We are well beyond addressing a whole audience segment and into the era of individualization. The first step towards this is Persona segmentation. A high-level clustering of audiences based not on their demographics and purchase pattern but also on their behaviour (using propensity scores based on time, content, offer, channel and location) and influence (both social and real world) characteristics is what we call as persona segmentation.

Once these persona segments have been defined using specific those parameters, new age automation systems should auto-fit audience data sets against them using machine learning algorithms and/or artificial intelligence instead of going purely by the marketer’s gut instinct, constantly learning and tweaking these groupings along the way.

It is of note that even within the same brand, persona segments vary based on the market, culture and audience behaviour. As a result, identifying persona segments and targeting them contextually on the right channel to achieve sales attribution, is key for the brand which should be constantly validated and updated by using machine learning.

At any point of time, a brand may have up to 4 or 5 persona segments. Of these, the first three segments are usually the primary target audience which should be constantly refined using machine learning and artificial intelligence algorithms leveraging deep learning techniques to engage the audience in a meaningful manner.

Resulticks, our real-time marketing automation platform enables brand marketers to define their persona segments and validates that with the data sets to auto-suggest the groupings and also score at the individual audience level.