The QR code market is projected to reach $9.8 billion by 2030. This growth mirrors the technology's rapid adoption but also its exploitation for fraud.
Key Takeaways
- 11.4% CAGR for the QR code market reported for 2023-2030
- $3.2 billion global QR code market size in 2023
- $9.8 billion projected QR code market size by 2030
- 2.9 billion people worldwide used smartphones in 2016
- ISO/IEC 18004 specifies QR code 2D symbology standard
- ISO/IEC 18004 is titled Information technology—Automatic identification and data capture techniques—QR Code bar code symbology specification
- QR codes became one of the most common forms of contactless engagement; in a 2020 survey, 53% of consumers used QR codes to access content
- In a 2020 survey, 41% of consumers said they would use QR codes again after COVID-related use
- In a 2020 survey, 66% of retailers offered QR codes for ordering, payments, or information
- QR codes had a median read range of about 5–10 cm for small sizes in typical mobile scanning conditions reported in practical testing
- QR code error correction allows recovery of data when up to 30% of the code is damaged (Level M)
- QR code error correction allows recovery of data when up to 25% of the code is damaged (Level Q)
- QR codes can be printed at high resolution with module sizes as small as around 0.3 mm in practical deployments (typical barcodes guidance)
- GS1 guidance states quiet zones and printing quality matter for scannability; minimum module/size guidelines are provided in GS1 QR/barcode practices
- Cost of printing QR codes is typically marginal because QR uses standard 2D printing, but implementation costs are dominated by linking/management systems
The QR code market is set to soar to $9.8 billion by 2030, growing 11.4% annually.
Related reading
01 · Category
Market Size3 stats
01
11.4% CAGR for the QR code market reported for 2023-2030
02
$3.2 billion global QR code market size in 2023
03
$9.8 billion projected QR code market size by 2030
Interpretation
Market Size Interpretation
With the QR code market growing from $3.2 billion in 2023 to a projected $9.8 billion by 2030, at an 11.4% CAGR, the data points to strong, sustained expansion over the next several years.
02 · Category
Industry Trends17 stats
01
2.9 billion people worldwide used smartphones in 2016
02
ISO/IEC 18004 specifies QR code 2D symbology standard
03
ISO/IEC 18004 is titled Information technology—Automatic identification and data capture techniques—QR Code bar code symbology specification
04
In the UK, police recorded 154,000 fraud and cybercrime incidents reported in 2022 (context: fraud affecting QR-based redirections)
05
Denso Wave introduced QR Code in 1994
06
QR Code was initially created for high-speed component tracking and labelling at manufacturing lines
07
In 2020, global smartphone shipments were about 1.25 billion units (context for QR scanning device base)
08
In 2021, global smartphone shipments were about 1.41 billion units (context for QR scanning device base)
09
In 2022, global smartphone shipments were about 1.22 billion units (context for QR scanning device base)
10
In 2023, global smartphone users were about 6.8 billion (context for QR scanning device base)
11
QR Code is a 2D symbology designed to be read by image sensors (camera-based scanning)
12
In a government cybersecurity guidance context, QR codes are used as a delivery mechanism for malicious URLs and phishing links, increasing user risk
13
CISA security guidance notes QR codes can be used to direct users to malicious websites via scanning
14
In the US, the Internet Crime Complaint Center (IC3) has reported hundreds of thousands of complaints annually for years (context: scams including QR lures)
15
In 2023, IC3 reported 880,418 complaints total (includes fraud categories that can include QR-based phishing lures)
16
In 2023, IC3 reported $12.5 billion in adjusted losses (context: fraud that can be driven by malicious QR-redirect URLs)
17
In Japan, QR code usage is mature; Denso Wave’s QR Code history emphasizes adoption in logistics and consumer applications
Interpretation
Industry Trends Interpretation
As smartphone adoption surged, with global users reaching about 6.8 billion by 2023 and shipments peaking around 1.41 billion in 2021, QR codes that were standardized in ISO/IEC 18004 and invented by Denso Wave in 1994 have become a far wider target for fraud, reflected in the UK’s 154,000 recorded fraud and cybercrime incidents in 2022 and the US IC3’s 880,418 complaints and $12.5 billion in adjusted losses in 2023.
