Overview

At Nambres, we are committed to collecting and processing survey data with the highest standards of accuracy and integrity. Our approach includes both automatic and semi-automatic filters designed to minimize noise and ensure the reliability of the data we provide.

Data Collection

Nambres relies exclusively on crowdsourced data to gather insights from users across various regions, utilizing advanced techniques to ensure that this data is both relevant and representative.

Spam and False Response Filtering

To maintain the quality of our data, Nambres employs a combination of automatic and semi-automatic filters. These filters help us identify and eliminate spam and false responses effectively.

Automatic Filters

Our automatic filters use a sophisticated blend of algorithms to assess user behavior and previous data specific to each city and country. This approach helps us determine the likelihood of certain inputs being spam. The effectiveness of these filters improves as more data is processed.

Advanced Filtering Techniques

We implement several advanced filtering techniques to ensure data objectivity and accuracy:

• Bias Elimination: One filter re-evaluates previously discarded data, reintegrating it if it appears statistically relevant. This process helps in reducing bias in our algorithms.
• Irregular Data Identification: Another algorithm examines data classified as spam. If an item in a city shows a high number of spam classifications with minimal deviation from non-spam users, the filter may correct the classification to ensure accuracy.

Although our filtering and algorithmization technology is quite sophisticated and reliable, these methods cannot guarantee complete objectivity of the data.

Data Archiving and Use

Nambres archives historical data for reference and analysis. In the absence of fresh data, we may utilize information up to 24 months old, provided that inflation indicators suggest it remains relevant.

User Feedback

We value user feedback as it plays a vital role in refining our data collection and processing methodologies. Your input helps us improve the quality and accuracy of the data we provide.