Synthetic Users — the summer of 2023 and the road ahead
We’ve been heads down building. Listening to our customers and building. Below are some of our thoughts as we’ve been in the thick of it.
Our job really boils down to: turning your negative feedback into positive
What we need is negative feedback. That tap in the back feels good, but it does not allow you to correct course. Unfortunately we don’t get that much negative feedback — so yes, we might just be getting some things right.
Learning about our real vs ideal customer profile
We thought we would start with SMEs but it’s the large corporates that are feeling the pain of how user research is conducted. It is the research groups with increasingly tighter budgets and timelines that wake up in the morning and feel the pain of doing research without recourse to tools that would profoundly accelerate their process.
Who cares pays
We were talking to an investor who mentioned the hierarchy of needs. Most startups don’t prioritise research because by virtue of their nature they don’t see risk mitigation as a priority. The priority is to build and learn and build some more. Risk is part of their DNA.
This means our initial hypothesis was wrong. It will take some work to become the Canva of research, something we were assuming we would be, right from the start. By putting Synthetic users out there we learned this. It’s the larger companies that need us more. The larger corporates are willing the pay first.
With large corporates we:
Continue to prove that we have organic / synthetic parity in many dimensions and that our interviews are the best.
Democratize research within the organisation. Make it easy for teams to share and collaborate on top of Synthetic Users.
For smaller companies and startups we need to:
We know smaller companies don’t do enough research. We have the data to prove it. How do we change this? That is our mission because in doing so we change the way products are made.
Dramatically lower the cost of user testing.
Ensure Synthetic Users is a part of the existing product development journey and not a separate branch. This means a plug and play UX strategy.
Progress on the synthetic organic parity:we came out on Science and bragged about it sufficiently. It was preceded by an article in the Atlantic. We’ve also been running our parity research in order to ensure we are indeed providing the best interviews and insights. We will continue to do this in parallel to ensure we are always on the right track.
Cost: an organic interview can cost from 50 to 1000USD (expert participants in narrow fields for example), depending on the nature of the interview. Our interviews are great value for money. From 3 to 5 USD each. Mind you, we are testing.
Plug and play: Our tool needs to be easily integrated into the existing product development process and tools used by product teams, rather than being a separate initiative that companies use only occasionally.
We are experimenting with plug and play features to make Synthetic Users usable throughout the entire product development journey. This includes ingesting customer support tickets and guiding the customer journey.
To achieve this, we need to allow for more dialogue between our customers and Synthetic Users. Without this, our tool will likely only be used occasionally, rather than on a constant basis like tools such as Figma. Our goal is not just retention, as we already have that, but instead a constant and consistent usage of our tool.
On the quality of our interviews and their readability
Going from who to why is how Synthetic Users will add value. But the who is important as we gain trust with our customers. Giving definition to Synthetic users allows for better glanceability and aids in building trust in our platform.
The big five for our Synthetic Users
Our synthetic users are all different. They are all unique. At the same time, they, just like us, all fall into the same big five personality traits.
At the core of our understanding of personality lies the Five Factor Model (FFM), more commonly known as the "Big Five" personality traits. As we strive to understand the complex nature of individuals, in order to better synthesise them, we turn to this scientifically tested framework, applying it within our platform.
Openness to Experience: This trait reflects how inventive and curious someone is versus being consistent and cautious. It's an essential aspect of how we engage with new ideas and experiences.
Conscientiousness: This highlights how efficient and organized a person is compared to someone who might be more easy-going or careless. It plays a crucial role in our ability to set and achieve goals.
Extraversion: This trait helps us understand if a person is outgoing and energetic or more solitary and reserved. It greatly influences social interactions and how we connect with others.
Agreeableness: This is about how friendly and compassionate we are versus being challenging and detached. It guides our relationships and how we interact with those around us.
Neuroticism: This helps us gauge if a person is sensitive and nervous versus being secure and confident. It affects our emotional stability and overall well-being.
At Synthetic Users, we recognize that everyone is unique, but these Big Five personality traits offer a concise way to understand and predict how different personalities might behave. By embracing this widely accepted model, we can categorize and model user behavior with greater insight and clarity.
While the Big Five is comprehensive and backed by extensive research, it may not encompass all the nuances of personality or cultural differences. Still, it serves us well, as a robust and reliable method for our purposes and our ever-evolving platform.
Products that build products
Our current focus with Synthetic Users (as of the summer of 2023) is to deliver the best user and market research at the lowest cost. To achieve this, we are fine-tuning our architecture for better product and go-to-market outcomes. We want to understand how successful products are created and tweaked, and which insights lead to better outcomes.
However, improving the quality of our interviews and insights is not our end goal. Our ultimate goal is to create a tool that builds products based on outcomes. To accomplish this, we need to invest more in multimodality. We envision a tool that defines the audience, identifies their needs, proposes solutions, runs ads to assess a prototypical product-market fit, and iterates on the edge between mostly synthetic product development and some organic feedback.
The road ahead towards winter
Dynamic scripting allows for more diversity in the results as it is a script generated by the product of your research goals.
Custom scripting allows you to feed your own script to your Synthetic Users. Our customers
Surveys: This is a no brainer. The quality of our synthetic users makes this feature a low hanging fruit.
Customer journey interviews: Our interviews are amazing. Beyond amazing. But we are underperforming on the customer journey queries. We are changing this and adding another type of interview to address this.
Richer reports: Synthetic Users are taking you on a journey from qualitative to quantitative data. We all start with the first but ultimately just want the latter. The comfort (we wouldn’t use the word certainty) and actionability numbers provide. All this to say that our reporting is getting richer.
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.