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Category: AI Labs

Why AI Agents Don’t Have to Be Scary

Posted on by Eric Keller

Halloween season is here! 

And while we’ve all been enjoying the costume parties, spooky decorations, and horror movie marathons, we want to take this opportunity to address some lingering fears marketers have about AI Agents.

While most teams are excited about AI’s potential, there are still a few concerns worth addressing.

(Don’t worry, these aren’t nightmare-inducing concerns. Once you take a closer look, you’ll see there’s a lot to be hopeful about!)

Fear #1: “Will AI Agents Replace Us?”

This has been an ongoing concern for several years now, especially with rapid improvements to AI. And it’s totally understandable. 

But there’s a compelling line of thought that AI Agents can enable businesses to achieve more, which necessitates larger teams to handle increased workloads. 

In other words, AI can lead to more headcount, not less.

We wrote an entire article about this a few months ago, which you can check out here: “Can AI Create More Jobs Than It Replaces?”

In that piece, we discuss how we automated a client’s campaign operations in a way that reduced launch times so dramatically that demand surged. This required them to triple their team from 2 to 6 people. 

Just as adding highway lanes attracts more drivers over time rather than reducing traffic, AI can act as an amplifier that creates opportunities for growth rather than simply replacing workers. 

The key is to remain adaptable and view AI Agents as tools that reshape roles and unlock new possibilities. Agents can enable small teams to do more than they imagined, and help large teams be more efficient than ever before.

Fear #2: “Yet Another Platform to Learn?”

Marketing teams already manage a complex tech stack. Marketo, Salesforce, analytics platforms, project management tools, and so on.

Adding yet another interface to this mix is off-putting for many. You need training, adoption, change management, and before you know it, that shiny new AI tool becomes forgotten.

It’s a legitimate concern, which is why we designed Otto (an AI teammate for Marketing Ops) in a way that integrates with the tools you already use.

We also wrote a piece on this titled, “Otto Meets You Where You Work”.

We detailed how you can chat with Otto in Slack, tag it on Asana tasks, or integrate it with any other ticketing platform you use. There’s no need to learn a new platform or interface.

And this natural integration reduces friction when it comes to the user experience and ultimately improves adoption. 

Fear #3 “Will AI Agents Kill My Creativity?”

It’s easy to understand where this fear comes from. 

With AI able to do things like write copy, generate images, and plan campaigns, many creative marketing professionals are wondering: What’s left for me?

If AI is handling more and more tasks, will our work lose its creative problem-solving element?

But that’s not what AI Agents are about. Agents like Otto don’t take over the creative process; they clear the path for it.

By handling the repetitive, operational work that eats away at your day, AI Agents give marketers back the space to think, explore, and experiment.

Less time cloning programs, importing lists, updating email templates, and so on, means more time on strategy and creative problem-solving that will be hugely impactful in the long run.

While these concerns are definitely valid and worth discussing, AI Agents don’t have to be scary. They can be dependable teammates who help you work faster, think bigger, and accomplish more. 

As marketers living in this unprecedented era of AI, we will thrive by embracing change and finding new ways to collaborate with technology.

And if you want to learn more about Otto, the AI teammate for Marketing Ops we’ve designed, go here.

Happy Halloween! 🎃

What OpenAI’s Agent Builder Means for Marketers

Posted on by Eric Keller

The last 12 months have been huge for AI Agents. 

Last December, Salesforce showcased “Agentforce 2.0”. Then, back in March 2025 at Summit, Adobe announced new AI agents for its Experience Platform. Shortly after that, HubSpot introduced “Breeze Agents”. And just a few months ago at RP, we launched Otto – your AI teammate for Marketing Ops. 

The next major leap for AI agents came just weeks ago, on October 6, 2025, when OpenAI unveiled its new Agent Builder at DevDay. 

Today, we’re going to look at OpenAI’s Agent Builder, how it compares to the way we currently build agents with various iPaaS solutions, and what this all means for Marketers going forward.

OpenAI’s Agent Builder: A Quick Primer

At a high level, Agent Builder provides a visual canvas where users can create workflows with drag-and-drop nodes. You can compose logic, set guardrails, access a Connector Registry to see what connectors are active in your workflow, and even use RAG (Retrieval-Augmented Generation) capabilities for leveraging files and knowledge bases. 

All of that is a great step forward, but it isn’t perfect yet. Agent Builder only supports a limited number of native connectors and relies heavily on MCP (Model Context Protocol), which is a standard for linking AI systems with other apps. 

