AllSERP: Exhaustive Per-Element Enrichment of the Versatile AdSERP Dataset

TL;DR

AllSERP is a comprehensive dataset that enriches the AdSERP corpus with detailed per-element annotations, enabling fine-grained analysis of user interactions on Google SERPs.

Contribution

It introduces pixel-accurate bounding boxes, semantic element types, and click attribution for the AdSERP dataset, enhancing its utility for search behavior research.

Findings

91.7% click attribution achieved with the new annotations

Internal consistency in ad-vs-non-ad classification across the dataset

Reproducible pipeline and tools provided for analysis

Abstract

We release AllSERP, a typed AOI and per-element behavioral enrichment of the AdSERP commercial-intent SERP corpus [4]. AdSERP ships 2,776 trials of full-page screenshots, captured SERP HTML, 150 Hz Gazepoint eye tracking, evtrack mouse telemetry, scroll, and pupil signals against real Google SERPs collected before AI Overviews -- but its bounding boxes cover only ad surfaces (15.5 % of attributable clicks). AllSERP adds pixel-accurate organic and widget bboxes via screenshot-anchored CV, semantic types across thirteen element types via an HTML parser, an inter-result gap-fill flavor (typed_gapfill), and X+Y click attribution that reaches 91.7 % of the corpus while flagging the rest at trial level. The Phase C ad-vs-non-ad partition is internally consistent with the shipped ad rectangles (0 disagreements across 38,250 classifications). We ship the pipeline, per-trial JSONs, a corpus CSV, and a browser-based replay viewer; everything is reproducible from the AdSERP Zenodo volume. The release enables per-element click, fixation, regression, and above-fold analyses that the shipped ads-vs-organic split could not resolve.