For digital agencies, big data as a competitive advantage is still very nascent, somewhat terrifying, and not tangible at all. However, marketers are starting to hear that it's the new secret sauce, and they're scrambling to figure out how to use it. And for good reason. Given the current trajectory, there's a large chance that big data will change the face of digital agencies in as little as five years. If you're part of a digital agency, here's what to consider.
How do Agencies Make Money with Big Data?
Data-as-a-Service (DaaS) can now feasibly be added to the agency menu because cloud computing costs have made common infrastructure affordable. DaaS also opens up more than one door to new revenue. Some agencies are using it to power original apps or campaigns on a client's behalf. Others are using it to enrich and support original research.
Selling insights gained from big data, like sophisticated customer profiling, personalized marketing campaigns, and reporting from multiple data sources is the next leap in competitive advantages, and agencies are feeling the pressure to jump on the opportunity. That said, it's important to note that the democratization of computer power and accessibility doesn't solve the talent problem, but it does mean that cost is no longer a defining variable.
What Types of Data Should Agencies go After and Why?
Client-side data is the new walled garden. In recent months agencies have developed the same vampiric thirst for data that we first observed from companies like Google, Facebook, and Groupon.
At first it was enough just to find and make sense of everyone that touched a brand. Now, agencies want to take those findings and put them in context to answer where and why that brand interaction happened. And context at that granular level is only achieved when outside data is mashed up against inside data.
When agencies are granted access to their clients' data the risks, and the rewards, are huge. And, it's an intimate new kind of collaboration. You might know your client's quarter-end results, but have you seen their cart bounce rate segmented by household income?
With access to client data, agencies can help them understand not just what the world is saying, but how those external measures correlate to business behaviors and results. For example, in the context of retail clients, as data flows in from point-of-sale systems around the country, agencies could help their clients match buying patterns against social activity streams and map exactly what event triggered a spark of purchases in a specific region.
With those insights in hand, they can then make a near real-time recommendation that would help recreate the same effect at a national scale. This, of course, requires agile execution, but insights such as this fundamentally change agency practice from campaign-based results to real-time results.
Those are powerful insights that directly impact revenue. But it takes the right people to get there. So now, let's talk talent.
What Personnel do Agencies Need to Use Big Data?
It's safe to say that most clients are relatively unsophisticated with their data. Otherwise, they'd be doing the work they hired the agency to do. This is part of why there's a growing demand for a new role within agency organizations, and a new interface with clients, much like the social media gurus of yesteryear, but nerdier.
Introducing: the data scientist, or perhaps, the growth hacker. Simply put, this is an individual focused on the practices of recording data, generating insights, and the latest technologies and techniques for using that data to improve the marketing function.
You do not need to go out and hire a data scientist, and given the market conditions you probably can't anyway. There's a happy middle ground. There are content strategists from brand journalism, and social media managers for all things conversational. It's time we had our own equivalent: Someone that talks tech and brand with equal ease. This internal role defines strategies that only they could see, and orchestrates a wider network of technologists, consultants, and infrastructure providers.
We've found that many of the top agencies already have someone suited for this role, usually in a "director of social analytics" role. Before you turn to a recruiter to help you find that data scientist, take a look at your own people within the social analytics group, and see how you can steer their technical understanding in new directions. There are enough resources and tools available in the big data market that a data guru can succeed even if he or she isn't an expert on Hadoop and HBase.
What's Ahead for Big Data and Agencies?
As the demand for data scientists continues to skyrocket, and as the demand from clients for data-as-a-service grows, agencies are going to find themselves in a place where they must stay competitive. Although it may not be easy to adopt at first, the big data agency tango is happening, and you don't want to be the firm left standing by the punch bowl.
Image courtesy of iStockphoto, Muhla1
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