consumer research / consumer behaviour research papers / consumer panels / online buying behaviour / types of consumer research

Your handy guide to research analysis for consumer research

. 4 min read . Written by Vanshika Goenka
Your handy guide to research analysis for consumer research

Conceiving a phenomenal business idea is an incredible feeling for sure, but it is often accompanied by doubt. Phenomenal idea or not, no one is immune from a misstep every now and then. And missteps regarding business can be particularly scary due to the high costs and stakeholders involved.

This is why consumer research is so important, especially when your idea is still in the stage of development. What is consumer research you ask? Well, nobody can answer that better than the PowerPass. With a PowerPass subscription, you can access knowledge on a variety of different subjects, ranging from social media marketing and search engine optimisation to consumer research.

Why do you need to analyse research?

All pursuits begin with the intention of eventual fulfilment. Similarly, research is begun with a purpose, and to fulfil this purpose, collected data needs to be analysed. Analysing consumer data brings insights that are useful for making business decisions, especially ones that require consumer input. As a general rule, research data can be divided into 2 types:

  1. Qualitative data analysis

If you're not the biggest fan of maths and statistics, analysing qualitative data might just be your calling as a consumer researcher. Qualitative data is data that is generally abstract and can be collected from focus groups, personal in-depth interviews or open-ended questions in surveys. It includes answers that are harder to analyse because these are answers about taste, preferences, experiences and opinions. Sounds tricky? Let us break it down for you -

Steps to analysing qualitative data

  1. Transcribing data

Focus group sessions and in-depth interviews spill out a lot of information that would otherwise be impossible to remember. Unless… you record the session. Of course, it is both ethical and practical to first notify the consumer panels that their responses would be recorded for research purposes. Once the Q&A session is done, you can go ahead and transcribe this audio—play, pause, note and repeat. An essential element of transcription is noting down the questions that you ask, so segregating answers can be simplified.

2. Identify the theme

Suppose your research concerns analysing the online buying behaviour of consumers, some ongoing themes might be related to price sensitivity, product availability, reaction to online promotions, UI & UX design, or search engine optimization. Identifying the themes surrounding research will help organise the data you collect.

3. Interpreting the data

Once the data is organised based on themed categories, it is time to start interpreting. Data interpretation should be done on the basis of the demographics, since respondents of a different demographic could have entirely different answers. Interpreting data at this stage should not take up a lot of time since you will already be familiar with it.

4. Present data

Once you’ve interpreted the data, you can go ahead and present it in a format that makes sense to you. This could be posted on social media in the form of a series of posts related to the topic or presented as part of consumer behaviour research papers.

2. Quantitative data analysis

Despite what the name suggests, quantitative data is not always a lot of data. It is simply data that can be quantified, i.e. numerical data. Quantitative data revolves around ages and ratings and hence, it is a great way of analysing data collected via surveys. Let's have a look at how quantitative data is analysed.

Steps to analyse quantitative data

  1. Evaluate your research question.

The ‘research question’ that you propose is entirely different from the questions asked in a survey. The research question encompasses the basis of your research objectives and analysing the research question helps align the analysis with the research objectives.

2. Cross-tabulate data

Cross-tabulating is not as hard as it might feel in spite of the numerous research variables. For instance, your research question could be to understand whether people prefer physical books, e-books or audiobooks. Your variables, in this case, would include—age, occupation, time spent reading or listening, and so on and so forth. You cross-tabulate by adding data to tables which will help break down how the data is interconnected and also how they vary.

3. Diagrammatic representation.

This might just be the most fun part of quantitative research analysis. Diagrammatically representing data in the form of charts, pie diagrams or graphs gives you a visual as well as a break from heavy statistics. Having a visual aid helps decipher entirely complex information.

4. Check and interpret data

Once the data is tabulated or diagrammatically represented you can start interpreting data. You might need statistical tools if your data is intricate otherwise you could just interpret a pattern and draw a conclusion. For instance, you could find out the percentage of respondents in a particular age group that prefer physical, audio or e-books.

Consumer research is the foundation of implementing a brilliant business idea and once you've analysed consumer research you would now realise whether or not your research question and hypotheses are relevant. This insight will allow you as the researcher to tweak the business idea or implement or modify a decision based on your key findings.

All in all consumer research does not have to be difficult. I mean, we’re consumers too right? How difficult could it be to analyse ourselves? *chuckles nervously*
But we have some good news for you, with Kool Kanya’s course, “Consumer research made EASY”, anyone can become a consumer research expert! Through this course, you will learn all about types of consumer research, research methods and analysis and get started on the right foot.

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