks.com/reports/customer-service-trends-2024/
- 24freshworks.com/company/newsroom/press-releases/2024-customer-experience-report/
- 15reportlinker.com/p05984133/AI-enabled-Customer-Service-Software-Market.html
- 16ofcom.org.uk/__data/assets/pdf_file/0026/268733/uk-consumers-online-experience-2023.pdf
- 30ofcom.org.uk/__data/assets/pdf_file/0020/233236/ofcom-call-waiting-time-report-2023.pdf
- 18nces.ed.gov/fastfacts/display.asp?id=3
- 19consumerfinance.gov/data-research/consumer-complaints/
- 22verizon.com/business/resources/reports/dbir/
- 23servicenow.com/content/dam/servicenow-assets/marketing-assets/documents/sg-automation-in-it.pdf
- 25growory.com/blog/ai-in-customer-service-statistics/
- 26hubspot.com/state-of-marketing







