TRANSPARENCY

Data TransparencyOur AI results are evidence-based

Every results figure we publish comes from industry research, with a verifiable source and year. Here we document the origin of each number so you can check it yourself.

Last updated: June 2026
01

Why we publish this page

In an enterprise artificial intelligence market saturated with inflated promises, we choose the opposite path: to show the source behind every data point. If a number appears on any Vantegrate page (about AI agents, WhatsApp Business automation, document OCR, conversational business intelligence or logistics), it has its entry in this source table, with the link to the original study. This is what we mean by transparency: verifiable data, citable benchmarks and zero unfounded guarantees.

Trust is not declared, it is demonstrated. Most B2B AI vendors publish results figures without saying where they come from, and many of those figures do not hold up to verification. We prefer to expose our sources so you can judge the strength of each claim on your own terms.

This page serves two functions. For you as a client or evaluator, it is the proof that our marketing claims have real backing in studies from consultancies, independent analysts and academic papers. For us, it is an internal commitment: no Vantegrate team can publish a number on the site without it having a documented entry here. In practice, it is the source of truth for every benchmark we communicate.

02

How to read our numbers

Not all numbers mean the same thing, and part of being transparent is explaining what kind of data you are reading in each case. That is why we classify each numerical claim into one of three categories, and we identify it in the "Type" column of each table:

Industry benchmark. This is a data point that comes from independent research: consultancies such as McKinsey, Bain or Deloitte, analysts such as Gartner or Forrester, peer-reviewed academic papers, industry associations and reference reports for the sector. When we say "industry studies show that...", we are in this category. It represents the industry average or range, not a result we guarantee to you. It is the basis of almost everything we communicate.

Vendor data. Some relevant figures are published only by companies that sell the solution the data describes. We include them because they provide useful reference when no independent source exists, but we always label them as such, because they come from an interested party and may be subject to selection bias. Whenever an equivalent independent source exists, we prioritize it over the vendor's.

Improvement documented in our own cases. When we publish a number as a Vantegrate result of our own, it is because it is measured in real production with a client who agreed to be a case study. These cases are always identified as such and are never presented as a general industry benchmark.

The rule that runs through all three categories is simple: you will not find any number presented as a universal guarantee of result. When a figure lacks solid backing, we do not publish it with a number; we replace it with a qualitative description such as "significant and consistent improvement." We prefer to say less than to claim something we cannot prove.
03

Sources and benchmarks by topic

The following is the complete list of sources that back every figure on the site, grouped by topic area. Each row includes the claim, the industry benchmark with its range and year, the link to the original source and the type of data.

Conversational communication (WhatsApp vs. email)

ClaimIndustry benchmarkSourceType
WhatsApp Business open rate vs. emailWhatsApp 75-98% (baseline 58-79% unoptimized); email 20-25% real-worldBird, "Measure WhatsApp Performance Against Benchmarks" (2024); Brevo, Marketing Orchestration Benchmark (2026)Industry benchmark
WhatsApp click-through vs. emailWhatsApp 15-45%; email 2-3%Bird (2024); MailerLite, Email Benchmarks (2025)Industry benchmark
Engagement lift over email4-6x on conversational B2C campaignsBird (2024)Industry benchmark
WhatsApp response rate5-10x higher than email depending on the use caseAurora Inbox (2026)Vendor data
Cart recovery by conversational channelWhatsApp 15-30% vs. email 2-5%Kanal (2026); Lojas Renner case via MetaVendor data
Note on email open rates: post-2021 email open figures are often inflated by Apple Mail Privacy Protection. The real comparable range is 20-25% (Brevo 2026; Mailchimp pre-2021). Values above 30% that appear in some recent reports are not comparable one-to-one with WhatsApp.

Document processing (OCR / IDP in accounts payable)

ClaimIndustry benchmarkSourceType
Cost to process a manual invoiceUSD 9.40 average; USD 12.88 non-best-in-class; USD 2.78 best-in-classArdent Partners, "AP Metrics That Matter in 2025" (N=212)Industry benchmark
Median invoice cost (general organizations)USD 21.40APQC, Open Standards Benchmarking (2024-2025)Industry benchmark
Invoice cycle timeBest-in-class 3.1 days vs. 17.4 days for the restArdent Partners (2025), via MediusIndustry benchmark
ML extraction accuracy on legible documentsHigh 90% rangeGartner, Market Guide for AP Invoice Automation (2024-2025)Industry benchmark
Touchless / STP rate on PO-backed invoices85-90%Basware, Medius, SoftCo (leading vendors in the Gartner Magic Quadrant 2025)Vendor data

Financial close and order status (WISMO)

ClaimIndustry benchmarkSourceType
"Where is my order" inquiries as % of support30-50% of volume (up to 70-80% at peaks)Salesforce, WISMO Guide (2024); Sendcloud (2024)Industry benchmark
Top-quartile monthly financial close~6 daysAPQC (2024)Industry benchmark
WISMO reduction with proactive trackingReductions of 25-90% depending on the caseSendcloud (2024)Vendor data

