How do you measure the ROI of the marketing mix with online and offline marketing data


MOA Digital Analytics Afternoon – A short summary of the presentation of our CEO, Martin Leeflang.

Martin took us for a ride in one of the major league players of multi-channel attribution. Based on a case presented at Esomar last year.

Martin took up Felipe’s baton well by promising to answer the question, using his methods, which web analytics could not answer: how many extra sales are realized on the basis of watching a Youtube video?

He brought his discourse along with us in the ever changing research landscape. People are having to deal with much more information through a great many more channels these days. For a traditional researchers it becomes near impossible to process this. Even more so when you have to take into account the laws of small numbers (the smaller the sample, the bigger the deviation) and the problem of motivation and memory. Because of the large amount of information and channels people often don’t know whether or not they’ve seen something let alone via what channel they saw it.

To illustrate how important it is to work with lots of data and therefor score the “runs” and “wins”, he showed us a clip from the movie Moneyball. This ‘based on a true story’ movie shows how an underdog with the right data can be a winner. Then he showed us, using a case from D-reizen) how you can apply the principle of runs (ways to win) and wins (success factors) in any business.

So how does this work? It’s impossible to explain the entire process in this article. Nevertheless, I will try to give you a small description. This definition however does not do justice to Martin’s job, but fortunately for us Martin promised that anyone who is interested in his methods is more than welcome to come and take a look under the hood.

  • Collect as much data as you can. Web Search, broadcast schedules on television and radio, outdoor advertising, social media and all other means of exposure you’ve had.
  • Extract, by combining the data, what part of you visiting a website is due to the campaigns.
  • Check on a daily basis what media you’ve used and how this has contributed to the objective.
  • Determine, in this way, the impact each medium has.

After that it’s time to optimize. Take a closer look at every medium and see where the profit lies. In his presentation, Martin gave the example of ‘ticket auction’ (NL: ticketveiling) and how an analysis of advertisements on various channels taught her what channels are valuable and what channels are best to be avoided. And better yet, it even taught her the best times of day to advertise.

If you’re a major market player that advertises via many channels than Communication Analytics is a tool that can easily be optimized. If you don’t use a lot of media or you don’t have the resources for a large analysis you can also get started yourself. Simply follow the steps above and explore where you could optimize. Martin’s tip here is to gather data in a disciplined and structured manner. You then combine the data and with a few simple calculations you can already take the first steps towards optimization. Just as Martin ended with another fragment from Moneyball:


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