Zhang Qiqi

Head of Programmatic, GroupM
Singapore

Leverage the latest technology to challenge long-held assumptions – that’s how innovation uncovers groundbreaking answers.

A trailblazer in unlocking the full potential of programmatic technology, Qiqi brings over a decade’s worth of expertise in driving successful campaigns. With a continuous test-and-learn approach, she seeks to explore how brands can forge more meaningful connections with consumers – using technologies such as AI in programmatic advertising.

LET’S TALK INNOVATION

What innovations do you see in programmatic that will redefine how advertisers approach audience targeting and media buying over the next few years?
With most audiences opting out of tracking, it’s important for our industry to proactively test alternative ID solutions – such as The Trade Desk’s UID 2.0.

Audience fragmentation is also growing with the number of digital services today – from Connected TV, display, audio to digital out-of-home. Thus, a truly omnichannel strategy with consistent audience planning is key to make media investments work harder. Especially when it’s planned around connected creative messaging and holistic campaign execution.
As compared to traditional programmatic strategies, how do your innovations help to reach and engage target audiences more effectively?
The combination of large datasets and AI allows for continuous, dynamic optimisation of media buying. Going back to consistent audience planning – by processing signals from bid streams, first-party data, third-party sources, and real-time campaign performance, these algorithms consistently improve efficiency.

After all, advertising aims to influence purchasing decisions across the funnel. As compared to last-click attribution and impression delivery, the integration of diverse data sources has revolutionised measurement in more effective ways. For instance, real-time insights have led to more impactful campaign outcomes.
What are some of your best practices for data-driven decisions?
First and foremost, it’s important for us to make sure that decisions are accurate and actionable. That’s why we start by clearly defining the objective from the outset – articulating the specific problem we’re trying to solve and outlining the underlying assumptions. This creates a framework for us to revisit and validate throughout the process, to ensure we remain aligned with our goals – preventing misinterpretation of data that doesn’t address the core issue.

By setting this as the foundation, we’re then able to apply insights in a more agile manner. Knowing exactly what we’re aiming for, it enables us to quickly assess the relevance of data, select appropriate analytical methods, and efficiently translate findings into actions.
This information is provided solely for background and is not a representation or guarantee of any future performance.