We’re living through a dramatic change in the way consumers and businesses interact. It’s called the Decision Economy, it’s transforming the playbook, and it’s separating the winners from the losers as businesses work to drive sales in a very new world.

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Today, I’ll explain what the decision economy is –and why harnessing it effectively is make-or-break for your company’s future. We’ll talk about the ways today’s Attention Economy is evolving into the new Decision Economy. We’ll ask if marketers are ready for that new decision-based world. And we’ll explore the ways your company needs to shift its marketing to thrive in a future ruled by one word: decide.

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OK, so what is the Decision Economy? How does it differ from business as usual? Let’s dive in…

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It all starts with the new data deluge. You’ve probably heard plenty about this data deluge before. But I want to focus in on the scope—on how big that data explosion really is. Consider just one stat. According to one IBM study, over 90% of the data in the world today has been created in the last five years. That means that if you were to take a time machine and travel just five years back in time, the information you could engage with would be dramatically less. It would be a different world.

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Let’s look at that explosion a little differently. If you follow the evolution of computing -from the inception of modern computing with the first mainframes in the 1950s, to the birth of the Internet, then cloud computing, followed by the sensor-based information we’re seeing emerge today – you see that the data explosion is happening on not one, but two levels. First, the types of data we can interact with are dramatically shifting. There are a lot of problems you can solve on iPhone today that a goliath machine in the Mad Men era just couldn’t come close to. That’s a qualitative difference.

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Second, the amount of data we’re engaging with is growing exponentially. In 2006, the combined space of all computer hard drives in the world was estimated at approximately 160 exabytes. That’s a lot of information. But by 2016, we’re expected to surpass a zettabyte of IP traffic – that’s 1000 exabytes! You’re talking about mind-bending growth, in a matter of ten short years. When you take qualitatively different data being gathered and created, at a scale to the tune of thousands of exabytes –you’re staring right at a seismic shift.

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That shift changes a lot about how we, as human beings, behave. Access to all that data becomes a critical human need.

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The explosion of information also means that engaging with the data becomes central to how we experience the world – in ways that rapidly become a part of daily life. Take the way snapping photos with your phone went form something you’d never think of doing – to something you do all the time – seemingly overnight. Compare the scene at these two papal inaugurations – one for Pope Benedict in 2005, the second for Pope Francis just eight years later – and you’ll see what I mean.

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All the information is incredible. But here’s the thing: it turns out, we can’t actually use all the data that we produce. There’s only so many photos you can look at any given time. So with all that unprecedented data comes unprecedented information overload. All that data also drives something that economists call “The Attention Economy”: with so much information out there but only so much capacity to consume it, attention itself becomes a scarce resource. We’re all constantly making definitive choices – knowingly or not – to pay attention to one piece of information, and to ignore another. Engaging with the consumer – aka marketing—becomes the skill of gaining access to consumers’ scarce attention resource.

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So how are consumers navigating their way through the dizzying array of attention options? They’re turning to a new class of decision technologies that do essentially two things. First, these technologies present consumers with a clear array of the options they’re choosing from – so they know what they could be choosing out of the sea of options. They make their choices clear. Second, these technologies provide valuable data insights to help consumers choose amongst all these options. Together, these technologies give consumers unprecedented power to make informed decisions about which messages to engage with, which ones they’ll respond to.

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You’re pretty familiar with a lot of these technologies. One example is one you’ve likely been using for a while: DVR. At its core, DVR is a decisioning tool to help you understand what you could be watching—and to decide what you will, and won’t, ultimately choose to watch.

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And, of course, DVR has become a critical staple of the viewing experience along the way. But here’s the thing – it’s not just media that’s competing for consumers attention. And it’s not just media consumption decisions that consumers are turning to decision technologies for help with. The new wealth of data is helping consumers make decisions about a whole host of real- life issues. Issues like…

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…salad dressing. That’s not such a small decision when you consider just how many salad dressings we all need to choose from. In psychologist Barry Schwartz’s famous TED talk on the Paradox of Choice –the ways a flood of choice gives consumers more options, but might be making us all less happy – Schwartz talks about the 175 types of salad dressings in his local supermarket. That was in 2005—when online food shopping was a lot less common, and when there were fewer supermarket options (at least in the US).

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And it’s hardly just salad dressing. According to a recent Accenture report covered in the Wall Street Journal, the typical U.S. grocery store now stocks up to 50,000 products—up from 15,000 in 1991. That’s a lot of items to choose from on a shopping trip. In a world with so much choice, how do consumers survive? They survive by turning to decision tools that turn the shopping experience from this…

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…to this. To be sure, services like Amazon offer convenience that brick-and-mortar stores don’t. But what they also provide is decision interfaces that help customers navigate complex buying decisions, quantifying them into key data points – like price, product category, customer rating and popularity. (And if you’ve ever been stuck like a deer in headlights at the salad dressing aisle, you know how complex the decision really is!)

