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Magic Numbers: Shaun Au Yong on the Combination of Creative, Data and MarTech

05/04/2023
Advertising Agency
Singapore, Singapore
71
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Associate director, data and marketing effectiveness at Merkle, CXM Group, dentsu Singapore, on the approach to dream, do and deliver

Shaun brings over five years of digital analytics and MarTech experience: working on end-to-end data projects from conceptualisation, implementation, operationalisation, measurement, reporting to optimisation across the entire MarTech stack. Coupled with his subject matter expertise, he creates personalised marketing moments for clients and moves from gathering insights to data activation throughout all digital channels.

Through transforming clients’ marketing strategies to help them achieve personalisation at scale, he has proven results in reduced CPA in media and created incremental conversion rates by increasing relevance for their customers. 

Fundamentally, Shaun strongly believes that marketing today is fuelled by a combination of creative, data and MarTech, and that each pillar is equally important for the success of any business.


LBB> What’s the number one question that clients are coming to you with when it comes to how they can better use data to enhance the creativity of their content and experiences?

Shaun> There are usually two parts to their question – the first being on measurement and the second being on the improvement of the effectiveness and efficiency of content and/or experiences. 

Our approach is to dream, do, deliver. We do that by first attempting to understand the client’s digital maturity and identify the respective gaps in their current analytical/martech stack. Post that, we will co-establish what the gold standard is before implementing and deploying necessary enhancements to the client’s tech stack to make that gold standard a reality.

 

LBB> How can you make sure that data is elevating creative rather than forming a windtunnel effect and knocking all the interesting or unique edges off that make something distinctive?

Shaun> The beauty and purpose of data would be to allow clients to create a personalised experience for the end customer and/or user. The idea is not to use data to regress creatives to the “best performing” variant and just stick to that. 

We take an approach that utilises data to segment customers into distinct and unique personas. Once that happens, creative can be designed to resonate with that persona. Such relevancy elevates the creative and avoids that windtunnel effect. In fact, with proper data & Martech implemented, marketers can ensure that all creatives are distinctive for every single customer (e.g., via data centre outsourcing etc).


LBB> More brands are working to create their own first party data practice - how can a brand figure out whether that’s something that is relevant or important for their business? 

Shaun> There is absolutely no doubt that every single brand needs this practice. The intent of such a practice is to ensure that we progressively understand more about the customer, and we tune our marketing efforts in a way that’s relevant and personalised to the customer.

There is a need to be clear on the end outcome of this data practice. A lot of brands merely think that insights would be the end goal of a first party data practice. However, insights without data activation would just be another pretty dashboard floating around somewhere.

The bottom line here would be to ensure that the practice generates data/insights that are activated in an actual marketing campaign, automatically; in real time; and at scale.


LBB> We talk about data driving creativity, but what are your thoughts about approaching the use of data in a creative way?

Shaun> Successful data practitioners are masters in both art and science. Art/creativity is critical to create successful data strategies, as the first step in approaching any data problem would be to start with divergent thinking, i.e., finding & validating potential hypotheses to solve those business questions. This is an exercise in creativity and is the key differentiating factor between an average data practitioner and a good one.


LBB> "Lies, damned lies, and statistics" - how can brands and creative make sure that they’re really seeing what they think they’re seeing (or want to see) in the data, or that they’re not misusing data?

Shaun> This would be avoided by having a consistent and global measurement framework. For us, we measure companies across time and with a common methodology. We typically use annual data as a baseline and compare the progress year-on-year. Merkle would typically derive an overall score and define the key pillars/metrics that would move this score. 

This approach allows companies to know if there’s a problem and identify root causes quickly and easily, i.e., knowing whose neck to choke or what to clearly improve on. With this methodology, it would be clear as to which metric to improve, to raise this score and thereby the company’s performance.  

This removes the ambiguity of the data points presented and ensures integrity in actions taken from the data presented.

 

LBB> What are your thoughts about trust in data - to what extent is uncertainty and a lack of trust in data (or data sources) an issue and what are your thoughts on that?

Shaun> This is an incredibly big issue in practice, i.e., if there are questions as to the reliability of the data, no one would be confident enough to utilise this. If no one utilises the data, any and every data point would be essentially useless.

It is hyper-critical for data teams to perform and communicate periodic reviews and audits on their reports to ensure that nothing falls through the cracks. This would help ensure that the teams using the data have confidence in making decisions from it.


LBB> What does a responsible data practice look like?

Shaun> A responsible data practice is a team that promotes data democracy in the organisation. It is hyper-critical for everyone to have access and be able to create campaigns out of all data points that the organisation has.

It is the core responsibility of the data practice to make this happen and not keep it within data’s “ivory towers”.

 

LBB> In your view, what’s the biggest misconception people have around the use of data in marketing?

Shaun> The biggest misconception is the buzzword: “data-driven marketing”. 

Marketing today has been disrupted and the landscape has drastically changed in this digital world. To keep up with it, marketing can no longer just be “data-driven”. Marketing needs to instead be “data-reactive”, in other words, for every action/data point that the customer provides, marketers need to react to ensure relevancy and to capture mind space. 

To operationalise this, marketers need to ensure that campaigns are always-on, automated and be in real-time. In short, marketing today is an amalgamation of creative, data and Marketing Technologies.

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