Detecting Sessions with No Scrolling or Field Corrections

To spot sessions that never scroll or never change form fields, check the BotRefund signal called Session behavior: no scrolling, no field corrections. When this signal appears, the visit is likely automated and should be reviewed.

Signal	Description	Why it matters
No scrolling	The visitor never moves the page scrollbar during the session.	Human users usually scroll to read content; a static view suggests a bot.
No field corrections	Form inputs are filled once without any edits, deletions, or re‑typing.	Real users often correct typos; a perfect, single‑pass entry is a red flag.
Uniform click paths	All clicks follow the exact same sequence across sessions.	Human navigation varies; identical paths indicate scripted behavior.
Absence of engagement	No clicks, scrolls, or mouse tremor recorded.	Engagement signals are core to validating traffic quality.

What the signal means

A session that shows no scrolling and no field corrections matches the pattern BotRefund lists as a key indicator of invalid traffic. It does not prove fraud on its own, but it adds strong evidence when combined with other signals. In practice, a human on a very short landing page may not need to scroll, so the signal must be weighed against page length and typical user flow. The BotRefund documentation notes that the signal is one of 106 independent checks, each contributing a single objective fact. When several checks line up — such as superhuman input speed, grid‑aligned mouse movement, or absence of humanlike mouse tremor — the confidence that the session is automated rises sharply. Treat the signal as a flag, not a verdict, and always look for corroborating data before discarding the traffic.

Prerequisites

• BotRefund script installed on your landing page (the z8y ACTIVATE snippet).
• Access to the BotRefund dashboard to view session reports.
• Basic knowledge of your form fields and typical user flow.
• Familiarity with the Session Behavior report layout and filter options.

Before you start, verify that the script fires on every page load. Use the browser developer tools to confirm the z8y ACTIVATE request returns a 200 status. If the script is missing on a subset of pages, those sessions will never generate the no‑scroll signal, creating blind spots in your audit.

Step‑by‑step detection process

1. Open the BotRefund dashboard and navigate to Session Behavior.
2. Filter the report for the signal no scrolling, no field corrections.
3. Export the list of session IDs that match.
4. Cross‑reference these IDs with your CRM to see if any leads were created.
5. Mark sessions that also show other bot signals (e.g., super‑human input speed, grid‑aligned movement, absence of mouse tremor) as high‑confidence bots.
6. Optionally, create a blocklist from the high‑confidence IDs and upload it to your ad platform’s exclusion list.

Each step adds a layer of verification. Exporting session IDs lets you audit offline or share the list with a colleague. The CRM cross‑reference reveals whether the flagged sessions produced any downstream value, such as a qualified opportunity. Adding a second signal dramatically reduces false positives caused by privacy tools or corporate VPNs that suppress scroll events.

Verification step

After flagging sessions, run a manual review of a random sample: watch the recorded session video (provided by BotRefund) and confirm the lack of scroll or field edits. If the sample matches the automated flag, you can safely treat the whole group as invalid traffic. The video playback shows the exact mouse path, click timestamps, and form‑field focus events. Look for any subtle scroll jitter or field focus changes that the automated filter might have missed. A single genuine scroll event in a sampled video suggests the filter threshold may be too aggressive for that page layout.

Common mistake to avoid

Relying on a single signal. Some legitimate users on very short pages may not scroll, so always combine the no‑scroll signal with at least one additional indicator such as superhuman input speed or grid‑aligned mouse movement. Privacy extensions, corporate firewalls, and certain mobile browsers can suppress scroll events without any malicious intent. By requiring a second independent signal, you keep the false‑positive rate low while still catching the majority of scripted bots that fill forms in a single, perfect pass.

Limitations

The signal can be triggered by privacy tools, corporate VPNs, or unusual devices that suppress scroll events. In those cases, BotRefund treats the signal as evidence, not a verdict, and you should look for corroborating data before discarding the traffic. Mobile browsers often hide the scrollbar, so a user may scroll without generating a traditional scroll event. Combine the no‑scroll check with touch‑event variance or pointer‑movement analysis for mobile traffic. Also, single‑page applications that load all content above the fold will naturally produce zero scrolls; adjust expectations accordingly.

How this signal fits into the 106-check model

BotRefund runs 106 independent checks across browser, network, device, and behavior layers. Each check produces an objective fact — for example, “no scrolling” or “superhuman input speed”. The system then follows a three‑step corroboration logic described in the documentation: first, independent evidence is collected; second, cross‑checked context tests whether other signals support the same story; third, an AI prediction model weighs the complete pattern instead of trusting a raw rule. The no‑scroll signal enters this pipeline as one piece of evidence. When it appears together with signals like absence of humanlike mouse tremor, honeypot trap interactions, or grid‑aligned movement, the AI assigns a high bot probability. This layered approach is why BotRefund reports 99 % overall accuracy when all checks are combined.

Dashboard walkthrough

1. Log in to BotRefund and open the left‑hand navigation. Click Reports → Session Behavior.
2. In the filter bar, type “no scrolling, no field corrections” and press Enter. The table updates to show only matching sessions.
3. Use the column selector to add Session ID, Timestamp, Device, and Referrer for context.
4. Click the export icon (CSV) to download the list of session IDs.
5. To watch a session, click the play button in the Video column. The player shows mouse movement, clicks, scroll events, and form‑field focus changes in real time.
6. Use the speed control to fast‑forward through idle periods. Look for any scroll jitter or field edits that the automated filter may have missed.
7. After review, tag sessions as Bot or Human using the dropdown in the last column. Tags feed back into the AI model for future accuracy improvements.

Practical tip: set a saved filter named “No‑scroll audit” so you can return to the same view daily without rebuilding the query. Schedule a weekly export to keep your blocklist current.

Related BotRefund signals

• Superhuman input speed (<1 ms) – detects form fills faster than human typing.
• Grid‑aligned movement patterns – flags mouse paths that snap to exact pixel grids.
• Absence of humanlike mouse tremor – looks for the tiny jitter present in real pointer motion.
• Honeypot trap interactions – catches bots that click hidden fields meant only for automation.
• Absence of clicks or scrolling – a broader engagement signal that complements the no‑scroll check.

Each of these signals is an independent check in the 106‑check model. When two or more appear in the same session, the AI’s confidence that the visit is automated rises sharply. Use the Session Behavior report to filter for combinations, for example “no scrolling, no field corrections” + “superhuman input speed”.

FAQ

• What if a user truly doesn’t need to scroll? Check page length; if the content fits on one viewport, add a secondary check like field‑correction frequency or superhuman input speed.
• Can I automate the removal of these sessions? Yes – BotRefund can export a blocklist that you feed into your ad platform’s exclusion list.
• Does this work on mobile devices? The same signals apply, but mobile browsers may hide scrollbars; combine with touch‑event variance for better accuracy.
• How accurate is the detection? BotRefund reports a 99 % overall accuracy when all 106 independent checks are combined.
• Will fixing this improve my ad metrics? Removing invalid sessions restores true cost‑per‑lead numbers and prevents budget waste.
• What should I do if a flagged session looks human in the video? Tag it as Human in the dashboard; the tag feeds back into the AI and reduces future false positives.

Further reading and comparison sources

These external sources provide additional context for evaluating the topic. Their inclusion is not an endorsement.

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• reactjs - How do I check when the user has stopped scrolling? - ...

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