As it stands, HubSpot maintains an official MCP server, Salesforce is piloting one, and several third-party options are available for Marketo. But overall, the MCP ecosystem is quite young. While MCP in itself is a good solution, the fact that Agent Builder relies exclusively on such an underdeveloped protocol will pose some challenges.

With that aside, what makes the Agent Builder particularly interesting – beyond the welcomed visual approach to building workflows – is its adaptability. Agents built with OpenAI’s platform can reason dynamically. Meaning, they can decide which step to take based on context. 

While this opens up a world of possibilities when it comes to autonomous decision-making, dynamic reasoning isn’t always preferred, which is where the current iPaaS solutions come in.

Current iPaaS Landscape

For anyone unfamiliar with the concept, iPaaS stands for Integration Platform as a Service. These platforms act as “universal adapters” for software, connecting different apps together like Salesforce, Marketo, Slack, etc., so they can talk to each other and share data. 

Today’s iPaaS solutions have matured significantly. Here’s a brief overview of some of the major ones and what they’re typically used for:

  • n8n: Open-source platform supporting AI agents that make autonomous decisions, multi-agent systems, and integration with various LLMs beyond OpenAI

  • Zapier: 8,000+ integrations with AI Agents using natural language, though following predetermined workflows rather than adaptive autonomy

  • Workato: Enterprise-grade with advanced error handling, retry logic, and monitoring capabilities for mission-critical operations

  • Power Automate: Deep Microsoft 365 integration with AI Builder, supporting both RPA and digital process automation

When to Us What: Agent Builder vs. iPaaS

The fundamental difference between Agent Builder and other iPaaS solutions lies in their approach to automation. 

Agent Builder is a shift towards AI-native automation, where AI is determining the best path forward through fluid, conversational workflows. They’re ideal for tasks like intelligent customer support, content generation with context, exploratory data analysis, and other tasks where flexible reasoning is built in. 

Some AI-focused iPaaS solutions can handle conversational workflows too, but unlike Agent Builder, they excel at providing granular control over predetermined processes. They are great when you need practical workhorses for structured, repeatable tasks such as syncing records, triggering campaigns, or managing approvals. 

This is especially important when you want to automate processes that require a specific, enforced order of predetermined tests. 

For example: 

When importing a set of leads to Marketo, there’s a very specific order of API calls we must do. First, we have to create the job, then begin the job, then query the job status until it’s completed, then get the finalized import. The API calls must be in this order, and an iPaaS solution like n8n or Zapier allows us to enforce this order while OpenAI’s Agent Builder does not. 

The Path Forward

Over time, we think it’s likely that these categories will merge. OpenAI will expand its ecosystem, and iPaaS vendors will deepen their AI features. Marketers will find that the future of automation isn’t about choosing one over the other; it’s about combining autonomous intelligence with good infrastructure to get the best of both.

The next generation of marketing automation won’t just run scripts. It will understand goals, adapt to given context, and collaborate with teams. And that’s exactly what inspired Otto, our own AI teammate for Marketing Ops.

We designed Otto to integrate with the apps you already use, carefully assembling according to each client’s existing tech stack and governance model. It feels like working with another teammate in Slack, and it is ultimately designed to help more marketers do their best work.

If you want to learn more about Otto, go here.

We’re optimistic about AI Agents and where all this is headed. We can’t wait to see what major breakthroughs come next!

Otto Meets You Where You Work

Posted on by Eric Keller

When marketing teams bring on a new tool, the biggest hurdle often isn’t the technology; it’s adoption.

Asking marketers to log into yet another platform means learning a new interface and adjusting their workflows. 

Before you know it, a shiny new AI tool becomes another browser tab that sits forgotten, competing for attention with the dozen other platforms that teams already struggle to manage.

At Revenue Pulse, we’ve recognized this fundamental adoption barrier. So we designed Otto (your AI teammate for MOPs) to meet teams where they are.

Otto’s Native Integration

Instead of requiring teams to learn another interface, Otto adapts to your existing workflows and lives inside the applications you already use daily.

For example:

  • Marketing Ops Specialists can chat with Otto directly in Slack, just like they would with any other teammate. Otto will respond with progress updates, ask follow-up questions, and provide any additional information as needed. Interactions feel natural and intuitive. 
  • Project Managers can simply tag Otto on an Asana task and ask it to “work on this”. Otto will respond right there in the comments section of the task with progress updates and additional information.

