Amazon PPC doesn't perform the same way every hour of the day. That's why I like using heat map a...Amazon PPC doesn't perform the same way every hour of the day. That's why I like using heat map a...
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Amazon PPC doesn't perform the same way every hour of the day.
That's why I like using heat map and daypart analysis when auditing an account.
A campaign can look fine when you look at the overall numbers, but the hourly data can tell a different story.
For example:
→ Are we spending heavily during low-converting hours?
→ Are budgets being exhausted before the strongest hours?
→ Is there a pattern of weaker evening performance?
→ Are certain days consistently stronger than others?
→ Did something change in the account that explains a sudden performance shift?
The important part is not just finding a “good” or “bad” hour.
It's understanding why the pattern exists before making a change.
I don't want to increase or decrease bids simply because one part of the day looks weaker.
I'd rather investigate the traffic, conversion, spend, budget pacing and campaign structure first.
Don't just look at the average. Look for the pattern behind it.
📊 Superstore Sales Analysis — Complete Business Analytics Project
Turned 10,194 rows of raw retail data into a 3-dashboard Power BI system covering Sales, Customers, and Product Performance.
🔹 Main Sales Dashboard — ₹2.33M revenue tracked, 12.56% profit margin, regional & monthly trend breakdowns
🔹 Customer Analysis Dashboard — 800 unique customers segmented, top revenue drivers, repeat customer tracking
🔹 Product Performance Dashboard — 39K units sold, best-sellers vs. loss-making products flagged by category
Built end-to-end with Excel → MySQL → Power BI, this project turns raw transactional data into decisions: what's selling, who's buying, and where the money's leaking.
Tools: Power BI | Excel | SQL | Data Analysis
51 interactive visuals | 4 dashboards | Real business KPIs
📁 Full project + dataset on GitHub — link in profile
From data to business growth. 🚀
ARTHADṚṢṬI — Amazon Sales Intelligence & Business Performance System
What started as an analytics project became an opportunity to build something closer to a real-world business reporting system.
I worked with Amazon sales data and took it through an end-to-end analytics workflow:
Raw Data → Data Cleaning → Transformation → Data Modeling → DAX → Power BI → Business Insights
What I worked on
• Data profiling and quality checks
• Cleaning & transformation using Power Query
• Handling missing and inconsistent data
• Business KPI development
• Data modeling
• DAX measures
• Interactive dashboard design
• Sales, product, fulfilment & geographic analysis
The final system provides visibility into:
→ Sales & revenue performance
→ Orders and units
→ Category & SKU performance
→ Fulfilment operations
→ Monthly trends
→ Geographic distribution
→ Interactive filtering & drill-down analysis
But the biggest lesson from this project was simple:
A dashboard shouldn't just look good. It should make the underlying data easier to understand and act upon.
I’m also available for dashboard projects.
If you have Excel, CSV, or other business data that is difficult to analyze, I can help transform it into a clean, professional and interactive dashboard.
Services I can provide:
→ Power BI Dashboard Development
→ Excel Dashboard Development
→ Data Cleaning & Transformation
→ Power Query Automation
→ DAX & KPI Development
→ Business / Sales Analytics
→ Interactive Reporting Systems
Whether you need a dashboard built from scratch, an existing report improved, or messy data transformed into something usable, I'm open to working on it.
Have a dataset or reporting problem?
Send me a message. Let's turn the data into something useful.
Not where the dashboard says it stalls. Where people wait, re-enter information, hunt for context, or chase an approval.
That answer usually matters more than a long software wish list.
My first step on an automation project is to map the real handoffs. The goal is not to automate everything. It is to remove avoidable work without creating a new mess.
If you can describe the process in five sentences, I can usually spot the first useful improvement.