Google Results (merged)

Google Results Dataset
This dataset captures the number of Google-indexed pages that mention each target brand over a ten-year period (2014–2024). To extract this data, we employed a monthly querying strategy using Google Search’s built-in time filter capabilities. Specifically, the following advanced search operator was used for each brand and month:
"keyword" after:YYYY-MM-DD before:YYYY-MM-DD
For example, the query:
"Brand Name" after:2014-01-01 before:2014-02-01
retrieves the number of indexed pages containing the keyword within January 2014. This approach was applied for each month over the study period and for both brands (“Hamrah-e-Aval” and “Irancell”), resulting in a longitudinal dataset representing the digital content footprint of each brand across time.
All collected monthly results were stored in tabular format, forming the basis for indicators related to Share of Voice(SOV) in Google.
Google Search Index Retrieval Procedure and Stability Considerations
Google Search index counts are approximate by design and may fluctuate across days, devices, interfaces, and changes in Google’s retrieval policies. To minimise these instabilities, all monthly index measurements for both brands (“Irancell” and “Hamrah Aval”) were collected simultaneously and under identical conditions, ensuring that any temporary fluctuations or policy changes affected both brands in the same direction. This avoided the bias that would arise if one brand were queried on one day and the second brand on another day.
To assess the magnitude of natural fluctuations, the same monthly extraction procedure was repeated on multiple days. Although minor variations were observed, the relative difference between the two brands remained consistently stable across repetitions. While no formal statistical averaging (e.g., mean/variance) was applied, visual inspection across repeated pulls confirmed that fluctuations did not materially alter the directional relationship between the brands.
This behaviour aligns with well-documented properties of large-scale web data: even when raw counts are noisy or partially unavailable, comparative and ratio-based indicators remain stable and analytically meaningful, because behavioural patterns are encoded in relative rather than absolute magnitudes.
All data were collected manually—due to Google’s restrictions on automated scraping—using the official Google Web Search interface under a fixed locale (Iran), without VPN, using a desktop Chrome browser, and in the native Persian-language interface. This ensured full compliance with Google’s usage policies and guaranteed consistent retrieval conditions.
Given the known approximations of Google index counts, the SOVG and SOVGR indicators are interpreted as relative directional measures, where stability in ratios and trends is more important than absolute values. Normalisation to a 0–100 scale further mitigates the impact of minor fluctuations or partial unavailability of indexed pages.