--- title: "Trial-Site Traffic: Patients or HCPs? No Public Split Found" description: No public source splits trial-site traffic by patients and HCPs. Here's the registry data, plus what we found in a sponsor trial site's analytics. --- [xds.](https://madebyxds.com/) [Start a Project](https://madebyxds.com/contact-xds/) About us A founder-driven consultancy built around experience, clarity, and collaboration. - [More on XDS→](https://madebyxds.com/about-xds/) - [Insights→](https://blog.madebyxds.com/) - [Careers→](https://madebyxds.com/xds-careers/) - [Contact us→](https://madebyxds.com/contact-xds/) Our services Strategy, design, marketing, and technology working together to move healthcare forward. - [Services overview→](https://madebyxds.com/services/) - [Brand strategy→](https://madebyxds.com/services/brand-strategy/) - [Product & experience design→](https://madebyxds.com/services/product-experience-design/) - [Digital marketing→](https://madebyxds.com/services/digital-marketing/) - [AI, innovation & technology→](https://madebyxds.com/services/ai-innovation-technology/) Our work See how we turn complex healthcare challenges into meaningful experiences. - [Featured case studies→](https://madebyxds.com/the-work/) - [Shockwave→](https://madebyxds.com/the-work/shockwave-medical/) - [Upneeq→](https://madebyxds.com/the-work/upneeq/) - [Arcus→](https://madebyxds.com/the-work/arcus-biosciences-dx/) - [AngioSafe→](https://madebyxds.com/the-work/angiosafe-cardiovascular/) - [Aidoc→](https://madebyxds.com/the-work/aidoc-seo-strategy/) - [Seer Bio→](https://madebyxds.com/the-work/seer-bio/) [Start a Project](https://madebyxds.com/contact-xds/) Insights from XDS # Patient vs. HCP Traffic on Trial Sites: What the Data Shows Last Updated: October 14, 2026 **TL;DR** No published source splits pharma sponsor trial-site traffic between patients and healthcare professionals (HCPs). The closest public figure is ClinicalTrials.gov's 2019 user survey, where 5% of respondents identified as healthcare providers. Our own analysis of a sponsor trial site shows why the split stays hidden: default GA4 reporting can misplace paid traffic, and key events usually measure only patient behavior, so HCP use never shows up. ## Table of Contents - [Why audience mix matters for planning](https://blog.madebyxds.com/trial-site-traffic-patients-or-hcps-no-public-split-found#why-audience-matters) - [What the public registry shows](https://blog.madebyxds.com/trial-site-traffic-patients-or-hcps-no-public-split-found#public-registry) - [What the research on trial participation shows](https://blog.madebyxds.com/trial-site-traffic-patients-or-hcps-no-public-split-found#trial-research) - [What we found on a sponsor trial site](https://blog.madebyxds.com/trial-site-traffic-patients-or-hcps-no-public-split-found#what-we-found) - [Why the gap exists](https://blog.madebyxds.com/trial-site-traffic-patients-or-hcps-no-public-split-found#why-gap-exists) - [What we could not find](https://blog.madebyxds.com/trial-site-traffic-patients-or-hcps-no-public-split-found#what-we-could-not-find) - [How a sponsor can answer it for its own site](https://blog.madebyxds.com/trial-site-traffic-patients-or-hcps-no-public-split-found#answer-for-your-site) - [FAQ](https://blog.madebyxds.com/trial-site-traffic-patients-or-hcps-no-public-split-found#faq) - [Related Reading](https://blog.madebyxds.com/trial-site-traffic-patients-or-hcps-no-public-split-found#related-reading) - [Talk to XDS about your trial-site analytics](https://blog.madebyxds.com/trial-site-traffic-patients-or-hcps-no-public-split-found#cta) We wanted a published breakdown of patient versus HCP traffic on pharma clinical trial websites. We didn't find one for sponsor sites. The closest public figure comes from ClinicalTrials.gov, which surveyed its users in 2019. That's a registry, not a sponsor's site, so it doesn't settle the question for pharma. So we went to the data ourselves. When we dug into a sponsor trial site's analytics, the reason nobody publishes this split became obvious. Most sites aren't set up to see it. ## Why audience mix matters for planning Audience mix shapes what the site needs. A patient-heavy site leads with plain-language eligibility and an explanation of what participation involves. An HCP-heavy site needs protocol summaries, site locator information, and referral paths. Get the mix wrong and effort goes to the wrong reader. A site built for patients can frustrate a clinician looking for protocol detail, and a site built for clinicians can lose patients who arrived from a condition search. ## What the public registry shows ClinicalTrials.gov surveyed its users from July to December 2019 and received 3,399 responses. Respondents identified as 24% patients, 8% family or friends, and 5% healthcare providers. Researchers and other professionals made up 49%.