In addition to Slack and Asana, Otto can run natively in any other ticketing system or communication platform that your team is accustomed to. 

This natural integration reduces friction when it comes to user experience and ultimately improves adoption. There’s no training on a new interface, no passwords to remember, no bookmarks to save. Teams start working with Otto using the communication patterns they already know.

Assembling Otto for Your Team

Behind the scenes, what makes Otto powerful is the way we assemble it to your company’s specific tech stack, use cases, and business goals.

That assembly process is where our marketing operations expertise comes in. We configure Otto not only to understand Marketo, but also to understand your specific Marketo instance. Your programs, your workflows, your governance, and everything else that makes up your unique digital environment.

The result is a teammate who’s not only technically skilled but context-aware, so the output aligns with your strategy and processes.

If you’re ready to see how Otto can be assembled to fit your tech stack, book a free call with us here!

 

5 Marketing Ops Tasks That AI Can Do for You

Posted on by Eric Keller

Marketing Operations specialists are drowning in repetitive tasks.

Managing lead databases and setting up campaigns takes countless hours of manual work – not to mention the constant stream of requests from stakeholders.

And while these tasks are critical, they take away from strategic initiatives that can transform their organization’s marketing performance.

This is where AI Agents are changing the game.

Unlike traditional automation, AI Agents can understand context, make their own decisions, and execute complex, multi-step tasks that are normally reserved for humans.

At Revenue Pulse, we’ve built “Otto”: your AI teammate for Marketing Operations.

Otto seamlessly integrates with your Marketo instance, and lives in the apps you already use; you can chat with it in Slack and even tag it in Asana (or other ticketing systems), just like you would with any other teammate.

Otto is constantly learning new skills too. And while it would be impossible to go through every single thing Otto can do right now, we’re excited to showcase 5 tasks that most MOPs pros would be more than happy to delegate.

Let’s jump right in!

1. Merge duplicates in Marketo

In Slack, ask Otto to find a specific lead. Otto will search your Marketo instance for that lead and display any duplicates. Tell Otto to merge the records, and it will perform the merge for you automatically. You can then switch to Marketo to confirm there is now a single record for that lead. If needed, you can repeat the same steps for other leads without leaving Slack. 

2. Create webinar programs in Marketo (from Asana)

In Asana, simply comment “Otto, work on this” on a webinar creation ticket. Otto will then create a webinar program in Marketo from your template. It’ll place the program in the correct folder, leave Smart Campaigns deactivated, and fill the required tokens. You can see the program start to appear in Marketo as the build completes. Otto then posts a brief summary of what it created, so you know exactly what changed!

3. Send test emails

Once your webinar program is created, you can also ask Otto to send a sample of the follow-up email so you can review the exact content and formatting. After you confirm it looks right, tell Otto to activate the Smart Campaigns for attendees and no-shows. Otto turns those campaigns on and lets you know when everything is ready.

4. Create Salesforce campaigns that sync with Marketo programs

This time, let’s head back to Slack. When you ask Otto to create a program, it’ll build it in Marketo and update tokens. But it doesn’t end there. Otto will also create a matching Salesforce campaign with the required campaign member statuses. The statuses in Salesforce match the ones in Marketo, so both systems are aligned.

5. Import lists to Marketo

Send Otto a lead file (such as a CSV) and tell it which static list to import to. Otto will find the list, run the import, and report back with the results—including how many leads were processed and any failures that occurred. Just refresh your Marketo list to see the leads appear!

These are just a few examples of the time-consuming and repetitive MOPs tasks that Otto can take off your plate! And we’re developing new features and capabilities for Otto every day. Follow us here to be the first to know when new skills become available.

If you want to learn more about how Otto can help your team, book a personalized walk-through here.

Meet Otto: An RP AI Service Solution [Webinar]

Posted on by Eric Keller

We’re incredibly excited for you to meet Otto – our new service solution that’s going to change Marketing and Campaign Ops forever.

Join Joseph Peters, Darrell Alfonso, Lucas Gonçalves, and Andy Caron in the webinar above to see Otto in action!

Click the button below to book your personalized walk-through of Otto today.

Meet Otto

Which Is the Best AI for Email Copywriting? [May 2025]

Posted on by Eric Keller

Over the past few months, major LLMs like Anthropic’s Claude 3.5 Sonnet, Claude 3.7 Sonnet, and ChatGPT-4.5 have significantly improved in writing quality.

