Reporting & Automation with Machine Learning
Objective
For our client Travador, we developed not only an automated reporting system for various departments, but also tools to simplify, speed up, or even fully automate daily tasks.
The main objective of the reporting project was to deliver detailed, near real-time performance metrics for sales and marketing campaigns. This included the visualization of key performance indicators (KPIs) such as conversion rates, customer acquisition costs, customer lifetime value, and return on investment (ROI).
These insights were enhanced with powerful predictive algorithms, enabling proactive adjustments and decision-making — before it was too late to act.
In addition, we built reporting tools for operational error analysis, helping to streamline and accelerate internal processes.
About Our Case Study Partner
Travador is one of Germany’s leading short-trip travel companies. They offer unique travel experiences, luxurious wellness hotels, and unforgettable weekend getaways — always paired with exclusive deals.
API & Interface Development
We began by developing an integrated database to consolidate data from multiple sources. This involved connecting to several APIs, including those from Google and Meta, ensuring high data quality throughout the pipeline. Based on this unified data foundation, we were able to apply various forecasting models to deliver predictive insights.
Database Development
In combination with Travador’s booking system, we decided to build a dedicated reporting database using MySQL. This approach minimized potential interface issues with the booking platform. To protect the production environment, we implemented a mirror system, ensuring that our ETL processes and reporting activities had no impact on live operations.
Next, we designed a custom schema to structure data from diverse sources. The main data sources included Google Ads, Google Analytics, and platforms from the Meta ecosystem. Additionally, we integrated APIs from various affiliate networks, SEO tools, and other systems over time.
Predictive Models with Machine Learning
Based on a custom data schema, we developed the core logic for the reporting system. Initially, we used pre-built solutions from AWS, but we soon transitioned to building our own prediction models, focusing on key forecasting factors such as time of day.
At that time, Machine Learning algorithms were not yet widely accessible, so much of this work was pioneering and custom-built.
The most important model was an hourly revenue forecast at the individual offer level, designed to closely track and promote daily revenue development.
We also built the system to be flexible, extensible, and scalable — and it's still in use today.
Operational Reporting
After delivering the core reports for management, sales, and marketing, we turned our attention to operational excellence.
This included building reports that identified website issues based on predefined rules, allowing team members to quickly detect and fix them. We also implemented automated alerts for special offers or important booking events.
As part of a rapid prototyping approach, we developed early versions of tools that were later fully integrated into the website — including an interactive offer map and a system for automatically generating discount codes.
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Why Us?
Broad Tech-Stack
Depending on your database system — as well as your backend and frontend setup — we can develop solutions that fit your specific needs. Our team is experienced in working with a wide range of programming languages and technologies, ensuring maximum flexibility and seamless integration.
API Expertise
We have in-depth experience with a wide range of APIs — particularly those from Google and Meta — and have already implemented numerous custom solutions using them. In principle, we're able to integrate and utilize virtually any API, adapting it to fit your specific needs.
Custom Forecasting Models
We have developed several proprietary forecasting models in the past using Machine Learning. In addition, we can enhance or extend existing systems to improve their predictive capabilities.