Fair Exchange: Do marketing teams need dedicated data scientists?
by Erna George. What is the balance between data, gut feel and doing? I believe we require it all.
While watching Spectre, I remember smiling when, in response to a new government division seeking to terminate the “00” programme and instead source intel by monitoring everyone all over world all the time, the incisive M said, “That’s fine, but at some point you need to get into the field and look at the real situation and get involved to effect change.” This scenario plays out in the world of marketing, too, and this tension is present in many areas.
Good marketing practice includes strong strategy development, data sourcing and analysis (data science) to understand context and possibilities, and these two things put together result in brilliant executions for implementation. While I believe strongly that good marketers must be comfortable or have some experience in analysing numbers and other data, having a specialist data scientist function to help identify which data is key, source it, sort it and get the best insight from it, is invaluable. Evidence-based decisions and content creation from this are more critical today.
“How brands grow” by Professor Byron Sharp of the Ehrenburg-Bass Institute gained acclaim in the marketing world when published, and a few of the large multinationals are applying this approach to marketing, indicating a stronger shift to more application of data science. Data can offer the edge that helps shift brand from good to great. Even generating new creative is bolstered with a strong foundation of insight for highly targeted and relevant campaigns.
But the trick is two-fold:
- getting to the nib or the core insight, not having only numbers or stuff and
- balancing the facts with the flair.
Getting data today is far less challenging than when I first started in marketing in the ’90s. Without the broad-based web, you had the choice between mainly syndicated data or project-specific investment. You could also track metrics on each activity and compile a history, and an extensively used source was asking a senior, experienced someone who often started their sentences with “Back when I worked on brand x…” Even back then, trawling through Nielsen presentations or reviewing other market data, you needed thinking time to figure out the opportunities, challenges and more.
In 2016, where the amount of information has exploded, as has the number of methodologies for fresh insight or data, how do you choose?
There may be some who believe a data scientist is too restrictive. They may imagine someone only reliant upon the stats — but the opportunity cost of missing out on the right information may be massive. Missing the subtle shifts in market sentiment towards health and seeing growth across smaller health brands, added to the reviewing global trends and launches, could have made the difference between capitalising on the growing health needs of consumers or decline.
I find that good data scientists are rare. Why? We don’t need someone who only knows how to crunch the numbers. It’s not about telling us what the data says — most people can read a graph! — it’s about interpreting what the data means for the brand and the future. It’s also not about analysis paralysis as there is no time — it’s about someone who can track and source the most relevant and important information, sort and analyse data within the context of category and strategic imperatives, and then present this in the most impactful way. A talented individual blending science and art!
At a previous job, as a team we spent an inordinate amount of time working upon how to show the information — the visualisation. The most succinct and impactful way to tell a story to not only land the message but make it memorable. This is an art, as with multiple meetings, pieces of information and other noise, the most important “So what?” needs to be remembered and applied. Today, while I know how to go about the analysis and impactful packaging of data, I don’t have the time to add this onto my day job at the level of frequency and depth required to maximise information.
I like the thought of a permanent team member but, with the scarcity of these skills and with cost always being a factor, you can always consider an agency to assist but then it is key that it be a core partner.
Different way of working
It’s also vital to point out that shifting to data analytics at the heart of actions or decisions is a different way of working; it can challenge current beliefs and processes. For example, to exploit opportunities uncovered, lengthy decision processes and how we work in general may need to be reviewed and altered. Teams must be prepared to shift towards opportunities and to move faster and swifter. Without a commitment to action, what the data scientist unlocks is simply information that is nice to know. And imagine if data scientists in client and agency teams shared news and collated intel? The possibilities could be endless.
Marketers need data scientists ‘on’ the team to get the right focus on the relevant information within the context of the brand-strategic imperatives — this ensures effective channelling of insights in the most powerful way. Good data scientists are rare: find them, incorporate them into your strategic thinking and team work and remember:
- Avoid the trap of analysis paralysis — there is no time.
- Visualisation is mission-critical. It’s less about how much data and more about the story it tells.
- Be open to changing existing ways of working to let the facts have an impact.
Erna George is the marketing executive of Pioneer Foods’ Cereals & Other division. She has worked on both client and agency sides with diverse brands and categories — from FMCG, alcohol and agriculture to financial services and entertainment — in countries across many geographies, including South Africa, Mozambique, Nigeria, Kenya, India, Philippines and Brazil. She contributes the monthly “Fair Exchange” column, concerning business relationships and partnerships in marketing and brandland, to MarkLives.
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