How to Achieve Effective Personalization of the Marketing Mix with AI

Original article was published by Lazarina Stoy on Artificial Intelligence on Medium

1. Product

Content is king in digital marketing. Cognitive technology, can now both assist with content creation and sketching out a content strategy to help businesses fulfill the 50–30–20 golden rule of content:

  • 50% — trending
  • 30% — educational and relevant
  • 20% — sales

Through implementing data mining, opinion mining, and sentiment analysis, AI can discover and recommend trending content for the highest engagement. Using data analytics and NLP-AI, services can now also consult for optimal titles, captions, and tags to ensure your company’s sale posts sound organic and are click-worthy.

AI-based content strategy assistance saves time and provides tangible results.

The potential to search quickly through public information provides insight into engagement and sentiment patterns on a mass scale. Something market researchers have been attempting since marketing’s early days can now be done without extensive, time-consuming, and expensive consumer behavior measurement through intelligent agent technologies.

Staggering that this information is now at the tip of the fingers of those, working with AI, tightly packed in Excel sheets after running the software through the identified as key for the business data reference points.

What about non-digital products?

The technology is IoT and the tool is M2M (machine-to-machine) communication. Conversations are increasingly being held about the commercial personalization of products — a future, where screens can be projected onto any object.

In the present, geo-networks and space are being used by Google to predict traffic of connected devices. Space analytics can map heat-zones of consumer spaces to better understand how spaces and devices in stores can become more responsive to consumer desires. The same can be done for conventions and even outdoor events through drones and real-time analytics.

Data collected from wearables can also be used for product personalization. Attitudes towards wearable technology influence usage frequency and interaction, which can help in product tailoring and market segmentation.