Increasing Customer Acquisition and Retention

Job number one of most companies, certainly from an economic standpoint, is to sell more and sell better. So it’s no surprise that some of the leading ways organizations are monetizing information assets are focused on their sales and marketing functions. Many of these methods involve learning more about their customers and prospects, and doing more with this information. We are also starting to see an increased interest in gathering and leveraging a broader spectrum of information about markets and trends derived from external sources.¹

Creating a Supplemental Revenue Stream

Packaging up and licensing data is the most direct form of information monetization, but there are other ways to generate revenue from information by infusing it into products and services, or using it to develop new goods or services. In these forms of monetization, information is contributing right to the top line.

In most industries, from retail to telecommunications to manufacturing and of course in social media companies, information about customers, processes, and products is being licensed as a supplemental source of income. Most notoriously, retailers and grocers such as Dollar General, Rite Aid, and Kroger have made certain datasets commercially available to partners, suppliers, and others for a fee or other considerations.⁷⁸⁹ Retail industry experts place Kroger’s incremental information windfall at an impressive $100 million annually.¹⁰

Sometimes selling information is a preferable alternative to no revenue at all. The CEO of a midsize U.S. manufacturing company of sonic buoys and other inertial sensors shared with me how, instead of simply losing business to lower-cost manufacturers in Mexico or elsewhere, it licensed its well-honed expertise in the form of detailed manufacturing and testing processes to those who would otherwise undercut them. Competitors become partners, and a new revenue stream materializes!

Often directly monetizable information is hidden in plain sight. This unutilized or underutilized “dark data” takes on several forms. Often it is captured during the course of doing business, but somewhat overlooked for ancillary purposes. Most frequently you will find it in the form of unstructured content. For example, the real estate aggregator Trulia discovered that 90 percent of its web traffic is from people clicking on photos of homes. But Trulia had no information about what was in the photos. The photos had no descriptions or tags. So Trulia’s data science team trained a one-billion-node neural network to learn what is depicted in them. Now, according to Todd Holloway, who started Trulia’s data science program, “The system can find you a home in the Hamptons with photos of wine cellars.”¹¹ Helping a buyer find a home is one thing, but now Trulia can correlate sales data with what site users are looking at, and license this information and insight to realtors, homebuilders, appliance manufacturers, and any type of company within the periphery of the real estate market.

Too often organizations fixate not only on their own information, but on a subset of it. Admittedly, structured data can be much easier to leverage analytically, but the untapped economic potential in unstructured content can readily eclipse it.

Introducing a New Line of Business

As you become more proficient at and serious about marketing your or others’ compiled information assets, this may warrant establishing a specific business unit to do so. Communications and medical companies such as Juniper Networks, Orange, Verizon, Sprint, Telefonica, Teva Pharmaceutical Industries, and Nordic Wellness Products already have established business functions dedicated to productizing information.

In fact, you may find your core business isn’t the ideal line of business at all.

In 2012 when I first spoke with the budding entrepreneurs of Tru Optik, Andrew Swanton and Alex Geis, they gushed about the new file system they had developed for managing Big Data. These two budding entrepreneurs told me how they had proved the system’s capability by capturing high-velocity, high-volume BitTorrent traffic on the millions of videos, music, software, games, and other content being bootlegged (mostly) via this peer-to-peer communications protocol. Instantly, it occurred to me that this information was as or more valuable than their technology, and I suggested as much to them. Today, Tru Optik collects and monetizes Internet Protocol (IP)-specific—that is, geo-locatable—details on which content is being shared via BitTorrent and other platforms by more than five hundred million people across 150 countries.¹² This real-time historical data and other data integrated from YouTube, Instagram, Facebook, Twitter, Last.fm, IMDB, Spotify, and SoundCloud is available via their application program interfaces (APIs) or dashboards to help its customers such as production houses, media labels, advertisers, and networks identify unmonetized demand for entertainment content. Swanton even hinted that his system can predict Nielsen television ratings a week before Nielsen publishes them.

No, you may not want to pivot as much as Tru Optik did, but don’t overlook the possibility of introducing a new information-based revenue stream out of an incremental technology advance.

