Hey, marketers in the loop,

2025 is here, and it’s already shaping up to be a big year for AI. To start strong, I analyzed all the newsletter data from 2024 with a little help from ChatGPT. Here’s what I uncovered:

• You love curated, must-read content to stay ahead.

• There’s growing excitement around AI agents and their potential.

• Many of you are interested in practical, actionable advice for tackling real-world use cases.

With these insights, I’m introducing new sections to the newsletter this year, including “You Ask, I Answer”—a dedicated space where I tackle your most pressing questions and challenges.

We’ll kick off with a step-by-step guide on how to leverage AI as a strategic data analyst partner, a question a reader asked me last week.

What do you want me to cover in this new section? Hit reply and let me know—I’d love to hear from you!

Cheers,

Rei

In this issue:

• Using AI as your data analyst partner

• Zapier found a better way to aggregate buyer signals

• Google’s 321 generative AI real-world use cases

• 2025 predictions poll

• And much more

Reading time: 10 minutes

MY FAVORITE FINDS THIS WEEK

Must Read

▪️Google’s updated list of 321 real-world generative AI use cases (Google)
Note: look for your company, competitor, industry or relevant keyword, and if you are a Microsoft user they have a similar post with more than 200 AI transformation stories here

▪️Sam Altman's reflections on AI and OpenAI advancements (Sam Altman)
Notable quote: "We are now confident we know how to build Artificial General Intelligence as we have traditionally understood it. We believe that, in 2025, we may see the first AI agents “join the workforce” and materially change the output of companies."

▪️Prophecies of the flood: What to make of the statements of the AI labs? (Ethan Mollick)
Note: It provides an overview of the impact of AI and explains why now is the time to start having tough conversations and acting, before the "water starts rising."

Industry News

▪️Meta removes AI character accounts after users criticize them as ‘creepy and unnecessary’ (NBC)

▪️Instagram begins randomly showing users AI-generated images of themselves (404)

▪️What Meta's announcement about abandoning its fact-checking program and loosening its speech rules means for the AI industry (Axios)

▪️YouTube says that soon, its tech will be able to find AI copies of celebs and creators (The Verge)

▪️TikTok adds more generative AI features (Social Media Today)

Industry Reports

▪️28 AI marketing statistics you need to know in 2025 (Survey Monkey)

▪️Marketing executive’s playbook: How marketers can work & level-up in 2025 (Hubspot)

▪️These 4 graphs show where AI is already impacting jobs (Fast Company)

AI Agents

▪️AI marketing agents: 14 strategies for 2025 (Writesonic)

▪️Does ChatGPT recommend you, or a competitor? Compare your brand to a competitor's through the eyes of ChatGPT (Simple.ai)

▪️How are companies using AI agents? Here’s a look at five early users of the bots (WSJ)

Practical Tips

▪️Microsoft's pitch deck to get your organization on board with Microsoft 365 Copilot (Microsoft)
Note: if you are a Microsoft user, check all the resources in the last slides, especially the Adoption Guide. If you are not, these are great resources for anyone exploring AI

▪️Implementing AI in your marketing tech stack: tips and tricks you need to know (Hubspot)

Thought Leadership

▪️Optimizing ad spend with AI-powered marketing mix modeling (Fast Company)

▪️Guardrails and governance: How to protect your brand while using AI (MarTech)

▪️Digital ads could soon be directed at AI agents instead of the user (OfficeChai)

▪️Why early generative AI ads aren’t working and how creatives will shift to integrate the tech into their work (Digiday)

▪️Most marketing change management is stunningly ineffective: Here's a middle-out approach that could improve outcomes (MarTech)

YOU ASK, I ANSWER

Unlocking Marketing Analytics with AI

As we step into 2025, marketing leaders are sitting on a goldmine of insights buried within their 2024 data. The real question is: Are we tapping into this potential effectively? Many teams use AI for content creation and campaign optimization. Yet, there’s an overlooked opportunity—using AI as a strategic partner for data analysis. By doing so, you can unlock insights that might otherwise remain hidden, especially when evaluating year-end performance or planning for the year ahead.

Your AI Data Analyst: A Strategic Partner at Your Fingertips

AI platforms like ChatGPT, Claude, Gemini, and Copilot are no longer just tools for generating content. They’ve become powerful allies for data analysis. Here’s how these platforms can support your marketing efforts:

• Spot trends and patterns that may go unnoticed by human observation.

• Generate compelling visualizations that simplify complex data stories.

• Translate raw numbers into actionable insights, tailored to your business needs.

• Brainstorm innovative strategies by exploring historical and real-time data from fresh angles.

Best of all? These tools are intuitive, accessible, and ready to help you unlock the hidden value in your 2024 data.

