Building Your First AI-Driven Marketing Campaign

In this episode of the AI in Marketing: Unpacked podcast, it’s the fourth of a 4-part series designed to help you quickly get up to speed on key concepts and ideas as it relates to AI in marketing and your professional career.

1. Episode 1: Introduction to AI in Marketing
2. Episode 2: How AI is Transforming Social Media Marketing
3. Episode 3: Essential AI Tools and Technologies for Marketers
4. Episode 4: Building Your First AI-Driven Marketing Campaign (you are here)

Each of these bite-sized episodes is designed to take you just a little bit deeper into the world of artificial intelligence, and leaving you in control of how fast you go. Listen to them all at once, or take ’em one at a time and give you mind time to process what you’re learning. The choice is yours.

Future episodes of AI in Marketing: Unpacked will be a combination of guest experts in marketing and AI, and solo episodes with just me, Mike Allton. I may even bring on a surprise guest host or celebrity guest from time to time, so make sure you subscribe so you don’t miss future episodes. (Find us on Apple or Spotify, or wherever you enjoy listening to great podcasts.)

Now that that’s out of the way, let’s get into today’s episode introducing you to the impact AI is having on social media marketing. The idea here was to provide you with a step-by-step guide on how to plan, execute, and measure an AI-driven marketing campaign. Including how to provide AI with necessary data, and even how to prompt it.

Key Points:

  ✨ Planning and defining objectives with AI considerations.

  ✨ Executing the campaign using AI tools for optimization and automation.

  ✨ Measuring success and iterating based on data-driven insights from AI.

Key Tools or Resources Mentioned:

  ✨ Campaign Planner

  ✨ Magai

Full Transcript of Episode 4: Building Your First AI-Driven Marketing Campaign

(Lightly Edited)

Greetings, Program! Welcome back to ‘AI in Marketing Unpacked’. I’m your host, Mike Allton, and today we’re diving into something incredibly practical: how to actually build your first AI-driven campaign. If you’ve been following along, you’ve learned about the basics of AI in marketing and explored some essential AI tools and technologies. Today, it’s time to put that knowledge into action.

This exercise is designed to get you thinking – and actually exploring – how AI can help you in your marketing. Campaign-building is a core competency for marketers and it’s something I’ve talked a lot about throughout articles on my blog, The Social Media Hat. I even have a campaign planner marketers can download and use to help you with sales, product launches, or just general initiatives.

What’s powerful in the steps we’re about to walk through is what AI brings to the table – incredible analysis and knowledge. For instance, one of the steps we’re going to talk about is feeding AI data about your business and target customers. The more you can inform AI, the more likely it will be able to craft incredibly effective recommendations.

This is one of the key differentiators between a human marketer and AI – we simply don’t have the capacity to read, process, and analyze massive amounts of data like AI can. Tools like ChatGPT or Claude – or your own internal AI if you’re analyzing proprietary data – can not only reach conclusions swiftly, they can identify gaps in our thinking or past approaches, and even be prompted to ask us questions to help us all arrive at a brilliant marketing strategy together.

Creating an entire campaign with AI might even sound daunting, but I promise you, it’s not as complicated as it seems. With the right steps and tools, you can craft a campaign that’s both data-driven and highly effective. Let’s get started.

Planning Your AI-Driven Marketing Campaign

Every successful campaign starts with a solid plan. When integrating AI, the planning phase becomes even more crucial, and is one of the ways this process will begin to feel a little different than past campaigns you’ve worked on. But I promise you, that difference is what will help make these campaigns more successful than any you’ve ever launched. And, ultimately, you’ll save time too. Perhaps not the first or second time you go through this process as there’s training of both you and the AI that has to occur, but like any great intern, once the process has been nailed and followed a couple of times, it’ll happen smoothly and effectively each time thereafter.

Begin by setting clear, measurable objectives. What do you want to achieve with this campaign? Whether it’s increasing brand awareness, driving sales, or boosting engagement, defining your goals will help shape the entire strategy.

First, ask yourself what specific outcomes you’re aiming for. Are you looking to boost your email open rates by 20%? Or maybe you want to increase social media engagement by attracting more likes, shares, and comments? Whatever your goals, make sure they are specific, measurable, achievable, relevant, and time-bound—yes, good old SMART goals.

Next, identify the key areas where AI can make a difference. For instance, you might use AI for audience segmentation, personalized content creation, or optimizing ad placements. The key is to be specific about how AI will enhance each component of your campaign. If you’re unsure where to start, consider areas where your current strategies are falling short or where you spend an inordinate amount of time.

