Hello fellow organic users (if you're reading this we hope you are organic).
Yes, we have created a new product category
The market will tell you whether you have created a new product category or not. It turns out we have. How it feels? It feels like a lot of blue ocean ahead that we need to occupy as quickly as possible by ensuring you get real value out of our Synthetic Users.
As product people, we can (and like to) argue that it is our ability to collectively go from needs to ideas and ideas to products — that has shaped our civilization. We have created processes to accelerate those phases. We’ve mechanized innovation for humanity’s benefit. We are now entering a new era where we simulate to accelerate. Where going from needs to insights and ideas is becoming more affordable. Especially if you use our synthetic users.
Continuous feedback loop through amazing synthetic research
A continuous feedback loop between users and creatives needs to inevitably be powered by great research leading to actionable insights.
Synthetic Users can help in both but as a startup our lack of resources forces us to make choices, the quality of the interviews and insight is paramount to us and that is our focus over providing our users with a way to manage all of their research..
To this last point, a continuous feedback loop is a company strategy problem. High performance teams have the product discovery and product delivery duality baked in. It’s not a problem we’re here to solve but rather a reality we’re here to enable.
Our UX is a reflection of your product discovery journey
The above is based on our product discovery journey because that’s what we are here to accelerate. Another way of looking into it is as the embodiment of a lean hypothesis.
In order to undergo a product journey it helps to have a map with some key reference points. Something like:
We feel there is an A audience that has a B problem. We have a C solution. We will know we’re right when X happens.
Product discovery is a continuous iterative process defined as the journey from needs to insights and ideas. (Then through product delivery, ideas become products.)
Continuous product discovery is the ability to perpetually address customer needs. In order to do so we need to quickly and cheaply access potential users. In our experience as product creators this has not been easy so we decided on a completely different approach. We build users from the ground up through the LLM. We synthesize them.
At the core of our existence lies language. The ability to create and convey stories. Good products translate very clearly needs into solutions. Great product teams do this way before they start creating screens or prototyping. Large language models help us accelerate this process.
It is with this in mind that we’ve built our Synthetic Users Experience.
These: audience, problem, solution are connected variables. If you change one, the others will change. It can get very complex very quickly (3 pivots create a lot of mechanical complexity). AI coupled with your human instinct and that of your teams, will allow you to discover new insights. Your job will then be how to respond to those insights with the right product features.
Doubling down on desirability
We at Synthetic Users have started by testing desirability. One of our first instincts was to actually start testing usability. Plug Figma prototypes straight into the model and get feedback based on desired outcomes. But we’re still a few months away from being able to do this and as we started validating our assumptions about synthetic users we realized the right approach was to start with testing desirability.
Much before we test usability, feasibility, viability or sustainability — Desirability measures our audience’s appetite and visceral reaction to an idea. It informs us if we are addressing the needs of an audience. It’s at the beginning of the product discovery process.
Desirability is our first port of call. As a hypothesis it already contains the necessary ingredients to seed the research journey. how it works, what it costs, usefulness… It’s very aligned with a jobs to be done approach: I desire something because I want its outcome. How the outcome is achieved can very well be described and tested with words rather than screens or images.
Synthetic Users: Merging Qualitative and Quantitative Research, in seconds.
At Synthetic users we are blurring the lines between qualitative and quantitative research. Here's how we are going about this transformative approach, and what it means for the future of user experience and market research but more importantly to the future of business.
Large language models (LLMs) like GPT-4 serve as powerful "vibes engines," empathizing with diverse groups and generating contextually relevant content. Their applications span market research, customer support, user experience design, and mental health support, offering invaluable insights and personalized experiences. While not infallible sources of truth, LLMs enable creativity, personalization, and connection within the realm of human language.