Marketing Data: Analyzing Insights for Strategic Advantage

What is Market Research

Market research is the steps that you take to get to know your audience. You want to investigate your business’ buyer personas. So start to dig deep into your target audience and customers. This is how you will determine how viable and successful your product or service would be, or is, among these people.

Marketing research is crucial to companies because it guides them to focus their marketing efforts on the right customers. The more research businesses engage in, the more likely they are to make data-driven decisions. In turn, these decisions will drive growth and revenue for the business.

Market research includes the following data types:

Primary Data

Primary data is first-party data. So when we’re talking about primary data we're referring to first-hand data collection directly from the customer. This data type is very useful for market segmentation and determining an individual customer’s profile. Primary data is generally acquired using qualitative research methods. For example, focus groups and one-on-one interviews allow researchers to ask open-ended questions. And these types of questions are great for picking up on insights that would have been missed otherwise.

Secondary Data

Secondary data is data that was previously collected and organized by someone else. Sources of secondary data include government studies, journals, and other businesses in your industry. So it might be easier for you to get your hands on a lot of secondary data out the door. But the real value lies in what the customer can tell you themselves. So you must ask the important questions that will turn leads.

Steps in Marketing Research

1. Identify the problem or objective

One important thing is for businesses to determine what their intentions are for carrying out market research. This is the foundation on which the rest of your marketing research and the resulting data will stand. So, find out what your target audience’s pain points are. In some instances, if you see a general need you can also fill that. Simply ask yourself what problem you're trying to solve.

Then again, you might argue that some marketing campaigns are successful even though they don't know the customer very well in the real world. Toyota, for instance, doesn't ask its target market what kind of new car they would like to drive next. But Toyota has one of the top-selling brands in the United States.

And this is simply because Toyota's marketing campaign focuses on creating a reputation for dependability, safety, and affordability. Toyota knows that once its customers are hooked on these qualities, they'll keep coming back for more.

2. Develop a Research Plan

Determine the research methods and data sources that will help your business collect the most relevant data for the research objective. This calls for a detailed look at who you're trying to reach.

Marketing research is the process of identifying and collecting information about consumer needs, wants, desires, preferences, demographics, opinions, attitudes, and buying behavior. The goal is to gather data that can be used to guide decisions about marketing strategies.

But marketing research isn't just about surveys. It's much more than asking people what they think or want. It's about understanding how to meet your customers' real needs through better strategic planning or product development.

The marketing research starts with the development of a comprehensive market research plan. This will determine how much research is needed and what information will be collected. It also shows you what business intelligence will be derived from the data collection.

The marketing research plan is a strategy for collecting marketing data to help marketing managers make better marketing decisions. It defines the steps to be taken in the design and conducting of a marketing research project.

Management may need access to information for all aspects of a product or service line. There are several factors a company must consider when starting a marketing research program. These include:

• What business issues need to be addressed?
• What information is needed?
• Where should the information come from?
• Who should receive it?
• How much will it cost?

3. Data Collection

At this point, the actual research is conducted. Your data collection could involve reaching out to customers via online surveys or telephone interviews.

The data collection phase begins with the formulation of a hypothesis. This tells what it's that the researcher wants to accomplish with his research. It usually involves asking specific questions regarding consumer buying habits or behavior. This would also cover any opinions about brands or companies, etc.

Then you get to defining the target population for the study. The target population is generally defined by geographic location. So that would be city, state, country, age group, gender, ethnic group, and income range.

4. Analyze Data and Present Findings

Meaning is given to the data collected at this step. The data is organized and useful insights are extracted to better understand the business or any other matter.

Data analytics helps to give answers to the questions which are difficult to find out through conventional methods. It helps in optimizing the processes and improving decision-making capabilities.

With data analytics, you see exactly what kinds of results your marketing campaigns are having. You can look at the information gathered from the surveys and gain a better understanding of exactly how effective your marketing campaigns are.

When you use data analytics, it's easier for you to see how likely people are to respond to your marketing campaigns. You will also get insights into how likely they are to purchase whatever product or service you're offering.

Data analytic techniques are widely used in marketing research. On its own, research findings are merely considered as opinions or suggestions. They do not hold much value. But with the help of data analytics, you can make decisions based on facts rather than opinions.

5. Take Action

The ultimate goal of carrying out a market research project is to enhance the decision-making capabilities of an organization. Based on the findings, your business can now make data-driven decisions. Marketing campaigns should be based on the findings of the research.

When you use data analytics in your marketing campaign, you can see the performance of your campaign with the help of real-time tracking. So you can look at your business in a meaningful way. This way, you can make necessary changes quickly and improve the effectiveness of your campaign.

Data Analytics in Marketing Research

Before data can become a revenue-driving tool for a company, it has to be analyzed. Data analytics is the process of analyzing raw data to observe trends and draw meaningful conclusions.

Nowadays, data reigns supreme.  The reality is that if you're a data-driven business, you're automatically 23 times more likely to get customers over your competitors. Businesses unaware of the invaluable nature of big data will inevitably be left behind.

So it's good for us to learn about customer behavior and the driving forces behind them. But, it's equally important to figure out what didn’t work in the past. You can start marking regression and predicting future outcomes and identifying opportunities for growth through regression analysis. So you would identify your dependent variable and independent variable.

The fact is, integrating data analytics methodologies into marketing research empowers businesses to predict consumer behavior, increase ROI, and improve decision-making.

Exploratory Data Analysis and Market Research

An Exploratory Data Analysis, or EDA, is an exhaustive look at existing data from current and historical surveys conducted by a company. EDA is beneficial because it examines patterns, trends, outliers, and unexpected results in existing survey data, and uses visual and quantitative methods to highlight the narrative that the data is telling.