In the telecommunications sector alone, the global market for monetized data, estimated at $24 billion in 2015, is expected to grow to close to $80 billion by 2020.¹³ As the CEO and co-founder of Vistar Media commented, “If I was a CEO of any telecom operator in the U.S., I would be saying to myself I can do the same. That’s going to be something these guys are talking about in the boardroom.”¹⁴ Multiply this across all industries and the market opportunity for externally monetizing information, excluding data brokers and those primarily in the information product business, could be in the trillions of dollars.¹⁵

Yet again, due to mostly unrealistic privacy concerns among consumers, Gartner’s communication service provider industry expert, Charlotte Patrick, contends the market for information operates in some respects like a black market—with secret deals, devoid of publicity, off-balance sheets, and generally off the radar. As SAP Mobile President John Sims commented at an industry conference, “The mobile operators don’t want to reveal this. They are fearful people will take this and twist it into something that it isn’t”—no matter how much these companies stress that the data is anonymized and summarized.¹⁶

Yes, the ethical “creepy line” (as my colleague Frank Buytendijk calls it) for information monetization can be toed or even crossed, and legally so. But be sure to do so in a way that does not draw too much attention—and if it does, that customer benefits are front and center.

Entering New Markets, Quickly

Whether it’s introducing a new product into an existing market or an existing product into a new market, monetizing available information can mean the difference between success and failure. And it can open up new options when other kinds of investment vehicles may not be possible.

Throughout 2011 and 2012, Noam Bardin was looking to expand the presence of his company’s mobile mapping app throughout South America. He met with various providers of mapping information to get access to their proprietary geographic data. But he wasn’t about to pay with the precious limited cash he had. Instead, he bartered with the data his app collected on automobile traffic, roadwork, accidents, and police locations. Eventually a company called Multispectral went for the deal, and within the year Waze became available to Brazilian drivers. As Bardin said, “It would have taken us a year and a half to get there on our own.”¹⁷

Entering megamarkets like China requires an understanding of its cultural nuances and needs, a bit of interesting data, and some innocent ingenuity. And sometimes it’s a bit of understanding and ingenuity only a kid can muster. In Gloucestershire, United Kingdom, a sixteen-year-old girl has named over a quarter-million Chinese babies—or rather the online service she’s developed has. Beau Rose Jessup visits China regularly with her family where she says she is frequently asked to help family friends and even strangers select English names for their children. Choosing an English name is a common and serious practice that can make it easier for Chinese to assimilate when they study and work in Western countries. Jessup realized that many Chinese select English names from pop culture, because they do not have access to Western baby naming sites. This results in some embarrassing names. “I have heard of someone called Gandalf and another called Cinderella,” she says. For a mere 60 pence, her site, Specialname.cn, enables parents to select key attributes they wish for their child and have a list of easily pronounceable, socially acceptable candidate English names generated. Special Name also shares the list with family and friends over the WeChat social network to help with the selection process. And after the name is chosen, a printable certificate is generated with the name, its meaning, and examples of famous people with the same name.¹⁸¹⁹

In short, don’t overlook the benefits of information-based bartering arrangements to get new offerings off the ground more expeditiously, or the simplicity of creating an external information flow as a means to generate new revenue streams in new geographies.

Enabling Competitive Differentiation

Monetizing information can separate your products and services from those of others in the marketplace. In the examples of Dollar General and Kroger, consumer packaged goods (CPG) companies and other suppliers may find they prefer doing business with these retailers because of the transparency and value afforded by the sales and other data made available. And maybe Amazon’s new brick-and-mortar store will outmaneuver grocery giants by using cameras, sensors, deep learning, and automatic payments to track what shoppers are selecting and eliminate the checkout process altogether. This information is monetized also by eliminating the cost of checkers and point-of-sale systems, saving shoppers time during which they’re likely to shop more, and licensing or generating insights from the data.

Intuit’s TurboTax is another classic example of a service differentiated by both extracting and inserting information into its product. Intuit compiles data from the millions of tax returns prepared using its software. As more and more U.S. taxpayers migrate to its online software-as-a-service (SaaS) version, Intuit is able to collect more and more data on the usage of its product, but also details of its users’ tax returns. This deinformationalization of the product along with information it compiles on tax audits enables Intuit to informationalize its product further with information and analytics on tax audit risks and probabilities—thereby rendering its product differentiated from others. Human tax preparers by comparison can only guess at tax audit red flags based on their limited personal experience. Even if Intuit could monetize this information more directly, baking it into the offering instead creates a more valuable product—one which Intuit can defensibly raise the price of each year.

