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Surveys will only reveal one side of your customers. Facial recognition can do the rest.

We have all filled more surveys in our lives than we can count. We’ve been asked to rate a service, fill a customer satisfaction survey, assess our work environment, and so on. The list is endless.

What do all these surveys assume about people?

  • People know exactly how they feel.
  • People can communicate those feelings.
  • People always tell the truth.

Without these assumptions, polls would be meaningless. The information would be useless and any changes to your product or service based on people's opinions would be unproductive.

But these premises have flaws and this tool hasn’t been able to solve it. We continue to work with this data and rely heavily on people’s explicit reactions. Our marketing strategies might be based on half-truths. Let’s see what the main problems are and what we can do to change this.

Main flaws with traditional surveys

Structural factors

  • Language: Traditional surveys are based on a verbal report but language has many limitations. We use biased words when we formulate questions, we can completely misunderstand what is written, and many other issues with language interpretation..

    Look at the following example: "Where do you enjoy drinking beer?" This is a skewed question. We assume that the respondent drinks beer and forces us to respond in a way that doesn’t necessarily reflect our opinion. You can find a list of the most common mistakes in surveys here.
  • Response Rate: People not only tend to leave surveys unanswered completely, but many also don’t answer them at all. The average response rate is 33% (1 in 3 respondents) so we’ll need three times as many respondents to reach our initial goal. That’s a significant waste of time and resources! Now, there are differences between survey recollection techniques, but it’s still a significantly low rate.
  • Response quality: studies reveal that respondents take shortcuts to reduce the effort and attention when filling out a survey. Not only do they not read the questions carefully, but the answers given are unreliable too.

    For example, in multiple-choice questions, participants might decide to always fill one end of the column (or always click on the answer A) regardless of the question’s statement. Many ill practices put into question the reliability of the information we can get from these surveys.

Psychological factors

  • Honesty: people lie in surveys. A recent study found that only 16% of people are completely honest in them. Considering this low percentage, we might think twice about survey’s usefuluness. Plus, it’s very difficult to detect when people lie in them.
  • Social Desirability: people want to look good in front of others and they want to show a positive self-image. People seek social approval so they’ll choose responses that they believe others expect of them. This is more evident in societies that focus more on the collective well-being than on the individual, as it happens in Asian or Latin American countries.

    For instance, people often agree with phrases like "I would never lie to another person" or "I always keep my promises, no matter what happens." Personality questionnaires have introduced specific scales to detect this phenomenon, but common surveys don’t seem to use them.

Surveys have many limitations but we still use them as our main source information. 

When surveys are used in isolation, without any additional info gathering tools, there is a high risk of providing unreliable data. Consequences can be costly when we make decisions based on faulty information.

What’s next in data collection?

While traditional surveys have contributed to decision-making for decades, they're becoming increasingly outdated. The abovementioned issues decrease the survey’s usefulness which leads us to ponder a much-needed change in data collection.

There’s a bright future in other techniques such as eye-tracking, facial recognition, and other methods applying AI and neuroscience.

The main difficulty in surveys is that there’re many risks in language interpretation: biases, faulty reading comprehension, unknown vocabulary, outdated expressions (e.g. for older generations).

But if we could include other sources of information we can expand our reach and go beyond language risks. An analysis of people’s facial features can help in this endeavor.

Our faces show our emotions. Every emotion activates a distinctive set of muscles that we can read with specialized software. This software is constantly learning, contrasting it with thousands of facial traits in its database. 

Emotions are short term reactions. We express them without consciously controlling every muscle on our face.

Using facial recognition software can benefit your data collection in several ways:

  • It grants access to the respondent’s genuine emotions. These are accessible in real-time, unlike in traditional surveys. Surveys cannot collect information at such a depth.
  • The level of intrusion is minimal. You just need a video or image to run an analysis.
  • The probability of falsifying data is significantly reduced since facial reactions tend to be involuntary.
  • Since AI can recognize a person’s prominent features, there’s a decrease in the likelihood of identity theft which traditional surveys cannot control so effectively.

Our own facial recognition software, Alyze, can help you upgrade the quality of your data and have access to information no survey can provide. Give it a chance and see how it goes by signing for free here.

Takeaway

Data collection is evolving thanks to technologies that were unthinkable a couple of years ago. In this new scenario, traditional surveys will become obsolete if they’re not complemented by other sources of information.

All the aforementioned limitations are reduced considerably with this new technology. Facial recognition allows us to collect previously inaccessible information.

Customer data collection has been developing at an increasing rate and having access to this kind of technology is much easier these days. It’s really up to marketing departments, marketing agencies, influencers, and anyone wanting to have a more accurate picture of their customers.

Today the technological revolution is just a click away.

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