Chargeback disputes

ClaimIndustry benchmarkSourceType
Manual win rate with evidence (fraud)8-20%Chargeback.io, Chargeback Statistics (2026); Mastercard, State of Chargebacks (2025)Industry benchmark
Average US win rate (all categories)54% (Brazil 36.9%)Mastercard (2025), via ChargeflowIndustry benchmark
Win rate with evidence automation (CE 3.0)Up to 80%Chargeflow (2025)Vendor data

Business intelligence (BI)

ClaimIndustry benchmarkSourceType
Traditional BI adoption among employeesStalls at 25-35%Gartner, Survey Analysis on BI Adoption (2017-2022); BARC/Eckerson, via TechTarget (2022)Industry benchmark
We do not publish conversational BI adoption figures because no independent measured benchmark exists yet. Gartner's projection about conversational interfaces and data storytelling is a prediction, not a verified data point.

B2B SaaS

ClaimIndustry benchmarkSourceType
The 5-minute rule in lead response100x more likely to connect and 21x more likely to qualify vs. 30 min; industry average 47 hours; 78% buy from the first responderOldroyd, MIT/InsideSales (2007); Harvard Business Review, "The Short Life of Online Sales Leads" (2011); replicated by Casey Response AI (2026)Industry benchmark
Best-in-class Net Revenue Retention~110-120%; venture-backed median 106%ChartMogul, SaaS Retention Report (2024)Industry benchmark
Top-quartile enterprise NRR (ACV >USD 100K)130%+; enterprise median 118%Optifai (2026), cross-referencing ChartMogulIndustry benchmark
Average MQL-to-SQL13% cross-industry; B2B SaaS 18-22%; top quartile 25-35%HubSpot via Only-B2B (2025)Industry benchmark
Free-to-paid conversionMedian 8%; with card required ~30% (5x vs. no card)ChartMogul, SaaS Conversion Report (2026)Industry benchmark
Median CAC payback20 months in 2024 (up from 12-14 historically)KeyBanc / Sapphire Ventures, Private SaaS Survey (2024), via BantrrIndustry benchmark
On CAC payback: the historical "less than 12 months" ideal no longer represents the market average. The current, verifiable figure is 20 months median (KeyBanc 2024). Any reference we make to this topic is about moving toward the top-quartile range, not about guaranteeing less than 12 months.

Financial services

ClaimIndustry benchmarkSourceType
Digital bank onboarding abandonment63% average (up to 70% in some countries)Signicat (2020), via InnovatricsIndustry benchmark
Institutions losing clients to slow onboarding70% (highest figure on record)Fenergo, KYC Report (2025), via FinTech GlobalIndustry benchmark
Healthy cost-to-collectBelow 2% of the amount recoveredProdigal (2025), citing BLS/DeloitteIndustry benchmark

Healthcare

ClaimIndustry benchmarkSourceType
No-show rate before reminders~23% (median)Systematic review, NCBI (2021)Industry benchmark
No-show reduction with SMS reminders34-38% averageJAMA / Journal of Telemedicine and Telecare, via Klara (2023)Industry benchmark
Claims denial rate5-10% benchmark; 30% rejected on first submissionMD Clarity (2024); HBMA via Voyant Health (2025)Industry benchmark
First-pass acceptance target98% (efficient practices >90%)BellMedEx (2024)Industry benchmark
Adherence improvement with digital interventions+11-19 percentage points (Cohen's d = 0.40, p<0.001)JMCP (2020); JMIR (2025)Industry benchmark

Pharmaceutical

ClaimIndustry benchmarkSourceType
QC productivity improvement with digitization+30-40% productivity; -50% QC costs; -65% deviations; -90% deviation closure timeMcKinsey, "The Future of Pharma Quality Control" (2020-2024)Industry benchmark
Scale-up and batch release acceleration20-30%McKinsey (2020-2024)Industry benchmark
Annual losses from cold-chain excursionsUSD 2.5-12.5 billion globally (broad estimates up to USD 35 billion)IATA via DHL (2019); AJHP (2023)Industry benchmark

Logistics and foreign trade

ClaimIndustry benchmarkSourceType
Demurrage per container per dayUSD 2,008 average across the top 7 North American ports; USD 734 at LA/Long BeachContainer xChange + Drewry, Demurrage & Detention Benchmark Report (2023)Industry benchmark
OTIF required by large retailersWalmart 98% (3% of COGS penalty); Amazon >=90%; top-performer 95-98%Walmart, via Zipline Logistics; Red Stag Fulfillment (2024)Industry benchmark
Clarification: the Container xChange demurrage figure measures the top 7 North American ports, not a global average. The pre-2020 range of USD 100-300/day is outdated.