And if it isn’t already obvious to you, Intuit isn’t just monetizing our tax returns through the core TurboTax functionality, Intuit is monetizing the U.S. tax code itself. The U.S. tax code is a veritable mountain of information, having grown from about 500 pages in 1800 to 1,000 pages after President Franklin Roosevelt’s New Deal, to 8,200 pages following World War II, to 26,300 pages in 1984, to nearly three times that length today. Intuit and others have brilliantly capitalized on an iconic scourge of U.S. capitalism and congressional recrement—the continually burgeoning 74,608 pages of United States tax code.²⁰

My colleagues Mark Raskino and Graham Waller would call these examples being “digital to the core” (coincidentally the name of their ground-breaking book on digitalization). Baking information deeply into business processes or reinventing processes by leveraging available information assets isn’t just a way to go digital—it’s another clever way to “level up” the economics of your business model.

Bartering for Goods and Services

Sometimes you want something someone else has but are unwilling to or cannot pay the cash price they’re asking. Or maybe you want to keep the exchange off-book for reasons of privacy, reputation, or taxation. In these cases, it makes perfect sense to revert back to the most ancient form of commerce: bartering.

As explained in chapter 1, “loyalty-based discount” is code for “free stuff in exchange for information about you and your purchase.” More than your loyalty, grocers and other and merchants with similar programs are after your information.

Exchanging information for goods and services is the basis of the upstart business HERE Life that affords students at the Universities of Illinois and Kansas special iPads, shared automobiles, and swank apartments in a new building in which their every movement (well, almost) is tracked and recorded. In turn, HERE Life markets analyses of this information to major consumer brands.

Recently, we see companies purely in the business of accumulating and monetizing information benefit from stratospheric valuation multiples. But why should they be the sole purveyors of information? Retailers, mobile and internet service providers, energy and utilities companies, and financial transaction processors are on the leading edge of bartering with information. This is because most information bartering examples today involve customer data. But other kinds of business information are becoming accepted currency as well, such as the retail product categorization and basic market data IRI trades with its customers in return for their transaction feeds. In industries like manufacturing and shipping, making operational data available to others throughout the business ecosystem is becoming more commonplace, and expected by business partners.

Bartering for Favorable Terms and Conditions, and Improved Relationships

While bartering with information for goods and services may make sense in a consumer product–oriented ecosystem, in the B2B world, discounts frequently are prearranged or based on volume. Sometimes however, it’s easier to win favorable contract terms in return for sharing information. Moreover, the liquidity and regulatory conspicuousness of money can make information a preferable form of currency. Traditionally, favorable terms and conditions are offered to customers in good standing or based on guaranteed purchase volumes. More often however, they’re based on the exchange of information. In the case of at least one major airline manufacturer, detailed visibility into its suppliers’ operations, processes, inventory, and other business dealings gives it increased supplier confidence which it rewards with favorable contract terms.

Contract terms aside, the exchange of information among trading partners facilitates improved relationships. Transparency breeds trust, and nothing embodies transparency better than the flow of information among businesses. However, other than for contract negotiations, most companies just don’t have anyone in an “information product” role, nor anyone particularly proficient at making these kinds of deals with their information or for another’s information. You should, though. Abe’s Market hired one.

Abe’s (now part of Direct Eats) was an upstart Israeli-founded online marketplace for healthy living food and other products. A few years ago, its Chief Revenue Officer, Kimberley Grayson, and her team capitalized on the opportunity to provide their multitude of mostly small suppliers with invaluable information from and about buyers. In a classic win-win-win triple play, she and her team devised a mechanism for capturing feedback from consumers in return for discounts (i.e., free stuff). This data and comparative insights were made available to suppliers in the form of a custom scorecard. Who bought the products? When and how many? When did they consume them? When do they intend to buy more? How were the product’s taste, value, and nutrition? Various dietary, demographic, and psychographic information was also gleaned from the transactions and surveys. In return, suppliers didn’t pay cash for this information. Rather they offered free products and deeper discounts just to get their hands on these invaluable insights to help them develop better or different products and optimize inventory levels and shipping. But Grayson didn’t stop there. She realized that this data in aggregate would also be valuable to major manufacturers of snacks (e.g., Kraft, Mondelez, Nabisco, etc.) to understand the emerging market for healthy snacks and lifestyles.²¹

This triple-play “everybody wins” relationship model should be part of just about every company’s business. You win through higher customer satisfaction and increased revenues; your suppliers win via improve products and increased sales; and consumers win via better products at lower prices—all by riding the same wave of information.

