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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 behaviour, 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 some data-backed strategies for analysing marketing data.

Data analysis in market research is the process of collecting, processing, analysing and modelling data to create useful insight. By using large pools of market research data, you can identify trends, patterns and connections that can shape your 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 optimise 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 towards ideas, points of refinement and tactics that boost their likelihood of success.

There are several benefits associated with using data analysis in market research:

Using data analysis in market research can help you precisely identify new target markets. By examining different demographic, behavioural and psychographic data points, you can identify audience segments that are 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 competitors’ products. By identifying trends in target markets, you can start 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 data sources that your business has access to. Data analysis in market research is indispensable for uncovering connections in customer behaviour and interaction. 

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

For example, marketing teams may identify that certain user segments are more likely to buy a product when it’s on sale. They could then email vouchers or codes offering a modest discount to this segment to increase the probability of a conversion. 

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

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

By analysing data from customer touchpoints, interaction with your business, purchase statistics and overall engagement, you can build up a comprehensive understanding of customer behaviour. 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 whether 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 start to fix them or reduce their impact. Data analytics focusing on consumer behaviour will help your organisation 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 the impact that any changes may have on a company. 

For example, businesses could analyse historical data on how similar products have performed with their audience instead of blindly launching a new product. By studying internal measurements, market trends and historical industry data, businesses can gain a better understanding of the risk associated with a particular decision before they commit to it.

Data-driven risk mitigation will reduce uncertainty when making decisions, helping marketing teams secure budgets for new endeavours 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 analysing data for market research.

Although data analysis is a powerful tool, you’ll struggle to gain any useful insight without a clear purpose. Establishing one or more clear objectives, including tracking metrics, will help point you towards the analysis method that you need to use.

Choosing relevant source data will be much easier once you have a target in terms 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 backwards to select and capture the data you need.

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

Determining your objectives helps to point businesses towards the data that they need to collect. Equally, it could suggest which previous data collections that 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 analyse your data will vary depending on your final objective. 

Here are some techniques you may use when analysing data:

  • Statistical modelling: Using statistical models to identify trends and patterns in data.
  • Data visualisation: Creating visual depictions of the insights you find in data, such as 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 in order to streamline their operations, enhance the customer experience and drive profit. However, to get to these exciting benefits, companies must act upon the insights they uncover.

Where possible, translate data analysis into actionable insights. From there, your business can implement changes and optimise 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 towards unique insights and data-backed strategies for success.

Start collecting, processing and analysing 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.