Setting Up for Success: Gather all necessary data before you begin. This means customer data, behavioral insights, and any historical campaign data you have. The quality of your data will directly impact the effectiveness of your AI tools. Clean and organize this data to ensure it’s ready for analysis.

This is one of those areas where you’ll spend more time up front, initially, but in future campaigns you will have already done most of the work and the AI will have this information already and be standing by to work on your next campaign.

Consider creating a data checklist:

• Ensure data accuracy by removing duplicates and correcting errors.
• Segment your data based on customer behaviors, demographics, and purchase history.
• Integrate data from various sources to create a comprehensive view of your audience.

Remember, the better your data, the more precise and valuable your AI insights will be. Use this data to inform your strategy and align your AI-driven efforts with your overall marketing goals. By starting with a clear plan and clean data, you set a strong foundation for your campaign.

Now, if you’ve never input data like this into an AI, you might be wondering how it actually works and what the best way to go about it might be. So let’s talk about how to feed this data into AI tools like Magai or ChatGPT. These AI tools typically require data to be structured in a certain way to generate the most accurate and useful outputs.

Data Formats and Best Practices:

• Structured Data: AI tools work best with structured data—think CSV files, spreadsheets, or databases where information is organized in rows and columns. Ensure your data is clean, meaning free of duplicates and errors.
• Text Data: For text-based tools like ChatGPT, plain text files or formatted input where each piece of data (like customer inquiries, social media posts, etc.) is clearly separated can be very effective.
• Contextual Data: Providing context is crucial. Tools like Magai and ChatGPT benefit from context-rich inputs. For instance, if you’re feeding in customer feedback, include information about the product or service they’re referring to.
• Data Size & Quality: While volume can be helpful, quality trumps quantity. Ensure the data is relevant and representative of the scenarios you want the AI to understand.

For instance, if you are sharing past campaign data and have inconsistent date formats, the AI may not correctly understand when or how long those campaigns ran. Similarly, if you’re sharing past posts or campaigns that aren’t categorized consistently, it can lead to misinformed recommendations or reporting. Take the necessary time to clean up those inconsistencies and build your data files properly.

Uploading Data: If you have a CSV file, you can typically upload it directly into AI tools that support file uploads. This is common with more advanced AI platforms and customer management tools that have built-in AI features. Bear in mind that subscribing to a tool like Magai gives you access to all of the major model’s paid features, for one low monthly subscription, so that’s what I use and recommend. For free tools, which may not support direct file uploads in a conversational interface, you would need to copy and paste the relevant parts of the data. Be mindful of the context and formatting to help the tool understand the input accurately.

AI Prompts for Data Input & Analysis

Now, one other aspect of working with AI is prompting – telling the AI what you want to talk about or accomplish. You’ve likely heard of prompts or prompt engineering but if you haven’t yet had a conversation with an AI tool like ChatGPT, the prompt is simply what you say to the AI to elicit a response.

In this use case, we want to prompt the AI to look at the data we’re giving it, draw conclusions, and provide recommendations. Because AI is conversational, this more like talking to a person than, say, the programmed chatbots you might be familiar with from years past. Those chat widgets where you could program specific questions and conversation flows and structure, but which were completely limited by the questions and responses you programmed in advance. AI is nothing like that all. You can ask whatever questions you want, in whatever format or order you wish, and the AI will make every effort to respond.

Here are some examples of prompts to help with this part of building a marketing campaign.

Sharing Data Prompts:

First, let’s talk about sharing data with the AI.

1. Customer Feedback Analysis: “Here is a CSV file of customer feedback from the past six months. Each entry includes the customer’s name, feedback text, product purchased, and date of purchase. Please analyze the feedback for common themes and sentiments.”
2. Sales Data Evaluation: “I have uploaded a spreadsheet containing our sales data from the last year. The columns include product ID, product name, date of sale, sale amount, and customer ID. Can you analyze this data to identify the top-performing products and any seasonal sales trends?”
3. Email Campaign Performance: “I am sharing data from our latest email campaigns. The dataset includes campaign ID, email subject line, open rates, click-through rates, and conversion rates. Please review the data and provide insights into which types of subject lines and content performed best.”

Just imagine if you had a spreadsheet filled with a couple thousand feedback entries from customers. Yes, you could spend hours reading each review, noting the theme and sentiment, and then building formulas that counted and charted the results to give you an analysis – or you can ask the AI to do that for you in a matter of seconds.

Analyzing Data and Getting Recommendations:

Second, here’s how you can dig into the data and get more detailed recommendations.

