Hey, marketers in the loop.

Welcome to the AI enthusiasts who joined Marketer In The Loop last week. Our goal is to provide actionable, jargon-free content to help you harness AI effectively in your marketing strategies. Let us know how we can help.

According to our AI Hype vs. Reality Index, “AI Marketing” is closer to Reality this week than it was 3 and 6 months ago. Adoption is steadily increasing, and the industry is expanding AI applications beyond content creation to enhance customer insights, targeting, and engagement.

Onward.

In this issue:

• Step-by-step guide to choose the right AI tool

• Casper's customer experience revolution

• Relevant industry reports

• And much more

Reading time: 10 minutes

MY FAVORITE FINDS

Events

▪️ The one presentation about marketing technology for 2025 — and the AI madness around it — you won’t want to miss (Chief Martech)

Industry News

▪️ What Trump’s victory could mean for AI regulation (TechCrunch)

▪️ Sam Altman from OpenAI claims that in 2025 machines will be able to 'think like humans' (Tom’s Guide)

▪️ Why Coca-Cola has committed to AI this Christmas (Creative Salon)

▪️ Walmart and Amazon are rolling out AI shopping assistants for holiday (Forbes)

▪️ What a fake Dior ad suggests about AI’s production potential (Adage)

▪️ AI-first marketing with OpenAI at INBOUND 2024 (Hubspot on Youtube)

Industry Reports

▪️ How gen AI is already impacting the labor market (HBR)

▪️ New Accenture research finds that companies with AI-led processes outperform peers (Accenture)

▪️ New BCG report: Who’s getting results from AI and why? (BCG)

▪️ Semrush studied 200,000 AI Overviews: Here's what they learned (Semrush)

Thought Leadership

▪️ ‘Avoid reinventing the wheel’: How marketers are approaching AI search (Marketing Week)

▪️ 5 ways to jump start AI adoption in marketing (MarTech)

▪️ Why starting small with AI pilots before scaling is a mistake (Martech)

▪️ 5 ways that AI analytics tools can make you a better marketer (Hubspot)

DEEP DIVE

How to Choose the Right AI Tool for Your Marketing Needs: A Practical Guide

The Big Picture

Today's social feeds are filled with "top AI tools" lists, which can confuse more than help. While generative AI and automation are reshaping marketing, each tool serves specific purposes. Choosing the right one is like selecting the perfect recipe for a dinner party - it depends on your guests' preferences, your cooking skills, and the occasion.

Why It Matters

Many marketers struggle to select and onboard AI tools due to:

• Inflated expectations: AI tools are often hyped up, leading marketers to believe they'll solve all their problems instantly. In reality, it requires careful planning, integration, and ongoing optimization to deliver results.

• Lack of integration: AI tools often need to work seamlessly with existing marketing tech stacks, like CRM, marketing automation, and analytics platforms. Without proper integration, data silos can form, leading to inefficiencies and missed opportunities.

• Underutilized capabilities: Many AI tools offer a wide range of features, but marketers may only use a fraction of them due to lack of awareness, skills, or alignment with business goals. This leads to wasted resources and suboptimal results.

A strategic approach is essential to harness AI effectively. Follow this step-by-step process to make the right choice for your needs.

The Process

 1. Identify Goals & Use Cases

Before exploring AI tool options, it's crucial to have a clear understanding of your business goals. Resist the temptation to start with a tool and instead focus on defining your objectives first. This approach ensures that you select an AI solution that aligns with your unique needs and contributes to your overall business strategy.

Once you have identified the business goals, the next step is to define AI goals that align with your overall business strategy. This alignment is crucial for identifying relevant and impactful use cases. Be specific about how AI will contribute to your business success by connecting your objectives with targeted use cases and success metrics. For example:

• Business goal: Staff augmentation and increase productivity

• How AI enables that goal: Augmented AI and automation increase productivity by shifting people away from repetitive tasks

• Use case to pursue: SEO, social media content generation, personalized landing pages

• Success metric: Productivity metrics, such as time spent on value-added tasks

Pro tip: AI delivers the most impact when companies tackle both cost savings and revenue growth simultaneously, rather than focusing on either alone.

2. Check Organization Readiness

AI projects struggle due to inadequate preparation. Before selecting tools, verify readiness across three essential areas - plus any other potential roadblocks you should address right away:

• Finance: Ensure you have budget for initial investment (including some buffer for potential hidden costs), ongoing maintenance, and team training.

• Team capabilities: Assess current skill levels, identify training needs, and verify resource availability for implementation and management.

