AIM - Data Quality in Market Research

Quality

Our Commitment to Delivering Superior Market Research for Strategic Business Growth

AI

"Measures"

AIM leverages advanced AI technologies to maintain high standards of data quality and fraud prevention. AI algorithms identify and eliminate duplicate entries, detect and block bot activity, and validate respondent locations through geo-IP analysis. Automated systems monitor survey timings and verify completions, ensuring accurate and reliable data collection. Custom fraud scores and AI-driven checks ensure consistent and high-quality responses across all surveys.

Response Time Analysis

Analyze the time taken by respondents to answer questions

Behavioral Analysis

Analyze respondent behavior during surveys, such as mouse movements, keystroke dynamics, and click patterns

Cross-Verification

Responses with external data sources or with previously collected data to check for consistency and authenticity

Social Media and Web Analysis

Analyze social media profiles or web presence of respondents to validate their identities and credibility

Data Clustering and Segmentation

Algorithms to group similar responses together. Anomalies or outliers within clusters can be flagged for further investigation

Validation Questions/Captcha code

Questions or trap codes within surveys to catch respondents who are not paying attention or providing random answers

Security

"BriefCase"

SHA-1(Secure Hash Algorithm 1)

AIM uses SHA-1 to securely hash and verify the integrity of data during transmission and storage. It helps ensure that data has not been altered or tampered with.

SHA256 (Secure Hash Algorithm 256)

AIM utilizes SHA256 for stronger data hashing and verification, enhancing the security and reliability of data integrity checks.

MD5 (Message Digest Algorithm 5)

AIM employs MD5 for data integrity checks, comparing hash values before and after data transmission to detect any changes or modifications.

SSL (Secure Sockets Layer)

AIM deploys SSL encryption to protect sensitive data, such as survey responses or research findings, from unauthorized access or interception by third parties.

S2S (Server-to-Server Integration)

AIM implements S2S integration to ensure secure and seamless data transfer, reducing the risk of data loss or interception during transit.

NLP (Natural Language Processing)

Enhance data quality through text analysis, sentiment analysis, and anomaly detection. AIM leverages algorithms to validate the authenticity and quality of responses in research data, improving overall data accuracy and reliability.