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These kinds of applications are guiding all kinds of decisions – from what salad dressings to buy, to what small businesses to interact with (or to avoid like the plague).

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Decision applications are also helping decide amongst many other choices, too – like which route to take from point A to Point B. The common thread is that these applications are revealing a wide array of options from amongst which consumers can choose, and helping them narrow choices down via key data – whether it’s price, rating, or length of a trip.

[Note: original talk delivered in Munich]

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In other words, through decision applications, consumers are harnessing the power of data to survive the “attention economy”, focus their attention, and make good decisions an exhausting sea of choices. With that power, the nature of the attention economy itself has changed. Consumers’ guiding force is no longer fleeting attention. It’s informed, data-driven decisions. Which brings us to the next evolution of the Attention Economy. Welcome to the Decision Economy.

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But as consumers are connecting with information, items, and brands through a new tool kit of decision applications of all kinds, are marketers responding with the right decision tools of their own to engage with the newly decisive consumer? Are businesses ready to engage with consumers in this new decision economy?

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Often, unfortunately, the answer is no. I say this because most marketers aren’t able to effectively quantify the impact of decisions they’ve already made. And if they can’t fully understand the ways their prior marketing choices impacts the bottom line, they can’t decide what they should do next, either. To offer just one of many examples: a 2014Oracle/Econsultancy survey found that nearly two-thirds of digital marketers place integrated cross-channel marketing—that is, coordinating all marketing efforts across outlets – as a very high priority. And yet less than half can quantify the ways their customers interact with their brand across all those marketing channels, and use that understanding to guide their marketing expenditures. Meanwhile, less than 1 in 5 of the nearly 1,000 professionals surveyed could measure the financial impact of cross-channel efforts. In other words, marketers know what they need to do – but they can’t get the hard data on the effectiveness of the things they’re doing. And without that knowledge of effectiveness, the can’t decide what needs to be their next move.

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And when marketers can’t quantify their results, they also can’t take credit for their wins – or avoid blame for their failures. This quote from an Intel executive about life just a few years ago—before they overhauled their marketing analytics program—is indicative of where many marketers live today.

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Meanwhile, without a clear path to the right decisions, marketing isn’t able to execute on its primary role – supporting sales. Some industry stats:

• 46% of leads die without follow-up

• 94% of leads never close

• 45% of companies believe sales and marketing are not aligned

• 52% of sales reps never achieve quota.

With all that context, it’s no wonder that marketers are overlooked as a professional class. 90% of CFOs believe marketing is unaccountable. Plus, marketers have only single-digit representation on boards, and almost never progress from the CMO role to the CEO position. Without the ability to say they’ve made the best decisions, marketers are being passed over as leaders.

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So while consumers are swimming in data-driven decision tools, marketers are less effective than they should be, and less professionally successful than they deserve to be, because of data blindness. That’s pretty dire. But the new math of marketing analytics is here to help. With it, companies and marketers can understand what’s working in marketing, what isn’t working, and how to make the right decisions for the new Decision Economy.

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So how do businesses market correctly – how do they leverage the math and technology in the right way, to win in the new world? They need to follow the 3 Steps to Decision Success.

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The first step is understanding all the factors that drive marketing success. Just like travelers can make better driving decisions when Google provides them with not just data about what streets go where, but information about a whole host of factors – like traffic and road conditions at any given moment; or restaurant-goers make better meal decisions when Yelp reviewers comment on a range of factors - not just about food quality, but about things like ambience, location, and service—marketers make better decisions when they understand the whole host of factors that work together to make marketing succeed or fail.

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That starts with going beyond measuring the obvious. Most marketers already know the great performance measurement they receive from outlets with a clear path of clicks from marketing engagement to a purchase – like email or paid search. But to understand how all of your marketing is really performing, you need to stretch the limits of what you’re going to evaluate and measure. Here’s one example of a hard-to-measure medium – social – and some coverage we got for a recent analysis we did on the impact of Twitter on automotive sales in the US…

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Nor can you understand how each part of the marketing equation operates in a silo. Let’s go back to the Google Maps analogy: you can make better driving decisions if you know about routes, traffic, and road conditions. But that information is of limited use if can’t combine them together into one view. And in marketing, getting combined information is all the more important, because no marketing you do acts in a vacuum. The TV ad you ran can make consumers more responsive to your catalog they receive in the mail. Those two channels combined may make consumers more responsive to your online video ad. So you can’t measure the impact of the online video ad without understanding how the TV ad and the catalog drop worked together to help make the video ad an even bigger success. Evaluating the merits of all your channels – and deciding how to allocate marketing budgets going forward – will mean giving each channel credit for the amount it contributed to the overall program. And while most marketers understand this in theory, many marketers are still analyzing each of their marketing efforts as a separate P & L. That means, when they tie each marketing outlet back to business impact, each outlet seems to have driven a lot more revenue than it really did. If the brand ran a TV ad and sales went up by a million dollars, the TV advertising group will take credit for a million dollars in revenue, and TV gets credit for a million dollars. But at the same time, the brand might be running an online campaign – and the digital group will take credit for the same million dollars. So you have two marketing groups, together, claiming credit for two million dollars’ worth of sales –when in reality only a million dollars of revenue has been produced. Situations like the quote you see here abound.

