[HKML] Supercharge your Marketing with Data & ML . [HKML <> IAB] . Off-Season #1


  • Thursday, September 5, 2019 from 6:00 PM to 8:30 PM


This meetup was actually organised by the Interactive Advertising Bureau (IAB), an association that promotes digital marketing, and Korey Lee from SCMP.

The meetup was full. A couple of seats were offered and reserved for HKML members.

The audience of this meetup was mostly business and marketing focused. Many people were from Google and Facebook, including the speakers, but not from the research or software engineering departments (none of which are based in Hong Kong as far as I am aware). Presentations were about deployment of Machine Learning solutions from a business user perspective who cares essentially about ROI.

The ratio women/men was around 80% which contrasts strongly with the 10% of the regular HKML meetups (more science & ML engineering focused).

As I’m not a marketing expert, my comments below may be of limited interest.

Some readings to have a grasp at the ML + marketing field:


6:00pm - 6:30pm Networking

6:30pm - 7:00pm Keynote

7:00pm - 7:30pm Drinks and nibbles

7:30pm - 8:30pm Lightning Talks & Panel

8:30pm - 9:00pm Networking

Topics to be covered:

Keynote: What is Machine Learning and the growing importance of ML

Derek Kwok, Head of Google Marketing Platform, Greater China & Korea

A general introduction to machine learning applications by Derek Kwok, the keynote speaker for this meetup.

Basically, putting Machine Learning in production is getting easier and easier thanks to APIs provided by the top tech companies (translation, speech recognition).

Many domain of applications: manufacturing, retail, health & life sciences, travel & hospitality, financial services, energy & utilities...

For marketing, Machine Learning can help improving the customer experience, user acquisition, automating processes, and reducing media waste.

  • Advanced & Mature ML Solutions: What are some of the bespoke ML solutions and what are some of the successful cases?

Wallace Leung, Product Marketing Manager, Facebook

Ads campaigns are already very optimised by ad-tech companies. Customers can also opt for tailored bespoke solutions. Interesting point during the point: Liquidity + Signals. Liquidity: Allowing every dollar to be spent on the most valuable impression. Signal: A signal is behavioural data that a machine learning model uses to make predictions. Ads marketplaces have become very similar to financial markets: Liquidity should bring efficiency (no arbitrage in a broader sense, ~fair pricing), yet powerful signals from more informed players exploit inefficiencies to print for cheaper, and doing so erase these inefficiencies progressively.

You have to establish a rigorous process (strategy) to deploy, evaluate, and refine you're ML solutions.

  • Productised ML Solutions: What are some of the readily available machine learning solutions and how can marketers get started?

Darren Chiu, Google Technical Services Professional Services

Interactions with customers are getting more complex (e.g. voice queries) and may require advanced AI (e.g. speech recognition) to reach them more efficiently.

Google has automated many marketing tools, for example creating automatically ad videos from raw content provided by the user.

Precision targeting of customers is a key benefit of machine learning in the marketing field.

  • Case 1: The role of Machine Learning in customer segmentation

Cedric Delzenne, Managing Director @ 55

Basically, using a clustering algorithm for performing customer segmentation (k-means, g-means). What's hard is to do all the plumbing around.

  • Case 2: The role of Machine Learning in driving both on and offline transactions

Jing Ma, Data Strategy Lead, Google Hong Kong & Taiwan

Find the key potential customers amongst all the window shoppers.

Repeated online viewing may lead to in store buying.

Host Saron Leung, Industry Manager, Google (IAB HK Data & Measurement Committee Lead)



  • Korey Lee, VP of Data, SCMP (IAB HK Data & Measurement Committee Member)