Click-through rate vs scan rate — what counts as success

A "good" click-through rate depends entirely on the channel, the audience, and what the link is asking the person to do. A 1% CTR on a programmatic display banner is a strong result; the same 1% on a transactional confirmation email is a campaign that quietly broke. QR scan rates have the same problem — a 2% scan-to-impression rate on a billboard is roughly the published industry expectation, while a 2% scan rate on a printed restaurant menu means most of the table never looked at the code. The number alone tells you nothing. The number against the right baseline tells you what to fix.

This post is the benchmark you can use. Industry-baseline rates for the channels that matter — email, SMS, paid social, organic social, programmatic display, print, retail packaging, outdoor — pulled from primary research wherever it exists, and flagged honestly when a channel doesn't have a clean public number. The middle section explains how to read your own data against those baselines without misdiagnosing the gap. The widget at the bottom takes your channel, impression volume, and observed CTR or scan rate and tells you which band you're in.

What "click-through rate" actually counts#

Click-through rate is the number of clicks divided by the number of people who saw the link. The denominator is where channels diverge. Email CTR is usually clicks divided by delivered emails (not opens). Paid display CTR is clicks divided by ad impressions. Organic social CTR depends on whether the platform counts "reach" or "impressions" as the denominator, and the two numbers can differ by 30% on the same post. The first thing to check when comparing your CTR to a published benchmark is which denominator the benchmark uses, because the same observed clicks can produce three different CTRs depending on the formula.

A scan rate is the QR-code equivalent: scans divided by people who plausibly saw the code. The denominator is harder. A poster at a bus stop is seen by every commuter who passes; a code on a coffee cup is seen by exactly one person. Most published "scan rate" benchmarks split the difference and use impressions where they can measure them (a media-buy's reported impressions, a print run's circulation figure) and educated estimates where they can't (foot traffic past a sign, table turns in a restaurant). Treat scan-rate benchmarks as the right order of magnitude rather than a precise comparison.

The second thing to check is whether bots are filtered. Microsoft Defender, Mimecast, and Proofpoint pre-fetch links in corporate inboxes to scan for malware — they generate clicks no human ever made. Google Ad's filtered IVT (invalid traffic) report is also imperfect. The corporate-gateway distortion is one of the failure modes the tracking links in email post covers in depth; for QR codes, the equivalent is page-pre-fetch from messaging apps that follow the resolved URL after a scan. Subtract a generous 5-15% from any raw click count for email; 1-3% for QR scans, where the only bot-shaped traffic comes from follow-on pre-fetchers after the scan happened.

Email — the channel with the cleanest benchmarks#

Email CTR has the most-studied numbers in marketing, mostly because every email service provider publishes industry averages from their own customer base. The shape is consistent across providers and across years.

Three sources to anchor email CTR:

• Mailchimp's customer-base benchmark (refreshed annually) reports an industry-average CTR around 2.6% across its catalogue of senders, with sector medians spanning roughly 1.4% to 4.6%.
• Campaign Monitor's customer benchmark, drawn from a different sender base, lands at an industry average of approximately 2.3% across sectors.
• HubSpot's annual State of Marketing report gives a similar range — usually 2-3% as the broad-market expectation for transactional and marketing email.

Three caveats on the numbers. First, CTR is calculated against deliveries, not opens — a 25% open rate and 10% click-to-open rate produces a 2.5% CTR. Some providers quote the click-to-open rate (CTOR) instead, which makes any campaign look more successful than the CTR alone suggests. Cross-check which number you're being shown. Second, transactional emails (password resets, order confirmations, magic links) regularly see CTRs above 15% — they're a different category and skew industry averages if mixed in. Third, the open-rate denominator has been broken since 2021, when Apple Mail Privacy Protection started pre-fetching images and inflating apparent open counts on iCloud-routed mail; click rates remain trustworthy, but the click-to-open ratio drifted down across the industry without any underlying behaviour change.

A practical interpretation: if a marketing email broadcast to a clean list lands above 2% CTR, you're at or above industry average. Above 4% is strong. Below 1% on a non-transactional broadcast is a campaign that's losing on either subject line, offer, or list quality — the hidden cost of not tracking your short links post covers the diagnostic order for that drop, since the standard mistake is to retest the offer when the list segment was actually the problem.

