Luka Ignjatović, Data Scientist, Polaris (I&f Grupa)

The Marketing Appliance of Data Science

Data science revolves around the interpretation and analysis of data arriving from different sources, as well as different types and structures of data. Various scientific methods, processes, algorithms and front-end solutions are fed with countless rows of data in order to extract patterns of behaviour, insights or information

When it comes to applying data science in marketing, the goal is to provide insights that let marketers know if their decisions have paid off. These insights can help brands dig deeper into customer psychology by quantifying intent, desires, experiences and behaviour. This, in turn, will enable business strategists and planners to optimise their media spend, improve media buying efficiency, reach narrower target audiences and pick the right creatives, leading to significant improvements in media planning and cost-efficiency.

Luka Ignjatović Logo PolarisIn order to achieve these goals, certain rules have to be in place when handling data, along with appropriate digital infrastructure and a team of people. In terms of infrastructure, specialised tools have to be in perpetual use to ensure past, present and future data is stored.

Rules in the form of internal conventions are necessary when handling data. This ensures understanding among everyone in the organisation who’s involved in data-related processes. Lastly, a team of people that work with the data has to be ready to apply mathematical, statistical and programming knowledge to extract insights. In the world of marketing, data scientists work closely with people from agencies during projects, because their invaluable domain knowledge puts raw data points into context.

The projects that can be offered by data science departments’ blend of skills are extremely diverse in goals and content, like maximising TV exposure for a new brand on the market or raising brand love for an already established one. It is merely up to the client to ask the questions or have a media/sales objective in mind. Then data science teams can build the right analytics or modelling solution to meet their needs.

It should be noted that there is a trend in the industry that includes shifting the data storage paradigm from relational databases to a newer one called “big data”. Big data’s defining properties are 3Vs (volume, variety and velocity) and they have emerged out og a technological need to handle data that comply with the aforementioned three Vs.

We here at I&F Grupa jumped aboard the “Data Science” bandwagon early-on by establishing a brand new analytics-focused agency – Polaris. The task was not an easy one, as all the existing client data infrastructure and reporting processes needed to be maintained, while simultaneously being updated and improved.

We have also successfully built and tested media and sales models that help brands plan for the future by identifying their leading sale indicators and optimal media spends to improve their profit margins.

Building synergy between the technical and business side in data science is very much a continuous process, so you can expect even more of our solutions that offer improved segmentation of user bases, more powerful media buying, advanced social media marketing, and more precise results management and understating of key metrics to our clients.

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