Researchers that conduct exploratory data analysis can:

1. Identify mistakes that have been made during data collection, and areas where data might be missing
2. Map out the underlying structure of the data
3. Identify the most influential variables in the dataset
4. List and highlight anomalies and outliers
5. Test previously proposed hypotheses

For market research, it provides tools for hypothesis generation. So you can figure out research questions based on product lines. Exploratory data analysis allows for visualizing and understanding of data usually through graphical representation. This part of your research process opens up the avenue for data discovery.

3 reasons for Data Analytics in Marketing Research

1. Customer Segmentation

Customer segmentation is when you can group customers based on similarities. The target audience is divided into smaller segments. And this is dependent on factors such as demographics, interests, values, and more.

However, customer segmentation assumes that you already know who you want to target. For a simple example, let’s take demographics. As a segment, it's very broad and can be grouped down into smaller segments like age, income, gender, etc. If you're in the business of dog grooming, you want to speak to the consumers looking to purchase those services.

Segmentation would help with identifying people who can afford your product. But it would be much more helpful to identify people in these segments who would be most likely to buy dog grooming services.

Cluster Analysis

To help our dog grooming business target the right customers, we can use a statistical technique called cluster analysis. It resembles segmentation in the aim to group customers based on similarities. Powered by AI, cluster analysis uses mathematical models to discover groups of similar customers based on the smallest variations within each group. In terms of our dog grooming business customers, we’d collect quantitative data on:

• the number of grooming appointments booked online
• the number of home dog grooming kits purchased
• time spent viewing the website

Clustering could help us to identify that we need to be targeting customers who book online more often via email. Our emails to customers buying the home kits could promote similar products that make at-home grooming easier.

This type of marketing data analysis gives useful information for carrying out more accurate segmentation which inevitably leads to better personalization. So it's not always about how much data. But you want the right data to provide a good experience.

2. Reduce business costs and increase conversions

Business owners are constantly searching for ways to cut operational costs while increasing profits. Marketing research backed by data analytics and big data can help companies do just that. Over 40% of companies worldwide use big data analytics. And many are now enjoying a variety of benefits from big data.

Predictive analysis

Marketing costs can be reduced by using predictive analysis to direct marketers to the right channels to focus their ad spend. Predictive analytics leverages AI and machine learning with statistical techniques like data mining, to predict consumer trends and behaviors.

Using past insights, predictive analytics helps marketers identify customer segments closer to making a buyer decision. Similarly, it reduces time and resources spent on trying to reach uninterested customer segments. This is where factor analysis comes in to help you simplify certain data sets.

Artificial Intelligence and Machine Learning

Apart from the obvious intention of making sales, marketing seeks to strengthen certain processes. But even with sales data, the application of machine learning and AI removes routine tasks. If you have been wondering how those companies can create such personalized content for every single user, this is exactly how.

Marketing research can be time-consuming and expensive. But Artificial Intelligence (AI) and Machine Learning (ML) tools make you more efficient in your marketing research projects.

The AI/ML revolution is upon us, and it's changing how we do business. But many marketers are not sure where AI/ML fits into their marketing mix. Some marketers are even afraid to use AI/ML in their work. It all boils down to the age-old belief that machines will take over all of their jobs. But, bear in mind that when used the right way, machines can propel your business forward.

3. Competitive Analysis

Data analytics applications help businesses analyze competitors' strategies, market share, pricing models, performance metrics, etc. It provides deep insight into how competitors are operating in the same field.

Competitive analysis is a method of evaluating the strengths and weaknesses of your organization. The reason you do this is to identify opportunities for improving the performance of your business. The competitive analysis involves studying your competitors in terms of their products, pricing, distribution channels, promotion, and overall marketing strategy. Here you can see your qualitative data versus quantitative data.

The main objectives of a competitive analysis are:

1. To gather accurate information about your competitors.
2. To compare the data with your data in order to highlight areas where you can gain a competitive advantage.
3. To evaluate this data in terms of its potential effects on strategies and tactics for each product category in each market segment.

Top reasons to do a thorough competitive analysis

• Pricing

Pricing is a marketing decision that requires various techniques and data analytics processes to determine its effectiveness. The key to this process is the ability to collect, analyze, and understand information about your competitors.

Look at your competitive analysis as a way to gain a clear understanding of your competition and their strategies in terms of pricing. It also helps you understand what your target customers prefer and why. You gain insights into which prices your target clients like and dislike, which products they like and dislike, and how they make business decisions about price. This is where conjoint analysis comes into play.

• Competitive Benchmarking

Competitive benchmarking is when you can measure your performance against competitors. It's the part of your data analysis process that involves collecting data on how competitors are performing. Social media and search engines are good places to start. But there are various sources you can use. This way, you can identify things like their strengths and weaknesses. So, looking at content, a content analysis helps you to sort and compare the comparative data effectively.

• Product Performance

It's necessary to measure the performance of your product or service against that of your competitors. Product performance data allows you to identify what strategies are working for your business and what strategies need improvement

Conclusion

The point of all this is to provide a good customer experience based on your market research data. We cannot deny how advantageous marketing research is for businesses. But, on its own, only half the story is told. It helps to have data analysts who know how to use data science to help you navigate through meaningful data points. Knowing your market and customer is key to business success. That's how you provide the right answer at the right time.

However, digital marketing is always changing. And with it, data analysis methods will evolve. So being able to anticipate customer needs can catapult your business to higher heights.

Do you need help with data analytics in your business? Schedule a a free consultation with a specialist, today!