Analytichat

Did you copy my post about the creepy comment :-)

Haha! Creepy indeed!

Organizations must foster relationships built on trust by acting authentically and transparently at every level

I think a lot of creepy v magic hinges on providing value to the customer.. and of course respecting their privacy!

Trust eliminates the creepiness!

If they are truly timing it right, it wont be creepy. Noone will think about that when its just what they need. Its only when its done wrong...

First I think firms can't be to invasive. I am guessing when people start getting text messaging constantly while walking through a mall, or driving past businesses and are inundated with offers there will be backlash

@stubilick We new what you were going to say before you even said it - was it magic or predictive analytics? LOL

The blind pursuit of gathering more #Data and performing deeper Customer #Analytics has created a growing #Privacy backlash. Org's who routinely cross the "Creepiness Line" may soon find themselves subjected to Regulatory Scrutiny & Punishment. @IBMRisk

I blogged on this exact topic a few years ago: http://analyzingmedi...

@IBMAnalytics knew*

Businesses can balance the creepy vs magic factor by actively notifying customers about cookies and other tracking that will be done after they visit a website. Opt-in advertising is another way to mitigate the creepy factor.

Offers have to be limited, targeted and relevant, which gets to Richard's earlier point about good predictive capabilities
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It will become the norm/not be viewed as creepy for long. When Kodak first introduced the modern-day camera, it was viewed as an invasion of privacy since people no longer had to stand still for a long period for their image to be captured.

I wrote a number of blogs on this topic for the @IBMBigData Hub under the title of "The #Privacy Corner" @IBMRisk

It comes down to modeling customer journeys with an eye toward you, in your data/analytic-fueled biz processes, avoiding pushing them into "creepy" (e.g., privacy intrusive) paths on those journeys.

One of the best outcomes of the shift towards a future fueled by #analytics is that it will force every entity to become an authentic organization

somehow, dealing with privacy policies has to evolve past "trust us and whatever third parties we do biz with now or in the future"

@zjory Couldn't agree more! People used to think security cameras were creepy too

Ancestry.com was in the news recently for sharing DNA data with law enforcement that led to a wrong ID. the tables are turned when access to analytics and vast stores of personal data are involved.

the key is transparency. If consumers are aware of what their info is being used for...its less creepy #analytichat

@theRab Yes, excellent point!

I hear that Data Scientists make a pile of money... is there a shortage of people with those skills?

#DataAnalytics is quickly becoming one of the most desirable skills, but continues to be one of the largest knowledge/talent gaps

The vast majority of #CEO's, Boards & Senior Executive Teams are "#Analytics Illiterate". We must solve this challenge. #Unicorns will not suffice. We need Core Competencies in #Data, #Information & Analytics in all Organizations. @IBMRisk

Knowledge gap? We're talking IBM here. We have so many brilliant analytic-minded business pros, so much great data, and so many vital analytic apps and tools in use that the issue becomes: avoid analysis paralysis. Focus on key business metrics

All the IBMVision tracks will help fill in those gaps!

IBM has a huge data-scientist team. The "knowledge gap" becomes: how to apply their expertise where it's needed most?

@jameskobielus Outside of IBM, do you believe there is an #analytics knowledge gap?

More than 250,000 people have signed up for bigdatauniversity.co... for free big data courses!

Making sense of all the data and not being overwhelmed by it all

imo the gap is not just in tooling or technology but operational usage of data and data science

One of the gaps I see the most is getting access to the right data!

I see one of the major difficulties being asking the right questions. We have plenty of data to analyze, but need to make sure that data is helping answer important questions.

Perfect example of how we close the knowledge gap on analytics: bigdatauniversity.co... as a resource for anyone (IBM, partners, customers, college student in dorm room, etc) to train themselves, gain the skills they lack.

Trusting the data. We are used to relying on our past experiences. Or at least using a combination of experiences and data.

Interesting finding from leadership research puts premium on "network leadership". Knowing you need to turn on a dime is not the same as turning on said dime.

IMHO networking in the social age is still a challenge and analytics tools have been difficult to access for this

Offers have to be few, targeted and relevant which gets to Richard's point about good predictive capabilities

Remember the story about Target where they sent coupons to a pregnant team? They were right, but her father thought they were wrong!

Without naming them, a well known north American bank refused to fund a cash secured loan because their loans division couldn't get data from the banking division.

i.e., they weren't able to share data across divisons and verify the funds to secure the loan existed.

I like when banks stop my credit card from being used when they think it's been compromised... but hate it when I can't answer my own security question!

I would proffer that most Business's fail their customers by being "bad-data-driven" than not being data-driven at all. @IBMRisk

My previous telecommunications carrier (name withheld) consistently failed to recognize my specific needs, complaints, etc. They didn't drive a "single version of James Kobielus, customer" into any of my discussions with their channels. I churned!

my main qualm with customer experience fails is when loyalty programs aren't tied to buying preferences / requirements. often times you see this implemented as two systems and that is not only a big miss but an annoyance.

Remember when the London Olympics oversold 10,000 tickets due to a spreadsheet keystroke error? That's 10,000 angry people!!

My bank keeps sending me the same offer that is completely irrelevant to me. With their data, they should have been able to understand the offer is inappropriate. It is like the movie Groundhog Day, the offer keeps arriving over and over

Spreadsheet error at Fannie Mae cost the company in excess of $1 billion, causing the share price to fall from $73.10 to $2.25 after the error was announced

A top financial institution identified a $2.6 billion error when one of its accountants omitted the minus sign on a net capital loss of $1.3 billion and incorrectly treated it as a net capital gain. Accurate data is key!

Businesses fail me all the time not so much by their failure to keep accurate or comprehensive data on me and my family, but on failure to use it smartly to target specific offers or experiences that are valuable to me.

@IBMAnalytics when divisions within a financial company run on different databases that aren't shared and to complete a transaction the user has to work separately within two online sites

@InfoMgmtExec Awesome point! Still a fail if they use the wrong data! Or good data in the wrong way.

Big bank just this week shut down my credit card bc I tried to charge the cab fee from airport to hotel. they should know i'm in vegas. nuts really

The pregnant teen story is in @JSEllenberg 's book How Not to be Wrong, Chapter 10: Are you there God, it's me, Bayesian Inference. Day two Keynote at #ibmvision

Last year, a spreadsheet mistake cost Tibco Shareholders $100 million!