• Organizational support: Secure commitment from executive sponsor, IT, legal/compliance teams, and end users who will work with the tools.

Pro tip: Addressing readiness gaps early costs less than fixing problems later. If you want to go deeper, check this practical guide to assess AI readiness and these tips to work effectively with IT and legal.

3. Define Core Requirements

After confirming readiness, defining clear requirements helps narrow down your options and avoid costly mistakes. Focus on three key areas:

• Technical requirements: IT infrastructure, integration with marketing stack, data security, privacy and compliance standards (i.e.: SOC 2, CCPA, GDPR), governance capabilities, necessary APIs, potential required performance levels.

• Operational priorities: main features, potential customizations, industry-specific needs, scalability and flexibility to handle growing workloads, ease of use and intuitive interfaces that minimize training needs, reliable customer success and support, proven accuracy rates, total cost of ownership, including implementation and ongoing maintenance.

• Strategic considerations: vendor reputation, market adoption, product roadmap, responsiveness and time to market, how it maintains compliance with industry regulations.

Pro tip: Prioritize must-haves vs. nice-to-haves, and identify the top 3 features that the team who will use the tool wants the most - you may need it later to create a vendor shortlist. And for reference only, see what marketing operations considers the most important criteria when evaluating new tools:

So the email got too long and I've created a detailed post covering the remaining steps instead of providing just a high-level overview.

The guide is packed with data and insights—and as someone who's spent the last 2 years onboarding new capabilities in a large enterprise, I promise it's worth your time if you're planning to implement a new AI tool. 😊 

Click the button below to read the complete 10-step process, or view the flowchart below for a visual overview.

AI Tool Selection Decision Flow:

CASE STUDY

Casper's AI-Powered Customer Experience Story

What if buying a mattress could be as comfortable as sleeping on one? That's the question Casper answered by turning mattress shopping from a dreaded chore into a personalized experience that keeps customers coming back.

The Customer Service Conundrum

Casper had already transformed mattress buying once. But even as a billion-dollar brand, they faced a new challenge: their initial chatbot, Luna, couldn't meet the varied needs of customers and often escalated inquiries to call center teams. They needed to revolutionize the customer experience again, this time focusing on building lifelong relationships.

Enter Luna 2.0: AI with a Personal Touch

That's where Sierra came in. Together, they launched Luna 2.0, an AI agent designed to make mattress shopping feel personal and pressure-free. But they weren't just building another chatbot – they were creating a sleep consultant that could guide customers through their entire journey, from mattresses to pillows and beyond.

Marc Butakis, VP of Operations, admits he was skeptical at first:

Behind Luna 2.0's success is a dedicated team including Alie Leahy, CX Project Manager, and Antonia Young, Sr. Fraud & System Analyst. They review conversations daily, ensuring the AI stays current and effective. This human oversight ensures Luna 2.0 isn't just smart – it's genuinely helpful.

"In the past, 97% of our interactions began with small talk," explains Butakis. "AI doesn't hesitate – it's direct and efficient while maintaining a conversational tone. Good service means solving problems quickly so customers can get back to their lives."

The Results That Keep Everyone Awake (In a Good Way)

The numbers tell a compelling story:

• 74% resolution rate during peak sales events

• 70% of product questions handled without human intervention

• 20% boost in customer engagement

But the impact goes beyond metrics. "It's fascinating to see how open people are to having meaningful, consultative conversations with AI," notes Danny Cassotta, Sr. Manager Customer Experience. Many customers feel more at ease discussing their sleep preferences with the AI than with a salesperson.

The Bigger Picture

Casper's AI transformation reveals several key insights:

• AI can make big purchases feel more personal, not less

• 24/7 support doesn't have to mean sacrificing quality

• The right balance of human oversight and AI automation is crucial

• Customer comfort sometimes increases when talking to AI

Looking Ahead

By turning a traditionally stressful one-time purchase into a series of helpful interactions, Casper is building relationships that last far beyond the first unboxing.

"We're using AI to meet customers where they are," Cassotta reflects. "Our goal isn't just to sell them a mattress—it's to be their partner for every phase of their sleep journey."

As Casper continues to evolve the sleep industry, they're proving that the best kind of innovation isn't just about making things easier – it's about making every interaction matter. And that's something worth staying awake for.

ICYMI

▪️ Agency (Or Other Partners) Using AI? Here's What You Need to Know

▪️ Transforming AI Anxiety Through Open Source Change

▪️ AI And Copyright: A Quick Marketing Guide

▪️ How to Minimize AI Hallucinations

▪️ Creating an AI Policy That People Will Actually Follow

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