Wise Choice

Streamlining CRM Data Migration with ChatGPT and Python

Justin Wise's photo
Justin Wise
·

4 min read

When transitioning from one CRM platform to another, one of the most time-consuming tasks is often cleaning up and reformatting customer data. Exported CSVs from the old system rarely match the exact format required by the new CRM, leading to hours or even weeks spent manually manipulating spreadsheets. However, by leveraging AI tools like ChatGPT alongside some Python scripting, much of this process can be automated, dramatically reducing the transition time.

Eliminating Duplicate Records

One common issue when exporting data from a CRM is duplicate contacts, either due to user error over time or because of how certain CRM systems store records. Importing this messy data into a new system perpetuates the problem. With a few lines of Python though, we can deduplicate an exported CSV based on email address:

import csv

def deduplicate_csv(input_file, output_file, dedup_field):
    seen = set()
    with open(input_file, 'r') as infile, open(output_file, 'w', newline='') as outfile:
        reader = csv.DictReader(infile)
        fieldnames = reader.fieldnames
        writer = csv.DictWriter(outfile, fieldnames=fieldnames)
        writer.writeheader()
        for row in reader:
            if row[dedup_field] not in seen:
                seen.add(row[dedup_field])
                writer.writerow(row)

deduplicate_csv('contacts.csv', 'deduped_contacts.csv', 'Email')

This script reads in the exported CSV, checks each row to see if the specified field value (in this case email address) has been seen before, and if not, writes that row to a de-duplicated output CSV.

Reformatting CSVs with ChatGPT

Another challenge in migrating CRM data is getting the CSV in the exact format expected by the new system. Column names and orders often vary between platforms. While Python could be used here as well, an even faster approach is to use ChatGPT's natural language capabilities.

For example, say the exported CSV has columns for first name, last name, and email, but the new CRM expects full name and email columns. We can simply ask ChatGPT:

Here is a CSV with columns "First Name", "Last Name", and "Email". Can you give me a Python script to output a new CSV with columns "Full Name" that combines first and last name, and "Email"?

Within seconds, ChatGPT will generate the needed Python code:

import csv

with open('input.csv', 'r') as infile, open('output.csv', 'w', newline='') as outfile:
    reader = csv.DictReader(infile)
    fieldnames = ['Full Name', 'Email']
    writer = csv.DictWriter(outfile, fieldnames=fieldnames)
    writer.writeheader()
    for row in reader:
        writer.writerow({'Full Name': f"{row['First Name']} {row['Last Name']}", 
                         'Email': row['Email']})

Real-World CRM Migration Success

Janie R., Account Manager at natural supplement company Natural Heritage Enterprises, recently led a transition from their legacy CRM to a modern cloud platform. They have sold Essiac Tea on their website Remedies.net for over 35 years, and are only now exploring new CRM solutions. She shares:

"I dreaded the data migration aspect, as our old CRM had over a decade of customer records in desperate need of cleanup. However, by using Python scripts and ChatGPT to automate reformatting and deduplication of our exported data, what would have taken weeks took only a couple days. It was a huge relief and let us get up and running on the new system much faster than anticipated."

With powerful AI assistants like ChatGPT and some basic scripting skills, the days of painstakingly cleaning CRM data by hand are over. By automating the tedious parts of the process, businesses can focus on what's really important - building relationships with their customers.

JW, an e-commerce consultant and founder of WeissChoice.org, frequently works with online businesses struggling with outdated CRM systems. He has found ChatGPT and Python to be invaluable tools in his consulting practice.

"Many of my clients are stuck on legacy CRMs that are hindering their growth," Justin shares. "The data is often a mess, and they dread the thought of migrating to a new platform. That's where I come in - by leveraging AI and automation, I'm able to dramatically speed up the process of cleaning and reformatting their customer data for import into a modern CRM."

Justin believes that learning these skills is essential for anyone working on the backend of an e-commerce business. "Being able to manipulate data efficiently is a superpower in today's digital landscape. Tools like ChatGPT and Python are incredibly empowering - they allow you to accomplish in minutes what used to take days or weeks. I always encourage my clients to have their teams develop these capabilities."

As more and more commerce moves online, the ability to effectively manage and utilize customer data is only becoming more critical. By embracing AI assistants and learning some fundamental programming skills, businesses can not only streamline their operations, but also gain a significant competitive advantage. The future of e-commerce belongs to those who can harness the power of data - and tools like ChatGPT and Python are making that easier than ever before.

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