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Businesses conduct research on markets to identify the ongoing new trends and customer behaviors throughout time. Although, as technology is advancing, researchers seem to take an interest in AI powered surveys to automate their customer engagement through machine learning algorithms. But how do they work?
With AI surveys, machine learning algorithms can be programmed to interact with the respondents and manage back-end data which then goes into implementation and reporting. Although there are various ranges of takes on technology supported surveys, with the right difference between hype and genuine promise, it is possible to leverage AI technology to turn out in your favor.
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As Dr. Melanie Mitchell puts it “Artificial Intelligence Hits the Barrier of Meaning,” AI is outstanding at doing what it is told, but not at uncovering human meaning. So how will AI technology really work in conducting surveys and carrying them out? Let us discuss it in the next section.
We discussed what AI surveys are and how they operate while conducting surveys. Let us see how it behaves with various factors along the way.
Traditional surveys were too long to respond to. And AI surveys are not, which helps reduce customer fatigue. Well, not quite. The length of surveys depends on how poorly it is crafted irrespective of the instrument used to craft it. The major difference that AI makes is to make it seem less computerized and more humanized with respect to interactions.
AI uses a friendly approach which makes respondents feel at ease and respond more freely. Well, as helpful as it sounds, there is still a possibility that this may be a downside because people will also be likely to respond less and not so genuinely.
AI treats open-ended questions and their responses smartly. First, it gives you ready-made thematic analysis of the descriptive answers. You get the data organized based on the essence of what they mean which makes it easier to derive insights from.
Another benefit of using AI for your surveys is that it not only derives thematic analysis but also measures their relative importance. This shows you not only the meaning of the data but also its relatedness and context in which it differs from other responses.
AI has claimed to be a booster when it comes to getting insights and integrations with other data sources in real-time. Data science has been proven to tell us what is happening with the data but not necessarily show us how it is happening. And this can be due to its limitations with not uncovering the behavioral patterns of the data.
Structured data like NPS® scores which is direct quantitative data, we will still need human intervention to make sure the data’s meaning and its significance.
It is true that AI technology in surveys gives you a richness of insights and data themes. But as discussed earlier, referring to various data sources and their cross-platform analysis will still need human intervention. The process will need humans to coordinate and feed in the inputs and manage their inter-dependability.
The self-learning abilities that AI possesses are still limited to the level of machine learning it is allowed through hardcore programming. And that seems to be still under human control, so human interference is inevitable.
The claim is that AI surveys can be created instantly and automatically. There are various tools in the market that create survey questions using pre-fed data. Although, it makes us think how reliable it is? Well, when the researcher isn’t trained enough, it may rely on the questions and let the respondents choose their questions based on the response they feed the algorithm. But when it comes to letting AI craft questions for your survey, it is always a good practice to trust but verify them.
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Now it is time to measure how both AI and traditional survey systems are similar in a way that makes much difference when used interchangeably.
There are numerous ways to gather data for your studies, like referring to past studies, going through past research papers and so on. When we talk about surveys, the only source of data remains is the participant. Both AI surveys and traditional surveys ask participants questions. The questions can be focused on gathering audience’s views, opinions and thoughts and reviews. Any reason may it be, both survey methods use a question-answer approach to gain data to derive insights from.
Surveys look at the cheapest way to gather information. You can cover a huge number of participants in relatively less time and cost. Well, this goes for both AI surveys and traditional surveys.
Both survey methods get their questionnaires crafted and delivered to the population to respond to and get huge amounts of data in return and in no time.
Surveys have different forms when it comes to their crafting and conduction. Although, it is true that no two survey methods are exactly the same, both AI surveys and traditional surveys can be molded to be conducted for any purpose there is.
Both forms of surveys can be used to conduct feedback surveys, repetitive product development surveys and customer review and behavior surveys.
Done with the importance of AI surveys and how it is similar to traditional surveys, we will look more into how both survey methods are different from each other.
Traditional surveys are rather static. You define a fixed set of questions and that survey goes out to every respondent. So, it is basically one same survey to everyone. But when it comes to AI surveys, you can shift the questions based on how the respondent answers the previous questions.
This way you get to have a number of questions and that too without making the survey short, and on top of everything, personal to each and every participant.
The important point to consider regarding platforms for both traditional surveys and AI surveys is that traditional surveys can be conducted offline (on paper) as well as online (sharing the survey through the internet). Whereas AI surveys only need to be conducted online. When it comes to traditional surveys, there are still people who consider conducting offline surveys a better way to interact with the audience. AI surveys on the other hand go on the internet with tools to analyze data then and there.
The primary reason why most people conduct AI surveys over traditional surveys is the ability of AI surveys to yield more finished and polished results. AI surveys end up analyzing data to form results that give both quantitative and qualitative data analysis results. When it comes to traditional surveys, you are limited to what humans can do and rather end up spending more time and money deriving the most basic insights.
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