Today, we’re bringing you the latest in AI-powered marketing and business strategies. Here’s what’s inside:

🚨 AI Top Story: Learn how first-party data future-proofs publishing success.

📊 AI Use Case of the Week: Learn how to build, train, and deploy automated chatbots for seamless query resolution and lead collection.

🎯 Killer Marketing Prompt: Unlock the power of A/B testing - refine ad copy, test headlines, and optimise CTAs to drive engagement and boost conversions!

🌟 Creator Spotlight: Meet Adam Biddlecombe, a tech innovator showcasing ChatGPT-01’s advanced problem-solving capabilities to tackle complex workflow challenges.

The Winning Strategy Publishers Use to Attract More Ads

How Publishers Keep Advertisers Coming Back for More

The digital publishing world is changing fast, and first-party data is leading the way.

This is data publishers collect directly from their audience—like email sign-ups, site activity, and preferences. It’s more accurate, more reliable, and now more valuable than ever as privacy laws tighten and third-party data becomes less accessible.

Advertisers are flocking to publishers who can deliver high-quality, compliant audience data.

Tools like Ezoic’s ezID are helping publishers manage this data effectively while building trust with their readers.

By leveraging first-party data, publishers can provide advertisers with engaged audiences that drive measurable results.

The result? Tailored content, better ad revenue, and stronger, more loyal relationships.

Publishers who succeed with first-party data don’t just collect it—they embed it into everything they do. It helps them predict what audiences want, deliver personalised experiences, and optimise campaigns for maximum impact.

In industries like retail, finance, and consumer goods, first-party data is driving revenue growth, reducing costs, and enabling faster innovation.

The takeaway? First-party data isn’t just a useful tool—it’s the backbone of modern publishing success. It provides the insights publishers need to build deeper connections with audiences, exceed advertiser expectations, and future-proof their businesses in an ever-evolving digital landscape.

🤝 How AI Search Tool Perplexity is Sharing Ad Revenue With Publishers - A look at how Perplexity AI’s ad revenue model benefits publishers.

🛠️ Backflip Releases AI Model That Turns Text Into Physical Reality - Backflip’s new AI turns text into objects, backed by $30M funding.

⚠️ Why Most Marketers Are Using AI Wrong (And How To Fix It) - Insights on common AI marketing mistakes and how to avoid them.

📊 AI Market 2024 Year-End Review - A recap of the trends and developments shaping AI in 2024.

Writesonic

Writesonic is an AI-powered content creation platform that empowers users to produce high-quality, engaging content tailored to their needs. From marketers seeking compelling ad copy to entrepreneurs building engaging social media posts, Writesonic simplifies the creative process with intuitive tools and AI precision, making it accessible for both individuals and teams.

Here are some of its key features:

• AI-Generated Content: Writesonic uses advanced natural language processing to create articles, product descriptions, email campaigns, and more in a matter of minutes.
  

• SEO Optimisation: The platform integrates SEO tools to help users craft content that ranks well on search engines, driving organic traffic.
  

• Customisable Tone and Style: Tailor the output to match your desired tone, style, or audience, ensuring consistency with your brand's voice.
  

• Multilingual Support: Generate content in multiple languages, making it ideal for global campaigns and international audiences.
  

• Content Templates: Access a wide range of templates for various use cases, from social media posts to landing page copy, saving time and effort.

• Collaboration Tools: Teams can work together seamlessly, reviewing, editing, and approving content in a shared workspace.

ADAM BIDDLECOMBE - Streamline Your Daily Workflows With OpenAI’s New ChatGPT O1

AI-POWERED CHATBOT IMPLEMENTATION

Tools Needed:

ChatGPT (GPT-4 Turbo API) 
Zapier 
HubSpot
Intercom / Zendesk - for live chat support.
Google Sheets - for training data and response logs.

