Data, data and even more data

Column Lucas Hulsebos – CEO DVJ Insights

These past few years we have taken over many trackers at DVJ Insights. An exciting process for us, but above all for our clients. What differences are there and what do these differences actually mean? Because of this fear and the need to be consistent, we notice that a lot of companies choose to stick to the old. There is a big risk and the possibility of accumulating a lot of extra work isn’t that great of a prospect. Placing 2 sources next to each other becomes a fear, while it is actually a huge opportunity to learn more.

An easier transition

The solution for this situation lies in data, in particular the analyses of data. A better understanding of historical data starts with applying new techniques and ways of modelling this data, or “old data”. It is because of that, we developed a “back data” analysis that uses different data sources and thus places all accumulated data in a fantastic perspective. It teaches us the significance of historical data and what is – and isn’t – relevant to the future. The essence lies in the way we place input (media – PR – other marketing efforts) alongside the output (sales – brand position – etc.). By connecting these sources, we see patterns being created in the data that facilitate an easier transition from one tracker to another. These developed techniques are based on complex statistics, but lead to concrete results for marketing and research.

A source of inspiration

Through data and data modelling, it is much easier to understand and use changes in data. Within DVJ, this has led to various initiatives for the development of solutions that use data. Fear of data, different data sources or successive data sources are converted into knowledge. The researcher on the client’s side plays an important role in this. He or she must become the pivot in the processing of all data, not the transfer to other departments. Researchers are often greatly capable of interpreting and connecting data, so it becomes logical and relevant. By taking this central role, data becomes a source of inspiration, instead of a mountain of problems.