Issue #44: GPT-o1—Your new marketing brain? Expensive overthinking?

Good morning.

Caught between FOMO and skepticism over OpenAI's o1?

You’re not alone.

OpenAI's latest release, the o1 model (previously codenamed "Strawberry"), is loved by some, hated by others—and actually a marvel to use.

Forget the typical "faster, better" update.

This time, chain-of-thought reasoning means it thinks through problems in steps, simulating human-like decision-making that's ideal for complex marketing challenges.

In this issue, we'll do a deep dive on GPT o1 to figure out if it's worth your time and attention.

We'll also explore two exciting tools (Flux and Flair) that are helping entrepreneurs and scrappy marketing teams to level up their visual content.

Let’s get into it.

—Sam

IN TODAY’S ISSUE 👨‍🚀 

• GPT o1: Chain-of-thought reasoning or just another AI hype train?

• Salesforce's Agentforce: The next big thing—or déjà vu all over again?

• Flux & Flair: Leveling up your visuals without breaking the bank.

• The real deal on AI tools: Separating the game-changers from the time-wasters.

Let’s dive in.

ChatGPT o1 model for marketers & entrepreneurs

OpenAI's latest model o1, isn't just another incremental update like we’ve seen all summer. It represents a big shift in how AI approaches problem-solving.

Traditional AI models like GPT-4o can recognize patterns but often struggle to walk through a nuanced, multi-layered decision process. 

GPT o1’s chain-of-thought modeling, on the other hand, simulates human-like reasoning, allowing it to "think through" problems.

What Makes GPT o1 Unique?

• Chain-of-Thought Reasoning: Unlike models that predict the next word based on vast datasets, GPT o1 employs a "chain-of-thought" methodology. It breaks down complex problems into smaller, manageable steps, allowing for deeper analysis and more accurate results.

• Reinforcement Learning: GPT o1 has been trained using a new optimization algorithm that leverages reinforcement learning. This approach rewards the model for correct reasoning steps and penalizes it for mistakes, effectively teaching it to "think" more like a human.

• Enhanced Problem-Solving Abilities: In rigorous testing, o1 outperformed expert humans on PhD-level science questions and solved 83% of International Mathematics Olympiad problems—a stark improvement over GPT-4o's 13% success rate.

The “Million Dollar AI Question” is as always: 

Does this translate to tangible value for marketers already juggling a plethora of AI tools?

Here’s my recommendation:

GPT o1 has a great use case for advanced marketing tasks, strategic planning, and solving complex challenges that require deep reasoning. 

It can be used to uncover hidden insights, model intricate scenarios, and craft sophisticated strategies.

However, for routine content creation and simpler tasks, GPT 4, Claude or other existing AI tools are cheaper and more efficient. 

The decision to adopt GPT o1 depends on the complexity of your needs and the added value of deeper insights in your marketing.

But even if it doesn't end up as part of your permanent workflow, you should still mess around with it.

Here are some areas where I think GPT o1 can shine:

1. Strategic Insights and Scenario Modeling for Market Adaptation

For businesses navigating crowded, fast-moving markets—whether a B2B SaaS startup or an ecommerce brand—managing data on customer needs, competitor strategies, and partnership opportunities can be overwhelming.

Data to leverage:

• Anonymized Customer Data: Purchase history, feedback, churn rates, and customer support tickets.

• Competitor Data: Pricing models, product feature updates, marketing campaigns, and reviews.

• Market Data: Analyst reports, social media trends, consumer behavior shifts, regulatory news.

Prompt Example: “Analyze customer support tickets and competitor reviews to identify unmet customer needs and suggest new product features. Also, assess recent regulatory changes and predict their potential impact on our current product positioning over the next 12 months.”

2. Advanced Data Analysis for Campaign Optimization

Marketing campaigns generate enormous amounts of data across multiple platforms—website analytics, social media metrics, email performance. 

