How to Leverage AI in Marketing

I recently published two books on AI and marketing: The Modern AI Marketer in the GPT Era and The Modern AI Marketer: Guide to Gen AI Prompts. From my conversations with marketers, it’s clear everyone is at a different stage of their AI experimentation. Some are just exploring AI prompts, others are collaborating with IT and data teams to automate processes, and some are focused on establishing AI governance.

The key takeaway is that we’re all learning and experimenting—there’s no race, as AI is constantly evolving right in front of us. So, what can you do with AI right now?

Try different AI Prompts

If your company allows you to use AI bots such as ChatGPT, Gemini, Copilot, or other GPT tools, great. The first thing you can do is to ask AI business or marketing-related questions and see if it can help you to come up with ideas, processes, tools, or even writing various marketing outreach copy.

I offered >75 prompt examples for 13 sales and marketing categories in the Guide to Gen AI Prompts. The number 1 rule is to be as specific as possible when you write your prompts. The number 2 rule is to modify your prompts to get different responses. Your job is to determine which responses are sensible for your needs and situations.

Here are some examples from my book:

Target Audience: “I am a marketer for [business or organization name], an organization in the [industry type] that [describe your organization’s products or services]. Our competitors include [examples of top competitors]. Our current customer demographics consist of [describe details of your customer demographics]. What are some marketing strategies that could help us better reach our target customers? List [specific number] marketing strategies.”

Marketing Plan: Help me write a marketing plan with a proposed budget of [dollar amount] for [name of your business]. [Explain what your business does] and [its unique value proposition].

The plan’s target customers are [describe target customers in detail]. The plan needs to include recommendations with specific marketing channels such as [marketing channel examples].

The plan’s success metrics are [describe your success measurements] in [timeline].

Email Subject Lines: “I want to create engaging new subject lines for an email campaign. The email campaign promotes [describe specific product(s)/services(s)]. The campaign target audience includes [describe campaign target audience]. Write [specific number] email subject lines for this campaign that will get readers to open the email.”

Templates: “My organization wants to create a new email newsletter template. Our organization offers [describe products/services]. Our target audience for the newsletter includes [describe newsletter target audience]. We want to feature these key sections in the newsletter [list sections such as company news, product/service updates, team features, etc.]. Create an email newsletter template following these guidelines.”

Think of how you write your prompts as if you are briefing one of your agencies or vendors. Make it as clear as possible.

Utilize Your Existing Platform’s AI Features

Exploring the AI features of platforms you already use is one of the quickest and most effective ways to integrate AI into your marketing workflow without a steep learning curve. These AI tools are often designed to be user-friendly and can significantly enhance your productivity. Here’s a deeper dive into how you can make the most of these built-in AI features:

1. Salesforce’s Einstein AI

Overview: Salesforce’s Einstein is a comprehensive AI suite built into Salesforce CRM. It offers predictive analytics, automation, and personalized recommendations directly within your CRM environment.

Key Features:

• Lead Scoring: Einstein AI can analyze your existing data to predict which leads are most likely to convert, allowing your sales team to prioritize efforts effectively.
• Email Insights: AI-powered analysis of email content can provide insights into the effectiveness of communication and suggest the next best actions.
• Automated Workflow Suggestions: Einstein can recommend automations for routine tasks like scheduling follow-ups or sending reminders.
• Predictive Analytics: Use predictive models to forecast sales, anticipate customer churn, and identify upsell opportunities.

How to Use: Test how Einstein handles your lead data, campaign analysis, and sales performance reports. See if it’s providing insights that are actionable and align with your business goals.

2. Canva’s Magic Studio

Overview: Canva’s Magic Studio leverages AI to simplify the design process for marketers. It’s built to streamline content creation with a focus on visual assets.

