A Google Hangout with Eric Picard, CEO of RareCrowds; Chris Scoggins of Datalogix; Andy Monfried, CEO of Lotame; and Chris O’Hara, author of Best Practices in Data Management. Hosted by Stefan Tornquist of EConsultancy.
Today data is like water: free-flowing, highly available, and pervasive. As the cost of storing and collecting data decreases, more of it becomes available to marketers looking to optimize the way they acquire new customers and activate existing ones. In the right hands, data can be the key to understanding audiences, developing the right marketing messages, optimizing campaigns, and creating long-term customers. In the wrong hands, data can contribute to distraction, poor decision-making, and customer alienation. Over the past several weeks, I asked over thirty of the world’s leading digital data practitioners what marketers should be thinking about when it comes to developing a data management strategy. The result was the newly available Best Practices in Data Management report. A few big themes emerged from my research, which I thought I would share:
Welcome to the First Party
Digital marketing evolves quickly but, for those of us working as digital marketers or publishers for the past 10 years, we have seen distinct waves of transformation impact the way we use data for audience targeting. Early on, audience data was owned by publishers, who leveraged that data to control pricing for premium audiences. The Network Era quickly supplanted this paradigm by leveraging tag data to understand publishers’ audiences better than the sites themselves. Buying targeted remnant inventory at scale created new efficiencies and easy paychecks for publishers, who found themselves completely disintermediated. The DSP Era (which we are still in) continued that trend, by completely separating audiences from media, and giving even more control to the demand side. Today, the “DMP Era” promises a new world where publishers and advertisers can activate their first party data, and use it for remarketing, lookalike modeling, and analytics.
The ubiquity of third party data (available to all, and often applied to the same exact inventory) makes activating first party data more valuable than ever. Doing so effectively means regaining a level of control over audience targeting for publishers, and being able to leverage CRM data for retargeting and lookalike modeling for the demand side, as well as a deeper level of analytics for both sides. If there has been one huge takeaway from my conversations with all of the stakeholders in the data-driven marketing game, it is that getting control and flexibility around the use of your own first-party data is the key to success. As a marketer, if you are buying more segments than you are creating, you are losing.
The New Computing Paradigm
In order to successfully activate all of the data your company can leverage for success takes a lot of work, and a lot of advanced technology. Whether you are a publisher trying to score audiences in milliseconds in order to increase advertising yield, or an advertiser attempting to deliver a customized banner ad to a prospect in real-time, you need to store an incredible amount of data and (more importantly) be able to access it at blazing speeds. In the past, having that capability meant building your own enormous technology “stack” and maintaining it. Today, the availability of cloud-based computing and distributed computing solutions like Hadoop has created a brand new paradigm or what former Microsoft executive and current RareCrowds CEO Eric Picard likes to call the “4th Wave.”
“Being a Wave 4 company implicitly means that you are able to leverage the existing sunk cost of these companies’ investment,” says Picard. That means building apps on top of AppNexus’ extensible platform, leveraging Hadoop to process 10 billion daily transactions without owning a server (as Bizo does), or simply hosting portions of your data in Amazon’s cloud to gain speed and efficiency. As digital marketing becomes more data intensive, knowing how to leverage existing systems to get to scale will become a necessity. If you are not taking advantage of this new technology paradigm, it means you are using resources for IT rather than IP. These days, winning means applying your intellectual property to available technology—not who has the biggest internal stack.
Social Data is Ascendant
One of the most interesting aspects of data management is how it is impacting traditional notions of CRM. In the past, digital marketing seemed to end below the funnel. Once the customer was driven through the marketing funnel and purchased, she went into the CRM database, to be targeted later by more traditional marketing channels (e-mail, direct mail). Now, the emergence of data-rich social platforms had actually created a dynamic in which the funnel continues.
Once in the customer database (CRM), the post-purchase journey starts with a commitment beyond the sale, when a consumer joins an e-mail list, “friends” a company’s page, follows a company’s Twitter account, or signs up for special offers on the company’s site. The next step is an expression of social interest, when the consumer agrees to make public his “like” for a company or brand by “friending” a company’s page, following a company’s Twitter account. Beyond the “like” is true social activation, wherein the consumer actively (not passively) recommends the product or service, through commenting, sharing, or other active social behaviors. The final step is having the consumer sell on your behalf (directly via affiliate programs or, in the softer sense, as a “brand ambassador”). This dynamic is why Salesforce has acquired Radian6 and Buddy Media.
For digital marketers, going beyond the funnel and activating consumers through social platforms means understanding their stated preferences, affinities, and that of their social graph. Most companies already do this with existing platforms. They real key is tying this data back into your other data inputs to create a 360 degree user view. That’s where data science and management platforms come in. If you are not ingesting rich social data and using it to continually segment, target, expand, and understand your customers, you are behind the curve.