“Copy” in this context means short-form content such as landing page titles or email subject lines. Small and seemingly insignificant changes to these can lead to massive growth gains. We observed this on many occasions while working at Twitter. Tweaking a push notification copy from “Jack tweeted” to “Jack just Tweeted” brought 800K additional users to Twitter.

However, coming up with the copy, testing it, and optimizing different variants across users would take us forever—sometimes 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.

After experiencing this pain at Twitter, we observed the same problem at other companies like Reddit. After years of this, we are convinced that there’s enough evidence for this pain across the industry.

In our experience, the main challenges with copy optimization are:

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, one copy optimization becomes a 2-week project on an engineer’s roadmap, and companies are only able to prioritize a small number of changes a year.

Fragmented content: There is no copy repository, so companies lose track of the history of changes on a particular string, learnings from past experiments, and their occurrences across the product. With no systematic view, product teams make copy changes based on “vibes”. There is no way to fine-tune next iterations based on patterns obtained from previous experiments.

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:

No-code copy experimentation: You can change any copy, A/B test it, and ship it to production with zero code changes. All copy changes made in our UI get published to a dynamic config system that controls the production copy and the experimentation logic. This is a one-time setup with 3 lines of code. Once it’s done, all copy changes and experiments can be done via the UI, without code changes, deploys or app releases.

Nucleus of all product copy: All product copy versioning, experiment learnings, and occurrences across the product are in one place. We are also building integrations to copywriting and experimentation tools like statsig, so the entire workflow from editing to shipping, can be managed and reviewed in one place. By storing all this in one place, we draw patterns across experiments to infer complex learnings over time and assist with future iterations.

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, instead of running many sequential A/B tests.

We are opening up our private beta with this launch. Our pricing is straightforward - a 60-day refundable pilot for $2000 (use discount code: CTJW24), for one of the following use cases: landing pages, push notifications, email subject lines, or paid ad text. We will show visible growth gains to give you a substantial ROI on your pilot and refund the amount if we fail to deliver on it. We are inviting companies with >2K monthly users to try us out here: https://forms.gle/Q3xthubQFfZcXZe88. (Sorry for the form link! We haven’t built out a signup interface yet because our focus is on the core product for the time being. We’ll add everything else later.)

We would love to get feedback from the HN community on (1) the flavor of problems you have experienced in the world of copy changes, (2) how your or other companies are solving it (3) feedback on the product so far, or (4) anything you’d like to share!