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Market research allows businesses to uncover unique insights, find competitive advantages, and drive success. Effective data analysis is at the heart of market research, providing data-driven insight into consumer behavior, industry dynamics, and market trends.

Yet, 59% of marketers feel they don’t have the data they need to feel confident about their marketing campaigns. Struggles with data analysis are common in the marketing industry, with upward of 79% of marketers missing opportunities that could lead to higher revenue and growth.

Harnessing the power of data analysis in market research will help overcome these challenges and unlock strategic business opportunities.  

Let’s explore what data analysis is, the importance of analysis in market research, and data-backed strategies to analyze marketing data.

Data analysis in market research is the process of collecting, processing, analyzing, and modeling data to create useful insight. By using large pools of market research data, you can identify trends, patterns, and connections that shape their future business strategies.

Market research data can be quantitative or qualitative. The difference between quantitative and qualitative data is that the former helps provide numerical evidence, while the latter offers insight into why a trend may occur. Quantitative data might ask a customer to rate their experience with a brand on a scale of 1-10. Qualitative data would ask that same customer to explain why they chose the number they did.

When conducting market research, there are three core data analysis methods to be aware of:

  • Descriptive: Interprets data to identify trends and characteristics within the dataset.
  • Predictive: Combines analysis with statistical algorithms to understand past data and make informed predictions about potential future trends.
  • Prescriptive: Takes data analysis one step further by offering data-driven actionable insights that would help to optimize outcomes. 

Every department in a business draws insight from data analysis. For example, marketing data analytics will take the skills and methods of analytics and apply them to marketing-related goals and solutions. This subset of data analysis will provide marketing professionals with agile, data-driven strategies to stand out in highly competitive markets and engage potential customers.

One of the main objectives of market research is to find tangible, data-backed strategies that you can use to gain a competitive advantage. Data analysis in market research helps provide that insight, 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 precisely identify new target markets. 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.

Customer data is one of the most valuable sources that your business has access to. Data analysis in market research is vital in uncovering connections in customer behavior and interaction. 

Customers leave a traceable trail of data across every interaction that a customer makes with your business. From spending time on your website to building up a purchase history, everything becomes a data point you can turn into valuable insight. 

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.

Launching new business ventures or expanding into unfamiliar markets can pose a financial risk to businesses. Data analysis can mitigate this risk by providing predictive analytics of how changes may impact a company. 

For example, businesses could analyze historical data of how similar products have performed with their audience instead of blindly launching a new product. Businesses can better understand a decision's risk before committing to it across internal measurements, market trends, and historical industry data.

Data-driven risk mitigation will reduce uncertainty when making decisions, helping marketing teams secure budgets for new endeavors and streamline project launches. 

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. 

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