Persado

Persado predates the generative AI boom by a decade, and that history is its moat: it has been tagging marketing language by emotion, structure, and format since the early 2010s and correlating those tags with real campaign outcomes for banks, retailers, and telecoms. Where a general LLM writes plausible copy, Persado writes copy with a predicted performance score attached.

What we like

The empirical foundation is real. Persado's knowledge base links language choices to measured conversions across billions of customer interactions, and its methodology — generate variants, predict, test, learn — is closer to experimentation infrastructure than a writing assistant. For enterprises, the governance layer matters as much as the AI: brand voice controls and compliance workflows make it deployable in regulated industries where letting marketers paste into ChatGPT is a legal problem. Its case studies with major financial brands are among the more credible in enterprise AI marketing.

Where it falls short

Everything about Persado assumes you are large. There is no self-serve product, no published pricing, and a sales-and-onboarding cycle measured in months. The rise of capable general-purpose LLMs has also squeezed it from below — for a mid-market team, GPT-class models plus a decent testing culture capture much of the value at a fraction of the cost. Persado's edge is narrowest exactly where most companies operate.

Verdict

If you send tens of millions of messages a year and a 2% conversion lift moves real revenue, Persado deserves a pilot — the performance-data moat is genuine. For everyone below enterprise scale, it is simply not a purchasable product; build the discipline of systematic copy testing with cheaper tools instead.