Key Features:

• Magic Design: Automatically generate design templates based on your existing branding guidelines. The AI can suggest color schemes, layouts, and fonts that match your brand.
• Magic Write: Create compelling captions, descriptions, and product listings with AI-generated copy suggestions tailored to your design context.
• Background Removal & Enhancements: AI-driven tools to remove backgrounds, adjust images, and improve visual quality without needing advanced design skills.
• Text to Image: Generate unique images using AI based on textual prompts, perfect for quickly creating visuals for social media.

How to Use: Experiment with generating social media posts, email headers, or infographics. Determine if the AI’s suggestions align with your brand voice and visual style, and adjust templates as needed.

3. LinkedIn’s “Write with AI”

Overview: LinkedIn’s “Write with AI” feature is designed to help professionals craft better posts by generating content suggestions based on your topic or draft. It saves time and helps with writer’s block.

Key Features:

• Content Drafting: Enter a few key points, and the AI will generate a complete post draft that you can tweak and personalize.
• Tone Adjustments: Options to tailor the tone to be more formal, friendly, or persuasive depending on the audience and purpose.
• Content Suggestions: AI-driven suggestions for trending topics or industry-relevant content ideas based on your field.

How to Use: Use this feature to write posts quickly, especially if you’re looking to maintain a consistent posting schedule. Track engagement to see if AI-generated content resonates with your audience, and make adjustments accordingly.

How to Determine if AI Features Are Right for Your Needs

1. Test and Analyze: Begin with a few pilot projects using these AI tools. For example, create a LinkedIn post using “Write with AI” and compare its engagement metrics to your manually written content. Track how AI-generated content performs in terms of likes, comments, and shares.
2. Customization and Flexibility: Evaluate how customizable the AI tools are. Can you adjust the tone, style, and settings to match your brand? Do the recommendations make sense for your specific industry or audience?
3. Efficiency Gains: Measure how much time you save using these tools. Are they reducing the workload or streamlining repetitive tasks? Track the time taken to complete projects with and without AI assistance.
4. Content Quality: Check the quality of AI-generated output. Is it as good as or better than what your team could produce manually? Are there any specific areas where the AI excels (like imagery or data analysis) or falls short (such as nuanced messaging)?
5. Integration: Assess how well these AI tools integrate with your existing marketing tech stack. Do they sync effortlessly with other tools like your CRM, analytics platforms, or email marketing tools?
6. Cost vs. Value: Weigh the costs of using advanced features or paid versions of these AI tools against the potential value they bring. Some AI features are free but limited, while others require premium subscriptions—determine if the ROI justifies the expense.

Some Examples of AI Features in Other Platforms

• Adobe’s Sensei: AI-powered features for image recognition, content tagging, and automated video editing, making it easier for marketers to manage large content libraries.
• HubSpot’s Content Assistant: AI writing tools for blog posts, email campaigns, and landing page content—ideal for content-heavy marketing strategies.
• Microsoft Power BI AI: Built-in AI features for predictive analytics, trend forecasting, and advanced data visualization, giving you deeper insights into marketing data.
• Google Analytics 4 AI Insights: Automated insights for user behavior, conversion patterns, and predictive metrics to help you make data-driven decisions faster.

Build Your Own AI Bots

Building your own AI bots for marketing can be a game-changer, enabling you to automate processes, engage with customers, and gather insights efficiently. Here’s a step-by-step guide to help you get started:

1. Define the Purpose of the AI Bot

Target Audience: Who will be interacting with the bot? Are they prospects, customers, or internal team members?
Marketing Goals: Is the bot for lead generation, customer support, social media engagement, product recommendation, or content distribution?
Bot’s Role: Define what the bot will specifically handle (e.g., answering FAQs, scheduling demos, sending personalized content).

2. Select the Right AI Platform

Choose platforms that match your technical expertise and use cases:

• No-Code Platforms: Platforms like Chatfuel, ManyChat, or Tars are great for simple bots with predefined responses.
• Low-Code Platforms: Tools like HubSpot Chatbot Builder and ActiveCampaign are suitable for marketing-oriented bots with integrations to CRM systems.
• Advanced AI Platforms: For complex, NLP-driven bots, consider Dialog Flow (Google), Rasa, or Microsoft Bot Framework.

