How fast would a baseball need to travel to reach Digitaria's twelfth-floor San Diego office balcony overlooking the Padres' stadium? I have no idea, but the amazing view from atop makes you want to calculate the number and give it a try. Rather than delve deeper into this idea, though, I sat down with Digitaria President Doug Hecht, VP of Insights and Action Karen Bellin, and SVP of Strategy Mark Newcomer to talk about ways marketers can make the best use of data -- a task that can overwhelm even the most experienced marketers.
What Data Do I Need?
Start by defining the task. Is the goal to increase online conversions? Are visitors going deep enough into the Web site, finding what they need, and buying the products or the services? The first step is to find data supporting the answer to the basic questions. Don't assume there's a problem after looking at the data until determining the KPI.
Then determine the key performance indicators. Brand marketers collecting an overabundance of data that answers questions never asked won't find the answer.
Don't overanalyze the metrics. Marketers can become so lost in the data that they lose track of what's important. It doesn't matter if everything is 100% efficient. Sometimes answering the last 2%, 5% or 10% of questions can become so painful and time-consuming that it's no longer worth the trouble. It may take half the time to get 90% of the questions answered, and the other 50% of the spent sorting out the remaining 10%.
Having one good performance metric works better than giving them a bunch. Digitaria works with one car manufacturer that collects a ton of data. They have data on who designs cars in their online tool, but they don't use it. Once the brand understands the type of information consumers look for on their Web site, the marketer can narrow the type of analysis and start asking secondary questions.
Who Should Manage The Data?
Then decide what to do with the data and who will manage it. Should the brand own and manage its data, or should it rely on an agency partner? How does the democratization of the data change the way agencies work?
Managing the data when it's not core to the brand's business creates risk. Brand marketers should have the ability to rely on their agency partners to reduce risk. And while most believe it could work, the biggest issue remains trust. Brands need to trust their agency partner with the data, which seems a bit ironic.
Dear brands marketers, why is trusting agency partners with data so much different than trusting them with millions of dollars to run your company's campaigns? Ah, yes, customer data. It means sharing the data that customers trust you with, and now you must share it with agency partners. Larger brands already trust their agency to spend millions of dollars on their behalf.
Kantar Media reports U.S. advertising budgets hit at $140.2 billion in 2013, up 0.9% compared with the previous year.
At What Cost?
Managing data create risks. Marketers never want the cost of the analyses to outweigh the benefits from insights, per Bellin. Most agencies will say they advocate brands owning and managing the data because most brand marketers feel they should, but Bellin recently met a marketer whose brand created its own governance around data. Since investing in the infrastructure, the brand's team got laid off. It made her rethink the brand's position. She now believes agencies need to step up to provide a turnkey way for brands to access and use their data.
Build a master plan and stick with it. Newcomer points out that once companies have the basics down on reporting, they can move into more advanced data management. Brands must have a master data plan, but too many continue to struggle without one. He said this is a little less the case for marketers at ecommerce companies. Most know where all the data comes from, such as CRM platforms, marketing and channel data, but there's no one that has an overarching vision for data use across the organization. Brand also lack chief data officers, someone with stewardship over the data.
Testing should become a priority. It's important to design a hypothesis to test and measure against a control to see what moves the needle.