But with so many options available, which AI is the best for email copywriting?

To find out, we conducted an experiment that evaluated how different LLMs and AI-powered writing assistants produce marketing email copy. Click the button below to view the report (and the results!):

View Report

Note: This report was published on Tuesday, May 13th, 2025. Any new models or AI advancements after this date are not included in our testing!

Can AI Create More Jobs Than It Replaces?

Posted on by Eric Keller

Many marketers and professionals across industries share an understandable fear:

AI could soon make their roles obsolete.

Headlines over the past year regularly warn us that sophisticated AI models could replace numerous jobs.

But is that the full story? Not necessarily.

There’s a compelling line of thought that AI and automation might do precisely the opposite in many scenarios: When certain processes become more efficient, demand skyrockets. And this leads to more headcount, not less.

So, instead of shrinking teams, AI can enable businesses to achieve more, which necessitates larger teams to handle increased workloads.

You don’t have to take our word for it either. Here’s a real-world scenario we experienced that showcases this idea in action ⬇️

(Note: We are discussing these ideas with a short- to mid-term timeframe in mind. AI advancements are moving so quickly that it’s impossible to predict how things will look even 5 years from now.)

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Efficiency Gains Can
Create More Jobs

One of our clients (whose name we won’t disclose) had a team of 2 full-time campaign operations specialists who were overwhelmed by requests.

Each campaign took several hours, even days, of manual effort to complete. They had to clone programs, update emails, sync campaigns with Salesforce, and so on.

So, we came in and implemented a sophisticated ticketing system with robust automation that streamlined the entire process. The result was that the time to launch campaigns dropped dramatically.

The improvement was so pronounced that we all expected the team to do the same work with even fewer people.

Instead, the opposite happened.

With barriers removed and launch timelines shortened, the ease and speed of launching campaigns led to a massive surge in overall campaign volume. It quickly became too much for only two people to handle.

To keep up with demand, team headcount tripled from 2 to 6.

Greater efficiency led to more work, and ultimately, more people on the team.
 

Why Did This Happen?

It’s true that technology enables us to “do more with less.” But it doesn’t stop there. In reality, making something easier or faster often means people will do a lot more of it.

There’s a classic economic principle for this called Jevons’ Paradox. Put simply, it observes that increasing efficiency doesn’t always decrease consumption; in many cases, it increases it. This paradox originates from William Stanley Jevons. In the 19th century, when the use of coal became more efficient, Jevons noticed that coal consumption went up instead of down.

Think of AI and automation like expanding a highway. Initially, you might add lanes to ease congestion, with the expectation that there will be less crowded roads. But as traffic flows more freely, more drivers decide to use that route. Now the added lanes are starting to fill up. Before you know it, 2 lanes become 6 lanes (just as headcount tripled from 2 to 6 in our previous example).

The efficiency provided initially reduced traffic, but over the longer term, it increased demand.
 

AI as an Amplifier

This is where AI gets particularly exciting. It is the ultimate “efficiency gain” tool right now. LLMs (Large Language Models) and reasoning models from big players like OpenAI, Anthropic, and Google are rapidly improving, unlocking all sorts of new use cases and opportunities for amplified efficiency.

Broadly speaking, it’s helping knowledge workers across industries create content faster, generate data insights, streamline operational tasks, and more. At RP, we are constantly trying to push the envelope to integrate AI in safe and exciting ways.

And with Jevons’ Paradox in mind, AI becomes an amplifier that creates demand for more headcount, not a straight replacement for existing workers.

This has some major implications for those in leadership positions as well. A company that implements AI and robust automation, intending to reduce headcount, must strategically prepare for the possibility that the opposite could happen; more headcount could be needed due to increased demand.

Ultimately, successful AI implementation involves anticipating shifts in team structure, workload management, and workforce allocation. Businesses must become adept at not just deploying technology but also managing the growth and scalability that these innovations naturally encourage.

(If you’re looking for a starting point and a roadmap of what that AI implementation could look like for your company, check out our free AI Assessment Tool.)

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While the fear that AI might render certain roles obsolete is understandable, we want to highlight the importance of staying optimistic and adaptable.

Things are changing very quickly, but it’s not all doom and gloom! AI has the potential to reshape jobs, unlock new pathways and possibilities, and create unprecedented demand.