Step 1: Define Chatbot Goals and Use Cases

What to Do:

1) Identify the primary objectives for the chatbot:

- Answer FAQs.
- Route customer queries.
- Collect lead information.
- Provide basic troubleshooting.

2) Map out key use cases and customer journeys:

- E.g. "Customer wants to know pricing" or "User needs help resetting a password."

3) Compile a list of common customer questions and ideal responses using
Google Sheets.

Step 2: Train The Chatbot

What to do:

1) Prepare Training Data:

- Use the compiled FAQs and responses in Google Sheets as the foundation.
- Include multiple variations of each question to improve recognition.

2) Set Up ChatGPT API:

- Use ChatGPT (GPT-4 Turbo API) to train the chatbot.
- Fine-tune responses to match your brand’s tone and messaging.

Sample Prompt for ChatGPT Training:

"You are a chatbot for [Company Name]. Your role is to assist users with:

FAQs about [Product/Service].

Basic troubleshooting for [Issue].

Routing advanced queries to live support.
Maintain a [professional/casual/friendly] tone in responses.

Example Question: 'How do I reset my password?'
Example Response: 'Click on “Forgot Password” on the login page and follow the instructions."

Step 3: Integrate the Chatbot with Customer Support Tools

What to do:

1) Connect ChatGPT API with your live chat tool (e.g., Intercom or Zendesk).

2) Set up workflows using Zapier.

- Automatically log customer conversations into HubSpot CRM.
- Escalate complex queries to a live agent based on predefined rules (e.g., "I need to speak to someone").

3) Test the chatbot’s functionality across channels (e.g., website chat widget, social media, or email).

Step 4: Automate Query Routing and Lead Collection

What to Do:

1) Program the chatbot to recognise when to:

- Answer directly (e.g., FAQs).
- Collect customer information (e.g., name, email, query type).
- Escalate to a live agent.

2) Store lead information in HubSpot CRM via Zapier for follow-up and nurturing.

Step 5: Monitor Performance and Gather Feedback

What to Do:

1) Use the chatbot’s logs and Google Sheets to track:

- Query volume.
- Resolution rates.
- Common unanswered questions.

2) Input this data into ChatGPT for analysis:

Sample Prompt for ChatGPT:

"Here are 50 customer interactions the chatbot couldn’t resolve. 

Analyse the patterns and suggest improvements to the chatbot’s training data."

A/B Testing Framework For Ad Copy Optimisation

You are a marketing strategist tasked with designing and executing an A/B testing framework to optimise ad copy for [brand name]’s digital campaigns.

The goal is to identify the most effective messaging elements for [specific platform(s), e.g., Facebook Ads, LinkedIn, Google Ads] to drive higher engagement and conversions.

Start by outlining the objectives of the A/B test, such as increasing click-through rates (CTR), lowering cost-per-click (CPC), or improving conversion rates. 

Define the audience segmentation criteria, ensuring that the test reaches representative samples of [brand name]’s target demographic.

Develop variations of the ad copy, focusing on specific elements to test:

Headlines: Create attention-grabbing alternatives with different hooks or tones.

Descriptions: Write variations that emphasize unique value propositions or address specific pain points.

Calls-to-Action (CTAs): Experiment with urgency, exclusivity, or benefit-driven language.

Include guidance on crafting a hypothesis for each test, such as: “Changing the CTA to ‘Start Your Free Trial’ will increase click-through rates by 20% among first-time visitors.”

Propose methods for structuring the A/B test, such as running campaigns simultaneously to ensure equal exposure and avoiding overlapping audience segments. 

Outline key metrics to track during the test, including CTR, CPC, engagement rates, and conversion rates.

Finally, provide actionable insights for analysing the results and scaling the winning ad copy. Include recommendations for iterative testing, such as incorporating audience feedback or aligning copy more closely with seasonal trends or campaign goals.

This A/B testing framework should help [brand name] systematically refine its ad messaging, leading to measurable improvements in performance and ROI.