SMS — short, urgent, high-CTR#

SMS is the highest-CTR channel in the published-benchmark world, with the caveat that "short message + urgent CTA + opted-in audience" is the format that survives, not "SMS as a generic broadcast tool". Treat SMS CTRs as a property of the format, not of the channel.

Three numbers worth knowing:

• Attentive Mobile's annual SMS benchmark report puts the median SMS marketing CTR around 10-15% for engaged opt-in audiences, with the range spanning 7% to 25% depending on industry and offer.
• Klaviyo's customer benchmark reports a typical 15% CTR for promotional SMS to active subscribers.
• The CTIA (the US wireless industry trade group) reports SMS open rates above 95% within the first three minutes — every CTR benchmark assumes the message was read, because almost all of them are.

The structural reason SMS CTRs run an order of magnitude higher than email: the inbox is small (one open SMS thread, not a 200-message email backlog), the cost to send is high enough that operators self-filter to high-relevance messages, and the format itself implies urgency. The constraints of the 160-character segment matter — the URL shortener for SMS marketing post covers the technical limits, and a campaign that uses a 5-character branded short slug instead of a 25-character bit.ly link gets back roughly 10% of the message body for actual content, which feeds directly into the CTR.

A practical interpretation: SMS marketing CTRs below 7% suggest list quality, message timing, or carrier deliverability problems. Above 20% on opt-in promotional SMS is strong. Above 30% usually means a small list of highly-engaged subscribers, not a number that scales to broader audiences.

Paid social and organic social — where it gets messy#

Paid social CTR varies more by platform, format, and audience targeting than almost any other channel. Meta's published 2024 industry benchmarks for Facebook and Instagram ads cluster around 1-2% CTR for feed placements, with carousel and story placements lower. LinkedIn's published benchmark for sponsored content is around 0.5-1% CTR. TikTok's reported CTRs for in-feed video ads cluster around 1-2% but vary widely by creator-content match.

Organic social is harder. Most platforms don't expose impression-level click data to non-business accounts, and the "click" definition varies — Instagram's link clicks are different from its "link sticker taps" in stories, which are different from the bio link taps mentioned in the Instagram bio link strategies post. The honest answer for organic social CTR benchmarks is that there is no single industry-wide number worth citing, because the channels don't share a measurement model.

What's worth pulling out:

• LinkedIn organic posts. Industry chatter suggests ~1-3% engagement rate (likes, comments, shares) and a small fraction of that as actual link clicks. LinkedIn's own published data is largely advertising-focused.
• Twitter/X. The platform's published metrics shifted multiple times since 2023; reliable per-post CTR benchmarks are no longer maintained publicly by the company.
• Instagram bio link. The single bio URL receives the bulk of profile-tap traffic when a post says "link in bio"; the creator-economy benchmark studies cite a 70-80% concentration in the 48 hours after the prompting post.

Paid display and programmatic — the lowest baseline that still pays#

Google Display Network's published documentation cites a typical CTR around 0.35-0.5% across the network, with the qualifier that "good" varies enormously by vertical and creative. IAB and DoubleVerify data on programmatic display sit lower still — typical CTRs of 0.05-0.1% are routine, and a banner above 0.2% is considered strong performance by the trade body's reporting.

The reason display works at those numbers is the impression cost. A 0.05% CTR at a $2 CPM is a roughly $4 cost-per-click — comparable to or below the average search-ad CPC for the same vertical. The metric to optimise on display is rarely CTR alone; it's CPC, cost-per-acquisition, and view-through conversions, because most display impressions are seen but not clicked, and the conversion lift comes through the brand-recall channel rather than the click.

Google Search Ads sit at the other end. The published average CTR across verticals is roughly 3-6%, with high-intent commercial queries pushing above 10% and informational queries running below 2%. The structural difference: search ads land on queries the user typed, so the implied intent match is higher than any other paid channel.

"Good" CTR isn't a number — it's a number against the right baseline. A 0.1% display CTR is profitable; a 0.1% email CTR means the list is dead.

