Using Artificial Intelligence Software to Build Relentless Quality

Artificial intelligence software is on the rise, both in terms of usage, availability and amount of products — and for good reason, as AI can increase business efficiency by 40%

Productivity is especially important in the realm of market research, as it makes up but one chamber of marketing to maintain a business. With so many funds being allocated to marketing — from hiring freelancers, to SEO tools, to marketing automation and so on — it is especially important for market research to be of high quality.

Machine learning, one of the four main subsets of artificial intelligence, can be used to provide above-par data quality — with the correct capabilities and when consolidated with the proper software.

This article explains how artificial intelligence software forms high-quality data, the kind that market researchers can objectively label as being of relentless quality in the Pollfish online survey platform. 

Understanding Artificial Intelligence Software in Market Research

As market research projects demand hard and fast data available at speed and at scale, there is a need to access top-tier quality — that is, data that is not merely accurate, but exists in a system that provides human levels of accuracy, with machine levels of delivery.

Artificial intelligence software is the answer to the necessity of having access to the highest quality of data. This kind of software runs largely on AI, as its name implies, which is a kind of technology that simulates human intelligence and applies it to computer systems.

Artificial intelligence creates intelligent systems so that they perform tasks as a human would. As a technology, it is used to pair human capabilities with the speed of machinery, thus empowering systems with the capacity of both.

AI is used to improve efficiency and productivity and many businesses have been adopting it. However, although nine out of ten leading companies invest in AI, less than 15% use AI in their business. As such, not all businesses, including those who claim to be AI-run are using AI capabilities to their full advantage.

Market research software must fully incorporate its AI system aside from only its key functionalities, otherwise, the artificial intelligence software does not fully tap into its abilities. 

The Importance of Artificial Intelligence Software in Market Research

This kind of software has revolutionized the market research industry, allowing market researchers to gain all the benefits of digital innovations, such as agile data creation and much more.  

Firstly, it allowed the use of automation to enter the field of market research, liberating researchers from labor-intensive hours applied to each project just to garner respondents. 

Instead, the artificial intelligence software would assume various roles which would otherwise make the process laborious and difficult to fulfill. These roles include the following:

  • Screener creation
  • Questionnaire creation
  • Deployment
  • Reaching the correct respondents
  • Fulfilling a set amount of quotas

Not only has artificial intelligence software assured that these tasks would be completed from the platform itself, but done so in a fast and relatively inexpensive manner. Additionally, apart from carrying out these applications, AI has instilled a system of quality checks in market research software.

But not within each market research platform. These platforms are not all built with the same levels of AI prowess. As aforementioned in the previous section, market research software must fully implement its AI capabilities, that is, apply them to as many aspects of the data aggregation aspects as possible. 

In turn, it augments the quality of the data, thus boosting the veracity of the market research campaign.   

The Importance of Applying Machine Learning in Artificial Intelligence Software

The value of artificial intelligence software in market research goes far beyond the utility of automated surveys. The proper market research platform will use machine learning as part of its AI capabilities. 

As one of the main four types of AI software, machine learning allows the software to learn just as a human would, that is without assistance or programming. This is because this subfield of AI allows the software to learn from past experiences dealing with data.

Thus, machine learning permits a computer system to make decisions and predictions by way of extracting historical data, rather than being programmed to take such actions.

This frees up a lot of time for software developers and those on the tech support team, as the AI software itself learns how to deal with different issues so that it can produce better output as time progresses. 

The learning process in machine learning occurs through a massive sweep of structured and semi-structured data, which the AI software uses to create accurate results and make predictions based on that data. Thus, artificial intelligence software itself can be taught to perform a particular task and yield an accurate result.

This is of the essence for maintaining quality data, in that many respondents may provide faulty answers such as flatlining, gibberish answers and the like, in order to quickly finish a survey and gain survey incentives

The Pollfish platform uses machine learning to avoid this kind of low-quality data. Instead of merely automating the survey distribution and collection process, it works in real-time to filter out inaccurate information, so that only the highest quality of data is delivered to the researchers. 

How the Pollfish Artificial Intelligence Software Provides Relentless Quality

The Pollfish online survey platform uses artificial intelligence software to its fullest potential, which in turn allows it to deliver relentless quality in all of its functions. 

As aforesaid, it employs machine learning during the data aggregation process, so that low-quality data never makes it to the results of the survey. Thus, rather than having to comb through hundreds or even thousands of responses as a means of spot-checking for issues, the Pollfish artificial intelligence software performs quality checks, as it is deploying surveys and collecting responses.

