Staff Reporters
Jul 18, 2016

Machine learning: Threat or benefit?

As marketing transitions from intuition-based to data-oriented, will machine learning handle much of marketing down the road?

L-R: Florian Pihs, Ohad Hecht
L-R: Florian Pihs, Ohad Hecht

Participants:

  • Florian Pihs: Senior planning director, SapientNitro
  • Ohad Hecht: Chief operating officer, Emarsys

Which area of marketing is investing the most in machine learning?

  • Pihs: Pay-for-performance ads, brand ads, DSPs, DMPs, personalisation algorithms on content management systems and ecommerce platforms, A/B testing and multivariate testing for landing experiences and banners.
  • Hecht: Brands with a focus on ecommerce or e-tailing. Those who started online early have the advantage over traditional types.

Who are the biggest players in machine learning in marketing?

  • Pihs: Search engines, social and ecommerce. Ad tech and digital marketing platforms (Abobe, SiteCore, IBM) claim to use it. Big ad networks also invest, largely on the media side.
  • Hecht: All the internet and ecommerce firms. With instant messaging (IM) and mobile-first culture, personal communication and ecommerce are converging — a big area for machine learning.

How do marketers feel about machine learning and why?

  • Pihs: Some media are scared that parts of their inventory are devaluing and feel safer selling in bulk. This creates uncertainty for the industry.
  • Hecht: It depends on whom you ask in which market. If I were a website manager four years ago, I would’ve been relying on my preference in choosing content to post or product to sell. Now marketers are more aware that things are data-driven.

What are the obstacles to machine learning in marketing?

  • Pihs: Data integration/aggregation. Big Chinese platforms’ siloed ecosystems prevent integrated third-party-data aggregation.
  • Hecht: Having enough data to test and run control groups to optimise their campaign.

What can marketers do to make a start on it?

  • Pihs: As soon as you start using search ads, you’ve made a start. You can then utilise machine learning on DSPs and website personalisation to harvest the benefits of higher performance.
  • Hecht: Thinking about data collection and how to connect and unify the data.

How is it changing marketers’ role?

  • Pihs: The role hasn’t changed: the mindset has. Marketers need to think beyond campaigns and into always-on communications. 
  • Hecht: With so many data points, human mind simply can’t keep up. Machine learning won’t replace the role of marketers but will allow them to scale decisions by letting machines do the work.  

Related Articles

Just Published

1 day ago

How to prepare for hybrid commerce: Chinese ...

As consumers seamlessly hop between physical and online, brands are expected to provide real-time stock information and personalised experiences across all of their touchpoints. But they must demonstrate a value exchange to consumers to collect the data they need.

1 day ago

Data shows brands don’t need social media accounts ...

Data from a Jing Daily report shows that luxury brands no longer rely on their own social media accounts in China with more engagement relying on KOLs.

1 day ago

Apple debuts 2022 Chinese New Year film (clear some ...

The company's offering for this year is a 23-minute epic—shot on iPhones—about the making of an epic film within the film, also shot on iPhones.

1 day ago

How women’s health brands communicate on social ...

Female founders of women’s health brands say censorship makes it challenging to properly address women’s concerns.