2. Watch my video and learn how you can use ChatGPT to 10X your Excel skills as a finance professional

In this video, I explain how you can use ChatGPT to 10X your Excel skills as a finance professional.

Enjoy the video and subscribe to my channel to stay updated!

​Combining ChatGPT with Excel will save you a lot of valuable time and allow you to focus on what really matters.

Here are the steps on how you can increase your productivity by 10x:

#1: Identifying KPIs Without Sharing Confidential Data

The key to using AI like ChatGPT without compromising confidentiality is the clever use of data headers.

For example, you have an Excel file that contains product names, revenue from last year and this year, as well as details about promotions during those years.

Instead of uploading the whole dataset to ChatGPT, you simply provide the headers: “Product,” “Revenue Last Year,” “Revenue Current Year,” etc.

This way, ChatGPT can understand the context without accessing sensitive numbers, which helps keep your data secure (this is one of my exclusive tips I share with my students).

After you provide the headers, you can ask ChatGPT to suggest relevant KPIs for analyzing the promotion performance.

You can learn how to get the most out of Excel using ChatGPT in my YouTube video.

#2: Choosing the Right KPIs for Promotion Analysis and Getting The Right Formula

After inputting the headers, ChatGPT suggested several potential KPIs, including:

• Promotion Effectiveness
• Revenue Growth Rate
• Promotion Spending Growth Rate
• Revenue to Promotion Ratio
• Incremental Revenue per Unit of Promotion

Each of these KPIs tells you something different about how the promotions performed, but I found the last one particularly interesting because it helps identify how much additional revenue was generated for every dollar spent on promotions.

I then asked ChatGPT how to calculate this KPI in Excel.

ChatGPT provided a detailed explanation and even gave me an Excel formula to calculate the incremental revenue per unit of promotion.

What I found most useful was that ChatGPT also assumed certain columns for the data (e.g., “Revenue Last Year” in Column D).

I double-checked my Excel file to ensure that these columns matched, and they did, so I used the formula directly.

After entering the formula, I formatted the results, and just like that, I had the incremental revenue per unit of promotion for each product.

This KPI allowed me to quickly see which promotions were effective and which weren’t.

#3: Making the Data Speak: Conditional Formatting

But numbers alone can be overwhelming, especially if you have dozens of products to analyze. That’s where conditional formatting in Excel becomes a powerful ally.

I asked ChatGPT how to highlight the best and worst-performing promotions, and it suggested using conditional formatting.

With conditional formatting, I applied a color scale to the KPI column, making it easy to see which products performed well (in blue) and which did poorly (in red).

For instance, it was immediately clear that while walnuts had a high return on promotion, sodas didn’t perform as well.

You can find out more details and see how this is done in my YouTube video by clicking here.

#4: Visualizing the Data with Graphs

If you’re dealing with a lot of data, it can be challenging to communicate your findings effectively.

To make the data more digestible, I asked ChatGPT which graph would be best to represent the KPI data for all 50 products (SKUs).

It suggested a few options, such as a bar chart, scatter plot, and heat map.

Based on my experience, I decided to go with a scatter plot because it clearly shows the relationship between promotional spending and revenue performance.

ChatGPT even guided me step-by-step on how to create the scatter plot and label each point with the corresponding product name, making it easy to identify which products were overperforming or underperforming.

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#5: Visualizing the Data with Graphs

Once the scatter plot was ready, I wanted to understand what it meant for each product. I used ChatGPT again, asking how to interpret the graph.

The AI provided a helpful explanation that showed me which products had high promotional spending but low returns and vice versa.

For example, I noticed that walnuts were performing exceptionally well—we didn’t spend much on promoting them, but they generated a lot of additional revenue.

On the other hand, chicken promotions didn’t fare as well. I even filtered the data to focus on just the meat category, allowing me to compare beef and chicken directly.

Practical Tips for Your Next Analysis

• Use Headers Only: Always provide headers instead of confidential data when using AI tools.
• Conditional Formatting: Make large datasets easier to understand by color-coding key metrics.
• Visualize with Scatter Plots: Use scatter plots for clear visual representation, especially when analyzing multiple products.
• Ask ChatGPT for Explanations: Don’t hesitate to ask ChatGPT how to explain complex metrics to your boss or team.

​Watch the full video on how to combine ChatGPT and Excel and get the most out of it.

4. Freebies of the week

Have you ever used ChatGPT with Excel?
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Let me know!

​

Nicolas

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P.S.: Enroll in the free 5-day AI for Finance email course now and learn the path of becoming a master of AI for finance that will make you stand out from the crowd.