QR scan rate — the channel where benchmarks get rough#

QR scan-rate benchmarks are the messiest part of this post, and worth a moment of honesty: most published "industry average" scan rates come from QR-platform vendors with a strong incentive to report flattering numbers, drawn from customer cohorts that don't represent the broader market. The widely-circulated "60-million-scans-in-2022 in the US" type figures come from Statista panel data and Bluebird/Insider Intelligence projections, and they describe total scanning behaviour rather than scan-to-impression rates.

A few numbers with reasonable sourcing:

• Retail packaging. GS1's industry analysis on the rollout of GS1 Digital Link (the standard merging product barcodes with QR codes) describes typical scan-to-purchase rates in the 1-5% range across consumer packaged goods pilots, with food and beverage at the high end of that range.
• Print magazines. Industry coverage from Magazine Media (the MPA) cites scan-rate ranges of roughly 0.5-3% of circulation for full-page or partial-page QR codes in consumer magazines, with the higher end coming from inserts with explicit "scan to enter" or "scan for sample" prompts.
• Out-of-home (billboards, transit). The Out of Home Advertising Association of America (OAAA) tracks QR use in OOH campaigns; reported scan rates against impressions are typically below 1%, often in the 0.1-0.5% range, because OOH impressions count anyone who passes the surface.
• Direct mail. USPS-published research on QR codes in direct mail has cited response-rate lifts on the order of 1-3 percentage points when a QR is added to a mailpiece with a clear call to action, though the absolute scan rate on the QR itself is rarely the headline metric.

What's not well-sourced enough to cite: a single "industry-average" QR scan rate across all channels. Several QR-platform vendors publish their own customer-base averages (often 5-20% scan rate across the customer base), but those numbers are self-selected to surfaces where someone already decided to deploy a QR campaign. They're not comparable to your scan rate unless your deployment context matches theirs.

A practical interpretation: for a print or outdoor QR, expect 1-3% scan-to-impression as a typical band; treat below 0.5% as low and above 5% as strong. For a packaging QR sitting next to a clear CTA ("scan for recipe", "scan to register"), expect 5-15% scan-to-purchase. For a QR on a sign at a checkout counter or restaurant table, where the surface is held in hand for minutes, 10-30% is achievable. The QR code domain matters post covers the trust effect on whether a scanner who lands on the destination preview screen taps through, which is the second filter in the QR funnel. Platform-specific destinations have their own benchmark wrinkle — a Snapchat-bound QR splits scans between Snap-installed users who deep-link straight into the app (untracked at the web layer) and non-Snap users who hit the web fallback, and the breakdown of standard QR vs proprietary Snapcode placements walks through what that split costs in scan-side analytics.

The pattern: the closer the QR is to the user's hand, the higher the scan rate and the lower the source quality on industry-wide benchmarks. A QR on a billboard 30 meters away gets scanned by a sliver of passersby and there's good aggregate data on it. A QR on the table where someone is already sitting and waiting for their food gets a much higher scan rate, but there's no reliable industry-wide number because the universe of "people who sat at that table" isn't measurable from outside the restaurant.

How to read your own numbers#

Three questions when your CTR or scan rate looks worse than expected.

Is your denominator the same as the benchmark's denominator? Mailchimp's CTR is clicks/deliveries. If your platform reports CTR as clicks/opens (CTOR), your number will look much higher than the benchmark and you'll mis-read your performance as strong. Conversely, if you compare a QR scan rate against a benchmark that uses media-buy impressions while your scan rate uses a footfall estimate, you're comparing two different denominators and the gap might be measurement, not performance.

Have you stripped bot traffic out of the click count? Corporate inbox scanners can add 10-20% phantom clicks within seconds of a marketing email delivery. If your click counts haven't been filtered for that — most platforms don't filter aggressively by default — your CTR is inflated and the conversion rate downstream looks broken in a way that doesn't reflect reality. The short link not tracking clicks debug guide walks through the eight specific places that inflation creeps in.