Your Roadmap to AI-Powered Marketing Analytics

Follow these practical steps to leverage AI and extract actionable insights from your 2024 marketing data. This is the process I used to analyze my newsletter data—feel free to adapt it to uncover valuable insights for your business. And let me know if it helped you find any gold.

1. Define Your Objective

Before diving into the data, start by identifying a specific goal or KPI that matters to your business. AI can help refine your focus and suggest new areas to explore. Unsure where to start? Ask your AI platform to suggest potential areas of focus or refine your initial ideas until you fully understand the core problem or opportunity to address.

Common areas to explore:

• Customer behavior changes throughout the year

• Campaign performance trends across platforms

• ROI shifts by marketing channel

2. Prepare and Clean Your Data

Don’t aim for perfection—data doesn’t have to be flawless. AI can assist in organizing and cleaning both structured and unstructured data, flagging duplicates, filling gaps, and ensuring consistency across datasets. If gaps remain, add complementary data such as metadata to enrich your insights.

Steps to get started:

• Export your data: Begin with a CSV or other structured format. If your data is unstructured, that’s fine—AI can help sort and format it.

• Clean your data: Use AI to identify and remove duplicates, fill in gaps, and ensure consistency across datasets. It can even highlight missing data that may be critical to achieving your goals. For example, I used AI to extract metadata directly from my newsletter content, saving significant time and effort.

• Aggregate metrics: AI can reconcile and aggregate metrics, ensuring alignment across datasets. It can also identify discrepancies and suggest ways to harmonize your data.

3. Ask Insightful Questions

AI’s value is rooted in the quality of the questions you ask. Start by going wide—explore a broad range of possibilities—before narrowing your focus on specific problems. This ensures you uncover unexpected patterns or opportunities.

Example questions to ask AI:

• What unexpected patterns emerged in our Q4 campaigns?

• Which marketing channels delivered the highest ROI growth?

• What were the key drivers influencing customer conversions?

4. Validate and Iterate

Treat AI as a collaborative partner. It thrives on feedback and iteration to improve its outputs. Here’s how to maximize its value:

• Spot-check results: Look for errors, inconsistencies, or unusual patterns.

• Test prompts across tools: Experiment with different questions or tools to see which provides the most useful insights.

• Refine your prompts: Adjust your questions based on initial results to uncover more depth or clarity.

5. Communicate Your Findings

Once AI delivers insights, focus on making them actionable and shareable.

• Visualize your data: Use AI to create charts, graphs, and other visuals for presentations.

• Translate findings into action: Develop clear recommendations based on the insights.

• Pressure-test your analysis: Align findings with broader business goals to ensure relevance and accuracy.

Pro Tips for Success

• Collaborate with AI: Use it to brainstorm, test ideas, and refine your prompts.

• Protect sensitive data: Use enterprise-approved platforms to avoid exposing proprietary information.

• Understand platform limits: Each AI tool has data size and complexity thresholds (e.g., free vs. paid versions).

• Prioritize accuracy: Always validate AI outputs before acting on them.

Looking Ahead: Building a Data-Driven 2025

Your 2024 marketing data isn’t just a record of the past—it’s a strategic asset that can shape your 2025 strategy. By incorporating AI-powered analysis into monthly or quarterly reviews, you can proactively identify trends, adapt to changing market conditions, and make data-driven decisions with confidence.

The ultimate goal isn’t just to understand what happened in 2024 but to turn those insights into smarter strategies for 2025. With AI as your strategic partner, your data has stories to tell. Are you ready to discover them?

Ready-to-use prompt that you can customize for your business needs:

"I’m a [insert your role, e.g., senior marketer] seeking to analyze my 2024 [insert data type, e.g., campaign, newsletter, or sales data] to uncover actionable insights and optimize strategies for 2025. Below is a detailed outline of my needs:

1. Data Context

• Type of Data: [Briefly describe your dataset, e.g., campaign performance metrics, engagement rates, or sales figures].

• Time Frame: The data spans [insert time frame, e.g., January to December 2024].

• Scope: Includes [insert scope, e.g., email campaigns, regional sales data, or customer feedback].

• Format and Size: Data is in [format, e.g., CSV, Excel].

Additional Info:

• [Describe any known issues or challenges with the dataset, e.g., missing values, inconsistent formats, or duplicates].

2. Objectives

I aim to achieve the following:

• Identify key trends, anomalies, and outliers.

• Assess the performance of [specific initiatives, e.g., a marketing campaign, product launch, or newsletter series].

• Pinpoint underperforming areas and high-growth opportunities.

Additional Info:

• [List any specific objectives, KPIs, or focus areas you’d like to add].

3. Workflow for Analysis

Step 1: Understand the Data

• Review the dataset’s structure, key columns, and any potential issues (e.g., missing or inconsistent data).

• Confirm priority metrics, segments, or questions to address.

Additional Info:

• [Highlight any priority areas or specific segments to focus on first].

