Tag Archives: statistics

May 6 2012

Through the Eyes of A Market Research Methodologist #MRX

My name is Annie and I’m a market research methodologist. What does that mean you ask? Well, it means I pay more attention to the research design of a project than the actual product being researched. I didn’t realize until recently how it impacts the way I perceive the world around me but here are a few examples that just might explain.

Actual message: There is currently a nutrition supplement commercial on TV that proudly proclaims “Every drop has Vitamin D.”
What they’re saying: If you aren’t getting enough Vitamin D, you can use our product to compensate.
What I process: Jeez, this soda cracker in my hand also contains Vitamin D. Doesn’t the nature of the universe dictate that every ingestible product has vitamin D? Isn’t the issue how much vitamin D and whether that amount is sufficient to over-come my lack of Vitamin D? Get back to me when you can quantify what you intend to give me and what I actually need.

Actual message: In a laboratory study with 34 mice, excess doses of sugar were found to cause severe and untreatable cancer.
What they’re saying: Stop eating so much sugar or it’ll kill you.
What I process: n=34? What kind of statistical power is that? You can’t conclude anything from that other than you need to finish up your exploratory research and conduct some confirmatory research on humans. Get back to me when n=300 humans.

Actual Message: In a poll of 300 Americans, Obama leads in voting intentions with 49% favouring him and 45% favouring Romney (+/- 5.6%, CI=95).
What they’re saying: Obama is winning.
What I process: Plus or minus 5.6%? In other words, 49% equals 45%. There is no winner here! Why are you telling people there is? Why are you misleading everyone? Tell me someone is leading when your sample size is large enough to make those numbers significantly different.

3d florescent pie chart


Actual message: This pie chart indicates that 29% of people die from cardiovascular death while 23% of people die from infectious or parasitic disease.
What they’re saying: Cardiovascular and infectious disease are major causes of death.
What I process: How are you unable to see that 29 + 23 does not add up to 100? How do you not know that  pie chart data needs to add up to 100%? Is this why people have such trouble understanding the news? Because it’s not presented properly?

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So now I’m curious. Are your blinders on the research method or on the research conclusions?

Apr 6 2012

Really Simple Statistics: What is a standard deviation? #MRX

really simple statisticsWelcome to Really Simple Statistics (RSS). There are lots of places online where you can ponder over the minute details of complicated equations but very few places that make statistics understandable to everyone. I won’t explain exceptions to the rule or special cases here. Let’s just get comfortable with the fundamentals.

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Standard deviations are massively popular in all aspects of market research reporting. Any time someone tells you an average number, they’ll probably tell you  what the standard deviation is at the same time, even if you didn’t ask for it. At it’s most basic level, a standard deviation is a number that tells you how similar a set of numbers is.

For now though, let’s forget about all the technical language and think about a casual application. In your immediate family, most of the women are probably similar to each other in terms of their height. If your mom is 5 foot 3, chances are that many other women in your family are somewhere around 5 foot 3, and in fact most of them are probably within an inch or two of 5 foot 3. The “normal” woman is about 5 foot 3 and there is very little differentiation or deviation among the heights. The deviation is small.

On the other hand, get out the wooden ruler you’ve saved since public school, the one with your 4ever true love engraved on it, and hold it up to their hair. Some of the women have really long hair, others have shoulder length hair, while still others have short and snazzy hair. There’s a lot of  differentiation, a lot of disagreement, a lot of deviation in their hair lengths. Sure the average or normal length might be 8 inches, but the deviation from the norm could easily be 8 inches. The deviation is large.

In the market research space, you can look at standard deviations in a similar way. It can be interpreted as the amount of disagreement among people’s opinions. Let’s consider 100 answers to a purchase intent question asked on a five point scale from Definitely Will Buy all the way to Definitely Will Not Buy.

  1. If 50 people answered definitely will buy and 50 answered definitely will NOT buy, that’s a big difference among the answers, a lot of disagreement, a lot of differentiation. Half of the people are checking off the 5 and half of the people are checking off the 1. People haven’t come to any consensus on whether they agree or disagree. In technical words, that clear disagreement indicates a wide or large standard deviation. These wide standard deviations make our work as market researchers more difficult. It’s hard to recommend a new product when people can’t agree on whether they would buy it.
  2. But, if 90 people answered definitely will buy and 10 people answered probably will buy, there’s a lot of agreement there. 90% of the people are checking off the 5 and 10% of people are checking off the 4. People are generally agreeing with each other. They pretty much all intent to buy though some are a little more sure about that purchase than others are. That agreement reflects, inversely, very little differentiation, very little disagreement. It indicates a very narrow or small standard deviation. This is what market researchers love to see. We have a clear answer to our question and can proceed to recommend a product that most people would like to buy.

So here’s the general scoop:

  • Small standard deviation = Lots of agreement among the opinions
  • Large standard deviation = Lots of disagreement among the opinions

It’s that simple!

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Dec 12 2011

8 Christmas Gifts for Market Researchers #MRX

This isn’t necessarily my Christmas list but I have to admit a few of these would make me giddy. So, in no particular order, I give you geek gifts for market researchers.

1. Math Clock

mathematics clock

2. Pie Shirt

3.14 pi tshirt

3. Statistics Mug

statistics mug

4. Normal Distribution Ornaments

normal distribution ornament

5. Statistics Apron

statistics apron

6. Statistician Bib

statistician baby bib

7. Made Up Statistics

made up statistics

8. iPhone Cover

statistics iphone cover

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Nov 15 2011

Engage Your Users and Bring Home the Bacon #MRX

A cooked rasher. Raw bacon rashers are an esse...

Image via Wikipedia

[Fans of bacon should read this version instead.]

Do a quick search on Twitter or Google and you’ll instantly find 412 653 ways to encourage people to engage more with your product. Reply to people, ask questions, use polls, give a call to action, request videos and photos, give them user accounts. The list goes on and on.

Why do we do this? Because research says that when users are more engaged with something, they spend more money on it. And we all like money.

But wait. Something i paid little attention to in my introductory statistics class is nagging me. It’s telling me not to leap to assumptions. It’s telling me that just because someone spends more time on something does not mean they will consequently spend more money on something. It’s telling me that correlation does not equal causation.

You see, people who are more engaged with something, a website, a shoe company, a kitchen supply shop are already invested in it, more than people who are less engaged with something. These people are more engaged because they like the company. They buy the product because they like the company. They do not buy the product because they are engaged with the company.

It’s very easy to forget the direction of relationships among variables. Sure, you can convince a bunch of people to become more engaged, and sure some of them will grow to like the company, and sure some of them will make a purchase. But don’t fool yourself into thinking you can get a bunch of vegetarians to eat bacon by convincing them to create a user profile on your bacon website and share bacon recipes with them. The common denominator isn’t engagement. It’s the bacon. It’s always the bacon.

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Nov 5 2011

Statistics Poetry by Geeks and Nerds #MRX #Statistics

I couldn’t help myself. The creative juices started to flow and poetry spewed out of me like warm icing from pastry bag. And then, one poem let to another and another and the twittersphere united in poetry goodness. Do enjoy, then tweet your own poem about statistics, charts, or research methods. I’ll add it here. Enjoy!

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