Marketing Research Quantitative Survey Fielding Reflections

Marketing post this time! It’s the 4th post of the year and if you followed the narrative it’s time for a marketing post! Recently, I had the chance to carry out end to end planning and execution of a marketing research for my work on Branding and Pricing Strategy.

I learned marketing research in school, and ran researches while at NTU Students’ Union. Planning, fielding and analysing. Back then, I didn’t realise how hard fielding was. It was just a mass EDM (Email Direct Mailer not Electronic Dance Music) to the whole school, and gifts were provided to participants.

Marketing Research: Problem

Initially, I thought that fielding this survey would be a walk in the park. How hard can it possibly be? I could not have been any more wrong than that.

Marketing Research: Photo of Cold Storage Tampines 1
I was standing right here at the entrance.

After 4 hours at night, standing outside the supermarket with aching arms and legs, there was only 15 respondents, half of what I planned to get in half the time. Reflecting on the experience, I faced 3 main problems:

Firstly, I was abruptly cut off and rejected on introductions.

Good Evening, I’m a Market Researcher from Company X……

I believe that the lag time before running away would likely be glancing for free gifts or maybe something else.

Secondly, I held my tablet with one arm, and definitely that was not the best thing to do. Furthermore, I was travelling with a laptop slung on me inside my bag. As a result, my body was aching all over at the end of the day.

Thirdly, many people were rushing for time and could not take 5 minutes off their schedule to complete the survey.

Either way, my study received minimal participation.

Marketing Research: Solution

After an unsuccessful night, I needed to find a simpler way to get participants to take part in the survey. With careful thought, I thought of 3 solutions:

Solution #1: Refine the Pitch, Starting with Pain Points

I figured out that the first few words spoken influences if customers will continue to listen, and to tie it to their interests. For instance, I did this pitch:

We’re looking at improving our product offering in Company X. Can we take 5 minutes of your time for a short survey?

I started with the customers’ pain point, basically what they came to the supermarket for — to meet their needs.

Naturally, more customers became open to conversation, especially when their needs are met.

Solution #2: Travel Light and Position Strategically

When I turned up for the second day of the survey, I left my laptop at home, only armed with my tablet and QR Code (More on the QR Code Later). Besides that, I also found a place to station at. This meant that I did not need to carry the heavy tablet for the whole day, and could focus on delivering the pitch and executing the survey! The location which I picked also has some foot traffic, which allows more chances to deliver the pitch!

I stationed myself at an ice box where I could leave my items and also reach customers.

Solution #3: Explore Alternative Methods for Participation

If the customers are rushing for time and just have no time, you can bring the survey to them! I printed a QR Code to allow customers to scan and carry out the survey on the go, which solves the rush hour problem. In addition, when I went to the store on a weekend, I noticed the long queues forming. Instantly, I jumped onto the opportunity to survey the customers in the queue! When customers are already there and do not spend additional time, they are more open to being surveyed!

Did up a QR Code! Intentionally Truncated the QR so that it can’t be used!

Marketing Research: What more can be done?

While I did finish my survey after 3 days? What could I have done better? If I had more time to plan, I would have set up an actual booth, and prepare gift vouchers from the company as incentive for taking part in the survey.

Marketing research on a weekend!
Fielding my research on a weekend well spent!

Closing Words

Finally, I hope that this reflection provided a new perspective on improving your quantitative marketing research. I wish you aspiring market researchers the best of luck in your next research!

If you liked this post, do check out our course review on the Mini Masters in Marketing Management at NBS, where I have also reviewed about the marketing research course.

In addition, if you liked reading about this post, do follow us on our LinkedIn Page. Also, you might want to read about learning analytics versus marketing!

Image Credits: Original Photography from Tan Wei Xiang


What I learned from Text Mining 400 Spam Comments on my Blog using R

Hey everyone! Welcome back to another amazing analytics post this week. If you are a frequent visitor of my blog, and somehow made a genuine comment here, you would have noticed your comment never appears. If you saw the screenshot above, out of a total of 999 comments, I have marked 400 as spam.

I was reading through some really interesting comments on my blog and I was thinking, why not try doing some text analytics to see what are spammers most interested in talking about on my blog.

Some simple explanation, text mining is a common way to do sentiment analysis on long lines of text which many market researchers do not want to look through. By going through specific text found in the whole data, researchers want to find out what the general public is talking about. In this instance, I want to find out what spam comments are generally being posted to my blog.

A bit of Data Cleaning: The very manual and boring part…

I started off by copying 400 comments and saving it inside a txt file. As my professor always said, data analytics is about 80% data cleaning and 20% analysis. I would change the 20% analysis to 19% and add 1% in terms of insights, which is what the business world truly values.

My First Round of Analysis

After a whole massive cleaning exercise here are the first set of results, represented in a word cloud of my top 30 most popular words in the spam.

The most popular keyword is http… Which means people are spamming websites.

The most popular keyword in the list of comments is http, which many websites start with (https was also likely in the list with the s being removed and recoded as http.) The second most popular keyword is urlqhttp which is probably also a website.

In 400 posts, there were close to 8000 times http has appeared.

In 400 posts, there were close to 8000 instances a web address has appeared, which means on average, spammers were posting 20 links to my blog. (They are probably trying to create backlinks to their website to improve their search engine rankings, which also will damage my website search engine ranking if it has too many backlinks out.) Thankfully these comments did not see the light of day.

Site and blog were the next highest which would make sense to come out 1.5 times per comment. Things like: This is an amazing blog/site, before adding in other things.

These links all appeared 582 times, which should be more or less safe to assume they are posted by the same poster.

These websites were also the most frequent in the comments, in the same frequency, it is likely that a bot has been created by a poster to consistently post the same thing over and over again. (Or perhaps he is that free and did it manually.) It was nice to know that spammers on my blog is interested in reviews, trips and books, linking things, and some German place which consists of Freiheit, which means political freedom (Yes, I learned German for 4 years before.). I did not open the links as I was worried of any potential spyware.

Okay that is enough analysis for today. If you are interested, do drop by for round 2! If the viewership is high enough, I’ll likely run another analysis on more comments in future.

If you liked the analysis, you may like this analysis too!

Otherwise you might want to know how to put analytics and management together!