Morgenland Teppiche is a rug business specializing in high-quality, hand-knotted oriental carpets. Located in Hamburg, it is a hub for rugs flowing all around the globe to from Hamburg, Germany Morgenland serves customer from 9 different countries and is one of the trusted shops in Germany. Morgenland is build on top of Plenty Markets CRM

I worked as a backend developer here (40 hours/week). I was assigned various works and did independent research to fix the company day to day workflow and improve the company's daily workflow and implemented cloud computing with AWS.

The entire company process was extremely slow.

Everything was handled in excel files. 20GB of excel file

The website was static

Backend was poor like US and UK had the same currency rate

Sync process that was often dragging the sales process down

No user behaviour study

Little and outdated analysis of sales and orders

Very poor traffic handling capacity

Poor Cross selling strategy and its implementation

Poor and slow search and filters features

Poor organization documentation and knowledge base

After a year I managed to solve many of their problem. They just had the best off season for their standard and as of the time of this writing. I think they are on their way to have their best seasons. We are often using data driven descision and making them to move their descision making towards data took a lot of persuading.

Here is how we have changed

3 seperate databases now.

Organization Knowledge Base is now setup in Notion

User behaviour analysis is now implemented in the backend

Rest API and dashboard is implemented to empower data driven descision.

Cross sellings are now done based on user cart analysis and by using Machine Learning algorithms

Search and filters are now based on latest research on information retrieval systems and full text search with very high throughput.

Automation: Daily and frequently repeating tasks are now autmated

We setup cloud based solution in AWS for traffic related problems.

Seperate Database for each usecase: After careful inspection, our access pattern included the three following kind

2. Organizational Knowledge Base: Knowledge base for organizational knowledge was implemented in Notion which utilizes PARA method

3. Rest API and dashboard: We made rest api using Django, Django Rest Framework, and also utilized celery and flower for background task processing and automation needs.

4. Cross Selling: Now powered by user behvaviour. We utilized matrix factorization and shopping cart analysis with both explicit and implicit feedbacks.

5. Search and filters: Search and filters are now 100 times fast from 6s to 0.6s in P99. [Nginx logs report]. We also used postgres's full text search, reduced joins needed and utilized JSONB columns heavily.

6. Automation: Celery was used for automation pruposes and we made views for automating manual tasks

7. Insights Collection: We are now collecting insights from user behaviours on where can we improve our server. I did SQL aggregations and implemented logs parsing tricks to find opporunties

8. AWS: Now the whole infrastructure is build on AWS and we have build a wrapper server around the old CRM system extending its features. The system is there now as well but not much of pain right now. We use

Here are some of technical learning I gained during my time in Morgenland