Fraud Detection in Market Research Why & How?
Fraud Detection is the spinal cord if Research needs to be Closer to accuracy & perfection. Market is full of fraudsters & you never know how much you are leaking your revenue & business image both.
Market is full of fraudster; Fraud detection is crucial in online surveys for several reasons:
Data Accuracy: Online surveys often collect large amounts of data, and accurate information is essential for drawing meaningful conclusions and making informed decisions. Fraudulent responses can distort the data and lead to incorrect conclusions, making the survey results unreliable.
Maintaining Survey Integrity: Fraudulent responses can compromise the integrity of the survey. This can undermine the trust of participants and stakeholders, leading to a diminished willingness to participate in future surveys or other research initiatives.
Resource Optimization: Conducting surveys requires time, effort, and resources. Fraudulent responses waste these valuable resources by providing irrelevant or misleading data, which could have been allocated to genuine participants.
Avoiding Bias: Fraudulent responses may be biased towards specific demographics or opinions, leading to skewed survey results. Detection of such biases is important to ensure the survey accurately represents the target population.
Enhancing Survey Quality: By identifying and eliminating fraudulent responses, the overall quality of the survey improves. Quality data is essential for researchers and organizations to make informed decisions and formulate effective strategies.
Regulatory Compliance: In some cases, surveys might be conducted to meet specific legal or regulatory requirements. Fraudulent responses can lead to non-compliance, which may have legal implications.
Protecting the Survey’s Purpose: Each survey is designed to serve a specific purpose, such as market research, public opinion analysis, or academic studies. Fraud detection helps protect the intended purpose of the survey by ensuring that the responses align with the research objectives.
Preserving Relevance: Online surveys are often conducted to collect up-to-date and relevant information. Fraudulent responses can introduce outdated or irrelevant data, compromising the survey’s relevance.
To enhance fraud detection in online surveys, various techniques can be employed, such as IP address tracking, CAPTCHAs, attention checks, duplicate response detection, and statistical analysis to identify suspicious patterns. Maintaining the integrity of online surveys ensures that they remain effective tools for gathering accurate and valuable information.
How MR BUDDIES helps Clients in Execute the Quality Study & Obtain Unbiased Data –
Pre-Screening
Assess prospective participants before involving them – check if they are automated bots, recognized fraudulent individuals, or duplicates.
Prioritize evaluating potential respondents to ensure they are not bots, flagged for fraud, or repeating participants. In addition to our in-house scoring methods, we collaborate with “best of the web” anti-fraud services specialized in detecting e-Commerce and Ad Tech fraud, utilizing this data to enhance the quality of our data.
The Prescreening process is an effective way to filter out participants who may not be relevant to the survey’s objectives. It saves time, improves data accuracy, and ensures that the survey results are more meaningful and representative of the target population.
It’s essential for researchers to carefully design the Prescreening questions to focus on the specific characteristics or criteria that are most relevant to the survey’s goals. Additionally, the prescreening process should be user-friendly and not excessively lengthy to avoid discouraging potential participants from completing the survey.
Here’s How the Online Survey Prescreening Process Typically Works:
Invitation and Introduction: Potential participants are invited to take part in the survey through various means such as email, social media, or website banners. The invitation usually includes a brief introduction explaining the purpose and importance of the survey.
Screening Questions: To determine if the potential participant fits the desired criteria, prescreening questions are presented at the beginning of the survey. These questions assess specific characteristics or qualifications that the survey aims to target.
Eligibility Check: Based on the responses to the screening questions, the system determines whether the potential participant meets the required criteria. If they do, they are allowed to proceed with the full survey. If not, they might be redirected to a different survey or provided with a message thanking them for their time.
Incentives (if applicable): In some cases, online surveys offer incentives, such as gift cards or discounts, to encourage participation. Prescreening helps ensure that the incentives are given only to eligible participants, preventing fraud or misuse.
Pre-Screen Question Library:
MR Buddies Provides Wide Question Library for multiple countries & in multilingual. During the Sales Modules of MR Buddies, the Country Defined in the Project will map to the pre-screener & Pre-screener will open up all the questions mapped for the country defined in the project & in the Desired Regional Language.
Moreover, Prescreen Questions can also be imported via simple CSV OR can be created through editor.
MR BUDDIES FRAUD DETECTION SHIELD
1) Copy Paste: Abandon Copy Paste feature so as robots doesn’t hack your sample.
2) Bots Auto Fill: Get system with bots’ detection, so as your study does not get into bias 3) Speeder- Min Time (LOI) auto detection.
4) Geo IP Detection: Detect Mismatch Geo Location & Disqualify Respondent immediately.
5) Exclusion: Multiple time/Duplicate respondent exclusion based on previous study.
6) Identifies survey cookie deletion intention to commit fraud.
7) Gibberish Detection.
8) Verification: Respondent Email Domain Reachable & Email ID Verification in prescreen.
9) VPN Detection.
10 Captcha Verification for Robots.
MR Buddies helps its client growing big with accuracy.