Field service (on-site technical service)

ClaimIndustry benchmarkSourceType
First-time fix rate75-80% average; 88%+ best-in-classAberdeen Group via PTC/ServiceMax (2013-2024)Industry benchmark
Cost of a technical visit (truck roll)USD 200-300 base; USD 1,100+ fully loadedTSIA / Aberdeen, via Field Technologies Online; Help Lightning (2024)Industry benchmark
Visits requiring a second dispatch25-33%Help Lightning (2024)Industry benchmark

Machinery and equipment

ClaimIndustry benchmarkSourceType
Aftermarket EBIT margin vs. new equipment25% aftermarket vs. 10% new equipment (analysis of 30 industries)McKinsey, "Industrial Aftermarket Services: Growing the Core" (2017-2024)Industry benchmark
Aftermarket operating margin2.5x that of new equipmentDeloitte, via GenalphaIndustry benchmark

Manufacturing

ClaimIndustry benchmarkSourceType
World-class OEE85% (achieved by only ~3% of plants); discrete manufacturing average 66.8%TPM/Nakajima standard and ISO 22400; OXMaint (2024-2026)Industry benchmark
Unplanned downtime reduction with predictive maintenance30-50% within 12 monthsUpKeep (2024), via Manufacturing Lead Generation; OXMaint (2024)Industry benchmark

Retail and e-commerce

ClaimIndustry benchmarkSourceType
Conversion of retailers with omnichannel (BOPIS/curbside)3.7-3.9% vs. 3.1% without omnichannel (relative lift ~25%)Digital Commerce 360, Omnichannel Report (2025)Industry benchmark
Average ticket lift with omnichannel personalization and BOPIS10-15%Digital Commerce 360 (2025)Industry benchmark

Reference costs

ClaimIndustry benchmarkSourceType
Fully loaded cost of an SDR (US market)USD 106,000-141,000 annuallyThe Bridge Group, SDR Metrics ReportIndustry benchmark
04

On sources with a commercial interest

Some of the numbers above come from companies that sell the solution the data describes. We include them because they provide useful reference, but we always mark them as "vendor data" so you know they come from an interested party and may be subject to selection bias. When an independent source exists (consultancy, analyst, paper, industry association), we always prioritize it over the vendor's.

05

Geographic scope: global and LATAM benchmarks

Most available benchmarks are global or centered on the United States. Data specific to enterprise artificial intelligence in LATAM (Argentina, Mexico, Brazil, Chile, Colombia and Peru) is still scarce in analyst literature. When we use a regional data point (for example, the payment dispute win rate in Brazil or WhatsApp Business cases in the region), we flag it explicitly. In the remaining cases, absolute values may differ by country, and it is best to take them as directional reference, not as an exact figure for your market.

06

Frequently asked questions

Where do the numbers Vantegrate shows on its site come from?

Every results figure comes from one of three sources: an independent research benchmark (consultancies, analysts, papers), a figure published by an industry vendor (labeled as such), or our own case measured in production with a real client. All sources are listed with their link in the table on this page.

Does Vantegrate guarantee these results for my company?

No. Benchmarks describe the industry average or range according to industry studies, not a guaranteed result. Actual results depend on the implementation, the quality of the data and the adoption of each organization. We explain this in detail in the disclaimer at the bottom of this page.

What is the difference between an industry benchmark and vendor data?

An industry benchmark comes from an independent source with no commercial interest in the result (for example, a McKinsey study or an academic paper). Vendor data comes from a company that sells the solution the data describes, so it may be biased; we include it only when there is no independent source, and we always make that clear.

How often are the sources updated?

We review and refresh the sources periodically, and we correct any figure that becomes outdated relative to the latest research. The date of the last update appears at the bottom of the page.

What happens if a number does not have a solid source?

We do not publish it as a number. We replace it with a qualitative description, such as "significant and consistent improvement." We prefer to communicate less than to claim something we cannot back with evidence.

Why does Vantegrate publish a data transparency page?

Because trust is demonstrated with verifiable evidence, not with statements. It is our way of standing out in an enterprise AI market full of unsupported figures, and an internal commitment not to communicate any number we cannot document.

07

Legal disclaimer

The benchmarks on this page describe the average or range of each industry according to the research available at the time of publication. They are informational and for reference purposes.

None of the figures presented here constitutes a guarantee of result. Vantegrate does not guarantee that your organization will obtain the same numbers, or equivalent results, simply by adopting our tools. The benchmarks reflect what other organizations in the sector have reported, not what you will achieve.

Actual results vary from one company to another and depend on factors that are outside Vantegrate's control. Among them: the degree of responsibility and rigor each organization brings to implementing its processes, the correct configuration and use of the tools, the quality and cleanliness of the data available, the level of commitment and adoption from users, and the particularities of each company's operational, regulatory and market context. A partial implementation, low internal adoption or poorly defined processes can produce results substantially different from the reference benchmarks.

The content of this page also does not constitute legal, financial, regulatory or professional advice of any kind. For decisions that depend on these benchmarks, consult with qualified advisors in your jurisdiction.

Last updated: June 2026. We review and refresh the sources on this page periodically. If you find a figure you believe is outdated or incorrectly cited, write to us on WhatsApp.

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