Manually sifting through this to identify which elements drive success is tedious and time-consuming. 

While integrations and APIs help consolidate data, much of it remains siloed across different platforms.

Data to leverage:

• Campaign Performance Data: Click-through rates (CTR), conversion rates, bounce rates, dwell time.

• Audience Segmentation Data: Age, location, purchase history, interests, engagement times.

• Social Media Sentiment: Comments, shares, likes, and mentions over a defined period.

Prompt Example: “Compare the engagement metrics across social media and email campaigns for the last quarter. Identify the most successful audience segment and suggest ways to optimize messaging for the underperforming segments.”

3. Product Development and Market Expansion

Expanding into new markets or developing new products requires thorough research—analyzing competitors, customer needs, and broader market conditions.

Data to leverage:

• Global Customer Feedback: Product reviews from different regions, platforms, support tickets, and social media mentions.

• Competitor Product Data: Feature lists, pricing tiers, and customer reviews by geography.

• Economic and Regulatory Data: Market entry reports, trade regulations, local cultural trends from sources like TrendHunters etc, and economic forecasts.

Prompt Example: “Analyze global customer reviews and competitor offerings in the EU market. Identify product gaps or potential features that would appeal to European consumers, while considering regulatory constraints and economic trends."

The examples I gave here are basic, the point you need to understand is that GPT o1 is the place where you can upload any data that you want.

And then ask hard-hitting, strategic questions against that data.

And actually, get some insights worth their salt.

Something that current LLMs would struggle to deliver with any sophistication.

The Hype vs. The Reality

While the GPT o1 model boasts impressive capabilities, it's essential to temper expectations:

• Cost and Speed: o1 is approximately four times more expensive to use than GPT-4o and operates at a slower pace due to its complex reasoning processes. This makes it less practical for everyday tasks or quick responses.

• Not a Replacement for GPT-4o yet: OpenAI themselves acknowledge that "GPT-4o is still the best option for most prompts." o1 shines in handling complex, multi-step problems but may overcomplicate simple queries.

• Early Stages: As a preview release, o1 is a work in progress. Users may encounter quirks, and the model might not always provide the expected level of performance across all tasks.

Critical Perspectives

Industry experts and early users have offered a range of insights:

• Overthinking Simple Tasks: GPT o1 tends to provide exhaustive answers even when not required, potentially overwhelming users with unnecessary information.

• Transparency in Reasoning: The model's ability to display its thought process is a double-edged sword. While it offers transparency, it can also create an illusion of human-like thinking, which may not always align with the model's actual capabilities.

• Accuracy and Hallucinations: OpenAI has made strides in reducing instances of hallucinations (incorrect or nonsensical outputs). However, the problem isn't entirely solved, and users should remain cautious.

Here’s another take from Will Depue:

GPT o1 is a significant leap forward, but it's not a panacea. 

It's more expensive and slower than GPT-4o, and it's designed for complex tasks, not for quick, simple queries. OpenAI themselves admit that "GPT-4o is still the best option for most prompts."

But it would be a huge mistake to dismiss it and think it’s a lot of noise for nothing. 

It’s, for real, a big deal. It’s effectively removing the need for junior-level roles in most companies and marketing teams. 

Salesforce goes all-in on AI agents with Agentforce

Salesforce is throwing its hat into the AI agent ring with Agentforce.

At a glance:

• Pre-built AI agents like the Campaign Optimizer can automate entire campaign lifecycles.

• A Marketing Agent that crafts and optimizes campaigns based on your business goals.

• Custom Agent Builder lets you create bespoke AI assistants without coding skills.

• Integration with Salesforce's Data Cloud for hyper-targeted campaigns.

They're promising the moon and stars with pre-built agents, custom dev tools, and seamless integration across systems. 

But let's pump the brakes for a second—we've heard this song and dance before, haven't we?

Microsoft and others have been singing the same tune, and we all know how that's gone.