Defraying the Costs of Information Management and Analytics

In addition to top-line gains, monetizing information also can involve the expense side. Remember, monetization is about any kind of economic gain attributable to one or more information asset.

In just one year, discount retailer Dollar General realized a net income increase of 121 percent with a 9.5 percent increase in same-store sales. Part of these results were due to an intriguing project headed by senior VP and CIO, Ryan Boone. Despite the anxieties of externally exposing forty-five terabytes with seventy billion rows of data about $12 billion in sales from 8,800 stores, Boone engaged cloud-based data warehouse and analytics provider 1010data (now part of Advance/Newhouse) to consolidate data from a variety of databases. This provided deeper and more rapid insights into sales and other activity. Almost immediately, Dollar General discovered its stores were not open at the right times. Sales data indicated some of its outlets had heavy sales near closing time, implying they probably should be extending their hours.²²

But this isn’t where the story ends. Dollar General wasn’t the only company interested in this information. As an astute marketer of hundreds of thousands of products, it saw one more product to sell: its information. Soon Dollar General started generating dollars from the aggregate and analyzed data by selling it to retailers like Pepsi and Unilever. Not only could these CPG companies see how well their goods were selling, but for a premium they could benchmark themselves against competitors. Ultimately, one of the industry’s first data warehouses in the cloud started paying for itself. As 1010data’s CEO recounted, “This data is so valuable… that their data infrastructure becomes a profit center rather than a cost center.”²³

Another retailer found that just by updating its infrastructure to better handle Big Data processing, it shaved hundreds of thousands of dollars off its annual processing expense. The volume of sales data Sears had was bringing its mainframe and its competitiveness to their knees. With eight billion rows of sales data on eleven million Stock Keeping Units (SKUs), nearly two billion rows of inventory data, and about four thousand stores, it was only able to calculate item price elasticity quarterly, and only on a 10 percent subset of data. The business simply was unable to react to market conditions and new product launches. According to the project executive, Phil Shelley (now CEO of Datametica), moving this processing off the mainframe and into Hadoop reduced six thousand lines of batch code to four hundred lines of PIG, providing up to one hundred times improved performance, delivering $600,000 in annual savings, and enabling Sears to calculate price elasticity on a weekly basis using all available data.²⁴²⁵

Unfortunately, the vast majority of information and analytics leaders think and act only intramurally about their data warehouses or other data stores. Yet, the expanded economics of availing this data to others outside your four walls can be significant. Even worse, too many organizations short-change the economic benefits possible from their information assets because of deficient infrastructure.

Reducing Maintenance Costs, Cost Overruns, and Delays

Whereas information monetization focused on sales and marketing is most often oriented toward top-line economic gains, organizations (including those in public sector) also drive financial performance gains through improved operational efficiency.

Lockheed Martin supplies $46 billion of aeronautics, information systems, missiles and fire control, mission systems and training, and space systems to government organizations and some companies. With over 125,000 employees in nearly six hundred facilities in every state and seventy nations and territories working on thousands of highly technical, complex, and largely taxpayer-funded projects, Lockheed Martin’s leadership is extremely conscious about issues leading to cost overruns and program delays.²⁶ Delays can result in milestone payments, payment withholdings, write-offs, de-bookings, and a reduction in awarded contracts—each directly impacting cash flow.

But let’s back up to the hidden potential of monetizing “dark data.” Dark data is how some refer to unutilized or underutilized data—typically data that was collected and used for a single purpose, then forgotten about and often archived. Sometimes it’s jokingly referred to as “zombie data” in how it resembles the living dead, or as “digital exhaust,” or “digital debris,” or even “digital detritus” by those etymologically and alliteratively inclined. At a presentation I gave in 2011 at a Microsoft event, the CIO of one of the Big Four systems integrators asked, “We’re a consulting firm, what dark data could we possibly have?” I suggested that his firm likely is sitting on twenty years of archived emails and project communications that, if mined and correlated to projects which had suffered from certain kinds of issues (e.g., as scope, budget, personnel/staffing, technology, and so forth), could yield leading indicators of similar project issue for current client engagements.

