Marketing ops · Production

Holiday Extras rolls out ChatGPT Enterprise across every team, boosting productivity by 500 hours weekly

The problem

Holiday Extras' single marketing team must produce copy in multiple languages for many European markets, non-technical employees lack data fluency for self-serve analytics, and customer support faces challenges of scale.

Workflow diagram · grounded in source
1
Multi-language content localization
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“ChatGPT Enterprise plays a critical role in localizing copy across different locales, which was previously very time-intensive. "Tasks that would have taken weeks before only take hours now," Reuther said.”
2
Non-technical CSV analysis
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“People who are less technical or data-literate are able to upload CSVs and identify trends, something they never could have done before.”
3
SQL query acceleration
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“using ChatGPT Enterprise has allowed them to write queries 80% faster”
4
Engineering thought partnership
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“Junior engineers might use it as a thought partner to validate their approach, while more senior engineers use it for communication, especially in higher-stakes situations like presenting to the board.”
5
UX scoring and design feedback
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“We've built a UX Scoring GPT to help us become more metrics-driven. The GPT captures research about UI/UX principles from authoritative sources, as well as my personal guidelines and recommendations. Not only can it provide a quantified …”
6
Customer support AI bot triage
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“30% of customer service inquiries now being handled by an AI bot before getting to a human”
Reported outcome

ChatGPT Enterprise delivered over 500 hours saved per week across the company, equivalent to $500k in annual savings, with 95% weekly adoption, 92% of employees saving over 2 hours per week, code debugging times reduced by 75%, and NPS scores rising from 60% to 70%.

Reported metrics
Hours saved per weekover 500 hours
Annual cost savings$500k
weekly ChatGPT Enterprise adoption95%
Employees saving 2+ hours per week92%
Show all 9 reported metrics
hours saved per weekover 500 hours
annual cost savings$500k
weekly ChatGPT Enterprise adoption95%
employees saving 2+ hours per week92%
code debugging speed improvement75%
SQL query writing speed80% faster
customer service inquiries handled by AI before human30%
NPS score changerisen from 60% to 70%
translation task timeweeks reduced to hours
Reported stack
ChatGPT EnterpriseUX Scoring GPT
Source
https://openai.com/index/holiday-extras/
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

ChatGPT Enterprise delivered over 500 hours saved per week across the company, equivalent to $500k in annual savings, with 95% weekly adoption, 92% of employees saving over 2 hours per week, code debugging times reduc…

What tools did this team use?

ChatGPT Enterprise, UX Scoring GPT.

What results were reported?

Hours saved per week: over 500 hours; Annual cost savings: $500k; weekly ChatGPT Enterprise adoption: 95%; Employees saving 2+ hours per week: 92% (source-reported, not independently verified).

How is this marketing ops AI workflow structured?

Multi-language content localization → Non-technical CSV analysis → SQL query acceleration → Engineering thought partnership → UX scoring and design feedback → Customer support AI bot triage.

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