AnalyticsActionable AnalysisToo Much Data Means Too Much Data

Too Much Data Means Too Much Data

Don't get distracted by what you might get, but focus on what you know you can have.

actionable-analysisThe digital marketing industry is one of the few that talks of a surfeit of resources. This is not only anomalous but cause for real concern. What would you say about a restaurant that had “too much food” or an energy company that had “too much natural gas”?

You might scold them for whining, of course. Or you might take a page from King Ludwig of Bavaria when he told Mozart his opera had “too many notes.”

The surfeit in our case is a problem, not an asset. It is a warning sign, not a harbinger of great achievements to come.

A common definition of “too much” is “more than we need.” And if you’ve seen the slide decks at recent digital marketing events, you know that many presenters see it as a badge of honor that data is piling up at a stunning rate while the ability to use and process this data is lagging farther and farther behind. There is a gleam in the eye of the data-miner, who believes there are more nuggets because there are more mines (and certainly more work for data miners!).

Do We Already Have Enough?

The real news is that we may have already exceeded the useful amount of data being captured. Data mountains are not like Everest: you don’t climb them “because they are there.” You climb a data promontory because you need to see your assets on the field of battle. And if you can do that with a pair of binoculars and a position upon a strategic hill, you really would be wasting everyone’s time and money by hiring Sherpas and pack mules and going atop Everest where you can’t breathe and must carry your own oxygen. In fact, all you might see up there would be other mountains of data!

We certainly can have plenty of data about our target markets. And we certainly have constituencies that love the pileup of data because it allows them to deploy ever-niftier algorithms and ever-more-rapid access to petabytes of information; selling into our fear of falling irredeemably behind the data curve.

Just Another Buzz

But “big data” is really the latest buzz-meme more than it is a goal to conquer. The next most recent buzz-meme, “social media,” has been brought somewhat to earth with the realization that a million “likes” will get you on the bus only if you also have the fare. It’s now clear that social media is a campaign, and that without a tieback to conversion or sale, it’s “a whole lotta nothin” as they might have said in the old vaudeville acts.

It isn’t so different with big data. Big data thrives on the notion that ever more granular information will provide the ability to perform ever better targeting. However, beyond a certain point – a point I believe we have now passed – it becomes an exercise in futility. For instance, how much more targeted can your communications get before you simply exceed the ability of even the most savvy creative genius to craft the perfectly targeted message? And how many microsegments would you care to chase and at what cost toward what benefit? Moreover, how small a segment can you target before you simply freak out your prospect by seeming to know too darn much?

Some might argue for endless data collection with a throttle on its use. But then, the pile of unused data becomes just another bag on the Sherpa’s back as you trudge rather egotistically up the north face.

The answer today is to target not your customer so much as your data collection. Of course, you need to define your marketing goals more carefully than ever. And you’ll need to target your expertise as well, since technology and analysis can get costly. But you want to focus data collection based on need, not ability.

Half a century ago, the automobile reached a performance level that began to exceed the ability of humans to control it. It was possible but impossibly costly and even frightening to put Joe Driver behind the wheel of a 20-foot long heap of hurtling chromium that could make a thoroughbred seem hobbled and lame by comparison. Did it make sense to keep supercharging the engine for even more raw power? Or did it make more sense to refine the mechanics for efficiency and safety? With hardly a V-8 in production today, I think we have our answer.

The Big Data Mythology

Big data is the V-8: mythologized for the burble of its throughput. But beyond fabulously vertical line charts and a feeling of domain mastery, where is the benefit of this mountain of data? My suggestion is that there’s little benefit and a great deal of wasted time, money, and effort.

Never mind the sales pitch from big data specialists. Much of it is today’s equivalent of the kandy-kolored-tangerine-dream with a competition clutch and a big spoiler on the back. You can’t drive this baby anywhere but in circles on a closed track.

But if you keep it simple, you might find yourself leading a cultural revolution. Remember the little bug they called Volkswagen, and what it did to the roaring monsters from Motown?

Collect all the data you need and forget the rest. You won’t miss it. But you will miss the cost. Focus analysis on whether your audience did what you wanted them to do (this is really the heart of the matter and always has been) and don’t bother with trying to sell a different flavor of breadcrumb to every ant under the magnifying glass. They won’t notice the difference, and it will be cheaper for you.

Simplify. Concentrate. Don’t get distracted by what you might get, but focus on what you know you can have. And that is, a targeted data set used against defined goals, properly implemented, and carefully managed to achieve the return on investment that makes beautiful music in anyone’s ear.

Too much data is too much distraction. Keep your compass in hand. The near hills are full of low-hanging fruit, and the picking is good.

Andrew is off today. This column was originally published on May 7, 2012 on ClickZ.

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