Data Science and Marketing, time to close the gap

Posted by Sirine Karray on Oct. 2, 2018


Data Science & Marketing Analytics

Information Age, Digital Revolution, the Era of Digitalisation, the Rise of Digital Economy… are all different terms that came to describe the natural outcome of the increasing adoption of technology.

Smartphones are considered to be the main contributor to this growing trend. According to eMarketer’s forecast, mobile will be the new leader in terms of time spent in electronic devises in the US by 2019. As a logical consequence, mobile ad spending in the US is expected to grow by 14.7 percent compounded annually through 2022 (Forrester Research report).

This massive adoption of technology of all shapes and forms resulted in a significant increase in data volume and hence an increasing interest in data-driven tools, to help of course take advantage of all the data created.

Big data analytics are expected to improve business decisions and increase annual GDP for retail and manufacturing by up to $325 billion by 2020 (McKinsey Global Institute new report “Game changers: Five opportunities for US growth and renewal”)

For Marketers, this means a huge opportunity awaits the brands they manage if they succeed to harness the power of the data created and understand its full effects and implications.

The real question though is where to start, as data is big, diverse and floating all around. From web visitors to social media followers, to traditional offline consumer shopping data, marketers can’t help feeling overwhelmed by the data Velocity, Volume, Value, Variety, and Veracity.

Collecting data is good but consolidating it across all touch points and analysing it to capture real consumer trends is where the real value lays.

Today, the gap between marketing and data science has never been narrower: consumers are becoming increasingly tech-savvy which translates in more sophisticated paths to purchase and which in turns makes adopting consumer-centric approach a must to optimise brand performance and achieve the desired business KPIs.

There was and there still is a lot of talks around Big Data and its implications in marketing, but we think that it is time to shift the debate to the creation of intuitive tools that can run on big data, extract meaningful patterns through applying advanced & adapted machine learning algorithms to create actionable insight, optimise marketing strategies and improve consumer engagement and conversion.

At Mass Analytics, our philosophy is to help bridge the gap between Data Science and Marketers by creating intuitive tools that allow the latter to apply sophisticated data science techniques to their data and extract meaningful patterns to achieve optimal data-driven marketing decisions.

Dr. Sinda Ben Salem is Director of Data Science at Mass Analytics

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