just words

Optimize your product's copy for user growth

Marketing

Growth Hacking

Developer Tools

Visit WebsiteSee on Product Hunt

Hey all, we’re Neha and Kunal, co-founders of Just Words (https://justwords.ai). We help companies gain users through product copy optimization across any app surface or webpage, using inferences from past performance data. During our time at Twitter & Pinterest, we observed that small content changes would lead to massive growth gains. However, coming up with the copy, and optimizing different variants across users would take us several months. There was no methodical way to optimize copy on the fly and use what we learned for subsequent iterations. The entire process was managed ad hoc in docs and spreadsheets. In our experience, the main challenges with copy optimization are - (1) Engineering effort: Copies are hard-coded, either in code or config files. Every small change requires redeployment of the app. To run an A/B test, engineers must write if/else logic for each variant. As a result, it would be a 2-week project on an engineer’s roadmap, and companies are only able to prioritize a small number of changes a year. (2) Fragmented content: There is no copy repository, so companies lose track of the history of changes on a particular copy, and learnings from past experiments. With no systematic view, teams make copy changes based on “vibes”. There is no way to fine-tune next iterations based on patterns obtained from previous experiments. (3) Lack of context: Companies either test 1 copy change at a time for all users, or rotate a pool of copies randomly. In an ideal world, they should be able to present the best copy to different users based on their context. We built Just Words to solve these problems through 3 main features: (1) No-code copy experimentation: You can change any copy, A/B test it, and ship it to production with zero code changes. (2) Nucleus of all product copy: All product copy versions across the product are in one place. We also built integrations to copywriting and experimentation tools like statsig, so the entire workflow can be managed in one place. With this CMS, we draw patterns across experiments to infer complex learnings over time and assist with future iterations. (3) Smart copy optimization: We run contextual Bayesian optimization to automatically decide the best-performing copy across many variants. This helps product teams pick the winner in a short amount of time with one experiment. We'd love your feedback, especially if you are in growth/marketing. We'd also like to invite you to our beta pilots if your product has >2K monthly users: https://forms.gle/Q3xthubQFfZcXZe88