Personalysis: Bringing Segmentations to Life
Personas are a popular explanatory aid to bring qualitative and quantitative research data to life, especially when it comes to market segmentation. But they are time consuming to generate and require a lot of human thinking. However, we have found they can now be generated from primary data using Large Language Model AI, which takes a lot of the heavy lifting out of it.
We call this PERSONALYSIS.
- Manual persona creation is slow, shallow, and even potentially biased
- Doing this by hand is time-intensive and expensive
- It can’t be done at scale
- Personalysis uses AI to rapidly synthesize market research data into detailed, robust personas
- Brings speed, efficiency, scale and customization to persona development
- Enables affordable on-demand persona generation to bring Segmentations to Life
Almost all clients work with some form of market segmentation. So to prove the concept, from our own research data we created a values-based segmentation of the UK population. This surfaced all of the usual suspects who show up in commercial segmentations (Tech-Savvy Urbanites, Mainstream Suburban Families, and so on). We settled on 12 clusters for the persona experiment, and instructed our model to create 5 detailed personas per segment – a total of 60 ‘artificial people’ – representing different flavours and variations within a segment.
The starting point for Persona generation is always a detailed segment profile. Here is one example: Tech-Savvy Urbanites.
The segment profile is just the starting point
The client will usually have a huge amount of supplementary data on their segments. But of course, segments are also non-homogenous statistical constructs. So based on all of the available data – demographic, attitudinal, behavioural – the AI will create personas that represent the variability to be found within a segment, as well as the attributes that are shared. Here is an example of 5 auto-generated personas representing this segment, and their summary profiles. The images are AI generated too.
What happens then is that the AI will creatively expand and deepen each Persona, in line with some fairly specific criteria we have trained it in. This does depend on specific client requirements, but might typically include more lifestyle data, a week in the life, and so on. And of course the Persona comes with all Signoi’s usual metrics (such as Schwartz’s Universal Cultural Values).
Here is the expanded Persona for our Tech-Savvy Urbanite, Cameron:
As you can see, there is an unnerving believability about Cameron’s profile. But it gets better!
Using generative image software, we can even create an AI-generated mood board for Cameron, visualizing his life. Where he lives, where he works, where he goes, what he does…
By now, we may almost be starting to forget that Cameron does not really exist.
We believe this unique methodology has significant benefits.
- Personalysis leverages AI to quickly transform raw segment data into actionable, detailed customer personas at scale and depth.
- These Personas can become an essential source of interactive consumer truth and empathy that drives strategic decision making across the organization.
- Our AI methodology can therefore help make persona-based consumer insights easily accessible and affordable to unleash innovation and customer centricity.
When reviewing the personas we had generated we thought of many other random questions: what would be their taste in interior design? How do they feel about AI? What music do they like? Were their “personalities” really particularly different? And so on.
But the most significant question was really this: could the personas be used as an extrapolator or “expert witness” to generate synthetic consumer-like data, and how accurate would it be?
The short answer is that our AI Persona model does indeed appear to predict certain consumer responses to stimuli with a high degree of accuracy.
This makes Personanalysis not just a cool tool for enlivening Segmentations and other data, but a potentially ground-breaking option for testing ideas and concepts before (or even as a potential substitute) for market research.
You can read more about our results here.
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We’ll be writing more on this and other AI related subjects shortly, meanwhile please do get in touch if you found this interesting…
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