From PPT madmen to AI mathmen

2017/8/14

Carat’s tech team took a look at AI and machine learning.

AI
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With the dramatic drop in data storage tech and processing prices, complex machine learning applications have flourished.  Media and marketing teams are now rapidly adopting the applications to build more efficient campaign delivery.  Audience targeting and the use of AI to build lookalike models has led to significant improvements in ROI.

Software services and DSP providers are betting on the role for AI in programming applications and code development.  Their ambition is to achieve closer dialogue between their advertisers and consumers

But what is AI?  Are we using a new team of robots with the sophistication of Alicia Vikander in Ex Machina? Or we being missold ‘AI’ when in reality it’s a complex excel table? What does good look like?

Here’s our quick guide:

  1. CONSUMER CENTRIC: AI’s core benefit should be to intelligently centre and connect a fragmented digital ecosystem around the consumer.  AI will be the most effective model to distribute information to consumers -  upstream and downstream.  We will see more B2B chain collaboration automation in the next 12 months.
  1. START SAFE: The base has to be a safe, controlled, trusted platform.  Industry standards in China will need to rapidly develop to facilitate better automatic and intelligent marketing dialogue.  For marketers AI needs to be project that your board discusses.  Consider how you would benefit from core centralized management.  The prize is large-scale, high efficiency, low risk consumer dialogue.
  1. UNDERSTAND: AI marketing is based on the understanding of consumers. The recognition of consumer scenarios. This means you must enrich your existing customer data and invest in best practice data management.

AI marketing is going to become an inherent component of B2B2C platform architecture.  The data it uses and collects has huge potential to create value through closer connections as well as better ROI.

AI
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