To develop an effective multichannel marketing strategy, brands have to recruit people who can do magical things with data.  

But is it data analysts they want, or data scientists? And how many really know the difference? 

Our new Multichannel Customer Intelligence report sheds light on some of the key differences between these two roles, which one you need, and when. 

In the report, Fitness First’s Group Marketing Director David Langridge says he is beginning to engage more with data scientists than analysts, and that this prompts an interesting question for many marketing leaders...

Who do I need and what do I need them for?

While both roles are extremely important in their own way, understanding the distinction between each one is important if you want to develop a strong data-led approach to multichannel marketing. 

As with multichannel and omnichannel, the terms 'data scientist' and 'data analyst' are often used interchangeably by marketers as if they are one and the same. 

One example cited in the report is a 2013 CNBC article titled, ‘The sexiest job of the 21st century: Data Analyst’, which then goes on to describe a role that is much more reflective of a data scientist. 

Let’s take a look at each of the roles in more depth, according to the report.

The data analyst

Arguably the most important role of a data analyst is collecting, sorting and studying different sets of information. 

This process looks different depending on the organisation, but usually the goal is to pin down a fixed value to some process or function so it can be assessed and compared over time. 

The data has to be regulated, normalised and calibrated so that it can be taken out of context and used as standalone information or paired with other data without losing its integrity. 

Analysts are generally tasked with drawing conclusions from the data and educating other in the business on how to use it.

They are often the ones with the best sense of why the numbers are what they are. 

The data scientist

Data scientists, on the other hand, represent a kind of evolution from the traditional data or business analyst role. 

Data scientists dexter's laboratory

While the formal training is similar, the thing that sets data scientists apart is strong business acumen coupled with the ability to communicate findings to senior leaders in a way that can influence how the organisation approaches a business challenge.  

Talented data scientists don’t simply address business problems. They pick the specific problems that will have the most value to the organisation once solved.

Anjul Bhambhri, VP of Big Data Products at IBM, describes the role of a data scientist as part analyst, part artist. 

A data scientist is somebody who is inquisitive, who can stare at data and spot trends. It's almost like a renaissance individual who really wants to learn and bring change to an organisation.

A traditional data analyst might look at data from a single source such as a CRM system. But a data scientist will most likely explore and examine data from multiple disconnected sources. 

The ultimate goal is to discover a previously hidden insight that can provide a competitive advantage or help solve a business problem.

Ed Kamm, Chief Customer Officer at First Utility, says:

We have analysts for the more day-to-day stuff, but then also the scientists who have the ‘what ifs’. 

For lots more insight about multichannel customer intelligence, download the full report today

Jack Simpson

Published 16 November, 2015 by Jack Simpson

Jack Simpson is a Writer at Econsultancy. You can follow him on Twitter or connect via LinkedIn.

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Comments (5)


Debra Carey, Head of Digital Marketing at Mentor Digital

It's an interesting concept but how does one become a Data Scientist?

over 2 years ago

Jack Simpson

Jack Simpson, Writer at Econsultancy, Centaur Marketing

@Debra - By being significantly more intelligent than I am...

On a serious note, though, I believe the usual starting route is through a degree that lends itself to data and analytics: maths, statistics, physics, etc. From there I imagine you would apply for entry level roles, but from what I understand it is an extremely competitive jobs market.

over 2 years ago


Ben Atkins, Director of Digital and User Experience at Key Parker

Really interesting article. Its vital for companies to understand the importance and the insight that data can give. It will inevitably aid and often guide the strategic route us marketers take for our customers.

over 2 years ago

Javier Parra

Javier Parra, Director of Digital Intelligence at Súmate Marketing Online

I think the two professions, data analyst and data scientist, could be united under the term "digital intellligence". Digital intelligence covers the entire process, from analyting data to "what would happen?". This is an interesting reflection Jack, thank you.

over 2 years ago


Matt Lovell, Head of Customer Data, Insight & Analytics at Eurostar International Ltd.

I think this is an interesting one as to me the distinction isn't that clear and to suggest that they are two different professions is more likely to confuse than actually inform people outside of anyone performing any analysis / interpretation.

To suggest that data analysts would only look at single sets of data is a bit demeening and doesn't really help anyone trying to source this kind of resource.

On Debra's question, I think degree type is actually irrelevant but it's about having an interest bordering on fascination with data and understanding the numbers behind things alongside an ability to analyse / interpret this to help answer questions / guide decisions.

At a low level (i.e people looking for their first job) it tends to come down to people who have a decent grasp of the likes of excel, any data analysis tools or actually just an affinity for logic problems. Most of the rest can be learnt on the job...

over 2 years ago

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