03 · Category
User Adoption10 stats
01
QR codes became one of the most common forms of contactless engagement; in a 2020 survey, 53% of consumers used QR codes to access content
02
In a 2020 survey, 41% of consumers said they would use QR codes again after COVID-related use
03
In a 2020 survey, 66% of retailers offered QR codes for ordering, payments, or information
04
QR codes are widely used for ticketing; in the entertainment ticketing sector, barcode scanning acceptance relies on 2D codes including QR
05
Global QR code usage increased during COVID-19; Google’s Think with Google reported a sharp rise in QR code usage for payments and menus in 2020
06
QR codes are used in restaurant menus and contactless ordering; some surveys during 2020 show majority adoption among consumers and businesses
07
QR codes can be scanned by mobile devices with built-in camera and decoding apps; many smartphones support QR scanning via camera apps by default
08
Apple iOS supports scanning QR codes using the Camera app (iOS 11 and later)
09
78% of consumers in 2021 reported they used online-to-offline QR scanning for product info (survey-based adoption)
10
In 2020, 54% of consumers used QR codes for contactless information during the pandemic (consumer survey)
Interpretation
User Adoption Interpretation
In 2020, QR codes surged into mainstream use with 53% of consumers using them for content and 66% of retailers offering QR-based services, and this momentum continued as 41% of consumers said they would use QR codes again after COVID.
More related reading
04 · Category
Performance Metrics29 stats
01
QR codes had a median read range of about 5–10 cm for small sizes in typical mobile scanning conditions reported in practical testing
02
QR code error correction allows recovery of data when up to 30% of the code is damaged (Level M)
03
QR code error correction allows recovery of data when up to 25% of the code is damaged (Level Q)
04
QR code error correction allows recovery of data when up to 15% of the code is damaged (Level H is higher; Level L is lower at 7%)—Level L recovers about 7%
05
A QR code version 1 has a module grid of 21×21
06
Maximum QR code version is 40
07
QR code data capacity for numeric mode at version 40 is 7,089 characters
08
QR code data capacity for alphanumeric mode at version 40 is 4,296 characters
09
QR code data capacity for binary mode at version 40 is 2,953 bytes
10
QR code data capacity for Kanji mode at version 40 is 1,817 characters
11
QR code total modules for version 40 are 177×177
12
A QR code can be made with 4 error correction levels: L, M, Q, and H
13
QR Code uses Reed–Solomon error correction
14
QR code generation is free and standardized; the baseline QR Code specification supports 4 symbol structure levels
15
QR Code’s Reed–Solomon error correction enables data recovery under printing/occlusion issues
16
A QR code can encode up to 7089 numeric digits in version 40 (highest numeric mode capacity)
17
A QR code can encode up to 4296 alphanumeric characters in version 40 (highest alphanumeric mode capacity)
18
A QR code can encode up to 2953 bytes in binary mode at version 40
19
A QR code can encode up to 1817 Kanji characters in version 40
20
QR code version 1 uses a 21×21 module matrix
21
QR code version 40 uses a 177×177 module matrix
22
The QR code standard uses 4 levels of error correction to trade redundancy for robustness
23
Error correction Level H corresponds to ~30% recoverability
24
Error correction Level Q corresponds to ~25% recoverability
25
Error correction Level M corresponds to ~15% recoverability
26
Error correction Level L corresponds to ~7% recoverability
27
QR Code can encode up to 2953 bytes of binary data (version 40 binary capacity)
28
A paper on QR-code-based data transmission reports robust performance with correct error correction levels under moderate distortion
29
Error correction improves reliability: with Level H (~30% recovery), QR codes are more robust to partial damage
Interpretation
Performance Metrics Interpretation
Across QR versions up to 40, the biggest practical takeaway is that choosing a higher error correction level greatly boosts resilience, with Level H recovering about 30% of damaged data compared with roughly 7% at Level L.
05 · Category
Cost Analysis4 stats
01
QR codes can be printed at high resolution with module sizes as small as around 0.3 mm in practical deployments (typical barcodes guidance)
02
GS1 guidance states quiet zones and printing quality matter for scannability; minimum module/size guidelines are provided in GS1 QR/barcode practices
03
Cost of printing QR codes is typically marginal because QR uses standard 2D printing, but implementation costs are dominated by linking/management systems
04
GS1 provides barcode/QR implementation guidelines and specifications to reduce misreads and reduce operational cost
Interpretation
Cost Analysis Interpretation
With module sizes as small as about 0.3 mm still practical for high resolution printing and GS1 stressing quality and quiet zones, the biggest driver of cost and reliability is less the printing and more the linking and management systems.
Reference
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.
APA
Marcus Engström. (2026, February 13). Qr Code Statistics. Gitnux. https://gitnux.org/qr-code-statistics
MLA
Marcus Engström. "Qr Code Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/qr-code-statistics.
Chicago
Marcus Engström. 2026. "Qr Code Statistics." Gitnux. https://gitnux.org/qr-code-statistics.
Sources & references
20 datasets cited across this report · attribution is report-level
+5 additional datasets cited (not shown individually)