12 October 2021

From rough data to intelligent insights: how data science improves digital marketing

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It’s a great time to work in marketing. Thanks to a number of digital innovations, we can gather data on just about anything. But what value is all of this data to a digital marketeer if you don’t use it to improve your marketing strategy?

That’s where data science comes in. Data science is the science of extracting knowledge from large data sets and applying this knowledge to solve a wide range of societal and business problems. From decreasing traffic jams, to understanding healthy aging, to optimizing marketing campaigns; data science can help to identify patterns, answer major questions and solve challenges.

One field that can benefit greatly from using data science is digital marketing. During the latest Beyond Digital meeting, the knowledge-sharing discussion club organized by digital expert Ariad, David Melviez, Digital Marketing and Data Science expert, shared his insights on the use of data science for digital marketing.

“I initially turned to data science for a way to make my reporting more efficient, but the advantages go far beyond that.”

David Melviez, Digital Marketing and Data Science expert

The interdisciplinary field that is data science builds on statistics, informatics, computing, communication, management, and sociology to study data in order to transform data to insights and decisions. Applications for digital marketing include optimizing reporting by easily interpreting multiple KPI performances at once, which can give insights into how to optimize the media mix or increase conversions on a given channel.

David Melviez
has a background in sociology and marketing and has recently immersed himself into data science. “I’m always looking for ways to avoid repetitive tasks by automating them. So I first turned to data science as a way to optimize my reporting and work more efficiently.”

But data science is no plug and play solution for more efficiency, David explains. “There is a learning curve; it takes time to get it working, learn how to code, collect relevant data and reach a point where you can draw meaningful conclusions. Over time, it pays off, but it’s certainly an investment.”

Getting started with data science for digital marketing

David suggests starting with the most important data source that takes most of the reporting time. “Build your reporting on a few relevant KPI’s, such as your website’s bounce rate or most viewed pages, and set it up so that you only see relevant data. Focus on evolution rather than absolute figures and use conditions. For example, see the top 5 pages that answer 2 conditions (at least 2% of the traffic with a bounce rate evolution >10% over the 2 last months). This means you’ll be focusing on what matters and you will not be bothered with figures that have no impact on your business”.

Once you’ve got the hang of it, you can start aggregating data from multiple sources and build great visualisations. Data science is obviously great for exploratory data analysis, so while automating your reporting, you’re also gaining much more knowledge on your data itself.

When automation is running well, you can draw conclusions, put your learnings to the test, and ultimately, improve it with predictive models, if applicable. Notes David: “data science is a continuous process with many different types of benefits.”

Tools and software for collecting, synthesizing and sharing data

There are number of tools and software in existence that can be helpful when starting with data science. But, warns David, there is no one-size-fits-all tool for a company starting to implement data science. “It really depends on a number of factors. First and foremost, you will need to define the questions that you’re trying to answer. Then you can look for the software and skills needed to get there. Similarly, your company or team structure might require certain features in regards to usability, sharing and security.”

Challenges for implementing data science

One of the main challenges you can run into when trying to implement data science for digital marketing is having the right talent on board, as it requires a range of different skills. As Stefano Aprile, Global CRO Specialist at TVH, puts it: “it’s not just about having someone who can find the numbers and data that can answer your questions, you really also need someone who can transform this data into a compelling story.”

The interdisciplinary nature of the field either requires to someone who can wear many hats, or a multidisciplinary team that works together seamlessly on the different fronts. But regardless of which way you go, it involves a learning curve, which in turn requires a shift in priorities to accommodate for the time investment needed to start with data science. Especially for companies that are not digital native, this can be discouraging. “It may feel like you’re hardly making any progress, but bear in mind that this exercise finds its value in the long run,” advises David.

The shift in required skills combined with the fact that it can take a long time before reaping the benefits make it something not to take lightly. Julie Lateur, E-commerce Lead at Telenet can relate: “The value it generates is indirect and will mostly show in the longer run. That makes it difficult to prioritize starting with data science over other projects that have a direct value and require less effort up front. It’s also not easy to find the right people with the right skills, people who have enough feeling with the business and its needs on the one hand, and who know data architecture and data science in general on the other hand.”

David agrees: “An unexpected hurdle when implementing data science is that numbers don't always speak for themselves; there may be a strong need for change management, to have all the stakeholders aligned on the idea data science can be a worthy priority.”

Whether you’re implementing data science or looking for other ways of future-proofing your organization, having stakeholders all be on the same page is a crucial aspect. So when it feels like different stakeholders don’t speak the same language, it is important to close that gap first. One of the steps to get there? Upskilling the workforce!

Want to join in on the discussion? Ariad’s digital professionals knowledge sharing club Beyond Digital brings together future-forward individuals working across industries in the largest brands in Belgium. No member fees, just a community of ambitious minds! Apply here for more information about this monthly event.