• by Belinda Barker , Op-Ed Contributor, October 10, 2017

For the past few months I have been spending a lot of time talking to senior researchers and analysts across agencies and advertisers as part of planning for an event. They have all been hugely passionate about the impact of the insights they glean from their "own" set of data on campaigns, whether it is survey data, TV panel data and big-brand tracking programmes of the researchers or the online behavioural, transactional and social media data of the data analysts.

Mark Greenstreet, chief research officer at Dentsu Aegis Network, said something that really struck me -- “Data analysts are from Mars and researchers are from Venus. They don't speak the same language.”

It's a really interesting point. Advertisers are investing more and more in understanding their customers, data is becoming richer and deeper by the second, and technology is making the automation of communications (driven by data and insight) increasingly fast and slick.

However, if advertisers and agencies have separate insight and analyst teams, and these teams are given different KPIs and rarely speak to each other, what are the chances of receiving the full benefit of understanding from all the information at their disposal? 

Some companies are capturing oceans of data without any real strategy for how will use it. Phrases such as "customer journey" and "single customer view" are far from new, but in reality, but for many companies these seem to be a long way off -- often pulled together with huge information gaps that could be filled if there were a meeting of minds and data from both the research and data analyst teams.

I talked with Greenstreet and also to Ian Liddicoat, chief information officer and head of data sciences at Publicis Groupe Media, to get the view from both sides of the fence -- to see how they have successfully bridged the gap. Here is my takeaway from these conversations about why these disciplines remain as silos in many organisations, and the best ways to overcome the problem.

Educate the senior executives

Data and research professionals, in many instances, still have not managed to take a place on the Board. Those at the top often lack an understanding of the difference between the two disciplines, or the benefit of combining the two, so things remain the same.  It's time for researchers and analysts to put their heads above the parapet and talk about how powerful results can be when you break down the barriers. After all, anything that brings competitive advantage and better results tends to get their attention.

Create a mutual advertising lexicon

Research and data teams were originally set up to do different things -- research teams focused on long-term brand building,  and data teams focused on short-term ROI. As a result, they really have been talking different languages, especially when it comes to measurement. For example, terms such as reach, exposure and brand effect are simply not natural terms in the digital world. Ask one person for a definition of engagement and it's likely to be different than almost everyone else's. However, as advertisers increasingly look to digital for brand advertising rather than just performance, and digital brands like Google spend big on TV, it's time for advertising metrics and language to be integrated.

There must be an understanding among both parties of the role of each type of data, and an openness to learning about and accepting approaches that are different than those they were brought up with. And we all need to work harder to make ourselves understood by those that don't speak our language -- being clear about what we mean and doing away with the dreaded jargon that is so rife in the industry.

The rise of the data scientist

An emerging "hybrid" role in the industry seems to have had a major impact in bringing together data and research -- the data scientist. These new kids on the block tend to be digital natives who have grown up in a more integrated world. They are just as adept at writing code and creating cloud platforms as they are at running analytics. Advertisers and agencies need insight people to be more analytical and analytical people to be more insightful -- and this is manifested clearly in data scientists who are a true fusion of analytics and technology, creating intelligence and insight from all the data and information a client has.

Combining all these skills in one person benefits clients, as they end up with a more rounded solution and the individuals themselves are likely to have a broader career progression rather than being pigeonholed. As we see the role of data scientist grow in the industry (both through digital natives and ambitious insight specialists and analysts with an understanding of the direction the industry is taking), we are likely to see the spread of data scientists help to break down the silo walls. 

Look beyond the marketing world

We should not just sit back and wait for people with these skills to take a liking to the media. You can find accomplished data scientists in government, in banks, in interesting technology sectors like image recognition -- and not just from the UK and Europe, but in emerging markets like China and Singapore. What's interesting is that a data scientist coming from outside of the sector will look at the pigeonholed roles and ask "why is it organised this way" -- which in itself is a powerful way of breaking down silo walls.