\[3\] Two cautions apply. The survey is self-reported, so people chose their own role. And a registry's audience leans toward researchers. The number tells you something about registries. It doesn't tell you how a drug sponsor's site is used. ## What the research on trial participation shows Published work on trial participation mostly addresses comprehension and access, not traffic. A 2012 study of an online clinical trial matching site for breast cancer noted that less than 5% of breast cancer patients participate in clinical trials.\[1\] A 2019 pilot study tested a web-based decision aid with 100 patients and 100 caregivers. The authors reported that the site may help improve eHealth literacy, and that proficiency as an online health consumer was linked to how acceptable participants found the tool.\[2\] That work helps you decide how patient-facing content should read. It doesn't measure who visits a site. Do you know who's visiting your trial site? We review your GA4 setup and show you which audiences your reports can see, and which ones they can't. [Get a trial-site analytics review](https://madebyxds.com/contact-xds/) ## What we found on a sponsor trial site We reviewed GA4 data from a pharma sponsor's trial recruitment site covering 2025 and 2026. We're sharing patterns and ratios, not volumes or details that could identify the sponsor. Four findings stood out. ### Default channel reports hid more than half the paid traffic In some months, over half of all sessions landed in GA4's Unassigned channel. At first glance that reads like a consent or tracking failure. It wasn't. The traffic was paid social, and GA4's default channel rules simply don't recognize every campaign medium that media partners use. The visits were tracked fine. They just weren't labeled. Trial sites usually run several media partners at once, so this is common, and a custom channel group fixes it without touching any campaign. If your channel report shows a large Unassigned bucket, look at how the traffic is labeled before you blame the consent banner. ### Every key event measured patients, so HCPs were invisible The site's key events were built around the patient prescreener: confirming age, starting prequalification, entering a location. That's the right thing to measure for recruitment. It also means the analytics had no way to register an HCP visit. A clinician who reads protocol details and leaves creates no conversion. When a site defines success only in patient terms, its data can't answer the audience question. Not sure what your key events can and can't see? [Ask us to map your trial-site events to both audiences →](https://madebyxds.com/contact-xds/) ### Organic and direct visitors behaved like a second audience Paid visitors went into the prescreener. Organic and direct visitors did something else: they clicked out to the public registry about 20 times as often as paid search visitors. Leaving for full protocol detail is plausible behavior for HCPs, study coordinators, or well-informed caregivers. We can't confirm who they were. But it's a distinct segment, and the site's measurement wasn't built for it. ### One channel's results were too good to trust without checking A programmatic display buy recorded key events on almost nine of every ten sessions, mostly on the first prescreener click. No other channel came close, and the traffic stopped abruptly. That pattern fits either an unusually efficient buy or invalid traffic clicking through the first screen. The only way to tell is to compare it with actual referrals to study sites. Treat any channel that dramatically outperforms the rest as a question, not a win. ## Why the gap exists Sponsors and agencies keep trial-site analytics private, so the audience split rarely gets published. The bigger obstacle is that GA4 isn't built to answer it out of the box. It has no audience dimension, its default channel rules miss common media labels, and recruitment sites rightly prioritize patient conversion events. Seeing HCP behavior takes deliberate setup on top of that. ## What we could not find - No published source reports a patient versus HCP traffic split for a pharma sponsor's trial website. - Trial-recruitment studies we reviewed report visits, referral sources, and conversions, but not the role of the visitor. - The public registry is the only source we found with a real audience split, and it is a self-reported survey from 2019. - Our own site analysis can't confirm visitor roles either. It shows behavior patterns, not identities. - Our search was broad, not exhaustive. A sponsor with its own data may have an answer we can't see. ## How a sponsor can answer it for its own site Start with the channel data. Build a custom channel group