This is precisely what Lockheed Martin did with the help of Ayasdi’s machine intelligence platform and analytics services. As Prakash Sesha, senior corporate engineering manager with Lockheed Martin’s Technology and Operations Group, recounted at a Gartner event, “A program manager considers three things important: Are we delivering what we said we were going to deliver? Are we on target in terms of schedule? And are we at or below cost?”²⁷ The challenge was that Lockheed’s current metrics were trailing indicators, not leading indicators.

Only experienced program managers could tell “by their gut” that a program was going south, said Sesha, but they didn’t have the data to anticipate that degradation. In analyzing hundreds of variables including text analysis of project communications and documentations, Lockheed was able to detect specific signatures of programs predicted to degrade in performance with manageable false-positive rates, while decreasing the amount of historical data required to do so from six months to just two months. By monetizing project information in this way, Lockheed Martin now has 300 percent improved foresight into program assessments, saving potential losses in the hundreds of millions of dollars.

Although information assets regularly are deployed to assist with product maintenance, rarely are they deployed for project maintenance as effectively as Lockheed Martin has done. Yet the information for doing so is there. It may be hidden in emails or other project documentation, but don’t let that deter you.

Identifying and Reducing Fraud and Risk

Indirect forms of information monetization can include exposing and limiting fraudulent activity. While not selling or licensing or productizing information directly, using it to limit these kinds of unwarranted expenses certainly represents a measurable economic benefit.

In the U.S., Medicare and Medicaid fraud costs taxpayers $70 billion. So in 2015, the Health and Human Services Department hired a chief data officer and put in place aggressive plans to attack this problem. The result: the largest health care fraud takedown in history. In early 2016, 301 individuals were indicted in schemes totaling $900 million. But the key to the crackdown wasn’t just manpower. “Data can be the unsung hero,” commented HHS chief data officer, Caryl Brzmialkiewics. And even though this represents a fraction of the overall fraudulent activity, HHS metrics show this bust has had a deterrent effect on the order of another $1 billion in reduced fraudulent payments.³¹

But sometimes fraudsters are “slimier” even than those scamming the health care system. The City of New York has seven thousand miles of water mains, tunnels, and aqueducts delivering water to homes and businesses throughout the five boroughs. Accordingly, it also has 7.400 miles of sewer lines which return the wastewater from these locations and street sewers through ninety-six pump stations to fourteen treatment plants. Commercial businesses are required to install grease interceptors to separate oil, fats, and grease from wastewater and prevent grease from entering the city’s sewer system. Periodically these interceptors must be manually cleaned out and the grease carted away by licensed haulers. Increasingly, city inspectors had been discovering sewer pipes clogged with hardened grease which restricts the flow of wastewater, leading to flooding and backups. The city estimates over 60 percent of sewer backups are caused by improperly dumped grease, particularly from restaurant fryers.³²

Instead of pulling up every manhole in the city, the health department enlisted the Office of Policy and Strategic Planning, a “geek squad of civic-minded number-crunchers working from a pair of cluttered cubicles across from City Hall.”³³ They unearthed data from an obscure agency which certifies restaurant grease-carting services. Layering the geospatial data of restaurants without a current grease-carting contract to that of nearby sewers, the team was able to give inspectors a list of suspected derelict restaurants and clogged sewers. Sure enough, this simple integration of disparate data sources yielded a 95 percent success rate in tracking down grease dumpers. The result: an increase of 2 million gallons of sewer capacity by removing 30 million pounds of debris, and a more efficient deployment of city health and water department workers.³⁴

As the City of New York shows, fraud can be tackled by adeptly overlaying various information assets, and real economic benefits can be found in almost every corner in (or under) your organization.

