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Practical Insights for Skeptics & Users Alike…in (Roughly) Two Minutes or Less

ChatGPT for Basic Data Analysis

I want to focus today’s edition on a specific use case that many people are looking for: using ChatGPT for data analysis.

Lots of us are sitting on a goldmine of data but don't know how to make sense of it. Without a background in data science, it can feel overwhelming.

Here's how you can use ChatGPT for basic data analysis, even if you've never done data analysis before. Before we get into it, some basic tips for success here:

• Be specific about what you want to know

• Start with smaller sets of data as you get comfortable with the process

• Don't be afraid to ask ChatGPT to explain things in simpler terms

• Don’t share any data you consider private or sensitive

Getting Started

Start with What You Have

Whether it's a sales report, website traffic stats, or customer feedback, any data you have is a good starting point. No need for fancy formatting - just have it ready to share.

Strike Up a Conversation (“Prompting”)

Open ChatGPT and start by telling it what kind of data you have. For example, "I have three months of sales data from my online store." Then, ask what you want to know: "Can you help me understand which products are selling best?"

Share Your Data

Simply copy and paste your data into the chat. Don't worry about making it perfect - ChatGPT is pretty good at figuring things out.

Get Insights in Plain English

ChatGPT will analyze your data and give you a summary in easy-to-understand language. It might even suggest charts or graphs to visualize the information.

Dive Deeper with Follow-up Questions

The beauty of ChatGPT is that you can ask for more details or clarification, just like you would in a real conversation. "Tell me more about the top 3 selling products" or "What does this trend mean for my business?"

Real-World Applications:

• Analyze sales data to identify your best-selling products or slowest months

• Understand which social media posts are getting the most engagement

• See which pages on your website are most popular

• Summarize common themes in customer reviews

• Inventory Optimization:

  • Input stock levels, sales rates, and supplier lead times for analysis.

  • Example: "Using our inventory turnover rates, suggest optimal reorder points for our top 10 products."

Often, small businesses in particular don’t realize just how much valuable information they already have. This data comes from various sources including point-of-sale systems, financial records, customer interactions, and digital platforms. Sales data, customer purchase histories, website analytics, social media metrics, and inventory records are just a few examples.

Other often-overlooked data sources include employee performance metrics, customer service logs, appointment bookings, online reviews, and even foot traffic patterns for physical stores.

Tomorrow we’ll take a look at how to make visualizations using ChatGPT.

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