data blunders or big wins?

Data Blunders or BIG WINS?

Images: Fox

TARGET KNOWS YOU’RE PREGNANT BEFORE YOU TELL ANYONE

“Statistics are like bikinis. What they reveal is suggestive, but what they conceal is vital.”-Aaron Levenstein

Target’s Data Analytics is Spot On

Young woman changes purchasing habits and Target is ON IT.

What does she buy?

A purse big enough to be a diaper bag

Unscented lotion Small blue rug Vitamins

Target sends a flyer addressed to her with coupons for baby items

She was actually pregnant and had purchased those items because of her pregnancy BUT….

Target’s Only Oops

She was a teenager in high school and was living with her parents.

Her father, understandably upset, went to Target to complain to manager.

Her father, Later apologized to Target when he found out his daughter was actually pregnant

Images: Fox

Lessons from Target

Trust your data! It was absolutely correct in this case

Use that data to your advantage. Just make sure you keep an eye on key data points

- Knowing she was 16, and therefore not sending her targeted coupons would’ve prevented a headache

As Target later did, introduce targeted ads and coupons mixed in with random, untargeted ones

- They now mix baby ads with lawnmower ads, etc.

In short, don’t freak people out with your hyper-accurate data

“It ain’t what you don’t know that gets you in trouble. It’s what you know for sure that just ain’t so” – Mark Twain

LITTLE BIG HORN AND CUSTER’S

BIG BIG MISTAKE

Custer Began with Inaccurate Data

Only Native Americans not living on reservations would be involved

According to his strategist, there would be 800 Native American warriors at most

The Accurate Data

Custer commanded 650 US Soldiers

Native Americans from reservations joined the non-reservation warriors to fight against CusterSome estimates

show as many as 2,500 Native American warriors

Bad Data Bad Results

Colonel Custer lost the battle and his life

Almost half of his troops were either killed or wounded

Native American forces lost ~1/8 of their men

Instead….

Don’t make the data fit what you want or expect; let the data tell you what the truth is

“Errors using inadequate data are much less than those using no data at all.” -Charles Babbage, inventor of the first mechanical computer

YES, EVEN GOOGLE IS WRONG SOMETIMES

Google Mines Your Data

Google AdWords and AdSense target ads based on your Google searches

Using that data, a digital profile of you is created

Profiles are sometimes hilariously wrong

How Wrong is Google?

Meet Ben, an iLantern intern

He speaks English and French.

He likes airplanes, electronics, and finance.

He is 25.

Google’s version of Ben

- He speaks Japanese.

- He likes cleaning agents, Reggaeton, and women’s clothing.

- He is 35-44.

Ben’s Not the Only One…

Joel Stein, TIME Magazine (Check out this article on Data Mining)

• He lives in LA, not NYC• He rents compact cars, not

sports cars• He is upper-middle class,

not “high net worth”• He is a TIME columnist, not

a medical professional• He doesn’t drive a truck

Meet Joel Stein, Journalist

85% Ain’t so Bad, Google.

Google’s overall profile was about 85% correct for our intern, and that seems to hold true for a small poll of our friends’ Google Ads profiles

When dealing with targeted ads, having millions of profiles that are ~85% accurate is incredibly impressive and lucrative (That’s right, show me the money!)

Lessons Learned

If the data is sensitive, treat it as such

Just because you want the numbers to point in a direction doesn’t mean they do

Mostly accurate data can work in the right context – just be absolutely sure it’s the right context

Not every datum is relevant – you must eliminate extraneous data

Correlation does not prove causation

“True genius resides in the capacity for evaluation of uncertain, hazardous, and conflicting information.”-Winston Churchill

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data

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