When hiring an analyst, review candidates for these qualifications.
A key trait of an analytically empowered organization is its investment in "humanware," the right kind of people to extract value from the data and create insight. But what does "good look like" when it comes to analysts?
A good analyst has the capacity to analyze data and generate insight. Let's have a look at those words in a bit more detail. An analysis represents a "detailed examination of the elements or structure of something" and insight is defined as "the capacity to gain an accurate and deep understanding of someone or something." On that basis, the analyst needs to be able to look at data in detail and understand it. But it depends also on what you mean by "understand." In addition to understanding the data, an analyst must also understand and communicate what it means for the organization. So here are five things to look for in an analyst:
A good analyst must be able to handle data - any data. While analysts may have a functional speciality, such as a web analyst or a customer insight, they have to be comfortable in handling any data sources they encounter. In the data world, two and two really does equal five. That's because the value of data from one source increases when it is integrated with other data sources. Web analytics data is great, but it becomes even more valuable when it's analyzed alongside voice-of-the-customer data, customer experience data, and other customer data.
For me, analysis is a blend of the creative and the deterministic. A good analyst can look at a set of data and begin to see what the data is telling her. Data tells stories and the analyst is there to interpret the data and make sense out of what the data is saying. It's all about extracting signals from the noise.
Attention to Detail
On the other hand though, an analyst must have strong attention to detail. Data can be very nuanced at times; it might look like it's saying one thing when in fact it's saying something else. Or the data may be wrong. A good analyst must be able to spot problems with data that just doesn't look right.
An analyst must be aware of the ramifications of the what the data is saying. She needs to add value to the analysis by not only explaining, "This is what's happening and why" but by also elaborating on "This is what I think the impact is" and "This is what needs to be done about it." The latter analysis tends to come with experience, but any analyst at any level needs to interpret outcomes and not just outputs of their work.
All the above counts for nothing if the analyst cannot get her message across within the business. She must articulate and communicate what the business needs to know. So good analysts need to have good verbal and written communication skills, possess the ability to construct an argument based on evidence, and tell stories.
A lot of these characteristics can be learned or developed over time. If you are looking to hire talent, be sure she is comfortable with data and has the ability to understand how the data relates to the business. When we look to hire an analyst, we ask candidates to create a presentation from a set of data. We want to know not only that they analyze the data but whether they can make sense of it and then articulate and present that message in a clear and convincing way.
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Neil Mason is SVP, Customer Engagement at iJento. He is responsible for providing iJento clients with the most valuable customer insights and business benefits from iJento's digital and multichannel customer intelligence solutions.
Neil has been at the forefront of marketing analytics for over 25 years. Prior to joining iJento, Neil was Consultancy Director at Foviance, the UK's leading user experience and analytics consultancy, heading up the user experience design, research, and digital analytics practices. For the last 12 years Neil has worked predominantly in digital channels both as a marketer and as a consultant, combining a strong blend of commercial and technical understanding in the application of consumer insight to help major brands improve digital marketing performance. During this time he also served as a Director of the Web Analytics Association (DAA) for two years and currently serves as a Director Emeritus of the DAA. Neil is also a frequent speaker at conferences and events.
Neil's expertise ranges from advanced analytical techniques such as segmentation, predictive analytics, and modelling through to quantitative and qualitative customer research. Neil has a BA in Engineering from Cambridge University and an MBA and a postgraduate diploma in business and economic forecasting.
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