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Keep in mind that these silos are moving closer all the time. Ten years ago, you had completely divided marketing outlets - like TV, print, and digital. Today we’re headed to one seamless (and digital) customer journey. Your laptop ties to your mobile device, which ties to your smart watch and your step counter. They all tie to your connected home via products like Nest—which, significantly, is owned by Google, the world’s largest online advertising business. All the touch points connect. And so to decide how best to work across all of them, you need to unify the data. You need a holistic picture.

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It’s not just marketing and media channels that you need to examine when you’re looking at the interconnectedness of marketing decisions. The brand is another place to look to. It’s ironic: the brand is the through-line throughout all the marketing we do, and yet it’s rarely accounted for when you’re trying to understand your marketing efforts really work. How is the brand helping your other marketing work better—or how is it weighing it down? How far could you go without any marketing at all, just coasting on the value of your brand alone? How does advertising for your umbrella brand create a halo effect that impacts marketing for items across your product line? A lot of our work at MarketShare is dedicated to quantifying answers to questions like these. Because you really can’t understand the impact of any marketing decision you’ll make without understanding how all these pieces work together in the background—to help marketing efforts succeed or fail.

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Of course, the brand is hardly the only force that operates in the background to impact your marketing. Every consumer receives marketing messages in the context of a real world. A world with things like…berries. Why do I bring up berries? Because Walmart’s analytics team identified the precise temperature that’s ideal for selling berries. People are most receptive to berry messages, it turns out, when there’s low wind, and warm temperatures that are below roughly 27 degrees Celsius. Walmart also found that people prefer steak on days with higher winds and no rain, and that optimal conditions for selling salads include low winds and temperatures above 27. Walmart uses this information to guide their marketing choices—to sell more berries when it’s warm and more ground beef when it’s scorching hot. When you’re trying to understand why an ad worked or didn’t, or whether an ad will work, it’s critical to factor in environmental predictors like these. At MarketShare, we’re always sure to incorporate everything from the impact of weather, to the influence of pump prices, to the state of the economy into our mathematical models.

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So that’s the first step to decision success: capturing the full range of data on not just marketing initiatives alone – but also on how a host of factors work together to influence the ways marketing initiatives will perform. The second step to decision success is what I’ll call velocity. By velocity, I mean the ability to spot the information quickly, to use it to understand what needs to be done, and to act immediately. What’s an example of velocity in marketing? Take Nissan and DigitasLBi France's BrandLive initiative, a control center that scans news and trends for ideas that Nissan could leverage on social media. The center was able to spot rumors of a pending royal birth -and posted the above tweet just seven minutes after the rumors began to circulate. The whole story is great; but what’s especially impressive is that BrandLive was able to look through a world of noise amongst trending stories and swirling rumors to decide which story to latch on to – and to act on it right away.

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Velocity means you can take your understanding of what’s working and what isn’t, and apply those learnings to shift budget strategies on a dime. That’s one of the key learnings recently shared by the award-winning marketing analytics team at wireless provider C Spire.

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Which brings us to the third step to decision success. Corralling and acting on all that data, quickly, isn’t something we can do with good operations alone. You need the right decision technology. Invest in it. If you can do that right, you’ll be able to make the best marketing decisions. And you’ll be able to able to engage successfully in the new Decision Economy.

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How do you know what technology to go with? I think a great set of guidelines comes from a Forrester Research report on insurer USAA’s discovery process - as they sought to build or partner with a marketing analytics solution. (USAA eventually chose MarketShare DecisionCloud.) Forrester describes USAA’s choice as boiling down to five parameters:

• Business Fit – the need for solutions that answered the company’s specific business requirements and needs

• Data Integration – the need to incorporate the vast pools of data to drive fully-informed marketing choices

• Tool Functionality – because even the most sophisticated tools are only valuable if teams can use them

• Optimization Approach – the best math; and

• Measurable Impact – would they see ROI from their particular analytics investment?

On the last question, by the way, the answer has decidedly been yes. USAA went from 9% of sales from Marketing in 2008, at the start of their analytics journey, to 29% in 2012!

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The brands that are succeeding in the Decision Economy are doing so with the help of great technology. The consumers you’re selling to already have world-class decision technology at their fingertips, and they’re thriving for it too. They’re all using that technology to orchestrate insights across the available data - to understand their options quickly, make decisions quickly, and capture the wealth of opportunity available. Shouldn’t you do the same?

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