"Big Data" may have become the catchword darling of the year, but it's all too often a case of blind love.
Collecting and parsing vast amounts of consumer information from disparate channels, Big Data organizations present major profit possibilities. But for many companies, the term remains a bauble, as vague as it is sexy.
Why is Big Data so difficult to harness? Because companies are not using the basic data they already have in a way that engages consumers. Combining structured data (data warehouses, customer relationship marketing software, databases) with unstructured data (email, social media, consumer commentary) may seem the most logical approach for claiming that shiny prize of Big Data, but extracting the true value of this combined information can remain be a far-off dream.
Consider the results in a 2011 survey by the IBM Institute for Business Value and MIT Sloan Management Review. The study shows that of 4,000 executives, 30 percent said that the biggest challenge to analytics was that they didn't know how to use the data. In addition, only a third of the respondents said they had access to the information and analytics they needed to do their jobs successfully.
Clearly, there's a long way to go in both understanding and capability.
But perhaps even the term Big Data is misplaced. It implies that in order to be useful, the information has to be at scale. But for most companies, size should be the second objective.
Companies should start by focusing on the effective use of data, which is more a question of clear accountability and execution. Most organizations should start by defining "one version of the truth" in their data and then generate insights and make strategic decisions from these observations that will meaningfully effect their businesses. And this takes more than simply launching a Facebook fan page or loyalty program and then delivering offers to customers whenever there is a lull in spending or business results.
Data is a living organism, one that needs constant management, given the complexities of multiple channels, advanced analytics, and real-time marketing.
The challenge is many companies aren't effectively using the data they have, while misconceptions about data use has burdened the practice with an unfounded level of consumer worry.
Case in point: 87 percent of consumers say they are "often concerned" about how much of their personal information is being held by others, according to a LoyaltyOne survey of 2,000 American and Canadian consumers, conducted in June 2012, (the full report is forthcoming, access last year's here).
The implication is that company interactions become big and impersonal for consumers when it isn't clear what the organization is doing with their information. This makes consumers uncomfortable—do I have any control?
Even major brands have distanced themselves from data. Take, for instance, a March story about Lululemon that ran in the Wall Street Journal. In the piece, CEO Christine Day said the yoga apparel chain relies on in-the-aisle consumer monitoring rather than purchase tracking, because "big data" gives merchants a false sense of security.
But Christine Day does have a point—to rely on Big Data as the solution to retailer issues is to miss the bigger picture. While purchase information is a key component of consumer intelligence, it only succeeds when it is combined with a vitally strong strategic and operational mindset that considers the data insights in the context of what's happening on the front lines.
At Caesars Entertainment, for instance, varying strategic offers are developed through a sophisticated combination of data analysis, employee engagement and rewards systems. Members who log onto its website are encouraged to share the kinds of activities and entertainment they enjoy most—it may not even be gambling. And on the floor, "hosts" are assigned to high-value customers, gathering information about what wines they like and whether they play golf.
These insights are deployed to front-line workers, who can act upon the preferences immediately, essentially aligning Caesars' operational structure to better serve the right customer segments.
So if data is being underused, or used improperly, how do we fix it?
There is no question, data collection can be perceived as big and faceless—if it is managed that way. But in a marketplace dominated by national chains with tens of thousands of employees, we simply cannot operate like the corner store of a century ago. It is one thing to know who your best shoppers are in your back yard, but how about in Reno, Nevada, or Teaneck, New Jersey?
The answer is not in size, but in practice and principles. Better understanding a consumer's preferences is not just a matter of collecting gobs of data, but of aligning what the consumer needs with the organization's own goals, and then figuring out how customer information can achieve both in a way that is mutually beneficial.
In fact, these principles are built on rather small steps:
The data collected should be able to first show who the consumer is (for potential value), how the consumer prefers to shop (the experience), and what is motivating that purchase (point in time). Determine which resources to invest in to keep customers satisfied, while also recognizing underdeveloped customers who may want to spend more. Keep in mind that it makes sense to target based on both the current and potential value of the customer.
Data comes in many forms, from in-store shopping activity to online browsing patterns, and it can be sliced and diced to show many different aspects of a consumer. But there are four general areas that should help shape what inspires your customers: their physical location, their phase in life, their personal interests and their cultural influences. By developing its communications around these factors, an organization can demonstrate an understanding of its consumers needs, the shortest path to attaining relevance.
This should go without saying, but ascertain what you want to achieve with the customer data and then collect only what you need to do so. Once collected, use all of it in a way that benefits the consumer as much as the organization, which will earn the organization the right to obtain more data over time.
Big Data is a term that causes big confusion, but it doesn't have to be this way. By using data in more manageable ways, and by gaining confidence in how to create relevant experiences, organizations can show consumers they are not blind to their needs. And that can lead to big brand love.
Bryan Pearson is president and CEO of LoyaltyOne and author of The Loyalty Leap: Turning Customer Information Into Customer Intimacy. Follow Bryan's blog.
[Image: Flickr user Kevin Dooley]