JALCARD and NTT DATA use Azure for a 1.7X uplift in purchase rates
JALCARD offers a unique service combining credit cards and Japan Airlines’ frequent flyer program. With NTT DATA’s LITRON® Multi Agent Simulation (LITRON MAS) and Azure OpenAI, the enterprise conducted group interviews using AI personas generated from clustered member data to reveal the deeper psychology behind customer behavior. Group interviews using AI personas produce a 1.7-fold increase in purchase rates, boosting competitiveness through data-based marketing measures. Subsequent sales promotions based on the results saw a 1.7-fold increase in purchase rates.
- Agent or tool
- Azure OpenAI
- Topic
- Sales & Marketing
- Reported on
- Case study (Microsoft)
- Added
- 2026-11-11
Why it matters
Sales and marketing run on research, lists and follow-ups. Agents are starting to take on that groundwork, freeing people for the conversations that actually close deals. It is one of 613 sightings filed under Sales & Marketing on Agent Sightings (number 369 by interest), and one of 31 involving Azure OpenAI.
How you could try it
Here is a reusable prompt, written by us in our own words, that captures the task. Paste it into Azure OpenAI or any similar agent and adjust the details to your situation.
I want an agent to do the research and drafting for this sales or marketing workflow, and stop for my approval before anything is sent. The tool in the source case was Azure OpenAI.
Tip: Start small: run it once on a low-stakes example, read what the agent did, and only then let it run on real work.
Source
Read the original first-hand account on Case study (Microsoft): https://www.microsoft.com/en/customers/story/25246-jalcard-azure. Our summary is a paraphrase; details are in the source.
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