If you have any questions about how your company can boost marketing operations efficiency using AI and automation, you can book a free 30-minute chat with us here.

What are AI Agents and Why Should Marketers Care?

Posted on by Eric Keller

A few weeks ago, Adobe announced a series of new AI-powered “agents” at Summit 2025.

These agents will be designed to assist marketers and streamline tasks within their existing workflows, covering a wide range of use cases within Adobe’s tools.

The Marketo Journey Builder, one of the newly announced agents, is particularly interesting to us. We’ll take a closer look at it below, but as the name suggests, it’s intended to help marketers build and optimize campaign journeys with much greater efficiency.

If the concept of an “AI agent” is new to you, don’t worry. In this article, we’re going to explore:

  • What AI agents are (and why you should care)
  • Adobe’s new AI agents
  • Other great AI agents available for use right now

Let’s get right into it!

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What Are AI Agents (and Why Do They Matter)?

Essentially, an AI agent is a specialized assistant that can independently carry out preprogrammed multi-step tasks or workflows on a user’s behalf. They actively execute these tasks, make decisions with predefined goals, and can even interact with other software and tools.

In order to understand where we’re at with AI agents (and where we’re headed), let’s break down AI agent progression into 3 tiers ⬇️

1. Basic Assistants

These are the early assistants we’re all used to, like Alexa, Siri, and so on. These assistants are largely reactive, meaning they can answer questions, set reminders, play your music, or turn on your lights when asked. They’re useful (some more than others) but they operate within very fixed parameters and only respond to direct commands. They don’t carry out multi-step goals.

2. Workflow Agents

This is where we’re at right now. These are things like Agent.ai, OpenAI’s Operator, Adobe’s upcoming agents, and more (we’ll go into more detail on all of these below). This current generation of agents is far more capable than the basic assistants. They can handle complex, multi-step tasks by interacting with other software on your behalf, even going as far as controlling an entire web browser.

There are more general AI agents like OpenAI’s Operator that can perform a wide variety of tasks, as well as platforms like Agent.ai that host more specialized agents dedicated to niche use cases related to marketing, sales, etc.

It’s important to remember that the agents we have today aren’t fully autonomous (yet). They still work under human-defined goals and execute a sequence of programmed actions.

3. Fully Autonomous Agents

Which brings us to the future of AI agents. While we don’t know how long it will take to get there, eventually we may see fully autonomous agents that can tackle high-level objectives with almost no oversight. Ideally, we ask them to do something, and they figure out the sub-tasks and decisions along the way by themselves. The current iterations of autonomous agents are hit-or-miss and often require a lot of course correction. But we’re headed towards a future of fully autonomous “digital co-workers”.

So, why do AI Agents matter for marketers?

In a nutshell, these tools have the potential to massively increase efficiency and scale. Instead of just answering a question in a chat window, an AI agent may handle the entire process.

For example, they may be able to find leads in a CRM, email them a tailored intro, and schedule follow-ups. And on a smaller scale, they can significantly streamline day-to-day work by automating repetitive tasks entirely, such as segmenting audiences, personalizing campaigns, or analyzing journey performance.

Ultimately, it comes down to freeing up time so marketers can put more emphasis on creative, strategic activities that AI can’t replicate. AI agents help us do our best work, faster.

 

Adobe’s New AI Agents

As we mentioned earlier, the big theme of Adobe Summit 2025 was “Agentic AI” (check out our full recap of Summit here if you couldn’t attend!). In total, 10 new AI agents were unveiled at the conference. They’re each designed for specific workflows and are integrated into the Adobe Experience Cloud.

The agents at launch include:

  • Account qualification agent
  • Audience agent
  • Content production agent
  • Data insights agent
  • Data engineering agent
  • Experimentation agent
  • Journey agent
  • Product advisor agent
  • Site optimization agent
  • Workflow optimization agents

With more on the way soon.

And part of this launch was the introduction of the “Agent Orchestrator” in Adobe’s Experience Platform, which allows users to build and manage AI agents all in one place.

One particular highlight for us (along with many other Marketo users) was the Marketo Journey Builder Agent. Essentially, it is the aforementioned Journey agent embedded into Marketo Engage. It offers a new visual journey builder canvas for designing lead-nurturing campaigns with an AI agent working behind the scenes as a co-pilot.

