CX Surveying Before and After Artificial Intelligence

In order to understand what drives customers to buy, you have to ask them.

Over the past (almost) 100 years, the fundamentals of market research and voice of customer surveying have remained practically unchanged… until now.

The Birth of Market Research

During the roaring 20’s, when advertisements started showing up in media such as magazines, newspaper and radio, Market Research (MR) formally began. Daniel Starch, a psychologist considered to be the father of MR, theorized that advertising had to be seen, read, believed, remembered, and most importantly, acted upon, to be deemed effective.

Starch began approaching strangers, asking if they would take a look at newspapers and magazines and proceed to question them on which ads they could remember from the publication.

His team would then analyze the sample size versus the circulation of that publication to determine how effective the campaign was in reaching its audience. Hence, the birth of the pen-and-paper survey.

Traditional Survey Methodologies

Almost a century later, although technology and innovation have brought countless improvements to the process of gathering information, most traditional surveys in present day are still no more than digital versions of the old pen-and-paper surveys.

Surveying customers and post-collection data processing is a monumental task that requires a team of data analysts trying to make sense of numerous uncorrelated data.

By simplifying the process, metrics such as CSAT (Customer Satisfaction) and NPS (Net Promoter Score) have become increasingly popular since they are easily quantified and provide companies with goals that the whole team can get behind. Here are some of the most commonly used traditional survey methodologies:

• Customer Satisfaction (CSAT)
• Net Promoter Score (NPS)
• Customer Effort Score (CES)

Traditional methodologies are usually designed internally and used alongside extra questions that deep dive into each aspect of a product/service which allow individual departments within an enterprise to survey customers simultaneously.

CX Surveying Before A.I.

Up until now, if you wanted to survey your customers, there were quite few important steps to follow in order to guarantee a successful survey.

1. Determine Sample Size: To conduct a survey, the number one step was to consider sample size. Sample size is the number of respondents that you’ll need in order to accurately represent your entire base without needed to approach all of your customers on a frequent basis. Read more about calculating sample sizes here.
2. Pick your methodology: You would need to choose which methodology to use for your survey and how it would match up with your internal questions.
3. Design your questionnaire: Probably the hardest part. First, you’d have to make sure your questions were bias free; they must be ambiguous and not lead the respondent one way or the other. Secondly, you’d have to make sure the questionnaire wasn’t too long. If it was, respondents would possibly abandon the survey before it was over and would disqualify. Lastly, you’d have to ensure your questions flowed properly, with option trees for yes/no responses.
4. Choose your platform: You could choose between Do-It-Yourself (DIY) platforms or an all-in-one solution. If you chose DIY, you’d have to make sure you had the man-power and knowledge to collect, process and analyze results on your own. All-in-one solutions deploy, collect and analyze responses for you, as well as offering consulting services.
5. Deploy: Send your survey to customers through whichever channels you chose: email, text, phone, in-app or through social media platforms.
6. Response Anaylses: Extract relative and actionable insight from a sea of endless data. You’ll probably need a team of analysts to do a proper job.
7. Update: If you chose to use recurring surveys at multiple touchpoints along the customer journey over long periods, you’d need to constantly update your surveys to maintain relevance to your customer.

Why A.I. is a Game Changer

The $33B Market Research industry has relied heavily on the same methodologies and processes for decades. This is the first time that technology is changing survey methodologies, and not only data collection channels.

This means that although survey deployment (the way customers receive surveys) is much more efficient through use of modern channels such as email, in-app and SMS, going through customer responses to find actionable feedback is still extremely costly and arduous for companies.

And since deploying a survey is a massive undertaking, executives want to squeeze in as many questions as possible, which makes answering seemingly endless questionnaires an irksome task for customers.

By reversing the logic and allowing A.I. to design questionnaires, they remain short enough to stay interesting to the customer while still uncovering relevant, actionable insight.

This revolutionizes the way surveys are carried out. It places a lot more power into the hands of customers, enabling them to express their desires and concerns in a fast, clear way.

A.I. technologies allow each respondent to deliver valid insight about even the most specific features of a product or service; and from the company’s perspective A.I. surveys can use insight from multiple respondents to not only understand what features customers like, but also understand why and how they like them.

This gives companies the ability to focus on what is most relevant to the majority of their clients and see things from their customers’ eyes. All this without dragging them through a seemingly endless questionnaire about features and topics that might be irrelevant to that individual’s perception of value.

An A.I. Survey Methodology

The Worth Index: Worthix (that’s us!) uses Artificial Intelligence to measure how much a product or service is “worth it” to customers. It also determines what motivated your customers’ purchase and verifies whether your value proposition is up-to-date with your customers’ expectations.

This is how surveys have evolved with Worthix A.I. A couple steps still remain, such as determining sample sizes, but most have been simplified or eliminated.

• No need to design questionnaires. They’re pre-designed for each market segment.
• No bias. Companies cannot meddle with questions, thus preserving 100% Voice of Customer.
• Questions are tailored according to individual responses. This makes sure customers only answer questions that are relevant to them.
• Only 2 minutes long which increases qualified response rates.
• Ever-green questions that remain relevant despite market changes.

One of the most valuable benefits of an ever-green questionnaire is its use in enterprises. Most enterprises use surveys to monitor multiple touch points along the customer journey over mid to long term periods.

Imagine the man-power and hours it takes for every department to keep each survey for all touchpoints updated on a constant basis? With a self-adjusting questionnaire, not only do the surveys stay relevant, they also monitor the constantly changing customer expectations regarding value proposition.

This allows companies and executives to act swiftly and effectively, as opposed to basing decisions on cold-data and outdated propositions.

The Conclusion

The only way to get to know the customer is through surveys, which is why they have endured all of these years. But as with any business strategy, survey methodologies must use innovation and technology to improve over time.

In the Customer Experience Era, where being customer centric is mandatory, A.I. surveys allow companies to make the most of each question by focusing solely on what matters most: the voice of the customer.

Originally published at blog.worthix.com.