How to Use Quantitative Research Methods for Digital Marketing

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How can you measure the efficiency of your efforts if you don’t analyze your data? Research methods are a fundamental part of marketing strategy optimization.

As a digital marketeer, you always want to be uncovering hidden opportunities. Research is fundamental for this.

The field of research methods is considerably vast, so we will make use of two articles to cover its most important concepts.

This article will deal with quantitative methods, and the next one will cover qualitative research.

When to Use Quantitative Research Methods

graphic showing research and data

As the name suggests, a quantitative research method focuses on numerical analyses. This method is used when you want to measure an indicator numerically and use statistics as a tool to draw results.

Qualitative research, on the other hand, focuses on understanding why certain behaviors happen.

For example: quantitative research will measure how happy your customer or visitor is, while qualitative research will focus on understanding the reasons for that.

Here are some examples of when to use quantitative methods:

  • User profile: identifying user demographics, inferring whether certain groups are more likely to purchase your product than others, measuring customer satisfaction levels, among others;
  • User purchase behavior: what is the abandonment rate of your shipping cart, how many units of each product are bought, how often a sale is made, what is the actual profitability per customer;
  • Website traffic reports: how long does a visitor stay on your website, what are the most successful pages, what are the most common exit points;

Advantages and Disadvantages of Quantitative Methods

Quantitative methods are by far the easiest to analyze because they present structured data which can be handled in large amounts by software such as SPSS or Stata.

Another advantage of quantitative research is the possibility of testing hypotheses with the help of statistics. A/B testing is an example of how quantitative data is used to determine the optimal design of a web page. Quantitative research is also indicated for identifying which factors influence indirect constructs – indicators that are not directly observable in the population.

For example: you want to understand which factors affect your visitors’ satisfaction with your website and by how much they influence the outcome. Visitor satisfaction is an indirect construct, and you can think of several factors that might influence it: the design of the website, the speed, the relevance of content, among others. By collecting the data on the user satisfaction and on the individual indicators, it is possible, through statistics, to conclude the relative importance of each factor in your final construct!

Quantitative research, however, should be used with care. Since the questionnaires in a quantitative study offer a limited set of possible responses for each question, you might miss important data from your sample. In addition to that, it is very hard to find a fully reliable cause-effect relationship only with quantitative data (remember, correlation does not imply causation). When trying to understand the cause of certain behaviors, qualitative research might be your best option.

The Validity of Quantitative Methods

When collecting structured data on your visitors, how can you ensure the sample data is relevant and represents the entire population? Are you being careful to select your sample randomly?

Validity is about whether your quantitative instrument measures what you want to measure and whether you can generalize your findings to the entire relevant population.

Validity is sometimes straightforward: if you use Google Analytics on your website and want to check the audience statistics, you simply open the page and analyze the results immediately. In other occasions, validity must be considered more carefully.

When designing an online survey to measure customer satisfaction, you must consider whether the questions are sufficient and necessary to measure the indicator. In addition to that, you must make sure that the sample answering to the survey is representative of the entire population.

For example: if you send the survey only to those customers that did not register any complaints, your results will be highly biased and you will not be able to generalize them to the population.

Quantitative Methods for Digital Marketing

Now that the basics of quantitative research are covered, let’s dive into more practical cases of when and how to use it to obtain data about your visitors and target market.

Online Quantitative Survey

In order to help you craft an effective online survey, SurveyMonkey offers a detailed guide on how to elaborate survey questions that are relevant and unbiased.

While some websites such as Google Forms will let you create a survey in minutes, spread it to your audience, and collect an unlimited amount of responses, they are likely to have very limited analytical features (if they have them at all, which is not the case with Google Forms). In this case, the best course of action is to export the data to Excel and use the software to conduct your data analysis.

Paid softwares such as SurveyMonkey and Qualtrics offer complete solutions both to create the surveys and analyze the results. With them, you are able to run complex data analysis techniques and obtain relevant insights right from the platform. 

While free tools are very appealing, if you want to use online surveys as the main part of your digital marketing strategy, you should consider investing in a paid solution.

Gathering Data from Your Website

There are countless types of data you can track on your website. Some examples include:

  • Average time spent on each page of the website
  • Visitor flow when browsing your pages
  • Visitor demographics
  • Acquisition channels
  • Click density and heatmaps

Google Analytics is highly effective in collecting data to calculate a wide variety of indicators related to website audience, behavior, and acquisition. The Online Marketing Institute provides an insightful article on how to explore the hidden potential of the tool.

A great example that highly relates to quantitative research is the user segmentation feature. By segmenting your data, you are able to infer which segment is more likely to purchase your product, stay longer on your page, or share your posts on social media.

Google Analytics, however, is not the only analytical tool available. If you have more specific needs, you might want to consider some alternatives such as Hotjar, a tool that literally records each and every user visit to your website and tracks metrics like heatmaps, conversion funnels, or form analysis. ConversionReview has put together a list of the best optimization tools for websites. Make sure to check it!

Collecting Social Media Statistics

Social media can be used both for quantitative and for qualitative research. All the numeric data from social media – shares, retweets, likes, other interaction metrics, as well as user demographics, for example – can be considered of quantitative nature.

The major social media platforms normally offer access to the raw data relating to the activity of your page and posts. They also offer some statistics and insights on how to improve your social media presence. However, if you want to maximize the value from the raw data you have, the best course of action is to download it and use a specific software to analyze the set.

Secondary Research: Reusing Data Already Available

While primary research includes the activity of designing the research instrument and collecting the data, secondary research uses data already available to conduct new analyses and look for innovative insights.

Take, for example, the article from KDnuggest with a list of Social Media datasets. There are several databases listed in the article, and most of them offer free access to past data on social media platforms and other websites.

Secondary research is recommended when the cost of collecting the data is higher than the benefit. A simple example: if you are considering expanding your website to a new country – which involves several tasks such as translating the website, optimally hosting it, finding a good domain, hiring local website managers, among others -, you want to first know whether it is worth the effort. This type of research is normally done with the help of datasets that already contain information about the population of that country. 

Naturally, there are challenges involved in secondary research. The original dataset might not be optimal for the metrics you want to calculate (it might have been developed with other goals in mind), or it might be too messy to yield any relevant results. Pay attention to these and other characteristics of a dataset instead of blindly using it for research purposes.

Quantitative research must be an integral part of any online marketing strategy. There is an astonishing amount of data that can be recorded from your website visitors, and by combining it with well-designed surveys, you will definitely obtain great insights into how to optimize your website even more!

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