P
p-sharpe
Guest
Hi HN, we’re Patrick and James! Artificial Societies (https://societies.io) lets you simulate your target audience so you can test marketing, messaging and content before you launch them.
Here’s a quick product demo: https://www.loom.com/share/c0ce8ab860c044c586c13a24b6c9b391?...
Marketers always say that half their spend will be wasted - they just don’t know which half. Real-world experiments help, but they’re too slow and expensive to run at scale. So, we’re building simulations that let you test rapidly and cheaply to find the best version of your message.
How it works:
- We create AI personas based on real-world data from actual individuals, collected from publicly available social media profiles and web sources.
- For each audience, we retrieve relevant personas from our database and map them out on an interactive social network graph, which is designed to replicate patterns of social influence.
- Once you’ve drafted your message, each experiment runs a multi-agent simulation where the personas react to your content and interact with each other - these take 30s to 2 minutes to run. Then, we then surface results and insights to help you improve your messaging.
Our two biggest challenges are accuracy and UI. We’ve tested our performance at predicting how LinkedIn posts perform, and the initial results have been promising. Our model has an R2 of 0.78 and we’ve found that “message spread” in our simulations is the single most important predictor of actual engagements when looking at posts made by the same authors. But there’s a long way to go in generalising these simulations to other contexts, and finding ground truth data for evals. We have some more info on accuracy here: https://societies.io/#accuracy
In terms of UI, our biggest challenge is figuring out whether the ‘experiment’ form factor is attractive to users. We’ve deliberately focused on this (over AI surveys) as experiments leverage our expertise in social influence and how ideas spread between personas.
James and I are both behavioral scientists by training but took different paths to get here. I helped businesses run A/B tests to boost sales and retention. Meanwhile, James became a data scientist and, in his spare time, hooked together 33,000 LLM chatbots and wrote a paper about it (https://bpspsychub.onlinelibrary.wiley.com/doi/pdfdirect/10....). He showed me the simulations and we decided to make a startup out of it.
Pricing: Artificial Societies is free to try. New users get 3 free credits and then a two week free trial. Pro accounts get unlimited simulations for $40/month. We’re planning on introducing teams later, and enterprise pricing for custom-built audiences.
We’d love you to give the tool a try and share your thoughts!
Comments URL: https://news.ycombinator.com/item?id=44755654
Points: 51
# Comments: 33
Here’s a quick product demo: https://www.loom.com/share/c0ce8ab860c044c586c13a24b6c9b391?...
Marketers always say that half their spend will be wasted - they just don’t know which half. Real-world experiments help, but they’re too slow and expensive to run at scale. So, we’re building simulations that let you test rapidly and cheaply to find the best version of your message.
How it works:
- We create AI personas based on real-world data from actual individuals, collected from publicly available social media profiles and web sources.
- For each audience, we retrieve relevant personas from our database and map them out on an interactive social network graph, which is designed to replicate patterns of social influence.
- Once you’ve drafted your message, each experiment runs a multi-agent simulation where the personas react to your content and interact with each other - these take 30s to 2 minutes to run. Then, we then surface results and insights to help you improve your messaging.
Our two biggest challenges are accuracy and UI. We’ve tested our performance at predicting how LinkedIn posts perform, and the initial results have been promising. Our model has an R2 of 0.78 and we’ve found that “message spread” in our simulations is the single most important predictor of actual engagements when looking at posts made by the same authors. But there’s a long way to go in generalising these simulations to other contexts, and finding ground truth data for evals. We have some more info on accuracy here: https://societies.io/#accuracy
In terms of UI, our biggest challenge is figuring out whether the ‘experiment’ form factor is attractive to users. We’ve deliberately focused on this (over AI surveys) as experiments leverage our expertise in social influence and how ideas spread between personas.
James and I are both behavioral scientists by training but took different paths to get here. I helped businesses run A/B tests to boost sales and retention. Meanwhile, James became a data scientist and, in his spare time, hooked together 33,000 LLM chatbots and wrote a paper about it (https://bpspsychub.onlinelibrary.wiley.com/doi/pdfdirect/10....). He showed me the simulations and we decided to make a startup out of it.
Pricing: Artificial Societies is free to try. New users get 3 free credits and then a two week free trial. Pro accounts get unlimited simulations for $40/month. We’re planning on introducing teams later, and enterprise pricing for custom-built audiences.
We’d love you to give the tool a try and share your thoughts!
Comments URL: https://news.ycombinator.com/item?id=44755654
Points: 51
# Comments: 33