Are you comparing to the right channel benchmark? A B2B drip campaign sent to a list of trial users isn't comparable to a B2C newsletter to a 200,000-person consumer list. Vertical matters; intent matters; list age matters; the absolute "industry average" is the right starting point but not the right finish line for evaluating a specific campaign. The 95th percentile inside a single industry-and-list-segment cell is usually 2-3x the cross-industry median.

If after those three checks your number still looks low, the diagnostic order is content first, list second, channel third. A poor CTR on a healthy list usually means the offer or the subject line missed; a poor CTR on a tired list won't be fixed by better copy.

The benchmark widget — where do your numbers fall?#

The widget gives you a rough band to read your number against. It doesn't replace running your own historical baseline — your own past campaigns are a stronger comparator than any industry average — but it gets you to "is this in the expected order of magnitude" within a few seconds.

Building your own internal benchmark#

Industry averages are useful for a single number; your own historical data is what you should be optimising against. Two practical moves.

Tag every campaign consistently. UTM parameters on every link, in the structured form that survives platform handling, so that a year from now you can pull all email/SMS/social/print campaigns from the same time period and compare them on consistent dimensions. The single most common reporting problem in marketing isn't bad data — it's inconsistent tagging that makes year-over-year comparisons impossible.

Separate the click measurement from the conversion measurement. A CTR of 4% on a campaign that converts at 0.1% downstream is worse than a CTR of 2% on a campaign that converts at 1%. The honest metric for most senders is clicks × conversion rate × average order value, not raw CTR. The conversion tracking with QR codes and short links post walks through the server-side postback that closes the loop between click and revenue without per-recipient identifiers.

A practical setup: track CTR per campaign, scan rate per surface, and conversion rate from each. Roll the data into a single spreadsheet or analytics page that updates weekly. After 12 months, your internal baseline is more useful than any external benchmark, because it's your audience, your offer, and your channel mix — not a cross-industry average. The platform-side analytics for this live in the analytics docs and the traffic docs.

What "success" means in different channels#

A frame worth keeping in mind: CTR and scan rate are intermediate metrics. They aren't the goal. The goal varies by channel.

Email and SMS. The goal is usually direct conversion — a click that leads to a purchase, signup, or other revenue event. CTR is the leading indicator; conversion rate is the actual measure. A high CTR with no conversions means the click was driven by the subject line or wrap, not the destination — the email worked at the inbox but failed at the page.

Paid display and programmatic. The goal is usually attributable impact at acceptable cost. CTR is one signal but view-through conversions (the user saw the ad, didn't click, but converted later) are often as important. Strong campaigns optimise on CPC and CPA, not CTR alone.

Print and outdoor with QR. The goal varies by surface. A QR on packaging with a "scan for recipe" CTA targets engagement after the purchase happened. A QR on a billboard targets a tiny fraction of passersby and treats the brand-recall effect of the billboard itself as the primary value. Scan rate is the proxy; the actual return depends on what the destination does.

Restaurant menu, event signage. The goal is usually a service substitution (skipping a queue, opening a menu, completing a check-in). High scan rates are expected here because the friction substitute is real and immediate. Low scan rates usually mean the alternative path (human help, paper menu, traditional check-in) is easier than the QR path — fix the path before optimising the code.

You can interrogate any of these further with the free short-link generator, which lets you spin up a test slug and watch its real-time scan and click data before committing to a print run or a campaign send. For QR-specific surface testing, the free QR code generator does the same for static and dynamic codes with built-in analytics on every scan.

A short note on year-over-year drift#

Benchmark numbers drift. Email CTRs drifted down across the industry from the mid-2010s to the early 2020s as inbox volume climbed and engagement fragmented. Display CTRs have been roughly flat for a decade because the format is calibrated to its CPM. SMS CTRs spiked during 2020-2021 as a pandemic-era channel and have since normalised slightly lower but remain well above pre-2020 levels.

The implication for reading benchmarks: a number cited in a 2018 marketing article is not directly comparable to your 2026 campaign. Look for benchmarks dated within the last two years, and treat older citations as historical context rather than current targets. The Mailchimp, Campaign Monitor, and Attentive benchmarks linked in the sources below are refreshed annually and worth bookmarking for the same campaign categories year over year.