Guide 18: Discover your ideal customers in <30 mins
ChatGPT + Apollo = Ultimate Data Scientist
When it comes to data, it has always been the corporations that have the edge.
Small businesses simply don’t have the time, tools or knowledge to extract the insights a big company can.
But here's the problem: you're sitting on a goldmine of customer data that can make your business far more profitable and efficient.
Your email list, sales records, and user information hold valuable insights to help you understand who your ideal customers are double-down on targeting them
But how can you unlock this treasure trove of insights without a team of data scientists or expensive analytics tools?
Don't worry.
You don't need to be a tech giant or have a massive budget to harness the power of your data.
In fact, with a few simple steps and some clever use of readily available tools, you can perform a sophisticated persona analysis that rivals what the big players are doing.
Here's how to do it, step by step…
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The Process
Before we start, you’ll need a couple of tools for this process.
This includes:
An AI Chatbot like ChatGPT or Claude
A sales enrichment tool like Apollo or Claude
Let’s jump into it
1. Export your current user's email addresses
First things first, we need to gather all your user data in one place.
This includes both paid and free users.
Most email marketing platforms or CRM systems allow you to export your entire user list as a CSV file.
Look for the Export options in your platform's settings.
Why is this important?
Because this list gives us our total pool of potential customers.
It's the denominator in our conversion rate calculation.
2. Enrich customer data
Now, let's add some meat to the bones.
Services like Apollo.io or Clearbit can take your basic email list and return a wealth of additional information about your users.
This might include job titles, company sizes, locations, industries, and more.
This step is crucial because it allows us to segment our users and understand which types of customers are most likely to convert.
Are enterprise clients more likely to pay than small businesses?
Do certain industries have higher conversion rates?
This enriched data will help us answer these questions.
3. Export sales data with email addresses
Next, we need to know who actually purchased from you.
Export your sales data, making sure to include email addresses (to match with your user list) and the amount paid by each customer.
This sales data is the numerator in our conversion rate calculation.
It tells us who crossed the finish line and became a paying customer.
4. Upload both files to ChatGPT
Here's where the magic happens.
We're going to use ChatGPT as our data scientist.
Upload your enriched customer data file AND your sales data file to ChatGPT.
5. Query the data
Now, we'll give ChatGPT clear instructions on what we want to know.
Use a prompt like this:
"I want you to act as a data scientist. I will give you 2 files. The first file contains the total number of signups, it also shows the date of each sign up, some of these are paid sign ups and some are free sign ups. The second file contains the details of all sales (paid sign ups). The payment amount for each sale differs. I want to establish who the most profitable customers are. To do this, you should aggregate the user data into groups and create marketing personas based on the information available. Cross reference the data in both files and create an average revenue per customer for each group.”
This prompt tells ChatGPT exactly what we're looking for: Marketing personas that you can target, plus the value per customer for each persona.
You can combine this data with any data you have on where each customer came from to target the users who are most valuable and focus on the marketing channels where those users typically come from.
Pro tip
The beauty of this approach is its flexibility. You don’t need to stop with this first prompt.
You can adjust the prompt to ask different questions.
Do you need to know conversion rates by industry?
By company size?
Over different time periods?
Just modify your prompt accordingly.
Conclusion
By following these five steps, you've just performed a sophisticated data analysis that would typically require a team of analysts and expensive software.
You've unlocked valuable insights about your pricing strategy and customer behavior, all without writing a single line of code or spending a fortune on tools.
Remember, as a small business or solo founder, your advantage lies in your agility and ability to act on insights quickly.
This data-driven approach allows you to make informed decisions about your marketing efforts and optimize your conversion funnel.