1. Audience Segmentation: “Given the customer data including demographic information, purchase history, and engagement metrics, can you help segment the audience into distinct groups based on their behavior and preferences? Please provide a detailed analysis of each segment.”
2. Content Personalization Recommendations: “Based on the provided customer feedback and engagement data, what content topics and formats should we focus on to improve engagement and satisfaction? Please highlight any specific themes or content types that performed well.”
3. Ad Campaign Optimization: “Here’s our recent ad campaign performance data, including ad spend, clicks, impressions, and conversion rates. Can you analyze this data and recommend optimizations for better targeting, ad placements, and budget allocation?”
4. Predictive Sales Insights: “With the sales data provided, can you forecast sales trends for the next quarter? Additionally, please suggest any actionable strategies to maximize sales based on the identified patterns.”

Combining Data Sharing and Analysis Prompts:

Third, for more advanced campaigns and analysis, you can try these.

1. Combined Feedback and Performance Analysis: “Below is a CSV file containing both customer feedback and performance metrics for our recent webinar series. The columns include attendee name, feedback rating, feedback comments, registration date, and attendance duration. Please analyze this data to identify key areas of improvement and successful elements of the webinars.”
2. Cross-Channel Marketing Effectiveness: “I am providing a dataset with marketing performance metrics across email, social media, and paid ads. For each campaign, the data includes spend, reach, engagement, and conversion rates. Please evaluate the effectiveness of each channel and recommend where we should focus our efforts for maximum ROI.”

Structuring Prompts for Optimal Results

Some tips for structuring your own prompts.

• Ensure Clarity: Clearly state the type of data you are providing and its structure.
• Be Specific: Specify what kind of analysis or recommendations you are looking for.
• Provide Context: Include any relevant context or background information to help the AI understand the data better.
• Ask for Actionable Insights: Frame your prompts to request actionable insights or detailed breakdowns.

It’s important to understand that the AI’s core programming is to be as helpful as possible, which means if you do not tell it what you want, it will decide for itself what it thinks you want to try to provide that, which could waste a little time and usage credits. The more specific you are up front, even if it’s to tell the AI to simply accept the information you’ve provided and then stop and wait for the next prompt, the more efficient your time will be.

By the way, this idea of giving the AI multiple prompts in a strategic order is often referred to as chain prompting, and is a topic we’ll definitely touch on in future conversations.

By using these prompts, you can effectively feed your data into AI tools and obtain meaningful analysis and recommendations to optimize your marketing strategies.

My advice:

• Start Simple: Begin with small datasets to see how the AI interprets and what kind of outputs it generates. This allows you to refine your inputs without overwhelming the system or yourself.
• Provide Context: The more context you provide, the better the AI will understand and produce relevant results. For example, when inputting customer feedback, also provide information about the products related to that feedback.
• Iterate and Refine: Use the initial outputs from the AI to iterate and provide more refined data. This helps the AI learn and produce better results over time.

By starting with a clear plan, clean data, and understanding how to properly feed this data to your AI tools, you set a strong foundation for your AI-driven campaign, and every successive campaign.

Best Practices: Regularly revisit your objectives to ensure they remain aligned with your overall marketing strategy. Start with broad goals and narrow them down to specific, measurable outcomes. Continuously refine your goals based on insights gathered throughout the campaign. This iterative process will help you stay on track and adapt to any changes that may arise.

Executing with AI Marketing Tools

Now that you have a solid plan and all your data is cleaned, structured, and ready to go, it’s time to execute using AI tools. The data you prepared, and the AI analysis, will be the backbone of your AI-driven campaign. Let’s break down the key components of an AI-driven campaign and how this data will be used.

Audience Targeting with AI

First, dive into audience targeting. AI tools like HubSpot and Salesforce can segment your audience into highly specific groups based on the cleaned and structured data you’ve provided. That means the inconsistencies we addressed—like variations in date formats, text case, and categorizations—are now streamlined, allowing these tools to accurately parse and group your audience.

The AI will analyze this data to understand customer behaviors, preferences, and demographics, creating precise segments. For example, if your data contains customer purchase histories, the AI will identify patterns and segment customers who frequently buy a particular type of product. This segmentation ensures that your campaign reaches the right people with the right message, increasing the likelihood of engagement and conversion.

Using Data in Magai for Content Creation

For content creation, let’s look at Magai. By feeding Magai structured customer feedback and interaction data, it can generate content that resonates with your audience. The previously mentioned context—like consistent product names and properly formatted text—allows Magai to create relevant and personalized content.

For instance, if the data indicates that customers frequently mention “fast delivery” as a positive aspect, Magai can help you craft social media posts or email campaigns highlighting your quick shipping times. The AI uses the cleaned data to ensure the content it generates reflects real customer sentiment and preferences.

