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    The Chief Pitfall in Monetizing Data

    One of the best pieces of advice I ever received was from my manager when I worked in data analytics several years ago. Her mantra was: Don’t analyze anything that’s easy.

    Her point was that if something is easy to analyze, it’s probably not worth the effort — because almost anybody can look at the same data and get similar insights.

    That piece of advice has relevance in many aspects of life, but for me it has special relevance as it relates to one of the hottest topics in corporate America today: the monetization of data. To hear some people talk about it, you’d think that monetizing data was as simple as taking your corporate data about customers, obfuscating the Social Security Numbers and phone numbers, and then selling what’s left to the highest bidder.

    If this sounds like a reasonable approach to you, you’re not alone. In fact, it is by far the most common pitfall that I’ve seen in corporations’ pursuit of infonomics. But if you’re considering such an approach to monetizing data, I urge you to reconsider. In my opinion, the worst thing you could possibly do for your company is to sell personal information about your customers or partners — at least not anything even remotely close to raw data. Doing so could potentially create a public relations, financial, or even legal disaster, once word gets out about what you’ve done.

    Three tiers of data products

    The most important point to take away from this post is that not all data is created equal — and also, that some of what you may think is your data isn’t actually yours at all. In fact, it’s better to treat it like as a priceless valuable that you’re just borrowing.

    More broadly, an organization can have data products that exist on one of three tiers, each with its own rules for usage and level of risk.

    • Tier I – Every organization has sensitive data about customers and partners, which it should regard as never to be released to any third party, for any reason. Tier I data products are data at its most raw and basic level, before you’ve done anything to to derive any insights from it. Whether it includes personally identifiable data information (PII) or not, this is the type of data that can get you in the most trouble if you don’t treat it with the respect it deserves.
    • Tier II – These data products are created when a firm applies analytics to raw data assets to derive insights. These insights could be packaged and sold either as a one-time study, or as ongoing analytics provided on a subscription basis. A classic example is NASDAQ, which provides subscribing financial services firms with a financial index of various markets – containing analytical outputs or insights derived from such Tier I data products as positions, strike prices, puts, calls, buy side and supply side information, etc.
    • Tier III – These types of data products are possible only after a firm has created a unique type of resource for analyzing its own data, and then leverages that analytical method on other types of data. In certain cases, firms that have created such algorithms and analytical visualizations can package their analytics into delivery applications that external consumers can subscribe to for a premium. The subscription allows the end-user customer to configure its own application program interface (API) that uses the analytical product to generate the customer’s own unique data.

    Gentlemen, start your analytics

    My explanation of the three tiers of data was meant to convey that before you can make a penny off your data, you have a lot of analytical work to do. To begin with, you need to aggregate it, and in the process, remove any PII. Only then can you begin to gain new insights into the data that will become uniquely yours — something you can sell without any risk of customers feeling that their privacy has been violated.

    By the way, this is one of those cases where technology can make a bad decision immeasurably worse, and with far greater negative repercussions. Because of how social our culture has become, awareness that you’re selling the wrong type of data about your customers to the wrong third parties can quickly get out of control. Before you know it, you might not only be on the front page of the business section, but your company might also be the subject of snowballing complaints on social media, not to mention lawsuits.

    Even worse, if a buyer of your Tier I data is less than scrupulous, your customers could start finding themselves being exposed to marketing, spamming, or worse by unknown entities who seem to know things about them they thought were private — leaked knowledge that even a fairly unsophisticated customer could trace back to your organization. Was the money that you got for selling their information to a third party so valuable that you’re willing to lose actual satisfied customers — and far worse?

    A better approach

    A better approach is to start with a clean slate, and a careful review of your business model. Understand what role your customers and their information play in your business model, and then try to determine new ways to analyze that data and derive new insights from it — ideally, one that no one else could ever develop. It’s essentially the same advice my former boss gave me, but with a very different driver behind it.

    Your customers are the center of your universe, and you have a unique view of the ecosystem in which they live and work. That insight is uniquely yours, and there may be ways that you can share the lessons you’ve learned that companies in other industries and markets would find valuable. But before you actually start monetizing data, you must make sure that the data you’re selling truly belongs to you, and not your customers or partners.

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