This document provides an overview of how ChatGPT can be leveraged to enhance marketing campaigns in Marketo. It discusses fine-tuning ChatGPT models with customized data to better distinguish genuine from bot leads. It also describes how to retrieve lead engagement data from Marketo, structure it for ChatGPT, and use ChatGPT's responses to optimize email send times. Additional sections discuss calculating ChatGPT token costs and considerations around data privacy when using ChatGPT.

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11. Unleashing ChatGPT With Marketo
The Workflow Pro

12. Professor Details
Tyron Pretorius
Automation Guru
Marketing Operations Manager | Telnyx
Blogger, Freelancer, Professor | The Workflow Pro
3+ Years of Using APIs

13. ● 2 Ways to Interact with ChatGPT
● Using Zapier as a middleman
● Using Replit as a middleman
● Making ChatGPT Request Directly
● Bot Form-Fill Classification
● Refining your prompt
Talk Outline

14. 2 Ways to Interact with ChatGPT

15. 2 Ways to Interact with ChatGPT
1. Using Marketo webhooks to make ChatGPT requests directly
○ 30 second timeout limit on webhooks
○ Less control than using 3rd party tool
2. Using a 3rd party as a middleman e.g. Zapier, Replit
○ No timeout issue
○ Can use 3rd partys’ tools for parsing response, advanced
logic etc

16. Using Zapier as a Middleman

17. Using Zapier as a Middleman

18. Using Replit as a Middleman

19. Segmentation using ChatGPT
1. Messaging Application: Software applications where one of - if not their only -
primary feature sets revolved around enabling their customers to easily send
messages. This could be a bulk messaging service for sending out mass alerts for
events or it could be a promotional marketing tool focused around SMS outreach.
2. Patient / Customer Engagement Software: Software applications that enable
businesses to better communicate and engage with customers and/or patients.
These platforms often enable 2-way communications between the clients and the
business and likely integrate with other tools the businesses use so the
content/messaging can be tailored to the individual customer.
3. CRM: CRM stands for Customer Resource Management. These are software
platforms where all customer data is stored. With the advancement of
softare-based applications, many CRMs now incorporate communications features
such as click-to-call, call recording, and more that allow the CRM to be more than
just a collection of data but also a place where communications-based workflows
can be performed.

20. ”Using the list of 3 'sales segments' above that describe Telnyx's customer
categories and their potential use cases for Telnyx's services determine
whether the company with the website provided fits into each of these
sales segments. Format your answer to include the name of each sales
segment, a % confidence score, and an explanation as to why they do or
do not match the given segment like so: Sales Segment:
{{Segment}}nnConfidence Score: {{% Score}}nnExplanation:
{{Explanation}}”
Segmentation using ChatGPT

21. Segmentation using ChatGPT

22. API Crash Courses

23. Making ChatGPT Request Directly

24. Making ChatGPT Request Directly

25. Making ChatGPT Request Directly

26. Making ChatGPT Request Directly

27. Making ChatGPT Request Directly

28. Bot Form-Fill Classification

29. CAPTCHA Failings: Missed Bots

30. CAPTCHA Failings: False Flags

31. Downstream Issues

32. Solution

33. Usage

34. Refining Your Prompt

35. Questions?

36. Resources
● “Integrating Marketo with ChatGPT” blog post
● Marketo API Crash Course
● Demystify the API Crash Course

37. 1
Lucas Machado
St Louis and Kansas City MO MUG
08/24/2023
Future-Proofing Marketing:
Integrating AI with Marketo

38. 2
About me
🎓 Academic Background: Specialized in Applied and
Computational Mathematics.
💻 Tech Toolkit: Skilled in Python, Javascript, and adept with
APIs.
🧩 Problem Solver: Passionate about challenges and
puzzle-solving.
🌎 From: São Paulo, Brazil.
🥦 In the kitchen: Proud vegetarian
Lucas Machado
Marketing Automation Specialist
Revenue Pulse (RP)

39. 3
Agenda
- Fine-Tuning ChatGPT
- Engaging Leads on Their Terms: Leveraging
ChatGPT and Marketo.
- ChatGPT & API: Calculating Costs
- Ethics and Data Privacy

40. 4
Fine-Tuning ChatGPT

41. 5
ChatGPT's
Secret Sauce
Public vs. Personalized: While ChatGPT thrives on public data,
specific needs demand tailored datasets.
Bespoke Accuracy: Enhance precision for your unique use cases.
Customize with Confidence: Infuse ChatGPT with your own data
for a tailored experience.
Use cases
- Persona-Driven Lead Classification: Sort leads into distinct
personas for targeted engagement.
- Sift Genuine from Generic: Sharpen accuracy to distinguish
authentic leads from the noise.

