3 ways AI changed Consumer Insight and Market Research

Identifying and understanding your customers in order to improve sales is marketing 101. Customer Insight Market Research is used by businesses looking to better understand their customers’ behaviors, preferences, and needs.

In recent years, new technology has been introduced into the Market Research playing field – Artificial Intelligence (AI). This article will explain what are Consumer Insight, and discuss the impact AI technology has had on Market Research. 

What are consumer insights?

Consumer Insight is analyzed data providing a better understanding of customer attitude and sentiment. This information is used to gain extensive knowledge of consumer desires, needs, and motivations. Consumer Insights help improve a brand’s interaction with customers, which creates better customer experience and increases sales.

Useful Consumer Insights should be:

  • New – If you already know it, then it’s not an insight. 
  • Unexpected – Insights should be something you weren’t looking for, the information you weren’t initially aiming to find.
  • Relevant – The information might be new and exciting, but if it doesn’t match brand identity it’s useless.
  • Inspiring – Good insights should motivate future actions and innovations.

Consumer Insight are aggregated from data collected with different tools, like trend analysis, customer satisfaction surveys, focus groups, Social Listening, and more.

Why is AI used for consumer insights?

Market research and CX analysis is often evaluated by these 3 parameters:

  1. Efficiency – The research needs to be done ASAP in order to maintain its relevance. Delay in delivery often results in outdated insights and inaccurate sentiment analysis.
    1. AI-based market research tools deliver results in near real time. The AI technology collects the data form a selected target audience, automatically monitor and scan keywords or topics. And it does it all a lot faster than a human would.
  2. Effectiveness –  For the Research to be effective and provide quality information, the data collection tool has to be designed with the target audience in mind. For example, Customer Satisfaction Surveys (CSAT) that aren’t user friendly often cause low response rates that alter scoring or provide inaccurate information.
    1. Surveys created with AI technology are more interactive and can be modified using customer’s answers. This technology allows for a more dynamic analysis, and helps modify the existing tools to better suit the customers.
  3. Enhancement: The research has to provide highly granular analysis for marketing campaign design and resource allocation. Inaccurate data analysis results in unsuccessful marketing and lost sales.
    1. AI enhances traditional CX analysis methods. Research results are provided quickly, accurately and free of any human-errors or biases. The end product is a rapid, highly granular, spot on market research.

1. How AI became the future of consumer and market research

In recent years, AI-powered research and analysis tools have been taking up more and more space in the world of CX analysis. According to Salesforce, 51% of companies are using some form of AI, and another 25% look to integrate it into their businesses. 

AI technology is used both to improve customer service and experience, and to facilitate better collection of information for analysis. And since 93% of market researchers describe AI as an industry opportunity, no wonder AI insight analysis tools have become the future of CX and market research. 

Moreover, using Artificial Intelligence enables a more personalized customer experiences. The insights provided by AI technology are used to tailor brand innovation to customers’ needs and requests. This customization process costs significantly less than traditional marketing campaigns, and often has a better effect on sales and earnings.

2. How AI market research improves customer experience

According to Forbes, Customer experience can make or break a brand. Bad customer service or plain dissatisfaction with a product or service generates negative sentiment, that alienates potential buyers and hurts revenue. Well, the best way to insure that doesn’t happen is both monitoring and improving customer experience. And to do so as quickly and accurately as humanly possible.

But, what if you didn’t have to rely on a human? Unlike traditional market research, AI market research accounts for the entire customer journey, from the first click to the satisfaction surveys. All the information is scanned, collected and analyzed. The end result is an understanding of Customer Sentiment – valuable insights on customer satisfaction or critique of a product or service. 

The AI generated information is used for customer experience customization and optimization, improving consumer satisfaction that results in a higher bottom line.

Artificial intelligence requires a large training set in order to make predictions and perform accurate analysis. Most AI solution for customer experience are limited to consumer packaged goods (CPG) since it has the largest training set available.

3. How AI improves Social Listening

Social Listening is a CX analysis tool used to obtain a deeper understanding of customer sentiment as manifested on social media, or Social Sentiment. This sentiment analysis solution works in two stages. First, all social media activity is monitored and scanned to detect all comments, posts and tweets mentioning a certain brand. This stage is called Social Monitoring. Later, the data is analyzed and classified as “positive,” “neutral,” or “negative.” 

According to a Harvard Business Review, using social media to improve customer experience will generate a more positive sentiment. So, monitoring a brand’s social sentiment can provide crucial data that can be translated into better customer experience, which leads to brand growth and market dominance.

However, the vast number of social media users has made it quite difficult to effectively monitor and analyze social media activity. That’s where AI technology comes in. Computer learning software is helping marketers monitor, scan, collect, and analyze data efficiently, providing almost real-time social sentiment insights. The end result is a granular analysis of customer attitudes and a better mapping of the market.

Revuze Take on AI for consumer insights

Revuze developed the first self-training, low touch AI technology that collects and analyzes customer feedback automatically and serve back valuable consumer insights. This innovative AI technology collects data from a variety of sources simultaneously and independently. The data is scanned and analyzed automatically by self learning algorithms. 

The end result is highly granular Market Research that informes data-driven campaign design and resource allocation, improving revenue.

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