Improving Citizen Well-Being

While corporations are beholden to their shareholders, governments are accountable to and responsible for their citizens. In the U.S., the Freedom of Information Act (FOIA)—along with similar “open data” directives at a national and local level in the U.S. and many other countries—establishes an overarching mandate for the usage and availability of non-sensitive government information just for that purpose. But just to be sure, FOIA sets up a further roadblock prohibiting the monetization of that information by U.S. agencies. Information is considered part of the public trust. Although FOIA specifies how government agencies may be reimbursed for the cost of searching, preparing, and copying requested information which is not already available on government open data portals, lately some government organizations such as the Department of Commerce are testing the edges of FOIA by charging exorbitant fees for simple information requests.³⁵

But ultimately the government sharing of information usually is for the purpose of improving citizen safety, security, health, and opportunity. The ultimate monetization of this information takes the form of reduced government costs and economic growth.

Recently, I met with the Federal Aviation Administration (FAA), where Larry Grossman, its deputy chief security officer, recounted how the FAA is improving what information it makes available along with its format and structure.

“We already release tons of flight-related data based on formats and time intervals meaningful to us,” said Grossman, “But this isn’t the most efficient for external entities who are developing consumer products. It’s inhibiting innovation.” He went on to describe how its “External Data Access Initiative” benefits the FAA, pilots, and passengers: “Currently, we spend a lot of time and money producing these charts and other aggregate data products. But the plan is for the FAA to focus more on the data itself and make it more consumable, thereby encouraging the industry to produce innovative data products from it. Collaborating with the aviation industry in this way could save taxpayers the millions of dollars it costs us to produce these charts, and help spur greater innovation targeted at efficiency and safety.”³⁶

Grossman shared a specific example of how improved real-time information products produced by private enterprise using FAA data could save pilots money and improve passenger safety:

These are just a couple of examples from a single government agency. Across national and local government organizations throughout the world, similar initiatives have or are taking shape, such as with national postal services:

• Poste Italiane, the Italian postal service, has kicked off a project to have postal carriers collect and certify street numbers to make them available to mapping companies such as Google who still only have imprecise locations for many addresses, and
• Post Malaysia has a booming courier business along with its regular mail business. It is looking into having postal carriers observing and reporting on infrastructure issues such as potholes, damaged or missing signage, and construction problems. Other government organizations would fund this data collection to improve citizen safety and defray some postal service expenses.

Another increasingly common way local governments are monetizing information is through public-private partnerships. In 1876, the City of Los Angeles installed its first electric street lamp. Installing and maintaining street lighting is a significant expense for municipalities. Today, L.A. has over two hundred thousand streetlights, consisting of four hundred different models installed across 7,500 miles of roads and freeways. At night, crews patrol the streets to detect outages, and the city gets forty thousand calls from residents each year reporting issues. Recently L.A. and other cities have started installing smart, IoT-based LED streetlights that handle cellular and WiFi traffic. The city receives $1,200 per year in rent for each “SmartPole” and nets nearly $9 million per year in energy savings alone. The poles can also capture information on outages, nearby accidents, and traffic patterns—saving on maintenance and saving lives.³⁷

Assessing the economics of information in the public sector can be a bit trickier than with commercial organizations. Rather than a profit motive, government organizations are driven more by the economic and other benefits to citizens and businesses. Still, the opportunities to deploy information in measurably improving economic opportunity, safety, and well-being are endless, and just starting to be realized by national and local governments.

You’re Definitely in the Information Business, or Should Be

These examples highlight that every business is, can be, or should be an information business, monetizing information in a spectrum of ways. According to the CapGemini EMC Big Data Report, 63 percent of respondents consider that the monetization of data could eventually become as valuable to their organizations as their existing products and services.³⁸ But consider that a recent Gartner survey indicates fewer than 20 percent of organizations are either licensing or exchanging their information for goods and services from others, and a scant 31 percent are even measuring the economic benefits of using their information assets themselves.³⁹

Even if your information won’t ever become as valuable as your existing products or services, it is unconscionable to forgo an opportunity to monetize it in one or more ways. Whether it’s getting into digital business, digitizing your offerings, licensing your data to suppliers or partners, baking your information assets into existing products or services to extend their value, or measuring and leveraging the economic benefits of deploying information internally, you had better get your organization into the information business, or suffer the consequences of becoming a casualty of the Information Age. To get started, the next chapter presents a step-by-step process to monetize your (or even others’) information assets.