Language Models: If you need a conversational bot with deep understanding, you can leverage models like OpenAI’s GPT-3 or Anthropic’s Claude via APIs.

3. Design the Conversation Flow

Map User Journeys: Outline possible paths users might take. Use flowchart tools like Lucidchart or Miro to visualize interactions.
Conversation Scenarios: Design scenarios for handling different customer inquiries (e.g., How does the bot respond if someone asks about pricing?).
User Intent & Entities: Define user intents (what they want) and entities (specific data like product names or dates) for a more dynamic conversation.

4. Build and Train the Bot

Create Responses: Use a blend of scripted responses and dynamic data from your CRM to personalize interactions.
NLP Training: If you’re using NLP-based platforms, train the bot with example phrases (training data) for each intent.
Integration: Connect the bot to your CRM, email, or other marketing platforms (e.g., HubSpot, Salesforce) to pull user data and automate workflows.

5. Integrate and Automate Marketing Workflows

Lead Qualification: Automate lead scoring based on interaction data (e.g., download history, page visits) and trigger actions like assigning leads to sales.
Content Delivery: Schedule and send targeted content like eBooks, case studies, or webinars based on user inquiries.
Engagement Campaigns: Use bots for drip campaigns, onboarding sequences, or re-engagement efforts.

6. Test and Iterate

A/B Testing: Test different scripts, response formats, and user journeys to see what resonates best.
Feedback Loops: Monitor conversations, review bot interactions, and identify gaps or frequently misunderstood queries.
Analytics: Use platform analytics to track KPIs (engagement, conversion rates, customer satisfaction).

7. Deploy and Optimize

Channels: Deploy the bot on multiple channels (website, Facebook Messenger, WhatsApp, email) to increase reach.
Monitoring: Use analytics to measure success (e.g., lead quality, response time) and adjust accordingly.
Continuous Learning: If the bot uses machine learning, continue feeding it data to improve its responses and capabilities.

8. Personalization and Human Handoff

Segmented Messaging: Use the bot to segment audiences based on behavior and send targeted messages.
Human Handoff: Integrate a seamless handoff to human agents for complex queries or when the bot hits its limits.
Dynamic Personalization: Utilize CRM data to tailor responses based on a user’s history with your brand.

Tools and Platforms to Consider

• Chatbot Platforms: Dialogflow, Rasa, Tars, HubSpot Chatbot Builder, Drift.
• CRM Integration: HubSpot, Salesforce, Zoho.
• Marketing Automation: ActiveCampaign, Marketo, Pardot.
• Data Analytics: Google Analytics, Mixpanel, Amplitude.
• Customer Support: Intercom, Zendesk, Freshchat.

Example Use Cases

1. Lead Generation Bot: Qualifies leads by asking questions, scores them based on answers, and syncs data with CRM.
2. Content Distribution Bot: Recommends blog posts, case studies, or videos based on user preferences.
3. Customer Support Bot: Answers FAQs, troubleshoots, and escalates to a support agent if needed.
4. Social Media Engagement Bot: Responds to comments, handles DMs, and shares personalized offers.

Tips for Success

• Start Simple: Begin with a limited use case, such as an FAQ bot, and expand as you gather data and understand user behavior.
• Natural Language Tone: Make sure the bot’s language feels human-like and aligns with your brand voice.
• Continuous Improvement: Gather user feedback and iteratively refine the bot to handle more sophisticated queries over time.

Incorporating AI into your marketing requires careful planning around your goals and strategies. Consider what tasks AI can enhance and how best to implement it for maximum impact.

If you’d like to know more about Pam’s AI Training, including exclusive AI Copilot Training for enterprises, schedule a free call.