inbox insights

Takes large sets of email marketing data and displays it in an easy to read format. in order for businesses to better addresses there marketing strategy failures.

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Inspiration

getting spam emails which never convert me to purchase

What it does

It takes a user csv upload of raw data from a site such as klaviyo partitions this data into different tables storing it first into an S3 bucket raw data folder and next uses aws Glue to transform and load the data into a processed folder with s3 bucket.

next it uses aws glue crawler to create tables then Athena to query the data and store all data into separate csv files with another folder.

this queried data is then pushed to Google Sheets where users can finally see there email marketing strategy at work in a more digestible form.

How we built it

front end: flask and html + css hosted on ec2 instance

backend: using lambda functions s3 buckets aws glue and glue crawler google api

Challenges we ran into

many challenges with lambda not triggering among other lambda problems

also layers libraries downloading being too large

Accomplishments that we're proud of

setting up end to end data processing and outputting it to Google Sheets

What we learned

learning lots about AWS tools and leveraging them

What's next for inbox insights

having bedrock analyst data and give insights improve front end for user

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