In practice, this means the agent can suggest the next best touchpoints, identify if certain leads are “dropping off” at a stage of the journey, and even suggest a re-engagement path. Overall, it’s promising smarter campaigns with less effort. Newer marketers can lean on the agent’s recommendations to create effective campaigns, while more experienced marketers can iterate and refine campaigns faster than ever (by letting the agent automate tasks such as pulling performance reports or doing a segment analysis).

It’s like having a marketing strategist and automation expert rolled into one – and they live inside your Marketo instance!

 

Other AI Agents You Can Try Today

If you want to explore more AI agents, here are three platforms making waves that cover a wide variety of use cases:

Manus – A fully autonomous general-purpose AI agent. You can give Manus a goal or task, and it’ll attempt to handle all the steps to achieve it across web research, content creation, data analysis, and so on. Manus boasts that it “bridges minds and actions” by not just thinking, but delivering results. It’s like a personal executive assistant that never sleeps, though it’s a relatively new product, so expect ongoing improvements.

Agent.ai – Created by Dharmesh Shah, co-founder and CTO of HubSpot, Agent.ai is a platform where users can find and “hire” AI agents for repetitive and time-consuming work, and build their own agents for custom use cases. Through their Agent Network, marketers have access to hundreds of AI agents for tasks like company research and conversion rate optimization. With the Agent Builder, users can create custom workflows that combine existing agents, major AI models (ChatGPT, Claude, Gemini, etc.), YouTube, X, and HubSpot features to create new agents for unique use cases.

OpenAI Operator – Announced as a research preview in early 2025, Operator is essentially ChatGPT with the ability to take actions on the web. It uses a built-in browser to click, scroll, and input data on websites.​ For example, you can ask Operator to “Log into our Zendesk account, filter support tickets from the past 30 days for Product X, download the data, and summarize the top three customer frustrations mentioned in the tickets.” It will complete this multi-step task by navigating real tools online. Right now (as of April 2025), Operator is available to ChatGPT Pro subscribers in the U.S. as OpenAI gathers feedback.

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For marketers, AI agents like these offer a path to greater scalability and efficiency. We’re moving beyond using AI predominantly for insights or content creation, towards AI that takes action and executes complex, multi-step tasks to free up more time for higher-value work.

It’s an exciting time to be in marketing ops, as we continue to experiment with (and benefit from) these digital helpers that are reshaping our processes.

If you have any questions about AI agents or want to chat about optimizing your marketing and sales operations, reach out to us here!

AI Assessment Tool with Lucas Gonçalves

Posted on by Eric Keller

Where do companies actually start when it comes to “integrating AI?”

There is constant discussion about how AI is a game-changer. But successfully adopting AI on a company-wide scale requires careful planning, assessing, pivoting, and more.

And doing all this requires time that most organizations don’t have.

This is why we created a fully automated AI Assessment tool.

It’s pretty straightforward. Just complete a short questionnaire, and our AI Assessment tool will automatically generate a personalized report that details:

  • Where your company currently stands regarding AI adoption readiness
  • A customized roadmap your company can follow for successful AI integration.

To shed some more light on how our AI Assessment tool works and why it’s essential for businesses right now, we sat down with RP’s Director of AI & Automation, Lucas Gonçalves.

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For those who may not know Lucas, he is a Marketo Champion with a strong background in computational mathematics and several years of experience working with AI and machine learning. When ChatGPT 3.5 launched in November 2022, Lucas led RP’s initiative to explore various AI use cases in Marketing Operations. Over the past few years, he’s presented at multiple MUG events, Adobe Summit, and several RP webinars.

Today, Lucas continues to pioneer practical ways that marketers can benefit from AI — with RP’s AI Assessment tool being the latest example.
 

Why is RP’s AI Assessment tool important?

Lucas: In Marketing Operations, we are continuously discussing AI use cases and how AI can boost productivity and efficiency. But these are use cases that benefit individual tasks (ie. using AI in Marketo to optimize email send times, perform email sentiment analysis, and more).

There hasn’t been a structured approach that companies can use to understand the steps they should take to achieve wider-scale AI adoption. Until now!

This AI Assessment report is the perfect starting point that will add structure and clarity to the AI adoption journey. It will help leadership teams get engaged and excited, offering a strategic-fit framework that highlights the stepping stones needed to reach their AI goals.
 

What is RP’s AI Assessment tool?

Lucas: At its core, the AI Assessment tool is built on a set of questions that have been carefully designed to help generate a report on where your company is on its AI adoption journey.

