Data - Action or Insight?

There is no shortage of data available to marketers, but are they doing enough with the data to move their business forward?

Every day, we are constantly bombarded with information, breaking news, op-ed pieces, conferences, and recently launched start-ups all focused on Big Data. These news spots and businesses claim it’s the marketer’s new silver bullet, and a seller’s solution to declining CPMs and loss of revenue to commoditized inventory. Certainly Big Data is interesting on many levels, but for the most part, it’s just a big pile of wasted 1s and 0s. The vast majority of companies that bought into the hype started capturing data without a plan and lacked the tools and staff to leverage it correctly. Rarely do any of these companies, even the most well-intended, appropriately action the data to move their businesses forward.

Clearly, I’m not going to propose that brands, their agencies, or even publishers abandon data and go back to user surveys and content targeting to guide their marketing and business operations. But what I am going to suggest is a separation of data usage between Action and Insight. Without exception, every company should be capturing key performance indicators (KPIs), modeling them, and analyzing composition to inform everything from their inventory supply chain to their sales tactics. This type of data and use case is what I would call Insights, and many vendors and agencies are providing these types of metrics to brands. Consumer packaged goods (CPG), e-commerce, and other travel/auto clients are leveraging insights to make better product decisions and improvements to their value chain.

All the articles and conferences covering Big Data speak to the goal of using it to drive 1:1 communications. Most brands and even their agencies have not achieved this panacea yet. I’d like to address a few areas where I think brands miss their target, and why not every publisher or brand is even capable of achieving a 1:1 goal (at least on their own).

  • Scaled Data: To reach consumers with a dynamic and relative message, you must have scaled data at the start. Many brands have data on existing consumers but usually lack unique and informative data on the other 99 percent of potential consumers. Publishers and brands will never be able to access 100 percent of the marketplace on their own to construct models and data strategies that will get them the uplift required. This is where companies like mine, Xaxis, and others aid in rounding out the consumer profiles for driving insights, ultimately reaching those high-profile prospects.
  • Knowledge: Assuming that a brand or publisher can manage to get enough scale through their own consumer connections or via partnerships, most lack the staff to convert that data to action. Building models for reporting and data mining is a skill in itself, but taking those models and determining the best way to apply them to media for the purposes of driving a desired result is a completely different skill set. It takes technology, expertise, and historical experience to optimize and apply the models to a real-time stream of media inventory to see a true uplift while keeping costs down. Today’s ecosystem is very complex to navigate and requires a large, knowledgeable staff to execute a 1:1 consumer plan globally, or even in a single market.
  • Scaled Media and Global Footprint: In addition to experience, having access to high-quality media in each market is also critical. There are three legs to optimally reaching a consumer: creative, audience, and context. In order to maximize the results of a 1:1 campaign, you must have access to the right media inventory. Some would argue that simply plugging into the open exchange marketplace of inventory is good enough, but we have seen that applying data and great creative further up the inventory chain – closer to what a client would buy direct from a publisher – has a dramatic impact on performance and engagement with consumers. There are very few brands that can establish these types of arrangements directly with publishers, as most don’t have the budgets required to command a pole position in the inventory waterfall on their own.

These are only a few of the hurdles that publishers and brands face when auctioning data. Business can only leverage the full potential of Big Data when they have a plan on how to utilize it, when they work with the right partners to activate it, and when they understood the KPIs for tracking the results of how to apply and action the data. Without these, Big Data is nothing more than an endless, but useless stream of 1s and 0s.

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