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Market research reveals what your customers value and how you can serve them better than competitors. When you analyze customer behavior, industry shifts, and market trends, you can spot opportunities others miss and make decisions based on evidence rather than assumptions.

The challenge? Most marketers aren't there yet. Nearly 60% lack the data they need to run confident campaigns, and 79% are missing revenue opportunities because they struggle to analyze their data effectively.

In this guide, we'll show you how to turn market research into actionable insights. You'll learn practical data analysis techniques that help you understand your market and make strategic decisions that drive growth.

At its core, market research helps you discover patterns in customer behavior and market trends. This insight comes from two types of data:

  • Quantitative data gives you numbers to measure, like when customers rate their experience from 1-10
  • Qualitative data reveals the "why" behind those numbers, like when customers explain their ratings in their own words

The former helps provide numerical evidence, while the latter offers insight into why a trend may occur

Related: Understand the difference between quantitative and qualitative data

You can analyze this data in three ways:

  • Descriptive analysis shows what's happening now by identifying current patterns and trends
  • Predictive analysis uses past patterns to forecast what might happen next
  • Prescriptive analysis recommends specific actions based on these insights

For marketers, this analysis transforms raw data into practical strategies that help you engage customers and stand out in competitive markets.

Data analysis in market research helps by pointing companies toward ideas, points of refinement, and tactics that boost your likelihood of success.

There are several benefits of using data analysis in market research.

Using data analysis in market research can help you identify new target markets more precisely. By examining different demographic, behavioral, and psychographic data points, you can identify audience segments more likely to engage with your business. Different types of research will uncover distinct insights.

Perhaps buyers in a specific earning band are routinely buying competitor’s products. By identifying trends in target markets, you can begin to shape better strategies to break into new segments. 

Tailoring marketing campaigns using data analysis in market research will help locate, adapt to, and enter new markets.

Customers reveal valuable insights across every interaction with your business. Each website visit, purchase, and support conversation creates patterns you can use to understand their needs and preferences better.

For example, marketing teams may identify that certain user segments are more likely to buy a product when on sale. They could then send small coupons to this segment over email to increase the probability of a conversion. 

By adapting to customer behavior, marketing teams can more effectively engage with their audiences and meet customer demands. 

Data analysis allows you to track how customer behavior changes over time and across different touchpoints. A customer who’s unfamiliar with your business may behave differently when compared to a long-term buyer who’s already loyal to your company. 

By analyzing data from customer touchpoints, interaction with your business, purchase statistics, and overall engagement, you can build up a comprehensive understanding of customer behavior. Conducting market research can uncover a range of insights into how different consumer segments interact with your business.

Marketing teams could monitor website analytics to see if any pages have a higher bounce rate than others. By identifying weak points in your customer journey through data analysis in market research, you can begin to fix them or reduce their impact. Data analytics on consumer behavior will help your organization streamline the customer experience and increase conversion rates.

Data analysis helps you launch new products and enter new markets with confidence. Instead of guessing how customers might respond, you can study how similar products performed in the past. By examining market trends and historical data, you'll spot potential challenges before investing significant resources.

This evidence-based approach not only reduces risk but also helps you build stronger cases for new marketing initiatives and launch products more efficiently.

Data analytics transforms raw information into clear, precise, and useful insights that your business can use in decision-making. But great analytics doesn’t happen overnight.

Let’s explore the steps involved with analyzing data for market research.

While data analysis is a powerful tool, you’ll struggle to gain any useful insight without a clear purpose. Establishing a clear objective or objectives, including tracking metrics, will help point you toward the analysis you must conduct.

Choosing relevant source data will be much easier once you have a target of what you want to uncover. Equally, knowing which metrics you’ll use will help streamline the analytics process. 

You could collect all the data in the world, but if it isn’t directly related to your objectives, it isn’t useful. Collecting marketing data for analytics should align with your targets. If possible, work backward to select and capture the data you need.

For example, if you want to uncover data about customer satisfaction, you could identify that a Customer Satisfaction Survey (CSAT) would provide you with helpful information. Alternatively, you could look into other customer loyalty metrics, like Net Promoter Score® (NPS) and Customer Effort Score (CES).

Determining your objectives helps point businesses to the data they need to collect. Equally, it could suggest which previous data collections you already have could be useful in the analysis phase. 

Once you have all the relevant data, you can employ statistical analysis to derive insights. The methods you use to analyze your data will vary depending on your final objective. 

Here are some techniques you may use when analyzing data:

  • Statistical modeling: Using statistical models to identify trends and patterns in data.
  • Data visualization: Creating visual depictions of the insights you find in data, like graphs or charts.
  • Machine learning and AI analysis: AI-powered market research tools can streamline analytics and expedite research.
  • Correlation and causation analysis: Examining connections between variables with both quantitative and qualitative data.

In the analysis phase, you transform your raw data into precise, unique, and insightful information.

Data insight isn’t just a fun statistic or an interesting graph. Data insights can provide actionable pathways for businesses to take to streamline their operations, enhance the customer experience, and drive profit. But, to get to these exciting benefits, companies must take action on the insights they uncover.

Where possible, translate data analysis into actionable insights. From there, your business can implement changes and optimize strategies based on the data you uncovered. 

By adapting your strategies and continuously monitoring and generating new data, you can build a better business one day at a time. 

Data analysis in market research is a powerful tool that can drive your business toward unique insights and data-backed strategies for success.

Start collecting, processing, and analyzing data with SurveyMonkey to uncover competitive advantages and comprehensive insight. Learn more about our market research tools. 

兩位行銷部門員工,一位正在查閱品牌策略文章,另一位則拿著列印出來的圖表

Brand marketing managers can use this toolkit to understand your target audience, grow your brand, and prove ROI.

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Conduct market research faster for real-time insights and smart decision-making. Learn what agile market research is and how to apply the framework.

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Net Promoter, Net Promoter Score, and NPS are trademarks of Satmetrix Systems, Inc., Bain & Company, Inc., and Fred Reichheld.