Personalization with Adobe Express

When using design tools like Adobe Express, the structured data helps personalize visual content. For example, if your audience data shows a segment with a preference for certain colors or styles, you can tailor your graphics to match those preferences. The AI uses this data to suggest design elements and styles that align with your audience’s tastes, making your visuals more appealing and engaging.

Ad Optimization with AdRoll and Google Ads

For ad optimization, tools like AdRoll and Google Ads use the cleaned data to determine the best ad placements and bidding strategies. The accurate, structured data enables these tools to analyze patterns and trends effectively, ensuring your ads are seen by the right audience at the optimal times.

For example, if your data includes detailed customer engagement metrics, the AI can identify the times of day when your audience is most active and adjust ad placements accordingly. This maximizes your ROI and improves your campaign performance by targeting high-engagement periods.

Best Practices for Leveraging Data with AI Tools

To get the best results from these AI tools, remember to keep the following best practices in mind:

1. Regularly Update Your Data: Continuously refine and update your data to ensure it remains accurate and relevant. The more up-to-date your data, the better the AI tools can perform.
2. Use Context-Rich Inputs: When feeding data to AI tools, provide as much context as possible. This helps the AI understand the nuances of your data and generate more precise outputs.
3. Iterate and Optimize: Use the insights gained from your AI tools to iterate and optimize your campaign. Regularly review performance metrics and adjust your strategies based on the data-driven insights.

By leveraging the cleaned and structured data in AI tools, you can execute a highly effective, personalized, and data-driven marketing campaign that resonates with your audience and achieves your objectives.

Measuring Success and Iterating

Once your campaign is up and running, it’s crucial to measure its success and iterate based on the results. AI tools provide powerful analytics that go beyond basic metrics. Tools like Google Analytics and HubSpot offer real-time insights into how your campaign is performing.

Key Metrics to Track: Focus on metrics that align with your campaign objectives. This could include engagement rates, conversion rates, click-through rates, and ROI. Use these insights to understand what’s working and what needs adjustment. If your campaign has a social media aspect, make sure that you’ve published all of your posts, comments and direct messages with links using a tool like Agorapulse which can automatically track those links and associate any website conversions directly with those links, giving you accurate ROI reporting.

Best Practices: Regularly review and analyze your campaign data. Set up automated reports to keep track of your key metrics. Use AI tools to provide predictive insights that can help guide your next steps. Don’t be afraid to make changes mid-campaign—AI allows for real-time optimization.

Practical Tips and Encouragement

Launching your first AI-driven campaign might feel like a big step, but remember, every marketer started somewhere. The key to mastering AI in marketing is to start small, learn from each campaign, and build on your successes. Here are some practical tips to keep you motivated and on the right track.

Start Small: I mentioned this earlier… don’t try to overhaul your entire marketing strategy with AI overnight. Begin with a single campaign or even just a component of a campaign, like email marketing or social media ads. This will allow you to familiarize yourself with the tools and processes without feeling overwhelmed.

Learn and Adapt: AI technology is constantly evolving, and so should your approach. Take the time to learn from each campaign. Analyze what worked and what didn’t, and use those insights to improve your future efforts. Continuous learning and adaptation are key to leveraging AI effectively.

Use Resources and Support: Don’t hesitate to use the resources and support available to you. Most marketing-focused AI tools offer extensive documentation, tutorials, and customer support teams ready to help you succeed. Engage with communities and forums, attend webinars, and read up on case studies to see how others are successfully using AI. And, if I may be so bold, subscribe to this podcast and my newsletter! Each week I am interviewing incredible experts in both marketing and artificial intelligence. In upcoming episodes you’ll hear from brilliant minds like Christopher Penn, Katie Richman, Andy Crestodina, and Asavari Moon, and from brands you know and trust like Intel, Google, and more.

Stay Positive and Curious: Keep an open mind and stay curious about new developments in AI. The field is rapidly advancing, and there’s always something new to learn and get excited about. Approach each campaign as an opportunity to experiment and grow. Remember, every expert was once a beginner, and your willingness to learn and adapt will set you apart – I’m learning right alongside you.

Wrapping Up

As we bring this episode, and this initial 4-part series to a close, remember: building your first AI-driven campaign is all about careful planning, leveraging the right tools, and continually optimizing based on data-driven insights. By integrating AI, you can create more effective, personalized, and impactful marketing campaigns.

If you enjoyed today’s episode, please subscribe and share AI in Marketing: Unpacked with your colleagues. For more in-depth guides on the tools we discussed, check out the links in the show notes.

Future episodes will drop on Saturdays, and our next episode features the amazing Claudia Sandino, an expert in AI and social media marketing whom you’re going to be fascinated with and learn a ton from.

Until then, keep exploring the possibilities of AI in your marketing strategy.

Welcome to the grid.