Python/STAN Implementation of Multiplicative Marketing Mix Model, with deep dive into Adstock (carry-over effect), ROAS, and mROAS
This project implements a multi-floor hotel network with VLANs, OSPF routing, DHCP, and secure SSH access. It features inter-VLAN routing, wireless connectivity, and port security using Cisco Packet Tracer.
Multiple CCNA Labs
A complete end-to-end data analytics project analyzing marketing campaign performance across multiple channels (Search, Social, Email, Display). The goal is to measure campaign effectiveness, optimize spend, and improve ROI.
Google GeoX R package hand on training for calculating ROAS
Configuration of inter-VLAN routing, point-to-point Layer 3 connections, and testing connectivity between VLANs and the internet using Cisco Packet Tracer.
This repository provides open-source best practices for for conducting geographic randomized controlled trials (Geo RCTs) for measuring incremental sales effect of advertising cammpaigns. It includes details on one design type in particular, a multi-armed stepped experimental design that has particular advantages in terms of statistical strength.
Tkinter GUI to calculate key SEO & social metrics—CTR, clicks, impressions, CVR, avg. conversion value, ROAS, reach, and engagement—with tabbed UI and copy-to-clipboar
An analytics project that combines Google Ads + Meta Ads data and translates it into finance metrics.
This project is an ebook I developed shortly after my first work experience, where I applied my knowledge of Meta Ads products. It covers essential concepts, strategies, and insights to effectively leverage Meta Ads for advertising success.
ROAS Calculator - Digital Marketing Team Top Coach Indonesia
pymc implementation of the MMM with simulated data
📊 Analyze marketing campaign performance using Power BI and SQL. Track key metrics to optimize ROI and improve customer acquisition strategies.
Анализ эффективности рекламных кампаний и проверка корректности атрибуции пользователей. Проект включает работу с маркетинговыми данными: установки пользователей, рекламные расходы, доходы и каналы привлечения.
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