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Three key questions to ask potential digital analytics team members
Lots of folk are in the market for talented digital analytics professionals. Here's a few of my favorite questions to ask potential hires...
I loved the lede of a previous The New York Times story on data science: “Good with numbers? Fascinated by data? The sound you hear is opportunity knocking.” Since then, we’ve continued to see a growing trend in the need for qualified analytics professionals at all levels in an organization, including leadership. The need is painfully real: there are estimated 2.7 million open jobs in data analysis, data science and related careers (source: IBM). So it’s no surprise that finding top analytics talent, as with any specialization in-demand, can be challenging.
Although there is increasing demand, you still need to look carefully to ensure you are getting quality talent. To help, I thought I’d share some questions to ask, and the types of responses to look for, when bringing on a new analytics team member. Having viewed things from the perspective of leading digital agency teams and now as senior leader in-house, I hope this is a balanced perspective and useful for you.
1. We have several (varying) groups that need access to analytics insights, from product to marketing/PR and customer service. How would you efficiently get them all what they need?
What to look for in an answer: If someone can share their process here for efficiently getting each group specific reports and analysis that goes with it, that’s a great first step. But ideally, your hire would go beyond simply giving others their analysis and information. It’s powerful to train different stakeholders to be proficient with the tools you’re using and able to conduct their own analysis at whim. Your analytical lead should always be thinking of how she is going to democratize her knowledge throughout the organization. While it’s probably not realistic to get everyone to be an A-list analyst, it is possible to get everyone to think like an analyst and have at least a basic understanding of what your team does.
2. How do you see a breakdown of time spent on analytics between data capture, reporting, and analysis?
What to look for in an answer: According to Google’s digital marketing evangelist and friend of mine Avinash Kaushik, the ideal breakdown is roughly 15 percent data capture, 20 percent data reporting, 65 percent data analysis. Of course, what to look for isn’t the exact same numbers from Avinash. The point is to understand the importance of focusing a majority of time on analysis and providing insights for the rest of your team to take action on. Someone who articulates and understands that the reporting and capture – while important – are just the basic things to get right. That’s the easy part that should be made as efficient and automated as possible. The real value lies in effective analysis that leads to action: the creative, human element that can’t be replaced by scripts.
3. How do you plan to be data-driven in improving your digital marketing efforts?
What to look for in an answer: Ideally, the candidate would take you through the process of metrics > hypothesis > experiment > act > repeat. She would outline how she plans to establish all the elements of this, from implementation and analysis to developing theories to acting and iterating on all key strategies a brand has. But in addition to understanding how to actually win in business through being data-driven in theory, the candidate should share with you how she actually did this while on the client side or walked brands through establishing a data-driven practice while on the agency side (or both). Theory is nice, but experience is everything here, as there can be roadblocks at all of the steps and you want someone leading your efforts versed in what she’s doing.
While many organizations (and particularly the marketing operations within) still operate on “gut feel” as opposed to data-driven, the opposite will be true tomorrow. And tomorrow’s leaders are already here today, pushing things forward with a passion for data and interest in moving the needle for their organization. To sort the wheat from the chaff, ask the really tough questions and look for in-depth answers and experience from your analytics team members. Invest in them to thrive in your future. Also, if analytics sounds like an fun area to you, I wrote a previous story on how to be dangerous with data that may be of interest.
Bonus content - presentation expanding on above in detail: I previously gave a talk for digital marketers and analysts at MozCon in Seattle covering the above and much more on building an analytics practice. It’s from a few years ago but all the core concepts presented should be fairly timeless and agnostic of tools and technologies. If you’d like to dive deeper, you can watch via the embed below.