Categories
Research Methodologies
August 19, 2022
Fraud mitigation techniques to reduce bots’ impact on data quality.
Twitter is plagued by spam and fake accounts on the site – at least that’s the alleged reason that Elon Musk pulled out of the multi-billion dollar deal to buy the social media platform. The truth is that this kind of fraud is unavoidable, and I’d argue that it doesn’t take away too much from the overall value of the platform. After all, Twitter still has active users in the hundreds of millions, and many of them are quite influential in business and media circles.
In market research, we’ve been battling fraud for years. It’s pervasive, it’s persistent, and it certainly isn’t going to go away anytime soon – not when there is financial gain on the table for fraudsters taking surveys for incentives. Some sneaky characters that plague the industry are bots, presenting an automated threat to data quality. But we needn’t panic when we hear this word.
Bots are not limited by any means to the market research space. They can attack websites to make them vulnerable to malicious activities, automate dishonest posts on social media (i.e. Twitter case in point), text your mobile phone, send out spam to create larger infections, and much more. The financial industry is the most affected, with a whopping 97% reporting in 2020 that an API had been attacked by bots. While the U.S. remains the epicenter of bot fraud, with a Globaldots report showing that it represents 53% of bot traffic, it is an international issue.
Not all bots are bad – think about Googlebot’s search automation function – but the ones we are fighting in survey research certainly are. And the game of fighting them has become a moving target, as they become more and more sophisticated and complex. Our defense against them must undergo continual optimization and improvement. We need a wide mix of methods to stop bots by quickly identifying them and removing them from surveys before they affect our data quality.
The first step is employing the right approach to fraud mitigation. We won’t ever get rid of these little guys completely, but reducing their impact is critical when it comes to data quality – the central value proposition of market research itself. There are a few best practices that we’ve seen work when it comes to selecting sample to help reduce bots and fraud.
The truth is that there may always be bots in panels, no matter what protocols are in place. There is money on the table, in the form of incentives, and that is a strong motivator for bots to infiltrate surveys. Of course, we should, and must, continue to fight the good fight to keep them out and reach our data quality goals. But we must also keep calm, carry on, and realize that the cat and mouse game of chasing bots is part of the market research ecosystem. We just have to be better at finding them than they are at showing up.
Comments
Comments are moderated to ensure respect towards the author and to prevent spam or self-promotion. Your comment may be edited, rejected, or approved based on these criteria. By commenting, you accept these terms and take responsibility for your contributions.
Disclaimer
The views, opinions, data, and methodologies expressed above are those of the contributor(s) and do not necessarily reflect or represent the official policies, positions, or beliefs of Greenbook.
More from Patrick Stokes
Embracing Aggregation: What Buyers Need from Suppliers Today
Even though many of us are sick to death of analyzing the pandemic and its impact, the truth is that it has changed the face of market research for good.…
Similar to the realm of video streaming services, the MR sample space faces increased fragmentation.
Sign Up for
Updates
Get content that matters, written by top insights industry experts, delivered right to your inbox.
67k+ subscribers