Skip to content Skip to navigation

Data Analytics in the Media and Advertising Industry

Lee Wee Teck

Associate Director, Data Analytics - Publicis Media

Lee Wee Teck graduated from the MITB (Analytics) program in 2015 and has since gone on to take on different data analytics roles in companies like Zalora, Cognizant Technology Solutions and most recently, Publicis Media.

Much of what Wee Teck has done in his past and present roles leveraged on the foundation he gained from the MITB program. Modules that he took, such as Analytics Framework and Business Context, provided useful perspectives and outlines for getting a company started on utilising data analytics. Specialised modules of customer, operations, cloud and big data analytics gave him a well-rounded view of the data analytics universe. All the modules offered practice opportunities in applying different data science solutions to real-world data. These culminated in the capstone project, which enabled him to apply his new-found knowledge and skills to tackle real business challenges.

Data Analytics in the Media and Advertising Industry

The global media advertising spend has been growing almost linearly since 2011 and is estimated to reach USD 675 billion in 2019. Forecasted to grow further to approximately USD 811 billion in 2022 , advertising continues to be a huge industry where companies invest significantly to market products and connect with potential customers.

With increasing digitalization and continued growth of new marketing channels, companies continue to allocate substantial budgets for their marketing efforts, with digital spending leading the way.

Media agencies, like Publicis Media, contribute to this overall landscape by helping companies navigate the complex terrain of media advertising – to reach their target audience efficiently and effectively. The agencies leverage on their domain expertise to develop and execute optimal media plans, while keeping the costs manageable for companies through achieving economies of scale in media buying.

In-house data analytics teams add further value to the companies, providing actionable insights derived from solutions like marketing mix modelling, multi-touch attribution, marketing budget optimization and clickstream analytics.

Data Analytics in Action

As a senior manager, I lead the APAC data analytics team in Publicis Media. My team comprises analysts whose primary focus is to create and deliver business value to clients through the application of data analytics solutions to their marketing challenges.

Our engagements with clients frequently involve business consultations to determine the problems we are attempting to address, alongside hands-on data mining and analysis to uncover useful intuitions and delivery of results to drive meaningful impact.

It is a common sight to see us burying our heads in data, ranging from media spends and metrics, to website clickstream, to data generated from web publishers and ad servers. The data volume is typically massive and it is not unusual for us to process gigabytes or terabytes of data.

One of the projects we often undertake is the multi-touch attribution analysis. The objective of such a study is to correctly credit the contribution of different online media investments to a success metric like conversions or sales.

The intention is to utilize the outcome from the attribution analysis to guide marketing budget allocation decisions so that total returns can be maximized. Data is processed for this purpose using simple rule-based attribution methods like first-touch, last-touch, linear, and u-shaped, etc. to data-driven approaches like Markov chains and Shapley value.

Conceptually, Markov chains describe a sequence of possible events in which the probability of each event depends only on the state attained in the previous event. In the context of channel attribution, Markov chains provides a framework to model user journeys. It uses probabilities such that the contribution of each marketing channel towards a desired outcome, like purchase, can be quantified.

Separately, the Shapley value approach to marketing attribution is derived from a concept of cooperative game theory. Named after Nobel Laureate Lloyd Shapley, this algorithm computes the contribution of each marketing touchpoint; it compares the conversion probability of similar users who were exposed to a sequence of touchpoints, to the probability when one of the touchpoints does not occur in the series.

When properly implemented, a multi-touch attribution study coupled with a budget optimization exercise can result in substantial impact for a client; in one such exercise, we managed to increase a client’s return-on-investment (ROI) for a campaign by approximately 100 percent. This achievement was reached by re-assigning its marketing budget mid-way through the campaign, in response to findings from a multi-touch attribution analysis.

The Future of Data Analytics

Looking ahead, one of the growing challenges we face in applying data analytics in the media and advertising industry is the availability of quality data. Big technology companies like Google, Facebook and Amazon are fortifying their walled gardens to restrict data access, while data privacy laws like the General Data Protection Regulation (GDPR) in Europe, California Consumer Privacy Act (CCPA) in the US and Personal Data Protection Regulations (PDPR) in Singapore are also making it harder to collect user information.

The landscape is made even more complex with recent developments in web browser technology – which limits the use of third- and even first-party cookies that the industry has traditionally depended on to collect user data for analysis. There is no let-up from consumers either, with an increasing focus on protecting their own data and mounting pressure on companies to let them do so.

As the media and advertising industry continues to evolve rapidly amid digitalization and adoption of technology like artificial intelligence and blockchain, fresh opportunities and challenges will continue to surface.

For practitioners of data analytics, it would be imperative to constantly seek out opportunities to value-add to clients through analytical problem-solving and critical thinking, so that we can deliver on our promise of creating business value through actionable insights. While this has never been straightforward or easy, one can take comfort in the fact that excitement abounds in this space, whatever the challenge is.

Last updated on 09 Sep 2020 .