Take a phased approach to growing your firm's big data analysis capabilities.
Modern marketers need big data analysis. It helps us measure the return on investment on our multi-channel marketing campaign investments and make better decisions about those investments. It lets us leverage direct response and predictive analysis techniques to achieve dramatic increases in targeting precision, campaign lift, and ROI.
Unfortunately, the talent required to unlock the marketing value in data is scarce. One of the key findings in recent market research sponsored by our company is that a "shortage of data-savvy marketing talent" is the No. 1 issue inhibiting investments in marketing data. Talented data scientists - individuals with a combination of data management expertise, analytics modeling knowledge, and business analysis skills - are so hard to find because many technologies needed to tame big data didn't exist until recently. Most were invented within the past 10 years. However, every firm climbs a maturity curve over time with respect to their ability to leverage increasingly sophisticated classes of data analysis to create competitive advantage. Most firms start out with simple static reports. Insights gained from these reports often lead to follow-on questions and a need for more ad hoc reporting. Over time, demand for forward-looking views of the business lead to the use of predictive analysis techniques. And the most analytically sophisticated firms often use machine learning and optimization techniques to automate decision-making for key business processes.
Just as firms must take a phased approach in climbing the "Big Data Analysis Maturity Curve," they must also adopt a phased approach to acquiring talent to expose the marketing value in their data. Outsourcing to reduce risk is smart, but ultimately, marketers must build an internal competency around their data and the technology to analyze it. Start by hiring a self-managing hands-on individual to lead your big data analysis initiatives. You are looking for someone with a track record of delivering results - someone with a high probability of achieving outcomes that only a small set of possible candidates could ever achieve; someone with a low tolerance for mediocrity. A single exceptional data scientist can deliver more value than a dozen average performers, and it's critical to start here because exceptional talent will only work with other exceptionally talented people, so a bad first hire will put your entire big data initiative at risk. Expect to pay them well, but more importantly, recruiting success will depend on your ability to create a big data initiative that truly changes the game for your firm backed up by a commitment to its success from your entire executive team. Candidates will need to see evidence that you are building a culture that inspires and rewards technical talent.
Plan an "early win deliverable" for your big data leader that involves capturing new value from your marketing data assets within their first 90 days on the job. Make the success visible - both inside and outside your firm. Use this success to justify investments in the additional resources and talent required to achieve your next big data analysis objective, and iterate on this "Build, succeed, invest" cycle as you climb the "Big Data Analysis Maturity Curve."
Importantly, as you climb the "Big Data Analysis Maturity Curve," the technical challenges associated with your big data objectives become increasingly attractive to data scientists. The industry's top talent wants to work on the industry's top challenges. As a result, your ability to raise the quality bar on the talent you recruit will increase with every success you achieve. Marketers who are first to begin climbing the "Big Data Analysis Maturity Curve" - and climb it the fastest - will be the ones that win.
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Brad Terrell is responsible for maximizing the value that Netezza technology delivers to the many innovative digital media firms that power their large scale data analysis initiatives with Netezza's analytics appliances.
Before joining Netezza (IBM acquired Netezza November 2010), Brad led digital media initiatives at Endeca as director of business development and helped fuel the firm's rapid growth from $10 million to more than $100 million in annual revenue. Prior to Endeca, Brad helped design and launch products including the Spyglass Mosaic web browser, IBM PowerPC microprocessor, H&R Block online investing website, and FlightSafety International's FAA Level C-certified flight simulators.
Brad's entrepreneurial experience includes co-founding and serving as president of ElectricWish.com, ranked among the top five e-commerce sites on the web by ZDNet in 1999, and M-Nova, a pioneer in product development outsourcing to Eastern Europe. Brad holds an MBA from MIT Sloan and a computer science degree from Rice University.
Hong Kong, May 5-6, 2015
Gartner Magic Quadrant for Digital Commerce
This Magic Quadrant examines leading digital commerce platforms that enable organizations to build digital commerce sites. These commerce platforms facilitate purchasing transactions over the Web, and support the creation and continuing development of an online relationship with a consumer.
Paid Search in the Mobile Era
Google reports that paid search ads are currently driving 40+ million calls per month. Cost per click is increasing, paid search budgets are growing, and mobile continues to dominate. It's time to revamp old search strategies, reimagine stale best practices, and add new layers data to your analytics.
May 6, 2015
12:00pm ET/9:00am PT