### Introduction
As a Senior Product Marketing Manager, I led the development and successful launch of the AI Emporium, an innovative demo app designed to highlight Lokalise's capabilities in a real-world application. The AI Emporium is a revolutionary demo app that combines Lokalise, GitHub actions, and Nextjs to help sales teams showcase translation changes made via Lokalise on a real application instantly. This provides prospects with faster validation and an enriched experience.
### Problem
Previously, the sales team was limited to using simple "Hello World" examples during prospect demos, which lacked real-world context and usability for developers. There was a significant need for an impactful and genuine use case demo to provide a more tangible experience for prospective developers.
### **Outcome**
With the launch of the AI Emporium, the sales team is now able to succinctly demonstrate Lokalise's capabilities using tools that developers are already familiar with, bypassing the need to directly show Lokalise. This has effectively reduced the sales cycle as prospect tech teams can quickly validate Lokalise's utility and potential.
### **Tactics**
In creating the AI Emporium, I employed a blend of technical product marketing strategies, which included conducting extensive research on typical workflow processes and working closely with the Customer Success, Support, and Solution Engineering teams to design an app that aligns with our Ideal Customer Profile (ICP).
### **Market Research**
To further our understanding of the market needs, I conducted research on how other SaaS products are providing demos and investigated the typical CI/CD workflows employed by software tech teams. This invaluable data provided the foundation upon which we developed our tailored solution.
### **Sales Enablement**
To ensure the wider team was adequately prepared to utilize the AI Emporium, I spearheaded training sessions for the sales and customer success teams, providing them with quick start guides to effectively demo the app.
### Assets
1. [AI emporium lokalise demo app](https://github.com/lokalise/ai-emporium-lokalise-demo-app)
2. [How to continuously localize using GitHub Actions](https://lokalise.com/blog/how-to-continuously-localize-your-front-end-resource-files-using-github-actions/)
3. [Using GitHub Actions for Continuous Localization](https://ericsilberstein1.substack.com/p/using-github-actions-for-continuous?r=21q6j1\&utm_campaign=post\&utm_medium=web)
---
# Agent Instructions: Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.
Perform an HTTP GET request on the current page URL with the `ask` query parameter:
```
GET https://anilkumark.gitbook.io/portfolio/technical-product-marketing/lokalise-demo-app-ai-emporium.md?ask=
```
The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.
Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.