We marketers tend to hijack terms, and use them so often and in so many ways that they lose their intended meaning, quickly joining the ranks of marketing lingo. The term “actionable insights” has unfortunately suffered this fate, which is one reason I dedicated my last column for ClickZ, “Metrics That Matter: A New Framework to Reveal Truly Actionable Insights,” to exploring what “actionable” really means, and why the metric-happy marketer doesn’t always focus on what’s important.
“Real time” is another victim of such rampant use and abuse.
The “Convergence Analytics” research study conducted by ClickZ and Efectyv Marketing earlier this year reported that “about half of the respondents they surveyed said they require ‘real time’ data, but there was little consensus on what ‘real time’ means,” with definitions ranging from sub-second to next day. These diverging opinions are clearly a sign of the times. We are in the midst of a massive and rapid business revolution, driven by data explosion and powered by analytics. Companies are scrambling to get the right people, processes, and technologies in place to remain competitive. Not surprisingly, given the maturity level of each of these core ingredients, their approach to data, and ability to use it effectively, varies wildly.
Here is the issue: real-time data is relevant only if a business can actually make sense of this data and act on it in the right timeframe. That’s when real-time data enables right-time marketing. There’s no value in sub-second data collection if the actions on such data take hours, days, or even weeks to complete. The good news is that many companies have begun to use real-time data to optimize business performance in real time. While adoption is certainly not consistent across industries, there are many – and growing – numbers of great examples. Let’s take a look at some of these uses cases on the power and applicability of real-time data.
E-commerce companies, of course, have been using real-time data for years to engage buyers in digital environments in a variety of ways, including personalized offers, dynamic pricing, customer service, and order tracking. Amazon, clearly an industry trailblazer, has spent more than a decade fine-tuning its algorithms, which respond instantly to each new shopper interaction with new, personalized recommendations. Then there’s eBay, where real-time data is at the heart of auctioning and customer support; the company runs more than 100 petabytes of data through its systems daily. But data also informs how eBay manages its massive infrastructure supporting more than 100 million active users. The company used analytics to track patterns in infrastructure use, leading to repurposing servers and millions of dollars in savings.
Now we’re seeing rapid growth of another game-changer: real-time bidding for digital media advertising, a new industry that is expected to grow to $7 billion by 2016, representing 28 percent of digital display advertising spend. In effect, this puts the digital ad inventory on the market based on impressions, creating a dynamic pricing exchange. Marketers can buy and publishers can sell display ads based on these metrics.
How about a great many businesses whose profitability (even viability) often depends on their performance on a few major holidays? For them, the ability to analyze campaign effectiveness to adjust their marketing mix in real time means the difference between being in the red or black.
And in another arena, the social gaming industry is deeply rooted in its ability to analyze and understand its vast and diverse user base with games potentially altered hourly to optimize use – and monetization.
Media companies are also at the forefront of using real-time data, in their case to improve readership, subscriptions, and ad monetization. Given the fact that headlines have historically sold newspapers, it’s not surprising that The Huffington Post does real-time A/B testing of its stories. Readers see one of two headlines for the same story on a random basis. The version with the most clicks after five minutes gets the nod. The New York Times changes it home page throughout the day based on data. At the U-T San Diego, a top 25 media and news outlet, news writers see real-time dashboards, reporting readership by different story attributes throughout the day. Leveraging real-time analytics, the U-T was able to increase readership by more than 20 percent last year despite a paywall introduction.
Add to this list the airline and hotel industries, which are are among the biggest consumers of customer data. Their goal is not just to manage capacity, but also to optimize profitability from a resource that’s finite: the number of airline seats on a flight or rooms in a hotel. Now they do this with real-time data. One national airline I recently talked to is planning on using live web data as a leading indicator to predict demand and inform its revenue management system.
The examples go on and on. The point is, whatever the definition of real-time was a year ago, it’s evolving fast. We are in an era when we can monitor, analyze, and act on the high volume, variety, and velocity of data ever more rapidly. And, those who do reap tremendous benefits.
Not every industry or business currently does it right just yet. But the list is growing. Are you keeping up?
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