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Proof B Mixed signals

JPMorgan Chase

AI-generated marketing copy

IndustryBanking, insurance & fintechLeverAcquisitionFamilyGenerationImplementationMartech platformStageconsideration
Pattern proven in 8 industries still untouched in Media & entertainment, Travel & hospitality, Food & beverage +4 See the pattern map
jusqu'a +450%
Click-through rate lift on the AI copy (pilot), against 50 to 200% for human copy
"as high as a 450% lift in click-through rates" S2

In 2019, JPMorgan Chase signed an enterprise-wide 5-year deal with Persado to generate its marketing copy with AI, after a pilot showing up to +450% click-through rate against 50 to 200% for human variants.

Key points

  • Marketing copy (headline, body, CTA) generated and optimized by AI.
  • Via the Persado platform, on email, display, and push.
  • Pilot: up to +450% click-through rate against 50 to 200% for human copy.
  • Evidence B, living status mixed signals.

Objective

Increase the yield of Chase's direct marketing campaigns (Card, Mortgage, personal banking, home lending, wealth management) by entrusting the writing and optimization of copy to an AI engine rather than to marketers' judgment alone.

The deployment

Chase uses Persado's platform to generate the headlines, body copy, and calls to action of its direct-response campaigns. The engine starts from a base of words and phrases tagged by emotional charge, produces many variants, tests them in real delivery, and favors the wordings that perform. The partnership began with a pilot in 2016 on the Card and Mortgage businesses, then was extended in 2019 by a five-year enterprise-wide deal. In the pilot, the copy produced by Persado showed up to 450% lift in click-through rate, where human-written variants sat in a range of 50 to 200%.

Results Proof B

jusqu'a +450%
Click-through rate lift on the AI copy (pilot), against 50 to 200% for human copy
"as high as a 450% lift in click-through rates" S2

Pilot figure published in Persado's official press release (vendor, interested source) and picked up by name in trade press (Marketing Dive, Banking Dive). It is not an audited financial result, but several sources agree on the same figure and the same scope.

How it works

Inferred typical approach

The internal detail is not public. Here is a proven approach that leads to the same result, to adapt to your stack.

brief et contraintes de marquevariantes de copyboucle d'optimisation Donnees d'audience et decampagne Chase Marketeurs Chase (brief,garde-fous) Moteur de generation etd'optimisation de message Persado Motivation AI Email, display, push,creatives digitales Taux de clics etconversions par variante

The stack in detail

How it runs, concretely

For ops teams
CadencePer campaign, with an ongoing optimization loop on variant performance.
Operated byChase's marketing and growth team, interfacing with the Persado platform.
  1. 1
    Brief and framing marketing

    Marketers define the offer, the audience, and the brand and compliance guardrails.

  2. 2
    Variant generation AI

    Persado produces many wordings (headline, body, CTA) from its base of words tagged by emotional charge.

  3. 3
    Delivery and testing marketing / platform

    The variants run in real delivery on email, display, and push.

  4. 4
    Optimization AI

    Per-variant performance flows back into the model, which favors the winning wordings for the next round.

The signal that drives it

The click-through and conversion rate per message variant. Without enough exposure volume, the engine cannot statistically separate the wordings.

How your customers perceive this type of use

Sourced studies

Un ecart net separe les annonceurs des consommateurs : 77% des annonceurs voient l'IA positivement contre 38% des consommateurs (Yahoo/Publicis, 2024). Les mesures implicites confirment le rejet declare : en EEG, les pubs generees par IA produisent une activation memorielle plus faible que les pubs traditionnelles et sont decrites comme agacantes, ennuyeuses et confuses (NIQ, 2024). La disclosure a un effet ambivalent : elle augmente fortement la confiance quand elle est remarquee (Yahoo/Publicis), mais 27% des jeunes consommateurs disent faire moins confiance a une entreprise dont la pub est creee par IA (IAB, 2024).

77% vs 38%
Annonceurs qui percoivent l'IA positivement, contre 38% des consommateurs (2024)
72%
Consommateurs qui estiment que l'IA rend difficile de savoir quel contenu est authentique (2024)
+96%
Lift de confiance globale envers l'entreprise quand la mention IA d'une pub est remarquee (avec +47% d'attrait de la pub et +73% de credibilite de la pub) (2024)

Acceptance conditions

  • Une disclosure visible : quand la mention IA est remarquee, la confiance globale envers l'entreprise augmente de 96% (Yahoo/Publicis 2024)
  • Une qualite visuelle suffisante : les visuels IA de basse qualite augmentent l'effort cognitif et distraient du message (NIQ 2024)

Red lines

  • Le contenu IA non declare puis identifie : 72% des consommateurs disent que l'IA rend l'authenticite difficile a etablir (Yahoo/Publicis 2024) et les marques utilisant des pubs IA sont plus souvent jugees inauthentiques ou non ethiques par les consommateurs que par les dirigeants (IAB 2024)
  • Les mannequins et personnes generes par IA : 46% des consommateurs n'en veulent pas dans la publicite, l'inquietude premiere etant les standards de beaute irrealistes (Attest 2025)

Sources: Yahoo / Publicis Media (terrain Ebco) 2024 · IAB (avec Attest) 2024 · NIQ (NielsenIQ) 2024 · Attest 2025

See full acceptance: by country, by use, by generation

How to replicate

Inference, not sourced

Data prerequisites

  • Campaign history with per-variant performance
  • Sufficient audience volume to test statistically

Org prerequisites

  • Brand and compliance validation process compatible with generated variants
  • Acceptance of letting a model write the copy

Possible stack

  • Persado
  • Phrasee
  • Jasper or another marketing NLG
  • Native A/B testing of the emailing platform
Team to operate1 CRM/acquisition lead + 1 marketer per channel + compliance validation; no data scientist required

The plan, step by step

  1. Step 1
    Choose a high-volume channel (promotional email) and establish the performance baselineDeliverable: Per-variant performance history + defined test audience
  2. Step 2
    Frame the brand and compliance guardrails for generated wordings (essential in banking)Deliverable: Validation rules approved by compliance
  3. Step 3
    Have the platform generate the variants from the brief (offer, audience, constraints)Deliverable: Set of approved variants ready to deliver
  4. Step 4
    Test in real delivery against human copy on the same audienceDeliverable: CTR and conversion lift per variant, statistically separated
  5. Step 5
    Extend to the next channels and products and industrialize the brief-generation-validation loopDeliverable: Process in place with the ongoing optimization loop

First step: Choose a high-volume channel (promotional email) and test generated variants against human copy on the same audience.

Sources

  1. S1 JPMorgan Chase Announces Five-Year Deal with Persado For AI-Powered Marketing Capabilities Interested party persado.com · 2019-07-30 · accessed 2026-07-11 archive pending
  2. S2 JPMorgan Chase inks 5-year deal to generate marketing copy via AI Established press marketingdive.com · 2019-07-30 · accessed 2026-07-11 archive pending
  3. S3 JPMorgan Chase bets on AI to generate marketing copy Established press bankingdive.com · 2019-07-31 · accessed 2026-07-11 archive pending