Millennials: The Next ‘Pig in the Python’

FOR GRAYING BABY BOOMERS like me, the awesome power of demographics has in many ways defined our lives. There are a lot of us. We clogged our kindergartens, our universities, our workplaces, our media, our politics and our communities with sheer numerical might; and the retail marketing universe seemed to revolve around our needs and our sense of entitlement.

In his 1980 book, Great Expectations, author Langdon Y. Jones called this phenomenon “a pig in a python” – a rather visceral visualization of how the boomers’ demographic bulge has traveled through America’s culture, distorting as it goes.

Along the way we also had a lot of kids. So many, in fact that we engendered an echo boom that is numerically larger than our own. In case you haven’t noticed, those 75 million “millennials,” as the demographers like to call them, now largely dominate cultural, political and marketing discourse. Not to mention our consumer economy – the 18-34 cohort wields $2 trillion in purchasing power.

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Rise of the Retail Robots

Robo-ClerkFRUSTRATED WITH STORE EMPLOYEES? Maybe a mechanical clerk is the answer.

The retail industry today is making some fascinating, promising, and perhaps troubling moves toward the routine use of autonomous robots in human environments. The efforts seem energized by technical advances, affordability gains, and increasing wages for their human counterparts.

“Everybody is beginning to talk about robotics as a way to remove labor from the system,” said David Marcotte, a senior vice president with consulting firm Kantar Retail, a friend of this blog, in an interview in the Star Tribune newspaper.

As a confirmed sci-fi geek (occasionally prone to paranoid fantasy), I’m both fascinated and a bit leery about this development. There’s little doubt, however, that the robots are coming to retail from numerous directions.

Tenser’s Three Laws of Retail Robotics:

1 – A retail robot may not harm, mislead or impede a shopper, or, through inaction, allow a shopper to fail to complete a sale or have an otherwise poor experience.

2 – A retail robot must faithfully implement the merchandising plans given it by retailers except where such orders would conflict with the First Law.

3 – A retail robot must encourage and protect the sale, as long as such protection does not conflict with the First or Second Law.

(Adapted with great reverence from i Robot, by Isaac Asimov.)

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A Little Problem With Big Data

Courtesy RetailWire.comA STIMULATING DISCUSSION in RetailWire.com this morning led me to once again think deeply about how retailers are confronting so-called Big Data and applying it to their businesses.

The question posed was an intriguing one, given the continuing hype and mysticism ascribed to Big Data over the past several years.

What is your take on the advancements (or not) retailers are making in the use of data capture and analysis? Is it all leading to significantly improved customer experiences down the road, or something less?

The responses mostly seemed to accept two tacit assumptions: One, that all store data is Big Data. Two, that the primary goal of Big Data analytics is the creation of targeted promotional offers. I have a little problem with that.

When did retail POS data suddenly become Big Data? We’ve been collecting it (and mostly discarding it) for decades. Now that storage costs have finally declined, we can capture and hold it long enough to run a few queries and design a few models. Shopper in-store data really hasn’t changed much, but our ability to mine its potential has certainly advanced.

Certainly data flows from the POS and frequent shopper programs continue to expand. There are even some new sources, like in-store shopper tracking, entering the mix. Yes there’s lots of data. But is this really Big Data?

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Invoking Relevance

RelevanceBEST PRACTICE IN MOBILE ADVERTISING remains an oxymoron, as marketers grapple with the natural tension between intrusiveness and usefulness. There is a strong drive to justify ad spending and validate the business premise behind personalized promotions. Relevance seems to be the key, we are told, and the unique data-capturing and consumer-tracking capabilities of mobile devices should materialize a marketer’s nirvana in which every message is on-target and welcomed.

Recent consumer research from PriceWaterhouseCoopers suggests that this formula may need to be applied with greater subtlty, however.  In Mobile advertising: What do US consumers want?, PwC researchers find, “There is an overall aversion to the prevalence of mobile advertising. Even ads that are relevant to personal interests do not directly translate to ad interest or engagement.”

This poses a challenge indeed, since according to PwC, “The biggest challenge is to leverage the knowledge of how consumers are using mobile to improve monetization from ad delivery.”

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