Thus, it does not merely automate the process of retrieving the correct survey respondents based on the criteria entered in the screening section. Instead, it also automates the process of quality checks and the elimination of low-quality data.

This means that the Pollfish software does not stop iterating until it reaches the preset amount of survey completes, concurrently filtering out the low quality and inaccurate responses. Therefore, market researchers do not have to wait until after all the completed surveys are received to then check for accuracy and quality answers. 

As such, they avoid having to run another survey, as they won’t need to remove answers from the results and fill in those missing quotas afterward. 

The following explains all the other ways in which the Pollfish artificial intelligence software provides relentless quality to any market research campaign. 

Survey Fraud Detection and Prevention

Survey fraud refers to the phenomenon of respondents submitting fraudulent or inaccurate responses. Also called market research fraud, this adverse effect strikes the largest blow on a survey campaign, as it adds another issue, on top of the margin of error, a metric that gauges the magnitude of error in a random sample.

When researchers acquire fraudulent answers, they are in a worse-off position than they were had they not run a survey. The opposite should be true as fraudulent data only tarnishes a research campaign, defeating the purpose of using survey software in the first place.  

Pollfish detects a wide variety of survey fraud. It prevents fraudulent responses in the results automatically, i.e., in real-time. Thus, market researchers do not have to be concerned with low-quality answers.

Additionally, this artificial intelligence capability cancels out the need to outsource technical support. Researchers can delight in the fact that once the survey results are ready, they are as close to accuracy as possible.

Bot Removal

Market researchers can rest assured that the survey sample will be bot-free, as our machine learning staves off any respondents suspected of being fake users. This means that respondents on a VPN are strictly prohibited from gaining access to the surveys. 

Virtual private networks (VPNs) do not simply forge bot-friendly connections, but they also skew geolocation statistics and quotas. They are thus forbidden from taking part in Pollfish surveys. Additionally, a respondent is disqualified if the same user is detected attempting to sign in from multiple countries at once. 

Strict Adherence to Layers of Quality Checks

The Pollfish platform adheres to multiple layers of quality checks. As such, the machine learning function in this artificial intelligence software sorts through various issues concurrently. 

It disqualifies respondents on various criteria — virtually any behavior or activity that constitutes poor data quality bars respondents from the final count of the surveys. Only the highest quality of responses are collected and added towards the result of the survey. 

These quality checks are fully automated and ongoing; thus market researchers are assured that only accurate and relevant data will land in the results of the survey. Our machine learning approach incorporates several layers of technical quality checks.

These quality check layers include detecting and stamping out: 

  • Hasty answers
  • Gibberish/ nonsensical answers
    • Ex: sdjnf jfgid idjvf
  • Same respondents attempting to take the same survey
  • Long survey-taking times
  • Carrier inconsistencies
  • VPNs
  • Flatlining (providing the same multiple-choice answer consecutively)

Respondent Verification

The Pollfish AI software assigns each respondent an ID, a method to track respondents without giving away their identities. This function prevents duplicate IDs, whether they come from IP addresses or MAC addresses. 

Additionally, the software tracks and checks Google Advertising and mobile device identifiers to fend off those attempting to take a survey more than once, those who spend too much time on a survey or attempt to take any nefarious action.

In-survey questions are formed as yet another layer of security against survey fraud, by requesting an answer to a simple math problem or including identical questions in a survey with re-ordered response options to verify answer consistency.

Reputation Ranking 

An offshoot of respondent verification, reputation ranking is the newest vision in Pollfish, one that our developers are presently striving towards. This will work by filtering out every last one of questionable respondents who attempt to take a Pollfish survey, to ensure that only the highest quality of data is extracted. 

This approach will work much like a credit system for market research, as only those deemed reputable will be able to take the survey and have their responses qualified to the final results allotted into the Pollfish dashboard. Based on machine learning, this process will be the final layer of quality checking, assuring researchers that Pollfish delivers data that is truly relentless in quality.

Propelling Market Research with AI Software

The grandest indicator of the success or failure of a market research campaign is the online survey provider market researchers opt for. 

A potent system will employ artificial intelligence software to remove the burden of various tasks from the researchers, instead of having the platform perform it just as a human would and in a streamlined manner. 

With machine learning, such a platform can create efficiency in processes as it acquires more data. A strong online survey platform can apply machine learning to carry out numerous quality checks, so that the results are of the finest quality, assuaging researchers of this arduous task of spot-checking through massive quantities of data.

The Pollfish platform includes these capabilities, thereby allowing it to provide relentless quality for any market research endeavor.