Step 2: Identify Insights

• Summarize trends and performance metrics (e.g., engagement rates, ROI, sales growth).

• Highlight high- and low-performing categories or segments.

• Surface unexpected patterns, correlations, or opportunities.

Additional Info:

• [Provide any questions or hypotheses you’d like the analysis to explore].

Step 3: Create Visualizations

• Recommend visuals (e.g., bar charts, line graphs, heatmaps) to clarify trends.

• Confirm preferences for visual style and format.

• Generate visuals for review and refinement.

Additional Info:

• [Specify any preferences for visualization types, styles, or formats].

Step 4: Provide Recommendations

• Suggest actionable strategies based on findings (e.g., resource reallocation, A/B testing, optimizing underperforming areas).

• Confirm if additional analysis is needed to support recommendations.

Additional Info:

• [Indicate whether you’d like recommendations to focus on specific areas, campaigns, or strategies].

4. Customization Options

• Scope: Refine specific metrics, segments, or categories of interest.

• Data Types: Clarify if multiple datasets (e.g., social vs. email data) are included.

• Visuals: Specify preferences for visualizations (e.g., heatmaps, dashboards).

• Collaboration: Maintain a collaborative workflow, confirming direction and priorities throughout.

Additional Info:

• [Describe any customization preferences or unique requirements for analysis and deliverables].

5. Expected Deliverables

By the end of the analysis, I expect:

• A summary of key insights and trends across relevant dimensions (e.g., regions, product types).

• Clear, professional visualizations to illustrate findings.

• Actionable recommendations tailored to my objectives.

Additional Info:

• [List any specific deliverables or additional outputs you’d like to include]."

2025 PREDICTIONS POLL

CASE STUDY

How Zapier Leveraged AI to Streamline Go-To-Market and Drive Revenue Growth

In today’s dynamic marketing landscape, organizations are under immense pressure to align sales and marketing for maximum impact. Zapier, a leader in automation tools, has risen to the challenge by embracing AI to refine its go-to-market strategy and generate measurable outcomes. Through a partnership with Common Room, Zapier unified disparate customer data, unlocked actionable insights, and saw a tangible lift in meeting bookings and revenue.

Here’s how they did it—and what we can learn from their success.

The Problem: Disconnected Data and Missed Opportunities

Zapier faced a common issue: their data was scattered across platforms, making it difficult to see the full picture of customer behavior and intent. Without a unified view, identifying high-intent prospects and tailoring outreach at scale was a constant struggle.

The stakes were high: With thousands of businesses relying on their platform for automation, missing buying signals meant lost opportunities. Zapier needed a solution to consolidate their data and enable smarter decision-making.

The Solution: A Unified View with Common Room’s AI-Powered Insights

Zapier turned to Common Room, a go-to-market intelligence platform, to unify and enrich its data. Common Room aggregated customer signals from website, social media, support tickets, and CRMs into a single view. With AI, the platform identified high-intent prospects based on engagement patterns, product usage, and sentiment analysis.

For instance, when Zapier noticed a surge in questions around specific integrations within their community, they cross-referenced this activity with product usage data. This allowed the sales team to identify prospects primed for conversion and offer timely solutions.

The Results: More Meetings, Greater Revenue

Zapier’s investment in AI and data unification delivered measurable results:

• Higher Meeting Volume: By focusing on high-intent leads, Zapier saw a 31% boost in meetings booked.

• Faster Sales Cycles: With detailed customer insights at their fingertips, sales teams had more meaningful conversations, reducing the time it took to close deals.

• Revenue Impact: These smarter, data-driven engagements translated into substantial revenue growth, directly tied to the AI-driven improvements in lead prioritization.

Lessons for GTM Leaders

Zapier’s experience offers a blueprint for go-to-market professionals aiming to align their teams and accelerate growth. Here are three key takeaways:

1. Break Down Data Silos: Centralizing customer data enables a more complete understanding of your audience and their needs.

2. Use AI to Surface Priorities: Let AI do the heavy lifting by identifying patterns, uncovering opportunities, and highlighting the prospects most likely to convert.

3. Align Sales and Marketing: Unified data fosters collaboration between teams, enabling them to engage with prospects more effectively.

A New Standard for AI-Driven Growth

Zapier’s shows how AI can elevate go-to-market strategies from reactive to proactive. By leveraging insights hidden in customer signals, they turned data into decisions and decisions into results.

For businesses looking to scale smarter, Zapier’s approach is a testament to the power of integrating AI into your sales and marketing toolkit.

ICYMI

▪️AI Agents Will Make Your AI More Useful

▪️How to Choose the Right AI Tool for Your Marketing Needs

▪️Why Leaders and Employees Don’t See Eye to Eye  

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

▪️AI And Copyright: A Quick Marketing Guide

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