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Data Shock

Daniel Glickman

It’s 2017: Data Shock Should Not be All That Shocking

We’ve seen it coming: Brands and businesses now have access to infinite amounts of customer data, and the amount of data we are collecting doubles every year. By 2020, who knows what the collection rate will be, and what new marketing insights and powers we will gain—but right now, who cares, because we marketers have enough of our work cut out for us. Most of us are hyperaware of the fact that if we don’t already have a decent strategy in place for the where, how, why and what kind of data we are seeking, collecting, sorting, analyzing, and utilizing, we are standing directly behind the proverbial eight ball.

Of course, the collection, storage, and maintenance of data requires significant investment—and now more than ever, CMOs have to be vociferous: “Dear CEO, CFO, and CIO, Show my marketing team the money!”

I address in my forthcoming book, Disrupt That, the urgent need for marketing departments to request, win, earn, and justify a greater portion of their company or organization’s budget. We must, however, budget for this deluge of data responsibly—with our eyes wide open, because initially, dollar per data unit may be small, but the more we collect, the more we will have to spend. These financials aren’t simply a matter of the number of data units needed today or next quarter, but reflect also the ever-faster servers we’ll need to process our ever-growing data loads and the effort we’ll need to invest in, sorting, structuring and maintaining it all.

Bottom line: The cost to maintain, structure, and purge data is not linear—at a certain threshold, the cost per data unit will actually increase.

Data Shock - Daniel Glickman


So yeah, we’ve seen the data tsunami coming, and some of us are semi-prepared—but many are still lounging at their desks, kicking their feet up, and squinting their eyes into the metaphorically blinding sun: “Data? We’ve got plenty! What? Are you asking us how we actually use it? What do you mean?”

If you are one of the many marketers who hasn’t already figured out that most customer data is irrelevant… no, wait… let me restate that:

If you are one of the many marketers who hasn’t already begun to figure out how much of the data you are collecting on your customers is irrelevant to your brand or company, I’m here to remind you: There is a limit to how much data you can actually capitalize on! Just because data comes cheap and fast (at first), just because it simply “arrives” via your mega-amazing (and super-spendy) API and you know what altitude your customer is standing at right this very second, does not mean altitude matters.


Data Shock - CMO Confessions

So yeah, look at the data you collected: Were you smart about it, or just hungry for it? Did you take the time to acknowledge: “We don’t need X, Y, and Z… just Z.”

Data has no heart and soul—it simply follows the law of returns. We know the amount of data we’ll have access to is expected to grow exponentially and that some of us are already in the initial stages of data shock, where we are receiving lots more data with lots less return. CMOs who faced the data inundation early on and planned their systems well, have already begun to experience this friction point—where data has become a hindrance, a nuisance.

“Data as a nuisance?” you ask. “Really?”

Yes, really! 

And yes, at this point, most of us still do need more data. But knowing that some of the more forward-thinking marketers and brands out there have already hit saturation point, let’s commit to keeping our ears wide open to what they’ve learned so that we can work to alleviate, in advance, some of our own brand or company’s impending data shock.

What I’ve seen in my work with ROOJOOM, especially in the past year, is that improving ROI by better usage of customer data falls under the above-mentioned law of diminishing returns. Why? Because, micro-optimizing leads to micro-results… unless:

  1. Brands use customer data to develop entirely new services.
  2. Brands share their customers’ data with partners.
  3. Brands develop entirely new ways to deduct new conclusions from data.
  4. Brands tie data-driven customer facing systems with data-driven supply chain management systems to reduce inventories, cut costs, and reduce supply time.

Customers are learning to expect brands to have access to any and all of their relevant data, and this trend is being accelerated by new virtual assistants and voice activated interfaces that  will quickly become new platforms for brands to sell and service customers.

Who will win in this brave new virtual data-fueled world?

Consumer facing brands (in particular, services) who do the following:

  1. Actively seek to collect customer data from a variety of sources (such as from a third-party API, a home automation system, and an old-school survey).
  2. Gather insights from relevant data that:
  3. describe the customer’s general needs and preferences (Rachel lives in NYC, commutes 3x/weekly and works from home 2x/weekly.
  4. understand the customer’s current specific situation (i.e. Rachel has an important business appointment in 30 minutes at the other side of the city and time is of the essence).
  5. Manage data efficiently and dispose of irrelevant or old data.
  6. Develop strong reporting and business intelligent units that use customer data to drive innovation in new features and product offerings.
  7. Recruit an agile workforce that can adapt quickly to change and competing services.
  8. Remain transparent about the fact that they collect customer data, and develop a “data-sharing relationship” with the customer.

Some of the most successful companies—those that are setting themselves up to be able to emerge from the “data rubble” not only unscathed but savvier, are looking beyond the basic tactical approach to data, which more or less runs on: We have a certain need with a certain customer, so what data do we need? Data X, Y, and Z. Okay, now let’s store it in our system. (Commence thumb twiddling.)

Instead, these emerging companies are aiming first to build an entire system around a central data base that gives the entire company access to that data. For example, a production line can look in, understand what a customer wants, and build a custom-made widget on the spot. This type of central access to the same data seems a simple enough and a smart enough concept, but most brands and companies are light years away from embracing it. Too bad, because they are actively losing their competitive edge.

Think about it: What if a large drugstore chain (perhaps one that is trying to reposition itself as a healthcare company) developed an API that partnered with a social media and a fitness APP? And what if the store knew via  analyzing social data that Erin was depressed because her dog just died, and what if they knew via the fitness APP that she hadn’t run for four weeks? Imagine the action they could take—the ads for herbal anti-depressants, ice cream, and running gear they could send her. Or If they could determine Erin hadn’t run due to an injury, they could present her with ads and emails for pain killers instead.

The possibilities are, of course, endless. How shocking is that?

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