The data that drives business today is readily available in the text generated on the internet. Customer and product research is no longer a laborious process that involves trying to predict how consumers feel about shopping, brands, and products. The solution is data mining which is a process that produces actionable consumer insights from user-generated content. 

What Are Consumer Insights?

Consumer insights are created from the process of data mining. These insights provide an in-depth view of customers, their preferences, pain points, and what they look for in a brand. These insights are taken from the customers’ own words in reviews and social media updates. With a consumer insights tool, the texts are mined for data and drive product innovation and marketing strategies. 

What Is Data Mining? 

Data mining is the process of analyzing texts retrieved from the internet. It can be done for various purposes, such as identifying specific information in a text, placing content into categories, and clustering related information. Sentiment analysis is another function of data mining and its purpose is to determine the attitude or sentiment expressed in a given text. 

Data mining for consumer insights is performed on reviews or other brand-relevant content. Through automation algorithms used in consumer insights software, texts are evaluated for the sentiment. Each text is given a ranking or a numerical value indicating the feeling concerning the category or question ranging from very positive to very negative. This data is the basis of consumer insights. 

Benchmark Your Performance Against the Competition

Data mining and consumer insights provide an efficient way to compare your performance against the competition through quantitative data rather than guesswork. A common theme in many reviews and social media posts is to compare one product or brand against another with debates about the advantages and disadvantages of each. These conversations provide a goldmine of data. 

It is essential to retrieve reviews and social media posts comparing your brand with the competition. Also, do full research on your brand’s customers as well as those who do business with competitors. With data mining, it is possible to do a thorough, point-by-point comparison between your brand and various competitors based on reviews and other user-generated data. This provides a straight scoop on how customers feel and can provide clues to winning market share. 

Loyalty Programs

Loyalty programs are a winning strategy but not for the reasons many people think.  The advantages are obvious; the company provides discounts to customers who are considered to be loyal and likely to make purchases. Since a large proportion of sales are from established customers, it is clear that loyalty programs more than pay for themselves, despite the generous discounts they provide. 

However, loyalty programs offer another significant advantage. They allow a company to gain information about customer behavior and preferences. The loyalty program facilitates tracking transactions and allows a company to create consumer insights to personalize promotions. This is not an underhanded tactic; 87% of respondents said they would be open to a loyalty program using some of their information if they would receive more rewards. 

A loyalty program is a step towards the fulfillment of the goal of creating a customer-based strategy. Providing special promotions, incentives, and five-star treatment to high-margin customers creates loyalty and encourages them to spread the word. In addition, their communications give more indications of what they are looking for which can improve a company’s ability to fulfill their needs. 

Point of Sale Data

It is important not to neglect the point of sale data, because in some cases it can be the most crucial. If an eCommerce website is otherwise stunning and user-friendly but the checkout creates a pain point for customers, they may be less likely to make additional purchases. In addition, abandoned shopping carts provide hints about what needs to be improved. 

Collecting point of sale data can be easy with customer chat while checking out or a short survey after the purchase is made to rate the service. Interacting with a visitor about an abandoned shopping cart gives clues on what is keeping customers from making the final step. 

Perhaps the projected delivery is not fast enough? The price of the items are too high? There aren’t enough payment options? Data mining can offer answers to these questions about abandoned shopping carts through communications with customers and provide tips on what changes to make to increase conversions.

Mining for Data Gold

The opportunities to produce actionable data for business decisions are endless with the growing digital reality. Every Facebook post, review on Yelp, or comment on a forum can be the raw material for data mining and can produce valuable consumer insights. Using consumer insights software to analyze texts is an important step to creating actionable data that will contribute to eCommerce success. 

Also Read: 6 Web Scraping Tools for Extracting Data