that recognizes every medium your media partners use, so paid social, display, and vendor traffic land where they belong. Filter test traffic out of production reporting. Then measure more than the prescreener. Track registry click-outs, protocol and document downloads, site locator use, and visits to HCP sections as their own events. Segment by landing page and path, and by referral source. Where consent allows, add a short self-identification question and build GA4 audiences from the answers. Finally, validate your best-looking channel against downstream referrals before you scale it. A sponsor's own visitor data will plan that site better than any industry average, but only if the data is set up to see both audiences. ## FAQ ### Is there a published patient vs. HCP traffic split for pharma trial websites? Not for sponsor sites that we found. The closest public figure is ClinicalTrials.gov's 2019 user survey, which is self-reported and covers a registry, not a drug sponsor's site. ### What did the ClinicalTrials.gov survey find? Of 3,399 respondents surveyed from July to December 2019, 24% identified as patients, 8% as family or friends, and 5% as healthcare providers. Researchers and other professionals made up 49%. ### Why does a trial site show so much Unassigned traffic in GA4? Often because GA4's default channel rules don't recognize every campaign medium media partners use. On one sponsor site we reviewed, over half of sessions in some months were paid social traffic sitting in Unassigned. A custom channel group fixes it. ### Why can't most trial sites measure HCP visits? Their key events are built around the patient prescreener. An HCP who reads protocol details and leaves triggers no conversion, so their visits are invisible in the reports that matter. ### Can a sponsor measure its own audience split? Yes. Build a custom channel group, track HCP behaviors like registry click-outs and document downloads as events, segment by landing page and referral source, and add self-identification where consent allows. ## Related Reading - [Pharma SEO versus pharma AEO in 2026](https://blog.madebyxds.com/pharma-seo-vs-pharma-aeo-what-changed-in-2026), why the search layer HCPs use has changed. - [How to measure AI search leads in GA4 without overclaiming attribution](https://blog.madebyxds.com/measure-ai-search-leads-ga4-healthcare-b2b), a scorecard approach to channel measurement. - [Cookie consent for life sciences websites](https://blog.madebyxds.com/cookie-consent-for-life-sciences-websites-configuring-gtm-and-ga4-without-breaking-analytics-or-inviting-a-lawsuit), how to configure consent before adding audience signals. --- ## Talk to XDS about your trial-site analytics If you can't say how many of your trial-site visitors are patients and how many are HCPs, your site is being planned on assumptions. We can fix that. Start with a trial-site analytics review 1. We check how your channel reporting labels every media partner's traffic. 2. We map your key events against both patient and HCP behavior. 3. You get a measurement plan that shows who your site actually serves. [Book an analytics review](https://madebyxds.com/contact-xds/) Prefer to talk it through first? [Start a conversation with our team](https://madebyxds.com/contact-xds/). ## Sources 1. Cohen E, Belkora J, Tyler J, et al. Adoption, Acceptability, and Accuracy of an Online Clinical Trial Matching Website for Breast Cancer. J Med Internet Res. 2012. [https://pmc.ncbi.nlm.nih.gov/articles/PMC3409596](https://pmc.ncbi.nlm.nih.gov/articles/PMC3409596) 2. Flood-Grady E, Neil JM, Paige SR, et al. A Pilot Study Determining Comprehension and the Acceptability of a Cancer Research Study Website for Cancer Patients and Caregivers. J Cancer Educ. 2019. [https://pmc.ncbi.nlm.nih.gov/articles/PMC7015148](https://pmc.ncbi.nlm.nih.gov/articles/PMC7015148) 3. Williams RJ. ClinicalTrials.gov Modernization and How to Provide Your Input. FDA SBIA webinar, March 6, 2020, slide 15 (users by role). [https://sbiaevents.com/files2/Webinar-2020-03-06.pdf](https://sbiaevents.com/files2/Webinar-2020-03-06.pdf) 4. XDS own GA4 analysis. ## Related insights [All insights →](https://blog.madebyxds.com/) ### [Ensuring Cookie Consent Compliance for Life-Science Websites](https://blog.madebyxds.com/cookie-consent-for-life-sciences-websites-configuring-gtm-and-ga4-without-breaking-analytics-or-inviting-a-lawsuit) ### [How to Measure AI Search Leads in GA4 Without Overclaiming Attribution](https://blog.madebyxds.com/measure-ai-search-leads-ga4-healthcare-b2b) ### [Pharma Influencer Landing Pages: Review the Journey, Not Just the Post](https://blog.madebyxds.com/pharma-influencer-landing-page-review) We’ll Navigate the Chaos ## Let’s work together. 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