42. 6
How to tailor your model to
distinguish the real from the fake

43. 7
Data Preparation Options
- Hard way: .jsonl file - Easy way: .CSV file

44. 8
Base models
- Fine-tuning begins with a default 'curie' base model.
- Can be one of four GPT 3 Models or GPT 3.5:
- GPT 3.5
- davinci
- curie
- babbage
- ada
- For this instance, davinci was the selected model.
- Models to be deprecated in January 2024.
- OpenAI aims to allow fine-tuning for GPT 4 soon.

45. 9
Steps to create your model
1. Setup:
○ Install Python: Ensure Python is installed on your computer.
○ Open CLI: Access the Command Line Interface using cmd.
2. Install OpenAI Library:
○ pip install --upgrade openai
3. API Configuration
○ Set API Key: export OPENAI_API_KEY="<OPENAI_API_KEY>"
4. Data preparation:
○ openai tools fine_tunes.prepare_data -f <LOCAL_FILE>
5. Model creation:
○ openai api fine_tunes.create -t <TRAIN_FILE_ID_OR_PATH> -m <BASE_MODEL>
6. Wait: Allow the system to process and optimize your model.
https://platform.openai.com/docs/guides/fine-tuning

46. 10
URL: https://api.openai.com/v1/completions
Payload Template:
{
"model":"<YOUR_FT_MODEL>",
"prompt":"'<YOUR_PROMPT>'",
"max_tokens":1,
"temperature":0
}
Request Type: POST
Response Format: JSON
*Map the response to a specific Marketo field.
Setting Up a Marketo Webhook for
Completions

47. 11
Example Real Lead

48. 12
Example Bot Lead

49. 13
Engaging Leads on Their Terms:
Leveraging ChatGPT and Marketo.

50. 14
Pinpointing
ideal send
times
Understand Your Leads:
- Get the activity log using Marketo API.
ChatGPT Integration:
- Use ChatGPT to predict the best send times based on
engagement patterns.
Automated & Enhanced Campaigns:
- Return optimized timings to Marketo.
- Ensure emails are delivered when leads are most receptive.
The Result:
- Higher open rates, better engagement, and improved lead
nurturing.

51. 15
Retrieve your data
Utilize the Marketo API to extract your data and organize it into a spreadsheet.

52. 16
Treating your data
Data Readiness:
- ChatGPT requires structured data; a raw
spreadsheet won't suffice.
Individualized Processing:
- Segment each lead for targeted analysis.
Optimized Data Structure:
- Structure data in a format conducive for
precise ChatGPT responses.

53. 17
Crafting your Prompt for ChatGPT
Using the right prompt is crucial for achieving accurate results with ChatGPT.
Example Prompt:
“You are an Data Analytics assistant in a Marketing Automation and Operation Agency. I'm
going to send you the anonymized information of which emails a lead received, the
datetime it was received and the datetime it was opened. Your job is to respond when is
the best time to send an email to the specific lead to maximize the chance of the lead
opening the email. For example, the hour the lead most opened emails can be a best
parameter. Try your best to determine a best send hour. Respond only with the best send
hour in a 24 hour clock. If you can't define the best send time respond with -1.”

54. 18
Optimizing Marketo Campaigns
Data-Driven Recommendations:
- Leverage ChatGPT to determine the best email send times for each lead.
Intelligent Campaign Execution:
- Integrate ChatGPT's insights into Marketo's smart campaigns.

55. 19
Optimizing Marketo Campaigns
Advanced Timing Strategies:
- Utilize advanced wait steps in Marketo to precisely deliver emails at optimal times.

56. 20
ChatGPT & API: Calculating Costs

57. 21
Understanding Tokens in ChatGPT
Token Basics:
- Think of ChatGPT's tokens as its "coffee" – vital for its operation.
Token to Word Ratio:
- Typically, 1 token covers approximately ¾ of a word.
Monitoring Usage:
- Track token consumption in the API response for each request.
Tools & Resources:
- Use the OpenAI Tokenizer to count tokens in your input.
Quick Reference:
- On average, 100 tokens equate to about 75 words.

58. 22
Token Pricing Across Models
Variable Pricing:
- Different models have distinct token pricing structures.
Complexity Costs:
- Generally, advanced models have pricier tokens due to increased capabilities.
Model-Specific Rates:
- GPT 4: $0.03 per 1,000 Tokens.
- GPT 3.5: $0.0015 per 1,000 Tokens.
- Fine-tuned Davinci: $0.03 per 1,000 Tokens.
For Comprehensive Pricing:
- Visit OpenAI Pricing for a detailed breakdown.

59. 23
Ethics and Data Privacy

60. 24
Chat GPT Data Privacy
Is ChatGPT Confidential?
No.
Is ChatGPT Safe to Use?
Yes, when used appropriately and knowledgeably.
Data Retention with OpenAI:
Via the API: OpenAI does not use your data to improve its models.
Via the Browser: Data may be used for model improvement, but there's an option to deactivate this.
Note: OpenAI retains data for 30 days for operational and security purposes.
Recommendations:
Always ensure compliance with local data regulations.
Anonymize data whenever possible.

61. 25
Thank you!