There has been a lot of coverage about a looming skills gap in the data industry, especially insight analysts – or more fashionably, data scientists – who work with data to reveal patterns and relationships lurking below the surface, which in turn – as if by magic – help businesses communicate with their customers in a timely, relevant and customer-centric manner.
So what makes a great insight analyst? The three key qualities are:
Technical skills
Good numeric and statistical analysis skills are essential – preferably developed at degree level. But there’s no need for Carol Vorderman-level maths skills.
Insight analysts do need to be able to master statistical analysis techniques and software (such as SPSS, SAS and KXEN). They also need to be able to write and check their own code (and enjoy this process, as they will be doing a lot of it!).
Problem solving skills
Insight analysis is all about the appropriate and creative application of analytic methods to solve marketing problems. So it’s not enough just to know the methods: choosing the right methods for each problem is crucial. Experience helps with this, but even a novice analyst should be able to take an analytic problem, offer a range of solutions, and discuss the pros and cons of each approach.
A good analyst is also a curious analyst. The best analysts are hungry for knowledge: about analytic approaches, their client’s business, their data, and their marketing challenges. They ask the right questions and end up solving problems that clients didn’t know they had. How to get the most out of these analysts? Make sure they know why they are doing a piece of analysis and how it will be used, as with this information they can make an informed decision about what approach to take.
Understanding the client
Great analysts can put themselves in their client’s shoes and ‘feel their pain’ – including pressure to hit demanding sales targets. They understand – and are able to take account of – both the ‘big picture’: the client’s market, their business strategy, and their short and long term goals; and the granular, low level detail: including the intricacies of the client’s data and specific problems it can be used to solve. These analysts propose and deliver work that has immediate tactical or strategic applications. They also present back their work in a jargon-free, digestible form, so that the client fully understands how it can be applied and what it tells them about their customers..
So you’ve found a great insight analyst – how do you help them stay great? Analysts thrive on opportunities to solve hard problems. So feed them a regular dose of difficult marketing challenges such as:
My customer retention rate is in decline. What can we do about this?
We’d like to contact customers a year before they purchase a new car. How can we tell what date this would be?
Our propensity models show that the same small group of customers are among the ‘best’ customers to contact in every cross sell campaign. How can we achieve a ‘fair’ allocation of customers to campaigns without over contacting these ‘best’ customers?
Our business has a large volume of data on consumers seeking better value broadband packages. How can we monetise this?
As a result, you’ll benefit from a stream of thoughtful, actionable insights to set your marketing department or agency apart from the competition.
Carolyn Wong is an insight analyst at Amaze One
