I just finished judging entries to our internal annual awards show. I was tasked to assess about 20 entries to the best use of data and analytics in campaigns. It was a rather long, tedious task, but it was enjoyable and insightful. I should say, I am pleasantly surprised by the breadth of applications my colleagues in other countries have created and initiated to activate data and analytics for their campaigns.

At least two campaigns stand out in my head.

One is about the use of an established technique in marketing sciences (marketing mix modelling) in a rather new way to extricate the true impact of a campaign on sales and actual transactions. I thought it was a novel way of thinking about the tenets of MMM and econometrics.

Another campaign was about an innovative data gathering technique that collated data from various sources on the internet to create visualizations and analyses that are meaningful to consumers (!), not just the analysts themselves. The results of the campaign also showed significant contributions to the businesses of the brands — which is always a must in my head as a judge.

There were also other campaigns that were focused on specific tools — like Power BI, Google Data Studio, Tableau, and Python — but were (at least in my head) lacking in terms of strategy and clarity in results.

One thing that I will take away from this exercise: Have a clear statement of the problem and have a clear statement of having addressed the problem.

Without a clear statement of the problem that one is trying to solve, there is no direction. Strategies, insights, and executions are going to be unimportant without the clarity that is needed in the problem statement.

Ultimately, there must also be a clear statement of having addressed the problem. All data and analytics problems are business problems — or are rooted in business problems. How have these business problems been addressed by the techniques used? This should be clearly demonstrated as well in the case study.

Anyway, I am happy that we as a company are moving towards the use of meaningful data in our work.