The web has enabled surveys to be inexpensively developed and distributed to people and to substantially increase the number of respondents participating in survey-based research.

Unfortunately, data from internet-based surveys and opt-in panels are increasingly contaminated by fraudulent responses generated by survey bots.

The sophistication, ease of use, and range of tasks that bots can complete is growing rapidlywhile the costs are steadily declining.

One study estimates that just more than half of all web traffic is now generated by automated bots.

Bots can be very useful for web scraping, monitoring websites, or aggregating news; however, they are destructive when they are used to impersonate humans.

For example, ad fraud or click fraud has long been a plague on the digital advertising industry, as increasing numbers of bots drive up ad click rates and reduce the actual return on the advertising spend.

Fake data from bots often enter surveys via unscrupulous members of opt-in survey panels.

Individuals in survey panels can purchase a survey bot that dramatically increases the number of completed surveys attributable to a panel member and generates compensation for survey completion.

Even the most well-established panel and respondent providers have been affected by the problem.

The prevalence of bot-generated data isnt formally estimated but the problem appears to be growing as the number of commercially available survey bots is increasing.

At several points in the survey lifecycle, countermeasures can be employed to help maintain the integrity of your data or identify fraudulent responses.

You should work with your panel provider to make sure they have procedures in place to screen and verify the identity of respondents.

Fors Marsh Group (FMG) employs many of these measures, such as engaging in routine name and address validations and mailing incentives to physical addresses.

Unsophisticated bots will generate responses with the same patterns, so make sure to examine suspiciously high numbers of certain response choices.

Make consistency edits by examining response patterns that are unusual, such as young people with long histories of certain behaviors or other implausible answers.

Data from open-ended question fields should also be inspected for duplicate phrases or completely off-topic responses.

Multiple surveys from the same IP address are a reliable but not foolproof indicator that responses were automatically generated, so examine IP addresses and time signatures for duplicates.

Where possible, also look for surveys that were completed extremely quickly or slowly or well outside of the average completion time.

If you suspect you have fraudulent responses, make sure to flag the data rather than removing cases outright so that differences in flagged and unflagged analyses can be studied.

Although the number of responses generated by bots found in panel-provided data is likely to increase, researchers can stay a step ahead of bots by taking the preceding actions into consideration when preparing or analyzing your data.

The features that make bots powerful are often the same ones that can give them away, such as fast responses, stilted or boilerplate answers, and high rates of productivity.

Tim has several years of survey and opinion research primarily in the educational sector.

Survey Bot Taker