Salesforce will be releasing more details at their annual Dreamforce conference in a couple of days.

If Agentforce does what it says it does, this spells good news for Campaign Managers, Sales Leaders, Marketing Directors, and anyone else who oversees customer segmentation, and lifecycle management.

My recommendation: 

If your organization already uses Salesforce, keep an eye out for some beta-testing, or demo options.

If you don’t, take this as a clear signpost of where AI agents are heading in the marketing and sales space. You can already set up and use AI agents for a ton of marketing tasks. It’s only growing from here. 

I’m not sure where junior marketers or junior sales roles will fit in, if at all.

Right now, if you’re not upgrading your work and getting into more higher-level, senior type work—you’re probably going to have a hard time getting hired in the next 12-18 months.

The junior-level roles are starting to go away, as AI agents can handle most of them.

And AI agents aren’t getting dumber—as you can see with o1 above, every AI system is only getting “smarter”. 

It’ll be interesting to see how this rolls out over the next few weeks as early adopters put it through real-world scenarios.

FLUX: Visuals for marketing will never be the same

I like this image tool a lot. It can make incredible realistic images (for better or worse).

It’s especially valuable for small brands and marketers who don’t have a large budget for photography or design.

My recommendation: 

Flux is a tool that is ideal for product promotion, branding, and marketing in a cost-effective and scalable way. 

It offers a straightforward set of features out of the box:

• Custom Model Training: Users can upload images to train AI models for tasks like headshots, product photos, and brand visuals.

• Text-to-Image Generation: Use text prompts to generate images based on custom-trained models.

• Multiple Use Cases: Ideal for creating logos, product shots, marketing materials, and other brand assets.

• No Technical Expertise Required: The tool is designed to be user-friendly, with no coding or design skills needed.

And beyond Flux’s out-of-the-box capabilities, people are combining it with other tools in pretty cool ways:

Combined with LoRA:

Flux with Lora + Gen-3 Alpha image-to-video:

Flux + Kling AI

Flux is a tool that is ideal for product promotion, branding, and marketing.

You can generate images and graphics that don’t have that “AI look and feel” that so many other tools do. 

Use Flair for incredible marketing photoshoots

Flair is another great tool in the same vein as Flux, but geared toward product photography.

Here are the key features of Flair AI:

• AI-Generated Product Photography: Drag-and-drop interface for creating product photoshoots with customizable props, backgrounds, and lighting.

• Templates for E-Commerce: Pre-designed scenes to help brands create product visuals quickly and effectively.

• Real-Time Collaboration: Allows teams to work together on creating and editing images.

• Private AI Model Training: Users can train models to maintain specific product aesthetics for consistent branding.

Run a small digital marketing agency?

Have an ecommerce brand?

Point the creative people on your team towards this tool and watch it upgrade your output and quality big time.

Whether you're churning out product shots for your Shopify store or crafting product-focused social media campaigns, it’s a great cost-effective tool.

Here’s the takeaway: 

GPT o1 represents a real leap forward with its chain-of-thought reasoning.

Many actual AI experts (not the overnight AI gurus you see online) are calling it “smart graduate student”.

No matter what you’re calling it, the truth is:

GPT o1 is a valuable asset for strategic planning and complex marketing scenarios. It can handle it. Probably better than a junior marketer.

But let’s be clear: 

It’s not magic. The model is more expensive, slower, and better suited for intricate tasks rather than day-to-day operations.

But at the same time, its ability to handle complex scenario planning and data analysis will be a game-changer for those willing to invest. 

Start experimenting with o1, especially if you’re already leveraging AI in your workflow.

And don’t sleep on Flux and Flair.

It’s not just about churning out more content—it’s about scaling quality and creativity to levels that were once unreachable to teams without huge production budgets.

Remember:

The marketers who are winning right now are the ones who are testing and using the tools.

And they’re the same ones who have been quietly tinkering for months or years.

Talk soon,
Sam Woods
The Editor