Inspiration
We were job seekers. We struggled to find and collect many job opportunities in several scattered webs and forums and chat groups (Yes, In Indonesia we also use chat group for sharing info about job opportunity). From most of these things, some info not matched with us and the rest is incomplete info.
On the other hand, recruiters can't rely on sharing job opportunities with relatives, co-workers or friends. It's cheap, spread widely but not reliable because we can't track who interest in our vacancy. We can't directly search with our custom criteria.
On this day, where everything is AI and Automation, both problems still troublesome. So we created a chatbot called VacanSy to help vacancy easier.
What it does
VacanSy will respond to every message you send. It will ask your name and what can we help you with. The chatbot will understand your request and respond to you immediately. The scenario VacanSy has is:
- Recruiters can search for candidates based on their preference.
- Recruiters can post a vacancy with just copy-paste from default description, we will auto categorized it.
- Job seekers can search for opportunities based on their preference.
How we built it
We split our team into 2 division:
- PoC division
- Create high-level concepts, find and prototyping with technology to be used.
- Conversational division
- Create several flows of conversation and implement it to our bot
We want to create a meaningful product as soon as possible, so we focus on how the user interact with our bot. We choose Facebook messenger because it's easy to test and deliver to users. We research how the conversational UX design different from UX in an application.
Accomplishments that we're proud of
In a few days, we have created a chatbot that can follow up and understanding the context of the conversation. The chatbot will represent us as a functional system for gathering and managing job vacancies easier.
What we learned
We learn how the conversational UX design different from UX in an application. It's more expressive and makes us thinking several steps further about what will user type to our bot? Will our bot understand those words?
We also learn how to integrate the chatbot with our backend to create a more personalized conversation.
What's next for
- Creating a database to save job vacancy information
- Saving session for the same person
- Add local language support
- Launch the chatbot to public
Credit
Built With
- dialogflow
- facebook-messenger
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