The tool uses an AI adoption framework we created that consists of 4 levels:

  • Level 1: No Adoption – Individuals are using AI on their own without company approval, support, or assistance. In many cases, employees are breaking company policy by using AI.
  • Level 2: Individual Adoption – The company supports the use of ChatGPT or other LLMs on an individual level for daily tasks, but no company-wide integration exists.
  • Level 3: Organizational Adoption – The company has deeper, customized AI integrations that are tailored to their needs and processes.
  • Level 4: Overall Adoption – The company has reached a point where several custom AI integrations are in place with minimal issues.

The generated AI Assessment report will tell you which level your company is at (in our experience, most are between levels 1 and 2 right now). But it’s not just an evaluation of your current situation. It will also give your company 3 to 5 things to focus on, with a personalized road map on how to advance adoption.
 

Is the AI Assessment report generated by AI?

Lucas: The report itself is “AI-augmented”. While AI does build most of it, human eyes are making sure the end result is useful. And to be clear, the report you receive isn’t raw AI responses that you’d get from going to ChatGPT. We are using AI models and agents that are carefully trained on RP’s perspective, with guard rails in place to make sure the information you receive is accurate, relevant, and practical.
 

How is the AI Assessment report structured?

Lucas: The report will start with an executive summary followed by a brief introduction section. Then, it will cover 5 main areas of focus, divided into 3 “foundations for AI” and 2 types of “gains” as outlined below.

3 Foundations for AI:

  1. Team and Skills: Are team members comfortable with AI? Trained to use AI?
  2. Data: Is your data clean, structured, and ready to be fed into AI systems?
  3. Strategy: How can AI connect multiple areas such as Marketing, IT, Sales, etc?

2 Gains from AI:

  1. Customer Experience Gains: Better, more relevant copy, more optimized landing pages, better outreach timing, etc.
  2. Operational Efficiency Gains: Shorter time to launch new campaigns, reduced administrative overhead for projects, etc.

 
Where (and when) is the AI Assessment tool available?

Lucas: It is available right now for free here!

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We’re incredibly excited for you to give our new AI Assessment tool a try.

And if you have any questions or comments for Lucas and the rest of our team, don’t hesitate to reach out to us.

AI + Marketo: How to Implement 3 High Impact, No Risk Solutions

Posted on by Eric Keller

Whenever AI is mentioned in the workplace, there are normally concerns over data privacy, security, and compliance (and rightfully so).

So, how can marketers safely integrate AI into their work?

We answered this question by showcasing 3 AI use cases that protect your data, while still producing high-impact results.

It all happened last week in our event titled: “AI + Marketo: How to Implement 3 High Impact, No Risk Solutions”.

Hosted by: Andy Caron (President, RP), Lucas Machado (Director of AI & Automation, RP), and Tyron Pretorius (Owner, The Workflow Pro).

If you missed it, you can watch the FULL recording above!

Here’s a quick overview of what we covered.

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Before we get into the specific use cases, we went through a few “AI Fundamentals” including the differences between general models and fine-tuned models, pricing, and compliance.

Then, we went deep on the ChatGPT-Marketo connection, including the use of webhooks, integration platforms, and the Marketo API.

After that, we covered 3 specific use cases (with a bonus use case at the end):
 

1. Sentiment Analysis

For this, we demonstrate how to perform a sentiment analysis of your Marketo emails using ChatGPT, leading to enhanced content that resonates with your audience and improves open rates, click-through rates, and conversions.

Follow along with the webinar or read our in-depth guide here.
 

2. Finding the Best Email Send Times

Here, we show how you can extract email interaction data from your Marketo instance and use ChatGPT analysis to answer the age-old question: When is the best time to send emails?
Follow along with the webinar or read our in-depth guide here.
 

3. Persona Classification

Traditional classification methods often fall short due to constantly changing job titles, industry terms, and other parameters. The good news is, we can create our own fine-tuned GPT that understands the patterns of these term changes, then integrate directly into Marketo for enhanced persona classification.

Follow along with the webinar or read our in-depth guide here to learn how it’s done.
 

4. Sales Acceleration (BONUS)

For our final use case, we show you how to integrate ChatGPT, Marketo, and your CRM with an IPaaS solution like Zapier or Workato to automatically generate reports for your sales team – instantly contextualizing MQLs so your reps can have effective conversations that close more sales.

Follow along with the webinar or read our in-depth guide here.

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If you have any questions about integrating AI with Marketo, don’t hesitate to reach out to us!